Geoffrey Sonn
Associate Professor of Urology and, by courtesy, of Radiology (Body MRI)
Bio
Geoffrey Sonn, MD is a board certified urologist who specializes in treating patients with prostate and kidney cancer. He has a particular interest in cancer imaging, MRI-Ultrasound fusion targeted prostate biopsy, prostate cancer focal therapy, and robotic surgery for prostate and kidney cancer. He was the Stanford principal investigator of a major clinical trial using MRI-guided focused ultrasound to treat prostate cancer. The goal of this trial was to treat prostate cancer with fewer side effects than surgery or radiation.
Dr. Sonn was born in Washington State and lived there until leaving for college at Georgetown in Washington DC. After graduating magna cum laude at Georgetown he returned to the West Coast for medical school at UCLA. Following medical school, Dr. Sonn completed a 6-year urology residency at Stanford where he developed particular interests in the clinical care of patients with urologic cancers and research in cancer imaging. He then spent two years at UCLA as a urologic oncology fellow where he devoted all his time to gaining additional skills and experience in clinical care and research in urologic malignancies. Since finishing his fellowship, Dr. Sonn has been at Stanford where he applies the skills he gained in residency and fellowship to provide high-quality clinical care to patients with urologic cancers. Dr. Sonn also continues to work to develop new methods to better diagnose and treat urologic cancers through research. His primary research focus is in prostate cancer focal therapy and developing artificial intelligence methods to improve prostate cancer detection on MRI and ultrasound.
Clinical Focus
- Cancer > Urologic Oncology
- Prostate Cancer
- Kidney Cancer
- Ablation Techniques
- Biopsy
- Testicular Cancer
- Urology
- Robotics
Academic Appointments
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Associate Professor - University Medical Line, Urology
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Associate Professor - University Medical Line (By courtesy), Radiology
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Member, Bio-X
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Member, Stanford Cancer Institute
Honors & Awards
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First Place in Prostate Cancer Detection & Screening Poster Session, American Urological Association (2013)
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Research Award for Fluorescent Imaged Guided Surgery in Prostate Cancer, Longmire Surgical Society at UCLA (2013)
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First Place in Localized Kidney Cancer Poster Session, American Urological Association (2010)
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Third Place Resident Essay Contest in Clinical Research, American Urological Association (2009)
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CaPSURE Scholars Program, UCSF Department of Urology (2008)
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First Place Resident essay contest, Western Section AUA (2008)
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Richard K. Lo Resident Publication Award, Stanford Urology (2010)
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Mahoney Medal (Outstanding pre med with a liberal arts major), Georgetown University (2001)
Professional Education
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Residency: Stanford University Medical Center (2011) CA
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Residency: Stanford University Medical Center (2007) CA
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Medical Education: UCLA David Geffen School Of Medicine Registrar (2005) CA
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Fellowship: UCLA David Geffen School Of Medicine Registrar (2013) CA
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Board Certification: American Board of Urology, Urology (2015)
Current Research and Scholarly Interests
My primary interest is in improving prostate cancer diagnosis and treatment through MRI and image-targeted prostate biopsy. In collaboration with radiologists at Stanford, we are working to define the optimal role of MRI in prostate cancer. We hope to improve cancer imaging to the point that some men with elevated PSA may safely avoid prostate biopsy. For those who need biopsy, we are evaluating novel MRI-US fusion targeted biopsy, a technique that greatly improves upon the conventional biopsy method. More accurate prostate biopsy enables better decision making about treatment options such as deciding between active surveillance and surgery.
Moving beyond biopsy, I am interested in the use of imaging to select patients who are candidates for prostate cancer focal therapy. Focal therapy involves ablation of prostate cancers under image guidance without destruction or removal of the normal areas of the prostate and with less damage to important surrounding structures that are important for erectile function and urinary continence.
I am also interested in developing novel molecular imaging techniques such as near infrared fluorescence imaging to improve surgery for prostate and kidney cancer.
Clinical Trials
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A Comparison of TULSA Procedure vs. Radical Prostatectomy in Participants With Localized Prostate Cancer
Recruiting
Men with localized, intermediate risk prostate cancer will be randomized to undergo either radical prostatectomy or the TULSA procedure, with a follow-up of 10 years in this multi-centered randomized control trial. This study will determine whether the TULSA procedure is as effective and more safe compared to radical prostatectomy.
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EDRN Prostate MRI Biomarker Study
Recruiting
The commercialization of MRI fusion biopsies has resulted in a dramatic increase in the use of MRI imaging for prostate cancer. How best to use MRI in the initial prostate biopsy setting given the availability of validated prostate cancer early detection markers is uncertain.This study will allow investigators to determine if prostate MRI is superior to validated panel of laboratory biomarkers (e.g. PCA3, PSA and TMPRSS2:ERG) in the initial biopsy setting.
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Standard Systemic Therapy With or Without Definitive Treatment in Treating Participants With Metastatic Prostate Cancer
Recruiting
This phase III trial studies how well standard systemic therapy with or without definitive treatment (prostate removal surgery or radiation therapy) works in treating participants with prostate cancer that has spread to other places in the body. Addition of prostate removal surgery or radiation therapy to standard systemic therapy for prostate cancer may lower the chance of the cancer growing or spreading.
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68Ga PSMA 11 PET/MRI and 68Ga RM2 PET/MRI for Biopsy Guidance in Patients With Suspected Prostate Cancer
Not Recruiting
The objective of the study is to evaluate 68Ga PSMA 11 PET/MRI and 68Ga RM2 PET/MRI for biopsy guidance in patients with suspected prostate cancer.
Stanford is currently not accepting patients for this trial. For more information, please contact Jordan Cisneros, 650-498-7061.
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68Ga-PSMA PET/CT or PET/MRI in Evaluating Patients With Recurrent Prostate Cancer
Not Recruiting
This clinical trial studies gallium-68 (68Ga)-prostate specific membrane antigen (PSMA) (gallium Ga 68-labeled PSMA ligand Glu-urea-Lys\[Ahx\]) positron emission tomography (PET)/computed tomography (CT) or PET/magnetic resonance imaging (MRI) in identifying prostate cancer that may have returned after a period of improvement (biochemical recurrence). 68Ga-PSMA is a radiopharmaceutical that localizes to a specific prostate cancer receptor, which can then be imaged by the PET/CT or PET/MRI scanner.
Stanford is currently not accepting patients for this trial. For more information, please contact Pamela Gallant, 650-736-8965.
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A Pilot Trial Using BR55 Ultrasound Contrast Agent in the Assessment of Prostate Cancer
Not Recruiting
Pilot study to evaluate the ability of BR55 to identify prostate cancer lesions with Gleason Score ≥7 by ultrasound molecular imaging on the basis of a visual score in comparison with histopathology results
Stanford is currently not accepting patients for this trial. For more information, please contact Phuong Pham, 650-725-9810.
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Continued Access of Focal MR-Guided Focused Ultrasound for Localized Intermediate Risk Prostate Lesions
Not Recruiting
This extended clinical investigation is a multicenter, prospective, single arm study intended to provide continued access of the Exablate Model 2100 device (Exablate Prostate) to patients for treatment of prostate lesions and collect additional safety and effectiveness data during the 510(k) preparation and review period.
Stanford is currently not accepting patients for this trial. For more information, please contact Cancer Clinical Trials Office (CCTO), 650-498-7061.
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Focal MR-Guided Focused Ultrasound Treatment of Localized Intermediate Risk Prostate Lesions
Not Recruiting
The hypothesis of this study is that focal treatment with ExAblate MRgFUS has the potential to be an effective non-invasive treatment for intermediate risk, organ-confined prostate lesions, with a low incidence of morbidity. The study hypothesis will be tested by measuring treatment-related safety and initial effectiveness parameters in the ExAblate MRgFUS treated patients, as described above.
Stanford is currently not accepting patients for this trial. For more information, please contact Denise Haas, 650-736-1252.
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Photoacoustic Imaging (PAI) of the Prostate: A Clinical Feasibility Study
Not Recruiting
The purpose of our study is to image human prostate tissue using a transrectal photoacoustic imaging probe.
Stanford is currently not accepting patients for this trial. For more information, please contact Sri-Rajasekhar Kothapalli, 650-498-7061.
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Predicting Location and Extent of Prostate Cancer Using Micro-Ultrasound Imaging
Not Recruiting
The goal of this study is to use a clinical micro-ultrasound to systematically image the prostate before biopsy or surgery. The images from the ultrasound system will be saved and compared to other imaging modalities and pathology in order to develop better tools.
Stanford is currently not accepting patients for this trial.
2024-25 Courses
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Independent Studies (5)
- Directed Reading in Urology
UROL 299 (Aut, Win, Spr, Sum) - Early Clinical Experience in Urology
UROL 280 (Aut, Win, Spr, Sum) - Graduate Research
UROL 399 (Aut, Win, Spr, Sum) - Medical Scholars Research
UROL 370 (Aut, Win, Spr, Sum) - Undergraduate Research
UROL 199 (Aut, Win, Spr, Sum)
- Directed Reading in Urology
Stanford Advisees
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Med Scholar Project Advisor
Elijah Sommer -
Postdoctoral Faculty Sponsor
Hassan Jahanandish -
Postdoctoral Research Mentor
Hassan Jahanandish
All Publications
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Aggressiveness classification of clear cell renal cell carcinoma using registration-independent radiology-pathology correlation learning.
Medical physics
2024
Abstract
Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Clear cell RCC (ccRCC) is the most common RCC subtype, with both aggressive and indolent manifestations. Indolent ccRCC is often low-grade without necrosis and can be monitored without treatment. Aggressive ccRCC is often high-grade and can cause metastasis and death if not promptly detected and treated. While most RCCs are detected on computed tomography (CT) scans, aggressiveness classification is based on pathology images acquired from invasive biopsy or surgery.CT imaging-based aggressiveness classification would be an important clinical advance, as it would facilitate non-invasive risk stratification and treatment planning. Here, we present a novel machine learning method, Correlated Feature Aggregation By Region (CorrFABR), for CT-based aggressiveness classification of ccRCC.CorrFABR is a multimodal fusion algorithm that learns from radiology and pathology images, and clinical variables in a clinically-relevant manner. CorrFABR leverages registration-independent radiology (CT) and pathology image correlations using features from vision transformer-based foundation models to facilitate aggressiveness assessment on CT images. CorrFABR consists of three main steps: (a) Feature aggregation where region-level features are extracted from radiology and pathology images at widely varying image resolutions, (b) Fusion where radiology features correlated with pathology features (pathology-informed CT biomarkers) are learned, and (c) Classification where the learned pathology-informed CT biomarkers, together with clinical variables of tumor diameter, gender, and age, are used to distinguish aggressive from indolent ccRCC using multi-layer perceptron-based classifiers. Pathology images are only required in the first two steps of CorrFABR, and are not required in the prediction module. Therefore, CorrFABR integrates information from CT images, pathology images, and clinical variables during training, but for inference, it relies solely on CT images and clinical variables, ensuring its clinical applicability. CorrFABR was trained with heterogenous, publicly-available data from 298 ccRCC tumors (136 indolent tumors, 162 aggressive tumors) in a five-fold cross-validation setup and evaluated on an independent test set of 74 tumors with a balanced distribution of aggressive and indolent tumors. Ablation studies were performed to test the utility of each component of CorrFABR.CorrFABR outperformed the other classification methods, achieving an ROC-AUC (area under the curve) of 0.855 ± 0.0005 (95% confidence interval: 0.775, 0.947), F1-score of 0.793 ± 0.029, sensitivity of 0.741 ± 0.058, and specificity of 0.876 ± 0.032 in classifying ccRCC as aggressive or indolent subtypes. It was found that pathology-informed CT biomarkers learned through registration-independent correlation learning improves classification performance over using CT features alone, irrespective of the kind of features or the classification model used. Tumor diameter, gender, and age provide complementary clinical information, and integrating pathology-informed CT biomarkers with these clinical variables further improves performance.CorrFABR provides a novel method for CT-based aggressiveness classification of ccRCC by enabling the identification of pathology-informed CT biomarkers, and integrating them with clinical variables. CorrFABR enables learning of these pathology-informed CT biomarkers through a novel registration-independent correlation learning module that considers unaligned radiology and pathology images at widely varying image resolutions.
View details for DOI 10.1002/mp.17476
View details for PubMedID 39447001
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Reviewer of the Month: Geoffrey Sonn.
The Journal of urology
2024: 101097JU0000000000004299
View details for DOI 10.1097/JU.0000000000004299
View details for PubMedID 39423117
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Trends in pre-biopsy MRI usage for prostate cancer detection, 2007-2022.
Prostate cancer and prostatic diseases
2024
Abstract
Clinical guidelines favor MRI before prostate biopsy due to proven benefits. However, adoption patterns across the US are unclear.This study used the Merative™ Marketscan® Commercial & Medicare Databases to analyze 872,829 prostate biopsies in 726,663 men from 2007-2022. Pre-biopsy pelvic MRI within 90 days was the primary outcome. Descriptive statistics and generalized estimating equations assessed changes over time, urban-rural differences, and state-level variation.Pre-biopsy MRI utilization increased significantly from 0.5% in 2007 to 35.5% in 2022, with faster adoption in urban areas (36.1% in 2022) versus rural areas (28.3% in 2022). Geographic disparities were notable, with higher utilization in California, New York, and Minnesota, and lower rates in the Southeast and Mountain West.The study reveals a paradigm shift in prostate cancer diagnostics towards MRI-guided approaches, influenced by evolving guidelines and clinical evidence. Disparities in access, particularly in rural areas and specific regions, highlight the need for targeted interventions to ensure equitable access to advanced diagnostic techniques.
View details for DOI 10.1038/s41391-024-00896-y
View details for PubMedID 39306635
View details for PubMedCentralID 9084630
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Inter-reader Agreement for Prostate Cancer Detection Using Micro-ultrasound: A Multi-institutional Study
EUROPEAN UROLOGY OPEN SCIENCE
2024; 66: 93-100
View details for DOI 10.1016/j.euros.2024.06.017
View details for Web of Science ID 001271419500001
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Stockholm3 in a Multiethnic Cohort for Prostate Cancer Detection (SEPTA): A Prospective Multicentered Trial.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
2024: JCO2400152
Abstract
Asian, Black, and Hispanic men are underrepresented in prostate cancer (PCa) clinical trials. Few novel prostate cancer biomarkers have been validated in diverse cohorts. We aimed to determine if Stockholm3 can improve prostate cancer detection in a diverse cohort.An observational prospective multicentered (17 sites) clinical trial (2019-2023), supplemented by prospectively recruited participants (2008-2020) in a urology clinic setting included men with suspicion of PCa and underwent prostate biopsy. Before biopsy, sample was collected for measurement of the Stockholm3 risk score. Parameters include prostate-specific antigen (PSA), free PSA, KLK2, GDF15, PSP94, germline risk (single-nucleotide polymorphisms), age, family history, and previous negative biopsy. The primary endpoint was detection of International Society of Urological Pathology (ISUP) Grade ≥2 cancer (clinically significant PCa, csPC). The two primary aims were to (1) demonstrate noninferior sensitivity (0.8 lower bound 95% CI noninferiority margin) in detecting csPC using Stockholm3 compared with PSA (relative sensitivity) and (2) demonstrate superior specificity by reducing biopsies with benign results or low-grade cancers (relative specificity).A total of 2,129 biopsied participants were included: Asian (16%, 350), Black or African American (Black; 24%, 505), Hispanic or Latino and White (Hispanic; 14%, 305), and non-Hispanic or non-Latino and White (White; 46%, 969). Overall, Stockholm3 showed noninferior sensitivity compared with PSA ≥4 ng/mL (relative sensitivity: 0.95 [95% CI, 0.92 to 0.99]) and nearly three times higher specificity (relative specificity: 2.91 [95% CI, 2.63 to 3.22]). Results were consistent across racial and ethnic subgroups: noninferior sensitivity (0.91-0.98) and superior specificity (2.51-4.70). Compared with PSA, Stockholm3 could reduce benign and ISUP 1 biopsies by 45% overall and between 42% and 52% across racial and ethnic subgroups.In a substantially diverse population, Stockholm3 significantly reduces unnecessary prostate biopsies while maintaining a similar sensitivity to PSA in detecting csPC.
View details for DOI 10.1200/JCO.24.00152
View details for PubMedID 39038251
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External validation of an artificial intelligence model for Gleason grading of prostate cancer on prostatectomy specimens.
BJU international
2024
Abstract
To externally validate the performance of the DeepDx Prostate artificial intelligence (AI) algorithm (Deep Bio Inc., Seoul, South Korea) for Gleason grading on whole-mount prostate histopathology, considering potential variations observed when applying AI models trained on biopsy samples to radical prostatectomy (RP) specimens due to inherent differences in tissue representation and sample size.The commercially available DeepDx Prostate AI algorithm is an automated Gleason grading system that was previously trained using 1133 prostate core biopsy images and validated on 700 biopsy images from two institutions. We assessed the AI algorithm's performance, which outputs Gleason patterns (3, 4, or 5), on 500 1-mm2 tiles created from 150 whole-mount RP specimens from a third institution. These patterns were then grouped into grade groups (GGs) for comparison with expert pathologist assessments. The reference standard was the International Society of Urological Pathology GG as established by two experienced uropathologists with a third expert to adjudicate discordant cases. We defined the main metric as the agreement with the reference standard, using Cohen's kappa.The agreement between the two experienced pathologists in determining GGs at the tile level had a quadratically weighted Cohen's kappa of 0.94. The agreement between the AI algorithm and the reference standard in differentiating cancerous vs non-cancerous tissue had an unweighted Cohen's kappa of 0.91. Additionally, the AI algorithm's agreement with the reference standard in classifying tiles into GGs had a quadratically weighted Cohen's kappa of 0.89. In distinguishing cancerous vs non-cancerous tissue, the AI algorithm achieved a sensitivity of 0.997 and specificity of 0.88; in classifying GG ≥2 vs GG 1 and non-cancerous tissue, it demonstrated a sensitivity of 0.98 and specificity of 0.85.The DeepDx Prostate AI algorithm had excellent agreement with expert uropathologists and performance in cancer identification and grading on RP specimens, despite being trained on biopsy specimens from an entirely different patient population.
View details for DOI 10.1111/bju.16464
View details for PubMedID 38989669
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Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.
The Lancet. Oncology
2024
Abstract
Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale.In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5-10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4-6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov, NCT05489341.Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87-0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83-0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6-63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3-92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3-72·4] vs 69·0% [65·5-72·5]) at the same sensitivity (96·1%, 94·0-98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (-0·04) was greater than the non-inferiority margin (-0·05) and a p value below the significance threshold was reached (p<0·001).An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system.Health~Holland and EU Horizon 2020.
View details for DOI 10.1016/S1470-2045(24)00220-1
View details for PubMedID 38876123
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Patient Preferences for Benefit and Risk Associated With High Intensity Focused Ultrasound for the Ablation of Prostate Tissue in Men With Localized Prostate Cancer.
Clinical genitourinary cancer
2024: 102113
Abstract
INTRODUCTION: Food and Drug Administration must make decisions about emerging high intensity focused ultrasound (HIFU) devices that may lack relevant clinical oncologic data but present with known side effects. This study aims to capture patients' perspective by quantifying their preferences regarding the available benefit and important side effects associated with HIFU for localized prostate cancer.MATERIALS AND METHODS: Preferences for HIFU outcomes were examined using a discrete choice experiment survey. Participants were asked to choose a preferred treatment option in 9 choice questions. Each included a pair of hypothetical treatment profiles that have similar attributes/outcomes with varying levels. Outcomes included prostate biopsy outcome and treatment-related risks of erectile dysfunction (ED) and urinary incontinence (UI). We calculated the maximum risk of side effect patients were willing to tolerate in exchange for increased benefit. Preferences were further explored via clinical and demographic data.RESULTS: About 223 subjects with a mean age of 64.8 years completed the survey. Respondents were willing to accept a 1.51%-point increase in new ED risk for a 1%-point increase in favorable biopsy outcome. They were also willing to accept a 0.93%-point increase in new UI risk for a 1%-point increase in biopsy outcome. Subjects who perceived their cancer to be more aggressive had higher risk tolerance for UI. Younger men were willing to tolerate less ED risk than older men. Respondents with greater than college level of education had a lower risk tolerance for ED or UI.CONCLUSIONS: Results may inform development and regulatory evaluation for future HIFU ablation devices by providing supplemental information from the patient perspective.
View details for DOI 10.1016/j.clgc.2024.102113
View details for PubMedID 38845330
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PREDICTORS OF TREATMENT FAILURE AFTER FOCAL HIGH-INTENSITY FOCUSED ULTRASOUND (HIFU) OF LOCALIZED PROSTATE CANCER
LIPPINCOTT WILLIAMS & WILKINS. 2024: E411-E412
View details for Web of Science ID 001263885301276
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ARTIFICIAL INTELLIGENCE-ASSISTED PROSTATE CANCER DETECTION ON B-MODE TRANSRECTAL ULTRASOUND IMAGES
LIPPINCOTT WILLIAMS & WILKINS. 2024: E511
View details for Web of Science ID 001263885301468
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AI VS. UROLOGISTS: A COMPARATIVE ANALYSIS FOR PROSTATE CANCER DETECTION ON TRANSRECTAL B-MODE ULTRASOUND
LIPPINCOTT WILLIAMS & WILKINS. 2024: E1056
View details for Web of Science ID 001263885303367
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RAPHIA: A deep learning pipeline for the registration of MRI and whole-mount histopathology images of the prostate.
Computers in biology and medicine
2024; 173: 108318
Abstract
Image registration can map the ground truth extent of prostate cancer from histopathology images onto MRI, facilitating the development of machine learning methods for early prostate cancer detection. Here, we present RAdiology PatHology Image Alignment (RAPHIA), an end-to-end pipeline for efficient and accurate registration of MRI and histopathology images. RAPHIA automates several time-consuming manual steps in existing approaches including prostate segmentation, estimation of the rotation angle and horizontal flipping in histopathology images, and estimation of MRI-histopathology slice correspondences. By utilizing deep learning registration networks, RAPHIA substantially reduces computational time. Furthermore, RAPHIA obviates the need for a multimodal image similarity metric by transferring histopathology image representations to MRI image representations and vice versa. With the assistance of RAPHIA, novice users achieved expert-level performance, and their mean error in estimating histopathology rotation angle was reduced by 51% (12 degrees vs 8 degrees), their mean accuracy of estimating histopathology flipping was increased by 5% (95.3% vs 100%), and their mean error in estimating MRI-histopathology slice correspondences was reduced by 45% (1.12 slices vs 0.62 slices). When compared to a recent conventional registration approach and a deep learning registration approach, RAPHIA achieved better mapping of histopathology cancer labels, with an improved mean Dice coefficient of cancer regions outlined on MRI and the deformed histopathology (0.44 vs 0.48 vs 0.50), and a reduced mean per-case processing time (51 vs 11 vs 4.5 min). The improved performance by RAPHIA allows efficient processing of large datasets for the development of machine learning models for prostate cancer detection on MRI. Our code is publicly available at: https://github.com/pimed/RAPHIA.
View details for DOI 10.1016/j.compbiomed.2024.108318
View details for PubMedID 38522253
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Stockholm3 validation in a multi-ethnic cohort for prostate cancer (SEPTA) detection: A multicentered, prospective trial.
LIPPINCOTT WILLIAMS & WILKINS. 2024: 262
View details for DOI 10.1200/JCO.2024.42.4_suppl.262
View details for Web of Science ID 001266676900273
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Improving Automated Prostate Cancer Detection and Classification Accuracy with Multi-scale Cancer Information
SPRINGER INTERNATIONAL PUBLISHING AG. 2024: 341-350
View details for DOI 10.1007/978-3-031-45673-2_34
View details for Web of Science ID 001109643200034
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A deep learning framework to assess the feasibility of localizing prostate cancer on b-mode transrectal ultrasound images
SPIE-INT SOC OPTICAL ENGINEERING. 2024
View details for DOI 10.1117/12.3008819
View details for Web of Science ID 001223524400023
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Deep Learning for Prostate and Central Gland Segmentation on Micro-Ultrasound Images
SPIE-INT SOC OPTICAL ENGINEERING. 2024
View details for DOI 10.1117/12.3008845
View details for Web of Science ID 001223524400005
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SwinTransformer-Based Affine Registration of MRI and Ultrasound Images of the Prostate
SPIE-INT SOC OPTICAL ENGINEERING. 2024
View details for DOI 10.1117/12.3008797
View details for Web of Science ID 001223524400006
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ArtHiFy: Artificial Histopathology-style Features for Improving MRI-Based Prostate Cancer Detection
SPIE-INT SOC OPTICAL ENGINEERING. 2024
View details for DOI 10.1117/12.3006879
View details for Web of Science ID 001208134600061
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Prediction and Mapping of Intraprostatic Tumor Extent with Artificial Intelligence.
European urology open science
2023; 54: 20-27
Abstract
Background: Magnetic resonance imaging (MRI) underestimation of prostate cancer extent complicates the definition of focal treatment margins.Objective: To validate focal treatment margins produced by an artificial intelligence (AI) model.Design setting and participants: Testing was conducted retrospectively in an independent dataset of 50 consecutive patients who had radical prostatectomy for intermediate-risk cancer. An AI deep learning model incorporated multimodal imaging and biopsy data to produce three-dimensional cancer estimation maps and margins. AI margins were compared with conventional MRI regions of interest (ROIs), 10-mm margins around ROIs, and hemigland margins. The AI model also furnished predictions of negative surgical margin probability, which were assessed for accuracy.Outcome measurements and statistical analysis: Comparing AI with conventional margins, sensitivity was evaluated using Wilcoxon signed-rank tests and negative margin rates using chi-square tests. Predicted versus observed negative margin probability was assessed using linear regression. Clinically significant prostate cancer (International Society of Urological Pathology grade ≥2) delineated on whole-mount histopathology served as ground truth.Results and limitations: The mean sensitivity for cancer-bearing voxels was higher for AI margins (97%) than for conventional ROIs (37%, p<0.001), 10-mm ROI margins (93%, p=0.24), and hemigland margins (94%, p<0.001). For index lesions, AI margins were more often negative (90%) than conventional ROIs (0%, p<0.001), 10-mm ROI margins (82%, p=0.24), and hemigland margins (66%, p=0.004). Predicted and observed negative margin probabilities were strongly correlated (R2=0.98, median error=4%). Limitations include a validation dataset derived from a single institution's prostatectomy population.Conclusions: The AI model was accurate and effective in an independent test set. This approach could improve and standardize treatment margin definition, potentially reducing cancer recurrence rates. Furthermore, an accurate assessment of negative margin probability could facilitate informed decision-making for patients and physicians.Patient summary: Artificial intelligence was used to predict the extent of tumors in surgically removed prostate specimens. It predicted tumor margins more accurately than conventional methods.
View details for DOI 10.1016/j.euros.2023.05.018
View details for PubMedID 37545845
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Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning.
JCO precision oncology
2023; 7: e2200668
Abstract
Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes.Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues.From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC.Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.
View details for DOI 10.1200/PO.22.00668
View details for PubMedID 37285559
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Reply to Carmen Gravina, Riccardo Lombardo, and Cosimo De Nunzio's Letter to the Editor re: Yash S. Khandwala, Simon John Christoph Soerensen, Shravan Morisetty, et al. The Association of Tissue Change and Treatment Success During High-intensity Focused Ultrasound Focal Therapy for Prostate Cancer. Eur Urol Focus. In press. https://doi.org/10.1016/j.euf.2022.10.010.
European urology focus
2023
View details for DOI 10.1016/j.euf.2023.03.019
View details for PubMedID 37012086
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IMPROVING PROSTATE CANCER DETECTION ON MRI WITH DEEP LEARNING, CLINICAL VARIABLES, AND RADIOMICS
LIPPINCOTT WILLIAMS & WILKINS. 2023: E665
View details for Web of Science ID 000994549502147
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DETECTION OF CLINICALLY SIGNIFICANT PROSTATE CANCER ON MRI: A COMPARISON OF AN ARTIFICIAL INTELLIGENCE MODEL VERSUS RADIOLOGISTS
LIPPINCOTT WILLIAMS & WILKINS. 2023: E103
View details for Web of Science ID 000994549500202
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Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning
IEEE TRANSACTIONS ON MEDICAL IMAGING
2023; 42 (3): 697-712
Abstract
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a wide range of clinically relevant tasks. This limits the development of registration methods, the adoption of research advances into practice, and a fair benchmark across competing approaches. The Learn2Reg challenge addresses these limitations by providing a multi-task medical image registration data set for comprehensive characterisation of deformable registration algorithms. A continuous evaluation will be possible at https://learn2reg.grand-challenge.org. Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation. We established an easily accessible framework for training and validation of 3D registration methods, which enabled the compilation of results of over 65 individual method submissions from more than 20 unique teams. We used a complementary set of metrics, including robustness, accuracy, plausibility, and runtime, enabling unique insight into the current state-of-the-art of medical image registration. This paper describes datasets, tasks, evaluation methods and results of the challenge, as well as results of further analysis of transferability to new datasets, the importance of label supervision, and resulting bias. While no single approach worked best across all tasks, many methodological aspects could be identified that push the performance of medical image registration to new state-of-the-art performance. Furthermore, we demystified the common belief that conventional registration methods have to be much slower than deep-learning-based methods.
View details for DOI 10.1109/TMI.2022.3213983
View details for Web of Science ID 000971629600011
View details for PubMedID 36264729
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MIC-CUSP: Multimodal Image Correlations for Ultrasound-Based Prostate Cancer Detection
SPRINGER INTERNATIONAL PUBLISHING AG. 2023: 121-131
View details for DOI 10.1007/978-3-031-44521-7_12
View details for Web of Science ID 001115849400012
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NCCN Guidelines Insights: Prostate Cancer Early Detection, Version 1.2023.
Journal of the National Comprehensive Cancer Network : JNCCN
2023; 21 (3): 236-246
Abstract
The NCCN Guidelines for Prostate Cancer Early Detection provide recommendations for individuals with a prostate who opt to participate in an early detection program after receiving the appropriate counseling on the pros and cons. These NCCN Guidelines Insights provide a summary of recent updates to the NCCN Guidelines with regard to the testing protocol, use of multiparametric MRI, and management of negative biopsy results to optimize the detection of clinically significant prostate cancer and minimize the detection of indolent disease.
View details for DOI 10.6004/jnccn.2023.0014
View details for PubMedID 36898362
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A Pilot Study of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for Biopsy Guidance in Patients with Suspected Prostate Cancer.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
2022
Abstract
Purpose: Targeting of lesions seen on multiparametric MRI (mpMRI) improves prostate cancer (PC) detection at biopsy. However, 20-65% of highly suspicious lesions on mpMRI (PI-RADS 4 or 5) are false positives (FP), while 5-10% of clinically significant PC (csPC) are missed. Prostate specific membrane antigen (PSMA) and gastrin-releasing peptide receptors (GRPR) are both overexpressed in PC. We therefore aimed to evaluate the potential of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for biopsy guidance in patients with suspected PC. Methods: A highly selective cohort of 13 men, aged 58.0±7.1 years, with suspected PC (persistently high prostate-specific antigen [PSA] and PSA density) but negative or equivocal mpMRI and/or negative biopsy were prospectively enrolled to undergo 68Ga-PSMA11 and 68Ga-RM2 PET/MRI. PET/MRI included whole-body and dedicated pelvic imaging after a delay of 20 minutes. All patients had targeted biopsy of any lesions seen on PET followed by standard 12-core biopsy. Maximum standardized uptake values (SUVmax) of suspected PC lesions were collected and compared to gold standard biopsy. Results: PSA and PSA density at enrollment were 9.8±6.0 (1.5-25.5) ng/mL and 0.20±0.18 (0.06-0.68) ng/mL2, respectively. Standardized systematic biopsy revealed a total of 14 PC in 8 participants: 7 were csPC and 7 were non-clinically significant PC (ncsPC). 68Ga-PSMA11 identified 25 lesions, of which 11 (44%) were true positive (TP) (5 csPC). 68Ga-RM2 showed 27 lesions, of which 14 (52%) were TP, identifying all 7 csPC and also 7 ncsPC. There were 17 concordant lesions in 11 patients vs. 14 discordant lesions in 7 patients between 68Ga-PSMA11 and 68Ga-RM2 PET. Incongruent lesions had the highest rate of FP (12 FP vs. 2 TP). SUVmax was significantly higher for TP than FP lesions in delayed pelvic imaging for 68Ga-PSMA11 (6.49±4.14 vs. 4.05±1.55, P = 0.023) but not for whole-body images, nor for 68Ga-RM2. Conclusion: Our results show that 68Ga-PSMA11 and 68Ga-RM2 PET/MRI are feasible for biopsy guidance in suspected PC. Both radiopharmaceuticals detected additional clinically significant cancers not seen on mpMRI in this selective cohort. 68Ga-RM2 PET/MRI identified all csPC confirmed at biopsy.
View details for DOI 10.2967/jnumed.122.264448
View details for PubMedID 36396456
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The Association of Tissue Change and Treatment Success During High-intensity Focused Ultrasound Focal Therapy for Prostate Cancer.
European urology focus
2022
Abstract
BACKGROUND: Tissue preservation strategies have been increasingly used for the management of localized prostate cancer. Focal ablation using ultrasound-guided high-intensity focused ultrasound (HIFU) has demonstrated promising short and medium-term oncological outcomes. Advancements in HIFU therapy such as the introduction of tissue change monitoring (TCM) aim to further improve treatment efficacy.OBJECTIVE: To evaluate the association between intraoperative TCM during HIFU focal therapy for localized prostate cancer and oncological outcomes 12 mo afterward.DESIGN, SETTING, AND PARTICIPANTS: Seventy consecutive men at a single institution with prostate cancer were prospectively enrolled. Men with prior treatment, metastases, or pelvic radiation were excluded to obtain a final cohort of 55 men.INTERVENTION: All men underwent HIFU focal therapy followed by magnetic resonance (MR)-fusion biopsy 12 mo later. Tissue change was quantified intraoperatively by measuring the backscatter of ultrasound waves during ablation.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Gleason grade group (GG) ≥2 cancer on postablation biopsy was the primary outcome. Secondary outcomes included GG ≥1 cancer, Prostate Imaging Reporting and Data System (PI-RADS) scores ≥3, and evidence of tissue destruction on post-treatment magnetic resonance imaging (MRI). A Student's t - test analysis was performed to evaluate the mean TCM scores and efficacy of ablation measured by histopathology. Multivariate logistic regression was also performed to identify the odds of residual cancer for each unit increase in the TCM score.RESULTS AND LIMITATIONS: A lower mean TCM score within the region of the tumor (0.70 vs 0.97, p=0.02) was associated with the presence of persistent GG ≥2 cancer after HIFU treatment. Adjusting for initial prostate-specific antigen, PI-RADS score, Gleason GG, positive cores, and age, each incremental increase of TCM was associated with an 89% reduction in the odds (odds ratio: 0.11, confidence interval: 0.01-0.97) of having residual GG ≥2 cancer on postablation biopsy. Men with higher mean TCM scores (0.99 vs 0.72, p=0.02) at the time of treatment were less likely to have abnormal MRI (PI-RADS ≥3) at 12 mo postoperatively. Cases with high TCM scores also had greater tissue destruction measured on MRI and fewer visible lesions on postablation MRI.CONCLUSIONS: Tissue change measured using TCM values during focal HIFU of the prostate was associated with histopathology and radiological outcomes 12 mo after the procedure.PATIENT SUMMARY: In this report, we looked at how well ultrasound changes of the prostate during focal high-intensity focused ultrasound (HIFU) therapy for the treatment of prostate cancer predict patient outcomes. We found that greater tissue change measured by the HIFU device was associated with less residual cancer at 1 yr. This tool should be used to ensure optimal ablation of the cancer and may improve focal therapy outcomes in the future.
View details for DOI 10.1016/j.euf.2022.10.010
View details for PubMedID 36372735
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A Pilot Study of 68Ga-PSMA11 and 68Ga-RM2 PET/MRI for Evaluation of Prostate Cancer Response to High Intensity Focused Ultrasound (HIFU) Therapy.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
2022
Abstract
Rationale: Focal therapy for localized prostate cancer (PC) using high intensity focused ultrasound (HIFU) is gaining in popularity as it is non-invasive and associated with fewer side effects than standard whole-gland treatments. However, better methods to evaluate response to HIFU ablation are an unmet need. Prostate specific membrane antigen (PSMA) and gastrin-releasing peptide receptors (GRPR) are both overexpressed in PC. In this study, we evaluated a novel approach of using both 68Ga-RM2 and 68Ga-PSMA11 PET/MRI in each patient before and after HIFU to assess accuracy of target tumor localization and response to treatment. Methods: Fourteen men, 64.5 ± 8.0 (range 48-78) years-old, with newly diagnosed PC were prospectively enrolled. Pre-HIFU, patients underwent prostate biopsy, multiparametric MRI (mpMRI), 68Ga-PSMA11, and 68Ga-RM2 PET/MRI. Response to treatment was assessed at a minimum of 6 months after HIFU with prostate biopsy (n = 13), as well as 68Ga-PSMA11 and 68Ga-RM2 PET/MRI (n = 14). Maximum and peak standardized uptake values (SUVmax and SUVpeak) of known or suspected PC lesions were collected. Results: Pre-HIFU biopsy revealed 18 cancers of which 14 were clinically significant (Gleason score ≥3+4). mpMRI identified 18 lesions; 14 of them were ≥PI-RADS 4. 68Ga-PSMA11 and 68Ga-RM2 PET/MRI each showed 23 positive intraprostatic lesions; 21 were congruent in 13 patients and five were incongruent in 5 patients. Pre-HIFU, 68Ga-PSMA11 identified all target tumors while 68Ga-RM2 PET/MRI missed two tumors. Post-HIFU, 68Ga-RM2 and 68Ga-PSMA11 PET/MRI both identified clinically significant residual disease in one patient. Three significant ipsilateral recurrent lesions were identified, whereas one was missed by 68Ga-PSMA11. Pre-treatment prostate specific antigen (PSA) decreased significantly after HIFU by 66%. Concordantly, pre-treatment SUVmax decreased significantly after HIFU for 68Ga-PSMA11 (P = 0.001) and 68Ga-RM2 (P = 0.005). Conclusion: The results of this pilot study show that 68Ga-PSMA11 and 68Ga-RM2 PET/MRI identified the target tumor for HIFU in 100% and 86%, respectively, and accurately verified response to treatment. PET might be a useful tool in the guidance and monitoring of treatment success in patients receiving focal therapy for PC. These preliminary findings warrant larger studies for validation.
View details for DOI 10.2967/jnumed.122.264783
View details for PubMedID 36328488
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A review of artificial intelligence in prostate cancer detection on imaging.
Therapeutic advances in urology
2022; 14: 17562872221128791
Abstract
A multitude of studies have explored the role of artificial intelligence (AI) in providing diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection, risk-stratification, and management. This review provides a comprehensive overview of relevant literature regarding the use of AI models in (1) detecting prostate cancer on radiology images (magnetic resonance and ultrasound imaging), (2) detecting prostate cancer on histopathology images of prostate biopsy tissue, and (3) assisting in supporting tasks for prostate cancer detection (prostate gland segmentation, MRI-histopathology registration, MRI-ultrasound registration). We discuss both the potential of these AI models to assist in the clinical workflow of prostate cancer diagnosis, as well as the current limitations including variability in training data sets, algorithms, and evaluation criteria. We also discuss ongoing challenges and what is needed to bridge the gap between academic research on AI for prostate cancer and commercial solutions that improve routine clinical care.
View details for DOI 10.1177/17562872221128791
View details for PubMedID 36249889
View details for PubMedCentralID PMC9554123
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Tempering optimism for MRI-guided focused ultrasound therapy - Authors' reply.
The Lancet. Oncology
2022; 23 (10): e439
View details for DOI 10.1016/S1470-2045(22)00557-5
View details for PubMedID 36174620
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Tempering optimism for MRI-guided focused ultrasound therapy Reply
LANCET ONCOLOGY
2022; 23 (10): E439
View details for DOI 10.1016/S1470-2045(22)00519-8
View details for Web of Science ID 000878568900006
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Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study.
Medical image analysis
2022; 82: 102620
Abstract
Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion relies on accurate segmentation of the prostate on ultrasound images. Yet, the reduced signal-to-noise ratio and artifacts (e.g., speckle and shadowing) in ultrasound images limit the performance of automated prostate segmentation techniques and generalizing these methods to new image domains is inherently difficult. In this study, we address these challenges by introducing a novel 2.5D deep neural network for prostate segmentation on ultrasound images. Our approach addresses the limitations of transfer learning and finetuning methods (i.e., drop in performance on the original training data when the model weights are updated) by combining a supervised domain adaptation technique and a knowledge distillation loss. The knowledge distillation loss allows the preservation of previously learned knowledge and reduces the performance drop after model finetuning on new datasets. Furthermore, our approach relies on an attention module that considers model feature positioning information to improve the segmentation accuracy. We trained our model on 764 subjects from one institution and finetuned our model using only ten subjects from subsequent institutions. We analyzed the performance of our method on three large datasets encompassing 2067 subjects from three different institutions. Our method achieved an average Dice Similarity Coefficient (Dice) of 94.0±0.03 and Hausdorff Distance (HD95) of 2.28mm in an independent set of subjects from the first institution. Moreover, our model generalized well in the studies from the other two institutions (Dice: 91.0±0.03; HD95: 3.7mm and Dice: 82.0±0.03; HD95: 7.1mm). We introduced an approach that successfully segmented the prostate on ultrasound images in a multi-center study, suggesting its clinical potential to facilitate the accurate fusion of ultrasound and MRI images to drive biopsy and image-guided treatments.
View details for DOI 10.1016/j.media.2022.102620
View details for PubMedID 36148705
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Evaluation of post-ablation mpMRI as a predictor of residual prostate cancer after focal high intensity focused ultrasound (HIFU) ablation.
Urologic oncology
2022
Abstract
PURPOSE: To evaluate the performance of multiparametric magnetic resonance imaging (mpMRI) and PSA testing in follow-up after high intensity focused ultrasound (HIFU) focal therapy for localized prostate cancer.METHODS: A total of 73 men with localized prostate cancer were prospectively enrolled and underwent focal HIFU followed by per-protocol PSA and mpMRI with systematic plus targeted biopsies at 12 months after treatment. We evaluated the association between post-treatment mpMRI and PSA with disease persistence on the post-ablation biopsy. We also assessed post-treatment functional and oncological outcomes.RESULTS: Median age was 69 years (Interquartile Range (IQR): 66-74) and median PSA was 6.9 ng/dL (IQR: 5.3-9.9). Of 19 men with persistent GG ≥ 2 disease, 58% (11 men) had no visible lesions on MRI. In the 14 men with PIRADS 4 or 5 lesions, 7 (50%) had either no cancer or GG 1 cancer at biopsy. Men with false negative mpMRI findings had higher PSA density (0.16 vs. 0.07 ng/mL2, P = 0.01). No change occurred in the mean Sexual Health Inventory for Men (SHIM) survey scores (17.0 at baseline vs. 17.7 post-treatment, P = 0.75) or International Prostate Symptom Score (IPSS) (8.1 at baseline vs. 7.7 at 24 months, P = 0.81) after treatment.CONCLUSIONS: Persistent GG ≥ 2 cancer may occur after focal HIFU. mpMRI alone without confirmatory biopsy may be insufficient to rule out residual cancer, especially in patients with higher PSA density. Our study also validates previously published studies demonstrating preservation of urinary and sexual function after HIFU treatment.
View details for DOI 10.1016/j.urolonc.2022.07.017
View details for PubMedID 36058811
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A Pilot Study of Ga-68-PSMA11 and Ga-68-RM2 PET/MRI for Evaluation of Prostate Cancer Response to High Intensity Focused Ultrasound (HIFU) Therapy
SPRINGER. 2022: S497-S498
View details for Web of Science ID 000857046602123
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A Pilot Study of Ga-68-PSMA11 and 68Ga-RM2 PET/MRI for Biopsy Guidance in Patients with Suspected Prostate Cancer
SPRINGER. 2022: S484
View details for Web of Science ID 000857046602091
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Multi-institutional analysis of clinical and imaging risk factors for detecting clinically significant prostate cancer in men with PI-RADS 3 lesions.
Cancer
2022
Abstract
BACKGROUND: Most Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions do not contain clinically significant prostate cancer (CSPCa; grade group ≥2). This study was aimed at identifying clinical and magnetic resonance imaging (MRI)-derived risk fac- tors that predict CSPCa in men with PI-RADS 3 lesions.METHODS: This study analyzed the detection of CSPCa in men who underwent MRI-targeted biopsy for PI-RADS 3 lesions. Multivariable logistic regression models with goodness-of-fit testing were used to identify variables associated with CSPCa. Receiver operating curves and decision curve analyses were used to estimate the clinical utility of a predictive model.RESULTS: Of the 1784 men reviewed, 1537 were included in the training cohort, and 247 were included in the validation cohort. The 309 men with CSPCa (17.3%) were older, had a higher prostate-specific antigen (PSA) density, and had a greater likelihood of an anteriorly located lesion than men without CSPCa (p < .01). Multivariable analysis revealed that PSA density (odds ratio [OR], 1.36; 95% confidence interval [CI], 1.05-1.85; p < .01), age (OR, 1.05; 95% CI, 1.02-1.07; p < .01), and a biopsy-naive status (OR, 1.83; 95% CI, 1.38-2.44) were independently associated with CSPCa. A prior negative biopsy was negatively associated (OR, 0.35; 95% CI, 0.24-0.50; p < .01). The application of the model to the validation cohort resulted in an area under the curve of 0.78. A predicted risk threshold of 12% could have prevented 25% of biopsies while detecting almost 95% of CSPCas with a sensitivity of 94% and a specificity of 34%.CONCLUSIONS: For PI-RADS 3 lesions, an elevated PSA density, older age, and a biopsy-naive status were associated with CSPCa, whereas a prior negative biopsy was negatively associated. A predictive model could prevent PI-RADS 3 biopsies while missing few CSPCas.LAY SUMMARY: Among men with an equivocal lesion (Prostate Imaging-Reporting and Data System 3) on multiparametric magnetic resonance imaging (mpMRI), those who are older, those who have a higher prostate-specific antigen density, and those who have never had a biopsy before are at higher risk for having clinically significant prostate cancer (CSPCa) on subsequent biopsy. However, men with at least one negative biopsy have a lower risk of CSPCa. A new predictive model can greatly reduce the need to biopsy equivocal lesions noted on mpMRI while missing only a few cases of CSPCa.
View details for DOI 10.1002/cncr.34355
View details for PubMedID 35819253
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MRI-guided focused ultrasound focal therapy for patients with intermediate-risk prostate cancer: a phase 2b, multicentre study.
The Lancet. Oncology
2022
Abstract
BACKGROUND: Men with grade group 2 or 3 prostate cancer are often considered ineligible for active surveillance; some patients with grade group 2 prostate cancer who are managed with active surveillance will have early disease progression requiring radical therapy. This study aimed to investigate whether MRI-guided focused ultrasound focal therapy can safely reduce treatment burden for patients with localised grade group 2 or 3 intermediate-risk prostate cancer.METHODS: In this single-arm, multicentre, phase 2b study conducted at eight health-care centres in the USA, we recruited men aged 50 years and older with unilateral, MRI-visible, primary, intermediate-risk, previously untreated prostate adenocarcinoma (prostate-specific antigen ≤20 ng/mL, grade group 2 or 3; tumour classification ≤T2) confirmed on combined biopsy (combining MRI-targeted and systematic biopsies). MRI-guided focused ultrasound energy, sequentially titrated to temperatures sufficient for tissue ablation (about 60-70°C), was delivered to the index lesion and a planned margin of 5 mm or more of normal tissue, using real-time magnetic resonance thermometry for intraoperative monitoring. Co-primary outcomes were oncological outcomes (absence of grade group 2 and higher cancer in the treated area at 6-month and 24-month combined biopsy; when 24-month biopsy data were not available and grade group 2 or higher cancer had occurred in the treated area at 6 months, the 6-month biopsy results were included in the final analysis) and safety (adverse events up to 24 months) in all patients enrolled in the study. This study is registered with ClinicalTrials.gov, NCT01657942, and is no longer recruiting.FINDINGS: Between May 4, 2017, and Dec 21, 2018, we assessed 194 patients for eligibility and treated 101 patients with MRI-guided focused ultrasound. Median age was 63 years (IQR 58-67) and median concentration of prostate-specific antigen was 5·7 ng/mL (IQR 4·2-7·5). Most cancers were grade group 2 (79 [78%] of 101). At 24 months, 78 (88% [95% CI 79-94]) of 89 men had no evidence of grade group 2 or higher prostate cancer in the treated area. No grade 4 or grade 5 treatment-related adverse events were reported, and only one grade 3 adverse event (urinary tract infection) was reported. There were no treatment-related deaths.INTERPRETATION: 24-month biopsy outcomes show that MRI-guided focused ultrasound focal therapy is safe and effectively treats grade group 2 or 3 prostate cancer. These results support focal therapy for select patients and its use in comparative trials to determine if a tissue-preserving approach is effective in delaying or eliminating the need for radical whole-gland treatment in the long term.FUNDING: Insightec and the National Cancer Institute.
View details for DOI 10.1016/S1470-2045(22)00251-0
View details for PubMedID 35714666
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Computational Detection of Extraprostatic Extension of Prostate Cancer on Multiparametric MRI Using Deep Learning.
Cancers
2022; 14 (12)
Abstract
The localization of extraprostatic extension (EPE), i.e., local spread of prostate cancer beyond the prostate capsular boundary, is important for risk stratification and surgical planning. However, the sensitivity of EPE detection by radiologists on MRI is low (57% on average). In this paper, we propose a method for computational detection of EPE on multiparametric MRI using deep learning. Ground truth labels of cancers and EPE were obtained in 123 patients (38 with EPE) by registering pre-surgical MRI with whole-mount digital histopathology images from radical prostatectomy. Our approach has two stages. First, we trained deep learning models using the MRI as input to generate cancer probability maps both inside and outside the prostate. Second, we built an image post-processing pipeline that generates predictions for EPE location based on the cancer probability maps and clinical knowledge. We used five-fold cross-validation to train our approach using data from 74 patients and tested it using data from an independent set of 49 patients. We compared two deep learning models for cancer detection: (i) UNet and (ii) the Correlated Signature Network for Indolent and Aggressive prostate cancer detection (CorrSigNIA). The best end-to-end model for EPE detection, which we call EPENet, was based on the CorrSigNIA cancer detection model. EPENet was successful at detecting cancers with extraprostatic extension, achieving a mean area under the receiver operator characteristic curve of 0.72 at the patient-level. On the test set, EPENet had 80.0% sensitivity and 28.2% specificity at the patient-level compared to 50.0% sensitivity and 76.9% specificity for the radiologists. To account for spatial location of predictions during evaluation, we also computed results at the sextant-level, where the prostate was divided into sextants according to standard systematic 12-core biopsy procedure. At the sextant-level, EPENet achieved mean sensitivity 61.1% and mean specificity 58.3%. Our approach has the potential to provide the location of extraprostatic extension using MRI alone, thus serving as an independent diagnostic aid to radiologists and facilitating treatment planning.
View details for DOI 10.3390/cancers14122821
View details for PubMedID 35740487
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Bridging the gap between prostate radiology and pathology through machine learning.
Medical physics
2022
Abstract
Prostate cancer remains the second deadliest cancer for American men despite clinical advancements. Currently, Magnetic Resonance Imaging (MRI) is considered the most sensitive non-invasive imaging modality that enables visualization, detection and localization of prostate cancer, and is increasingly used to guide targeted biopsies for prostate cancer diagnosis. However, its utility remains limited due to high rates of false positives and false negatives as well as low inter-reader agreements.Machine learning methods to detect and localize cancer on prostate MRI can help standardize radiologist interpretations. However, existing machine learning methods vary not only in model architecture, but also in the ground truth labeling strategies used for model training. We compare different labeling strategies and the effects they have on the performance of different machine learning models for prostate cancer detection on MRI.Four different deep learning models (SPCNet, U-Net, branched U-Net, and DeepLabv3+) were trained to detect prostate cancer on MRI using 75 patients with radical prostatectomy, and evaluated using 40 patients with radical prostatectomy and 275 patients with targeted biopsy. Each deep learning model was trained with four different label types: pathology-confirmed radiologist labels, pathologist labels on whole-mount histopathology images, and lesion-level and pixel-level digital pathologist labels (previously validated deep learning algorithm on histopathology images to predict pixel-level Gleason patterns) on whole-mount histopathology images. The pathologist and digital pathologist labels (collectively referred to as pathology labels) were mapped onto pre-operative MRI using an automated MRI-histopathology registration platform.Radiologist labels missed cancers (ROC-AUC: 0.75 - 0.84), had lower lesion volumes (~68% of pathology lesions), and lower Dice overlaps (0.24 - 0.28) when compared with pathology labels. Consequently, machine learning models trained with radiologist labels also showed inferior performance compared to models trained with pathology labels. Digital pathologist labels showed high concordance with pathologist labels of cancer (lesion ROC-AUC: 0.97 - 1, lesion Dice: 0.75 - 0.93). Machine learning models trained with digital pathologist labels had the highest lesion detection rates in the radical prostatectomy cohort (aggressive lesion ROC-AUC: 0.91 - 0.94), and had generalizable and comparable performance to pathologist label trained-models in the targeted biopsy cohort (aggressive lesion ROC-AUC: 0.87 - 0.88), irrespective of the deep learning architecture. Moreover, machine learning models trained with pixel-level digital pathologist labels were able to selectively identify aggressive and indolent cancer components in mixed lesions on MRI, which is not possible with any human-annotated label type.Machine learning models for prostate MRI interpretation that are trained with digital pathologist labels showed higher or comparable performance with pathologist label-trained models in both radical prostatectomy and targeted biopsy cohort. Digital pathologist labels can reduce challenges associated with human annotations, including labor, time, inter- and intra-reader variability, and can help bridge the gap between prostate radiology and pathology by enabling the training of reliable machine learning models to detect and localize prostate cancer on MRI. This article is protected by copyright. All rights reserved.
View details for DOI 10.1002/mp.15777
View details for PubMedID 35633505
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Correlation of 68Ga-RM2 PET with Post-Surgery Histopathology Findings in Patients with Newly Diagnosed Intermediate- or High-Risk Prostate Cancer.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
2022
Abstract
Rationale: 68Ga-RM2 targets gastrin-releasing peptide receptors (GRPR), which are overexpressed in prostate cancer (PC). Here, we compared pre-operative 68Ga-RM2 PET to post-surgery histopathology in patients with newly diagnosed intermediate- or high-risk PC. Methods: Forty-one men, 64.0+/-6.7-year-old, were prospectively enrolled. PET images were acquired 42 - 72 (median+/-SD 52.5+/-6.5) minutes after injection of 118.4 - 247.9 (median+/-SD 138.0+/-22.2)MBq of 68Ga-RM2. PET findings were compared to pre-operative mpMRI (n = 36) and 68Ga-PSMA11 PET (n = 17) and correlated to post-prostatectomy whole-mount histopathology (n = 32) and time to biochemical recurrence. Nine participants decided to undergo radiation therapy after study enrollment. Results: All participants had intermediate (n = 17) or high-risk (n = 24) PC and were scheduled for prostatectomy. Prostate specific antigen (PSA) was 8.8+/-77.4 (range 2.5 - 504) ng/mL, and 7.6+/-5.3 (range 2.5 - 28.0) ng/mL when excluding participants who ultimately underwent radiation treatment. Pre-operative 68Ga-RM2 PET identified 70 intraprostatic foci of uptake in 40/41 patients. Post-prostatectomy histopathology was available in 32 patients in which 68Ga-RM2 PET identified 50/54 intraprostatic lesions (detection rate = 93%). 68Ga-RM2 uptake was recorded in 19 non-enlarged pelvic lymph nodes in 6 patients. Pathology confirmed lymph node metastases in 16 lesions, and follow-up imaging confirmed nodal metastases in 2 lesions. 68Ga-PSMA11 and 68Ga-RM2 PET identified 27 and 26 intraprostatic lesions, respectively, and 5 pelvic lymph nodes each in 17 patients. Concordance between 68Ga-RM2 and 68Ga-PSMA11 PET was found in 18 prostatic lesions in 11 patients, and 4 lymph nodes in 2 patients. Non-congruent findings were observed in 6 patients (intraprostatic lesions in 4 patients and nodal lesions in 2 patients). Both 68Ga-RM2 and 68Ga-PSMA11 had higher sensitivity and accuracy rates with 98%, 89%, and 95%, 89%, respectively, compared to mpMRI at 77% and 77%. Specificity was highest for mpMRI with 75% followed by 68Ga-PSMA11 (67%), and 68Ga-RM2 (65%). Conclusion: 68Ga-RM2 PET accurately detects intermediate- and high-risk primary PC with a detection rate of 93%. In addition, it showed significantly higher specificity and accuracy compared to mpMRI and similar performance to 68Ga-PSMA11 PET. These findings need to be confirmed in larger studies to identify which patients will benefit from one or the other or both radiopharmaceuticals.
View details for DOI 10.2967/jnumed.122.263971
View details for PubMedID 35552245
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68Ga-PSMA-11 PET/MRI in patients with newly diagnosed intermediate or high-risk prostate adenocarcinoma: PET findings correlate with outcomes after definitive treatment.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
2022
Abstract
Prostate-specific membrane antigen (PSMA) PET offers superior accuracy to other imaging modalities in initial staging of prostate cancer and is more likely to affect management. We examined the prognostic value of 68Ga-PSMA-11 uptake in primary lesion and presence of metastatic disease on PET in newly diagnosed prostate cancer patients prior to initial therapy. Methods: In a prospective study from April 2016 to December 2020, 68Ga-PSMA-11 PET/MRI was done in men with new diagnosis of intermediate or high-grade prostate cancer who were candidates for prostatectomy. Patients were followed up after initial therapy for up to 5 years. We examined the Kendall correlation between PET (intense uptake in primary lesion and presence of metastatic disease) and clinical and pathologic findings (grade group, extraprostatic extension, nodal involvement) relevant for risk stratification, and examined the relationship between PET findings and outcome using Kaplan-Meier analysis. Results: Seventy-three men, 64.0±6.3 years of age were imaged. Seventy-two had focal uptake in prostate and in 20 (27%), PSMA-avid metastatic disease was identified. Uptake correlated with grade group and prostate-specific antigen (PSA). Presence of PSMA metastasis correlated with grade group and pathologic nodal stage. PSMA PET had higher per-patients positivity than nodal dissection in patients with only 5-15 nodes removed (8/41 vs. 3/41) but lower positivity if more than 15 nodes were removed (13/21 vs. 10/21). High uptake in primary (SUVmax>12.5, P = .008) and presence of PSMA metastasis (P = .013) were associated with biochemical failure, and corresponding hazard ratios for recurrence within 2-years (4.93 and 3.95, respectively) were similar or higher than other clinicopathologic prognostic factors. Conclusions: 68Ga-PSMA-11 PET can risk stratify patients with intermediate or high-grade prostate cancer prior to prostatectomy based on degree of uptake in prostate and presence of metastatic disease.
View details for DOI 10.2967/jnumed.122.263897
View details for PubMedID 35512996
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MULTI-INSTITUTIONAL ANALYSIS OF CLINICAL AND IMAGING RISK FACTORS FOR DETECTING CLINICALLY SIGNIFICANT PROSTATE CANCER IN MEN WITH PI-RADS 3 LESIONS
LIPPINCOTT WILLIAMS & WILKINS. 2022: E959
View details for Web of Science ID 000836935508117
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Image quality assessment for machine learning tasks using meta-reinforcement learning.
Medical image analysis
2022; 78: 102427
Abstract
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is performed using machine learning algorithms, such as a neural-network-based task predictor for image classification or segmentation, the performance of the task predictor provides an objective estimate of task amenability. In this work, we use an IQA controller to predict the task amenability which, itself being parameterised by neural networks, can be trained simultaneously with the task predictor. We further develop a meta-reinforcement learning framework to improve the adaptability for both IQA controllers and task predictors, such that they can be fine-tuned efficiently on new datasets or meta-tasks. We demonstrate the efficacy of the proposed task-specific, adaptable IQA approach, using two clinical applications for ultrasound-guided prostate intervention and pneumonia detection on X-ray images.
View details for DOI 10.1016/j.media.2022.102427
View details for PubMedID 35344824
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The Learn2Reg 2021 MICCAI Grand Challenge (PIMed Team)
SPRINGER INTERNATIONAL PUBLISHING AG. 2022: 168-173
View details for DOI 10.1007/978-3-030-97281-3_24
View details for Web of Science ID 000786733400023
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Integrating zonal priors and pathomic MRI biomarkers for improved aggressive prostate cancer detection on MRI
SPIE-INT SOC OPTICAL ENGINEERING. 2022
View details for DOI 10.1117/12.2612433
View details for Web of Science ID 000838048600024
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Collaborative Quantization Embeddings for Intra-subject Prostate MR Image Registration
SPRINGER INTERNATIONAL PUBLISHING AG. 2022: 237-247
View details for DOI 10.1007/978-3-031-16446-0_23
View details for Web of Science ID 000867434800023
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EXTERNAL VALIDATION OF AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR PROSTATE CANCER GLEASON GRADING AND TUMOR QUANTIFICATION
LIPPINCOTT WILLIAMS & WILKINS. 2021: E1004
View details for Web of Science ID 000693689000506
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Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy
JOURNAL OF UROLOGY
2021; 206 (3): 605-612
View details for Web of Science ID 000711819100035
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DETAILED ANALYSIS OF MRI CONCORDANCE WITH PROSTATECTOMY HISTOPATHOLOGY USING DEEP LEARNING-BASED DIGITAL PATHOLOGY
LIPPINCOTT WILLIAMS & WILKINS. 2021: E813-E814
View details for Web of Science ID 000693689000126
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The stanford prostate cancer calculator: Development and external validation of online nomograms incorporating PIRADS scores to predict clinically significant prostate cancer.
Urologic oncology
2021
Abstract
BACKGROUND: While multiparametric MRI (mpMRI) has high sensitivity for detection of clinically significant prostate cancer (CSC), false positives and negatives remain common. Calculators that combine mpMRI with clinical variables can improve cancer risk assessment, while providing more accurate predictions for individual patients. We sought to create and externally validate nomograms incorporating Prostate Imaging Reporting and Data System (PIRADS) scores and clinical data to predict the presence of CSC in men of all biopsy backgrounds.METHODS: Data from 2125 men undergoing mpMRI and MR fusion biopsy from 2014 to 2018 at Stanford, Yale, and UAB were prospectively collected. Clinical data included age, race, PSA, biopsy status, PIRADS scores, and prostate volume. A nomogram predicting detection of CSC on targeted or systematic biopsy was created.RESULTS: Biopsy history, Prostate Specific Antigen (PSA) density, PIRADS score of 4 or 5, Caucasian race, and age were significant independent predictors. Our nomogram-the Stanford Prostate Cancer Calculator (SPCC)-combined these factors in a logistic regression to provide stronger predictive accuracy than PSA density or PIRADS alone. Validation of the SPCC using data from Yale and UAB yielded robust AUC values.CONCLUSIONS: The SPCC combines pre-biopsy mpMRI with clinical data to more accurately predict the probability of CSC in men of all biopsy backgrounds. The SPCC demonstrates strong external generalizability with successful validation in two separate institutions. The calculator is available as a free web-based tool that can direct real-time clinical decision-making.
View details for DOI 10.1016/j.urolonc.2021.06.004
View details for PubMedID 34247909
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Consumption of cruciferous vegetables and the risk of bladder cancer in a prospective US cohort: data from the NIH-AARP diet and health study.
American journal of clinical and experimental urology
2021; 9 (3): 229-238
Abstract
Abundant pre-clinical data suggest that consumption of cruciferous vegetables might protect against bladder cancer. While small-scale clinical evidence supports this hypothesis, population-level data is lacking. We tested the hypothesis that consumption of cruciferous vegetables is associated with a lower risk of bladder cancer in a large population-based study.We investigated the association between dietary consumption of cruciferous vegetables and the risk of bladder cancer in the NIH-American Association of Retired Persons (AARP) Diet and Health Study. Diet at baseline was collected with self-administered food-frequency questionnaires. Bladder cancer diagnoses were identified through linkage with state cancer registries. Hazard ratio (HR) and 95% confidence intervals (CI) were estimated with Cox proportional hazards models.Our analysis included 515,628 individuals. Higher intake of cruciferous vegetables, both overall and when stratified by variety (broccoli vs. brussels sprouts vs. cauliflower), were not associated with bladder cancer risk for men or women. A history of smoking did not affect the results.Our study shows no association between dietary consumption of cruciferous vegetables and incident bladder cancer.
View details for PubMedID 34327262
View details for PubMedCentralID PMC8303025
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Mapping PSA density to outcome of MRI-based active surveillance for prostate cancer through joint longitudinal-survival models.
Prostate cancer and prostatic diseases
2021
View details for DOI 10.1038/s41391-021-00373-w
View details for PubMedID 33958731
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A Pilot Study of68Ga-PSMA11 PET/MRI and68GaRM2 PET/MRI for Biopsy Guidance in Patients with Suspected Prostate Cancer
SOC NUCLEAR MEDICINE INC. 2021
View details for Web of Science ID 000713713600481
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Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on MRI for Targeted Biopsy.
The Journal of urology
2021: 101097JU0000000000001783
Abstract
PURPOSE: Targeted biopsy improves prostate cancer diagnosis. Accurate prostate segmentation on MRI is critical for accurate biopsy. Manual gland segmentation is tedious and time-consuming. We sought to develop a deep learning model to rapidly and accurately segment the prostate on MRI and to implement it as part of routine MR-US fusion biopsy in the clinic.MATERIALS AND METHODS: 905 subjects underwent multiparametric MRI at 29 institutions, followed by MR-US fusion biopsy at one institution. A urologic oncology expert segmented the prostate on axial T2-weighted MRI scans. We trained a deep learning model, ProGNet, on 805 cases. We retrospectively tested ProGNet on 100 independent internal and 56 external cases. We prospectively implemented ProGNet as part of the fusion biopsy procedure for 11 patients. We compared ProGNet performance to two deep learning networks (U-Net and HED) and radiology technicians. The Dice similarity coefficient (DSC) was used to measure overlap with expert segmentations. DSCs were compared using paired t-tests.RESULTS: ProGNet (DSC=0.92) outperformed U-Net (DSC=0.85, p <0.0001), HED (DSC=0.80, p< 0.0001), and radiology technicians (DSC=0.89, p <0.0001) in the retrospective internal test set. In the prospective cohort, ProGNet (DSC=0.93) outperformed radiology technicians (DSC=0.90, p <0.0001). ProGNet took just 35 seconds per case (vs. 10 minutes for radiology technicians) to yield a clinically utilizable segmentation file.CONCLUSIONS: This is the first study to employ a deep learning model for prostate gland segmentation for targeted biopsy in routine urologic clinical practice, while reporting results and releasing the code online. Prospective and retrospective evaluations revealed increased speed and accuracy.
View details for DOI 10.1097/JU.0000000000001783
View details for PubMedID 33878887
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Automated Detection of Aggressive and Indolent Prostate Cancer on Magnetic Resonance Imaging.
Medical physics
2021
Abstract
PURPOSE: While multi-parametric Magnetic Resonance Imaging (MRI) shows great promise in assisting with prostate cancer diagnosis and localization, subtle differences in appearance between cancer and normal tissue lead to many false positive and false negative interpretations by radiologists. We sought to automatically detect aggressive cancer (Gleason pattern ≥ 4) and indolent cancer (Gleason pattern 3) on a per-pixel basis on MRI to facilitate the targeting of aggressive cancer during biopsy.METHODS: We created the Stanford Prostate Cancer Network (SPCNet), a convolutional neural network model, trained to distinguish between aggressive cancer, indolent cancer, and normal tissue on MRI. Ground truth cancer labels were obtainedby registering MRI with whole-mount digital histopathology images from patients that underwent radical prostatectomy. Before registration, these histopathology images were automatically annotated to show Gleason patterns on a per-pixel basis. The model was trained on data from 78 patients that underwent radical prostatectomy and 24 patients without prostate cancer. The model was evaluated on a pixel and lesion level in 322 patients, including: 6 patients with normal MRI and no cancer, 23 patients that underwent radical prostatectomy, and 293 patients that underwent biopsy. Moreover, we assessed the ability of our model to detect clinically significant cancer (lesions with an aggressive component) and compared it to the performance of radiologists.RESULTS: Our model detected clinically significant lesions with an Area Under the Receiver Operator Characteristics Curve of 0.75 for radical prostatectomy patients and 0.80 for biopsy patients. Moreover, the model detected up to 18% of lesions missed by radiologists, and overall had a sensitivity and specificity that approached that of radiologists in detecting clinically significant cancer.CONCLUSIONS: Our SPCNet model accurately detected aggressive prostate cancer. Its performance approached that of radiologists, and it helped identify lesions otherwise missed by radiologists. Our model has the potential to assist physicians in specifically targeting the aggressive component of prostate cancers during biopsy or focal treatment.
View details for DOI 10.1002/mp.14855
View details for PubMedID 33760269
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MR method for measuring microscopic histologic soft tissue textures.
Magnetic resonance in medicine
2021
Abstract
PURPOSE: Provide a direct, non-invasive diagnostic measure of microscopic tissue texture in the size scale between tens of microns and the much larger scale measurable by clinical imaging. This paper presents a method and data demonstrating the ability to measure these microscopic pathologic tissue textures (histology) in the presence of subject motion in an MR scanner. This size range is vital to diagnosing a wide range of diseases.THEORY/METHODS: MR micro-Texture (MRT) resolves these textures by a combination of measuring a targeted set of k-values to characterize texture-as in diffraction analysis of materials, performing a selective internal excitation to isolate a volume of interest (VOI), applying a high k-value phase encode to the excited spins in the VOI, and acquiring each individual k-value data point in a single excitation-providing motion immunity and extended acquisition time for maximizing signal-to-noise ratio. Additional k-value measurements from the same tissue can be made to characterize the tissue texture in the VOI-there is no need for these additional measurements to be spatially coherent as there is no image to be reconstructed. This method was applied to phantoms and tissue specimens including human prostate tissue.RESULTS: Data demonstrating resolution <50 m, motion immunity, and clearly differentiating between normal and cancerous tissue textures are presented.CONCLUSION: The data reveal textural differences not resolvable by standard MR imaging. As MRT is a pulse sequence, it is directly translatable to MRI scanners currently in clinical practice to meet the need for further improvement in cancer imaging.
View details for DOI 10.1002/mrm.28731
View details for PubMedID 33608954
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3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction.
Medical image analysis
2021; 69: 101957
Abstract
The use of MRI for prostate cancer diagnosis and treatment is increasing rapidly. However, identifying the presence and extent of cancer on MRI remains challenging, leading to high variability in detection even among expert radiologists. Improvement in cancer detection on MRI is essential to reducing this variability and maximizing the clinical utility of MRI. To date, such improvement has been limited by the lack of accurately labeled MRI datasets. Data from patients who underwent radical prostatectomy enables the spatial alignment of digitized histopathology images of the resected prostate with corresponding pre-surgical MRI. This alignment facilitates the delineation of detailed cancer labels on MRI via the projection of cancer from histopathology images onto MRI. We introduce a framework that performs 3D registration of whole-mount histopathology images to pre-surgical MRI in three steps. First, we developed a novel multi-image super-resolution generative adversarial network (miSRGAN), which learns information useful for 3D registration by producing a reconstructed 3D MRI. Second, we trained the network to learn information between histopathology slices to facilitate the application of 3D registration methods. Third, we registered the reconstructed 3D histopathology volumes to the reconstructed 3D MRI, mapping the extent of cancer from histopathology images onto MRI without the need for slice-to-slice correspondence. When compared to interpolation methods, our super-resolution reconstruction resulted in the highest PSNR relative to clinical 3D MRI (32.15 dB vs 30.16 dB for BSpline interpolation). Moreover, the registration of 3D volumes reconstructed via super-resolution for both MRI and histopathology images showed the best alignment of cancer regions when compared to (1) the state-of-the-art RAPSODI approach, (2) volumes that were not reconstructed, or (3) volumes that were reconstructed using nearest neighbor, linear, or BSpline interpolations. The improved 3D alignment of histopathology images and MRI facilitates the projection of accurate cancer labels on MRI, allowing for the development of improved MRI interpretation schemes and machine learning models to automatically detect cancer on MRI.
View details for DOI 10.1016/j.media.2021.101957
View details for PubMedID 33550008
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ProGNet: Prostate Gland Segmentation on MRI with Deep Learning
SPIE-INT SOC OPTICAL ENGINEERING. 2021
View details for DOI 10.1117/12.2580448
View details for Web of Science ID 000672800200091
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Selective identification and localization of indolent and aggressive prostate cancers via CorrSigNIA: an MRI-pathology correlation and deep learning framework.
Medical image analysis
2021; 75: 102288
Abstract
Automated methods for detecting prostate cancer and distinguishing indolent from aggressive disease on Magnetic Resonance Imaging (MRI) could assist in early diagnosis and treatment planning. Existing automated methods of prostate cancer detection mostly rely on ground truth labels with limited accuracy, ignore disease pathology characteristics observed on resected tissue, and cannot selectively identify aggressive (Gleason Pattern≥4) and indolent (Gleason Pattern=3) cancers when they co-exist in mixed lesions. In this paper, we present a radiology-pathology fusion approach, CorrSigNIA, for the selective identification and localization of indolent and aggressive prostate cancer on MRI. CorrSigNIA uses registered MRI and whole-mount histopathology images from radical prostatectomy patients to derive accurate ground truth labels and learn correlated features between radiology and pathology images. These correlated features are then used in a convolutional neural network architecture to detect and localize normal tissue, indolent cancer, and aggressive cancer on prostate MRI. CorrSigNIA was trained and validated on a dataset of 98 men, including 74 men that underwent radical prostatectomy and 24 men with normal prostate MRI. CorrSigNIA was tested on three independent test sets including 55 men that underwent radical prostatectomy, 275 men that underwent targeted biopsies, and 15 men with normal prostate MRI. CorrSigNIA achieved an accuracy of 80% in distinguishing between men with and without cancer, a lesion-level ROC-AUC of 0.81±0.31 in detecting cancers in both radical prostatectomy and biopsy cohort patients, and lesion-levels ROC-AUCs of 0.82±0.31 and 0.86±0.26 in detecting clinically significant cancers in radical prostatectomy and biopsy cohort patients respectively. CorrSigNIA consistently outperformed other methods across different evaluation metrics and cohorts. In clinical settings, CorrSigNIA may be used in prostate cancer detection as well as in selective identification of indolent and aggressive components of prostate cancer, thereby improving prostate cancer care by helping guide targeted biopsies, reducing unnecessary biopsies, and selecting and planning treatment.
View details for DOI 10.1016/j.media.2021.102288
View details for PubMedID 34784540
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Weakly Supervised Registration of Prostate MRI and Histopathology Images
SPRINGER INTERNATIONAL PUBLISHING AG. 2021: 98-107
View details for DOI 10.1007/978-3-030-87202-1_10
View details for Web of Science ID 000712021400010
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UTILITY OF PSA DENSITY IN PREDICTING UPGRADED GLEASON SCORE IN MEN ON ACTIVE SURVEILLANCE WITH NEGATIVE MRI.
Urology
2021
Abstract
To determine whether PSA density (PSAD), can sub-stratify risk of biopsy upgrade among men on active surveillance (AS) with normal baseline MRI.We identified a cohort of patients with low and favorable intermediate-risk prostate cancer on AS at two large academic centers from February 2013 - December 2017. Analysis was restricted to patients with GG1 cancer on initial biopsy and a negative baseline or surveillance mpMRI, defined by the absence of PI-RADS 2 or greater lesions. We assessed ability of PSA, prostate volume and PSAD to predict upgrading on confirmatory biopsy.We identified 98 patients on AS with negative baseline or surveillance mpMRI. Median PSA at diagnosis was 5.8 ng/mL and median PSAD was 0.08 ng/mL/mL. Fourteen men (14.3%) experienced Gleason upgrade at confirmatory biopsy. Patients who were upgraded had higher PSA (7.9 vs. 5.4 ng/mL, p=0.04), PSAD (0.20 vs. 0.07 ng/mL/mL, p<0.001), and lower prostate volumes (42.5 vs. 65.8 mL, p=0.01). On multivariate analysis, PSAD was associated with pathologic upgrade (OR 2.23 per 0.1-increase, p=0.007). A PSAD cutoff at 0.08 generated a NPV of 98% for detection of pathologic upgrade.PSAD reliably discriminated the risk of Gleason upgrade at confirmatory biopsy among men with low-grade prostate cancer with negative MRI. PSAD could be clinically implemented to reduce the intensity of surveillance for a subset of patients.
View details for DOI 10.1016/j.urology.2021.05.035
View details for PubMedID 34087311
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Adaptable Image Quality Assessment Using Meta-Reinforcement Learning of Task Amenability
SPRINGER INTERNATIONAL PUBLISHING AG. 2021: 191-201
View details for DOI 10.1007/978-3-030-87583-1_19
View details for Web of Science ID 000780427600019
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Consumption of cruciferous vegetables and the risk of bladder cancer in a prospective US cohort: data from the NIH-AARP diet and health study
AMERICAN JOURNAL OF CLINICAL AND EXPERIMENTAL UROLOGY
2021; 9 (3): 229-238
View details for Web of Science ID 000672671600004
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Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER) for Clinical Photoacoustic Imaging.
IEEE transactions on medical imaging
2021; PP
Abstract
Photoacoustic (PA) imaging can revolutionize medical ultrasound by augmenting it with molecular information. However, clinical translation of PA imaging remains a challenge due to the limited viewing angles and imaging depth. Described here is a new robust algorithm called Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER), designed to reconstruct PA images in real-time and to address the artifacts associated with limited viewing angles and imaging depth. The method utilizes precise forward modeling of the PA propagation and reception of signals while accounting for the effects of acoustic absorption, element size, shape, and sensitivity, as well as the transducer's impulse response and directivity pattern. A fast superiorized conjugate gradient algorithm is used for inversion. SPANNER is compared to three reconstruction algorithms: delay-and-sum (DAS), universal back-projection (UBP), and model-based reconstruction (MBR). All four algorithms are applied to both simulations and experimental data acquired from tissue-mimicking phantoms, ex vivo tissue samples, and in vivo imaging of the prostates in patients. Simulations and phantom experiments highlight the ability of SPANNER to improve contrast to background ratio by up to 20 dB compared to all other algorithms, as well as a 3-fold increase in axial resolution compared to DAS and UBP. Applying SPANNER on contrast-enhanced PA images acquired from prostate cancer patients yielded a statistically significant difference before and after contrast agent administration, while the other three image reconstruction methods did not, thus highlighting SPANNER's performance in differentiating intrinsic from extrinsic PA signals and its ability to quantify PA signals from the contrast agent more accurately.
View details for DOI 10.1109/TMI.2021.3068181
View details for PubMedID 33755561
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Intensity Normalization of Prostate MRIs using Conditional Generative Adversarial Networks for Cancer Detection
SPIE-INT SOC OPTICAL ENGINEERING. 2021
View details for DOI 10.1117/12.2582297
View details for Web of Science ID 000672800100016
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Clinically significant prostate cancer detection on MRI with self-supervised learning using image context restoration
SPIE-INT SOC OPTICAL ENGINEERING. 2021
View details for DOI 10.1117/12.2581557
View details for Web of Science ID 000672800100052
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Clinical -Prostate cancer Multicenter analysis of clinical and MRI characteristics associated with detecting clinically significant prostate cancer in PI-RADS (v2.0) category 3 lesions
UROLOGIC ONCOLOGY-SEMINARS AND ORIGINAL INVESTIGATIONS
2020; 38 (7)
View details for Web of Science ID 000542437900009
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Registration of pre-surgical MRI and histopathology images from radical prostatectomy via RAPSODI.
Medical physics
2020
Abstract
PURPOSE: Magnetic resonance imaging (MRI) has great potential to improve prostate cancer diagnosis, however, subtle differences between cancer and confounding conditions render prostate MRI interpretation challenging. The tissue collected from patients who undergo radical prostatectomy provides a unique opportunity to correlate histopathology images of the prostate with pre-operative MRI to accurately map the extent of cancer from histopathology images onto MRI. We seek to develop an open-source, easy-to-use platform to align pre-surgical MRI and histopathology images of resected prostates in patients who underwent radical prostatectomy to create accurate cancer labels on MRI.METHODS: Here, we introduce RAdiology Pathology Spatial Open-Source multi-Dimensional Integration (RAPSODI), the first open-source framework for the registration of radiology and pathology images. RAPSODI relies on three steps. First, it creates a 3D reconstruction of the histopathology specimen as a digital representation of the tissue before gross sectioning. Second, RAPSODI registers corresponding histopathology and MRI slices. Third, the optimized transforms are applied to the cancer regions outlined on the histopathology images to project those labels onto the pre-operative MRI.RESULTS: We tested RAPSODI in a phantom study where we simulated various conditions, e.g., tissue shrinkage during fixation. Our experiments showed that RAPSODI can reliably correct multiple artifacts. We also evaluated RAPSODI in 157 patients from three institutions that underwent radical prostatectomy and have very different pathology processing and scanning. RAPSODI was evaluated in 907 corresponding histpathology-MRI slices and achieved a Dice coefficient of 0.97±0.01 for the prostate, a Hausdorff distance of 1.99±0.70 mm for the prostate boundary, a urethra deviation of 3.09±1.45 mm, and a landmark deviation of 2.80±0.59 mm between registered histopathology images and MRI.CONCLUSION: Our robust framework successfully mapped the extent of cancer from histopathology slices onto MRI providing labels from training machine learning methods to detect cancer on MRI.
View details for DOI 10.1002/mp.14337
View details for PubMedID 32564359
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Ga-68-PSMA-11 PET/MR Imaging before prostatectomy: correlation with surgical pathology and two-year follow up
SOC NUCLEAR MEDICINE INC. 2020
View details for Web of Science ID 000568290500168
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ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate.
Medical image analysis
2020; 68: 101919
Abstract
Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observer variability across radiologists, thereby contributing to missed clinically significant cancers, overdiagnosed low-risk cancers, and frequent false positives. Interpretation of MRI could be greatly improved by providing radiologists with an answer key that clearly shows cancer locations on MRI. Registration of histopathology images from patients who had radical prostatectomy to pre-operative MRI allows such mapping of ground truth cancer labels onto MRI. However, traditional MRI-histopathology registration approaches are computationally expensive and require careful choices of the cost function and registration hyperparameters. This paper presents ProsRegNet, a deep learning-based pipeline to accelerate and simplify MRI-histopathology image registration in prostate cancer. Our pipeline consists of image preprocessing, estimation of affine and deformable transformations by deep neural networks, and mapping cancer labels from histopathology images onto MRI using estimated transformations. We trained our neural network using MR and histopathology images of 99 patients from our internal cohort (Cohort 1) and evaluated its performance using 53 patients from three different cohorts (an additional 12 from Cohort 1 and 41 from two public cohorts). Results show that our deep learning pipeline has achieved more accurate registration results and is at least 20 times faster than a state-of-the-art registration algorithm. This important advance will provide radiologists with highly accurate prostate MRI answer keys, thereby facilitating improvements in the detection of prostate cancer on MRI. Our code is freely available at https://github.com/pimed//ProsRegNet.
View details for DOI 10.1016/j.media.2020.101919
View details for PubMedID 33385701
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Multicenter analysis of clinical and MRI characteristics associated with detecting clinically significant prostate cancer in PI-RADS (v2.0) category 3 lesions.
Urologic oncology
2020
Abstract
We sought to identify clinical and magnetic resonance imaging (MRI) characteristics in men with the Prostate Imaging - Reporting and Data System (PI-RADS) category 3 index lesions that predict clinically significant prostate cancer (CaP) on MRI targeted biopsy.Multicenter study of prospectively collected data for biopsy-naive men (n = 247) who underwent MRI-targeted and systematic biopsies for PI-RADS 3 index lesions. The primary endpoint was diagnosis of clinically significant CaP (Grade Group ≥2). Multivariable logistic regression models assessed for factors associated with clinically significant CaP. The probability distributions of clinically significant CaP based on different levels of predictors of multivariable models were plotted in a heatmap.Men with clinically significant CaP had smaller prostate volume (39.20 vs. 55.10 ml, P < 0.001) and lower apparent diffusion coefficient (ADC) values (973 vs. 1068 μm2/s, P = 0.013), but higher prostate-specific antigen (PSA) density (0.21 vs. 0.13 ng/ml2, P = 0.027). On multivariable analyses, lower prostate volume (odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.92-0.97), lower ADC value (OR: 0.99, 95% CI: 0.99-1.00), and Prostate-specific antigen density >0.15 ng/ml2 (OR: 3.51, 95% CI 1.61-7.68) were independently associated with significant CaP.Higher PSA density, lower prostate volume and ADC values are associated with clinically significant CaP in biopsy-naïve men with PI-RADS 3 lesions. We present regression-derived probabilities of detecting clinically significant CaP based on various clinical and imaging values that can be used in decision-making. Our findings demonstrate an opportunity for MRI refinement or biomarker discovery to improve risk stratification for PI-RADS 3 lesions.
View details for DOI 10.1016/j.urolonc.2020.03.019
View details for PubMedID 32307327
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Identification of Diagnostic Metabolic Signatures in Clear Cell Renal Cell Carcinoma Using Mass Spectrometry Imaging.
International journal of cancer
2019
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy (PN). However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In this study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal-tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal-tumor pairs were analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids, and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out cross validation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94% and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status. This article is protected by copyright. All rights reserved.
View details for DOI 10.1002/ijc.32843
View details for PubMedID 31863456
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Reply by Authors.
The Journal of urology
2019: 101097JU000000000000053402
View details for DOI 10.1097/JU.0000000000000534.02
View details for PubMedID 31789578
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Multimodality Hyperpolarized C-13 MRS/PET/Multiparametric MR Imaging for Detection and Image-Guided Biopsy of Prostate Cancer: First Experience in a Canine Prostate Cancer Model
MOLECULAR IMAGING AND BIOLOGY
2019; 21 (5): 861–70
View details for DOI 10.1007/s11307-018-1235-6
View details for Web of Science ID 000483788100009
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Variation in MRI-Ultrasound Fusion Targeted Biopsy Outcomes in Asian-American Men: A Multi-Center Study.
The Journal of urology
2019: 101097JU0000000000000534
Abstract
PURPOSE: Asian-American men have distinctly different prostate cancer epidemiology compared to other men. The role of multiparametric magnetic resonance imaging and targeted biopsy for elevated PSA in this population has not been assessed. We sought to define imaging and targeted biopsy outcomes in Asian-American men compared to other men.MATERIALS AND METHODS: A multicenter, prospective cohort of men who underwent magnetic resonance imaging-targeted with systematic biopsy for elevated prostate specific antigen was accrued. Outcome of interest was diagnosis of clinically significant prostate cancer (Gleason Grade Group≥2), stratified by PI-RADS score and history of negative biopsy. Multivariable logistic regression was used to assess the effect of Asian-American race on cancer detection.RESULTS: Of 2,571 men, 275 (11%) were Asian-American. Clinically significant prostate cancer was detected in 37% of Asian-American men compared to 48% in men of other races (p<0.001). Asian-American men were also less likely to be diagnosed with grade group 1 cancer (12% vs 18%, p=0.007). Additionally, there was significantly lower detection of significant cancer for PIRADS 3 in Asian-Americans vs. other races (12% vs. 21%, p=0.032). In adjusted analysis, Asian-Americans were less likely to be diagnosed with both significant cancer (OR 0.57, 95% CI 0.42-0.79, p<0.001) and grade group 1 cancer (OR 0.57, 95% CI 0.38-0.84, p=0.005) compared to non-Asians.CONCLUSIONS: Asian-Americans are less likely to be diagnosed with clinically significant prostate cancer on targeted biopsy, illustrating different performance of PI-RADS in this population. Conventional risk assessment tools should be modified when selecting Asian-American men for biopsy.
View details for DOI 10.1097/JU.0000000000000534
View details for PubMedID 31502942
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Simultaneous transrectal ultrasound and photoacoustic human prostate imaging.
Science translational medicine
2019; 11 (507)
Abstract
Imaging technologies that simultaneously provide anatomical, functional, and molecular information are emerging as an attractive choice for disease screening and management. Since the 1980s, transrectal ultrasound (TRUS) has been routinely used to visualize prostatic anatomy and guide needle biopsy, despite limited specificity. Photoacoustic imaging (PAI) provides functional and molecular information at ultrasonic resolution based on optical absorption. Combining the strengths of TRUS and PAI approaches, we report the development and bench-to-bedside translation of an integrated TRUS and photoacoustic (TRUSPA) device. TRUSPA uses a miniaturized capacitive micromachined ultrasonic transducer array for simultaneous imaging of anatomical and molecular optical contrasts [intrinsic: hemoglobin; extrinsic: intravenous indocyanine green (ICG)] of the human prostate. Hemoglobin absorption mapped vascularity of the prostate and surroundings, whereas ICG absorption enhanced the intraprostatic photoacoustic contrast. Future work using the TRUSPA device for biomarker-specific molecular imaging may enable a fundamentally new approach to prostate cancer diagnosis, prognostication, and therapeutic monitoring.
View details for DOI 10.1126/scitranslmed.aav2169
View details for PubMedID 31462508
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Prostate Magnetic Resonance Imaging Interpretation Varies Substantially Across Radiologists
EUROPEAN UROLOGY FOCUS
2019; 5 (4): 592–99
View details for DOI 10.1016/j.euf.2017.11.010
View details for Web of Science ID 000486156800014
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Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.
Ultrasound in medicine & biology
2019
Abstract
The question of whether ultrasound point shear wave elastography can differentiate renal cell carcinoma (RCC) from angiomyolipoma (AML) is controversial. This study prospectively enrolled 51 patients with 52 renal tumors (42 RCCs, 10 AMLs). We obtained 10 measurements of shear wave velocity (SWV) in the renal tumor, cortex and medulla. Median SWV was first used to classify RCC versus AML. Next, the prediction accuracy of 4 machine learning algorithms-logistic regression, naive Bayes, quadratic discriminant analysis and support vector machines (SVMs)-was evaluated, using statistical inputs from the tumor, cortex and combined statistical inputs from tumor, cortex and medulla. After leave-one-out cross validation, models were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). Tumor median SWV performed poorly (AUC = 0.62; p = 0.23). Except logistic regression, all machine learning algorithms reached statistical significance using combined statistical inputs (AUC = 0.78-0.98; p < 7.1 * 10-3). SVMs demonstrated 94% accuracy (AUC = 0.98; p = 3.13 * 10-6) and clearly outperformed median SWV in differentiating RCC from AML (p = 2.8 * 10-4).
View details for DOI 10.1016/j.ultrasmedbio.2019.04.009
View details for PubMedID 31133445
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How Often is the Dynamic Contrast Enhanced Score Needed in PI-RADS Version 2?
Current problems in diagnostic radiology
2019
Abstract
BACKGROUND: Prostate imaging reporting and data system version 2 (PI-RADS v2) relegates dynamic contrast enhanced (DCE) imaging to a minor role. We sought to determine how often DCE is used in PI-RADS v2 scoring.MATERIALS AND METHODS: We retrospectively reviewed data from 388 patients who underwent prostate magnetic resonance imaging and subsequent biopsy from January 2016 through December 2017. In accordance with PI-RADS v2, DCE was deemed necessary if a peripheral-zone lesion had a diffusion-weighted imaging score of 3, or if a transition-zone lesion had a T2 score of 3 and diffusion-weighted imaging experienced technical failure. Receiver operating characteristic curve analysis assessed the accuracy of prostate-specific antigen density (PSAD) at different threshold values for differentiating lesions that would be equivocal with noncontrast technique. Accuracy of PSAD was compared to DCE using McNemar's test.RESULTS: Sixty-nine lesions in 62 patients (16%) required DCE for PI-RADS scoring. Biopsy of 10 (14%) of these lesions showed clinically significant cancer (Gleason score ≥7). In the subgroup of patients with equivocal lesions, those with clinically significant cancer had significantly higher PSADs than those with clinically insignificant lesions (means of 0.18 and 0.13 ng/mL/mL, respectively; P= 0.038). In this subgroup, there was no statistical difference in accuracy in determining clinically significant cancer between a PSAD threshold value of 0.13 and DCE (P= 0.25).CONCLUSIONS: Only 16% of our patients needed DCE to generate the PI-RADS version 2 score, raising the possibility of limiting the initial screening prostate MRI to a noncontrast exam. PSAD may also be used to further decrease the need for or to replace DCE altogether.
View details for DOI 10.1067/j.cpradiol.2019.05.008
View details for PubMedID 31126664
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AUTOMATED DETECTION OF PROSTATE CANCER ON MULTIPARAMETRIC MRI USING DEEP NEURAL NETWORKS TRAINED ON SPATIAL COORDINATES AND PATHOLOGY OF BIOPSY CORES
LIPPINCOTT WILLIAMS & WILKINS. 2019: E1098
View details for Web of Science ID 000473345203470
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GENERALIZABLE MULTI-SITE TRAINING AND TESTING OF DEEP NEURAL NETWORKS USING IMAGE NORMALIZATION.
Proceedings. IEEE International Symposium on Biomedical Imaging
2019; 2019: 348-351
Abstract
The ability of medical image analysis deep learning algorithms to generalize across multiple sites is critical for clinical adoption of these methods. Medical imging data, especially MRI, can have highly variable intensity characteristics across different individuals, scanners, and sites. However, it is not practical to train algorithms with data from all imaging equipment sources at all possible sites. Intensity normalization methods offer a potential solution for working with multi-site data. We evaluate five different image normalization methods on training a deep neural network to segment the prostate gland in MRI. Using 600 MRI prostate gland segmentations from two different sites, our results show that both intra-site and inter-site evaluation is critical for assessing the robustness of trained models and that training with single-site data produces models that fail to fully generalize across testing data from sites not included in the training.
View details for DOI 10.1109/isbi.2019.8759295
View details for PubMedID 32874427
View details for PubMedCentralID PMC7457546
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Multimodality Hyperpolarized C-13 MRS/PET/Multiparametric MR Imaging for Detection and Image-Guided Biopsy of Prostate Cancer: First Experience in a Canine Prostate Cancer Model.
Molecular imaging and biology : MIB : the official publication of the Academy of Molecular Imaging
2019
Abstract
PURPOSE: To assess whether simultaneous hyperpolarized C-13 magnetic resonance spectroscopy (MRS)/positron emission tomography (PET)/multiparametric magnetic resonance (mpMR) imaging is feasible in an orthotopic canine prostate cancer (PCa) model using a clinical PET/MR system and whether the combined imaging datasets can be fused with transrectal ultrasound (TRUS) in real time for multimodal image fusion-guided targeted biopsy of PCa.PROCEDURES: Institutional Animal Care and Use Committee approval was obtained for this study. Canine prostate adenocarcinoma (Ace-1) cells were orthotopically injected into the prostate of four dogs. Once tumor engraftment was confirmed by TRUS, simultaneous hyperpolarized C-13 MRS of [1-13C]pyruvate, PET (2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), [68Ga]NODAGA-SCH1), and mpMR (T2W, DWI) imaging was performed using a clinical PET/MR system. Multimodality imaging data sets were then fused with TRUS and image-guided targeted biopsy was performed. Imaging results were then correlated with histological findings.RESULTS: Successful tumor engraftment was histologically confirmed in three of the four dogs (dogs 2, 3, and 4) and simultaneous C-13 MRS/PET/mpMR was feasible in all three. In dog 2, C-13 MRS showed increased lactate signal in the tumor (lactate/totalC=0.47) whereas mpMR did not show any signal changes. In dog 3, [18F]FDG-PET (SUVmean=1.90) and C-13 MRS (lactate/totalC=0.59) showed elevated metabolic activity in the tumor. In dog 4, [18F]FDG (SUVmean=2.43), [68Ga]NODAGA-SCH1 (SUVmean=0.75), and C-13 MRS (Lac/totalC=0.53) showed elevated uptake in tumor compared to control tissue and multimodal image fusion-guided biopsy of the tumor was successfully performed.CONCLUSION: Simultaneous C-13 MRS/PET/mpMR imaging and multimodal image fusion-guided biopsy is feasible in a canine PCa model.
View details for PubMedID 30793241
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Applying the PRECISION approach in biopsy naïve and previously negative prostate biopsy patients.
Urologic oncology
2019
Abstract
The PRECISION trial provides level 1 evidence supporting prebiopsy multiparametric magnetic resonance imaging (mpMRI) followed by targeted biopsy only when mpMRI is abnormal [1]. This approach reduced over-detection of low-grade cancer while increasing detection of clinically significant cancer (CSC). Still, important questions remain regarding the reproducibility of these findings outside of a clinical trial and quantifying missed CSC diagnoses using this approach. To address these issues, we retrospectively applied the PRECISION strategy in men who each underwent prebiopsy mpMRI followed by systematic and targeted biopsy.Clinical, imaging, and pathology data were prospectively collected from 358 biopsy naïve men and 202 men with previous negative biopsies. To apply the PRECISION approach, a retrospective analysis was done comparing the cancer yield from 2 diagnostic strategies: (1) mpMRI followed by targeted biopsy alone for men with Prostate Imaging Reporting and Data System ≥ 3 lesions and (2) systematic biopsy alone for all men. Primary outcomes were biopsies avoided and the proportion of CSC cancer (Grade Group 2-5) and non-CSC (Grade Group 1).In biopsy naïve patients, the mpMRI diagnostic strategy would have avoided 19% of biopsies while detecting 2.5% more CSC (P= 0.480) and 12% less non-CSC (P< 0.001). Thirteen percent (n= 9) of men with normal mpMRI had CSC on systematic biopsy. For previous negative biopsy patients, the mpMRI diagnostic strategy avoided 21% of biopsies, while detecting 1.5% more CSC (P= 0.737) and 13% less non-CSC (P< 0.001). Seven percent (n= 3) of men with normal mpMRI had CSC on systematic biopsy.Our results provide external validation of the PRECISION finding that mpMRI followed by targeted biopsy of suspicious lesions reduces biopsies and over-diagnosis of low-grade cancer. Unlike PRECISION, we did not find increased diagnosis of CSC. This was true in both biopsy naïve and previously negative biopsy cohorts. We have incorporated this information into shared decision making, which has led some men to choose to avoid biopsy. However, we continue to recommend targeted and systematic biopsy in men with abnormal MRI.
View details for DOI 10.1016/j.urolonc.2019.05.002
View details for PubMedID 31151788
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Framework for the co-registration of MRI and Histology Images in Prostate Cancer Patients with Radical Prostatectomy
SPIE-INT SOC OPTICAL ENGINEERING. 2019
View details for DOI 10.1117/12.2513099
View details for Web of Science ID 000483012700057
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GENERALIZABLE MULTI-SITE TRAINING AND TESTING OF DEEP NEURAL NETWORKS USING IMAGE NORMALIZATION
IEEE. 2019: 348–51
View details for Web of Science ID 000485040000074
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Validation of an epigenetic field of susceptibility to detect significant prostate cancer from non-tumor biopsies.
Clinical epigenetics
2019; 11 (1): 168
Abstract
An epigenetic field of cancer susceptibility exists for prostate cancer (PC) that gives rise to multifocal disease in the peripheral prostate. In previous work, genome-wide DNA methylation profiling identified altered regions in the normal prostate tissue of men with PC. In the current multicenter study, we examined the predictive strength of a panel of loci to detect cancer presence and grade in patients with negative biopsy tissue.Four centers contributed benign prostate biopsy tissues blocks from 129 subjects that were either tumor associated (TA, Grade Group [GG] ≥ 2, n = 77) or non-tumor associated (NTA, n = 52). Biopsies were analyzed using pyrosequencing for DNA methylation encompassing CpG loci near CAV1, EVX1, FGF1, NCR2, PLA2G16, and SPAG4 and methylation differences were detected within all gene regions (p < 0.05). A multiplex regression model for biomarker performance incorporating a gene combination discriminated TA from NTA tissues (area under the curve [AUC] 0.747, p = 0.004). A multiplex model incorporating all the above genes and clinical information (PSA, age) identified patients with GG ≥ 2 PC (AUC 0.815, p < 0.0001). In patients with cancer, increased variation in gene methylation levels occurs between biopsies across the prostate.A widespread epigenetic field defect is utilized to detect GG ≥ 2 PC in patients with histologically negative biopsies. These alterations in non-tumor cells display increased heterogeneity of methylation extent and are spatially distant from tumor foci. These findings have the potential to decrease the need for repeated prostate biopsy.
View details for DOI 10.1186/s13148-019-0771-5
View details for PubMedID 31779677
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Teaching Urologists "How to Read Multi-Parametric Prostate MRIs Using PIRADSv2": Results of an iBook Pilot Study.
Urology
2019
Abstract
To create an online resource that teaches urologists how to interpret prostate multi-parametric MRIs (mpMRI). As prostate mpMRI becomes widely adopted for cancer diagnosis and targeted biopsy, it is increasingly important that urologists are comfortable and experienced in assessing the images. The purpose of this study was to create an online mpMRI ibook and measure its effect on instilling proficiency amongst urology residents.We created a case-based ibook aimed at teaching clinicians how to identify and score prostate lesions on mpMRI using the Prostate Imaging and Reporting Data System (PIRADS) v2. Residents completed a 43-question pre-test before gaining access to the ibook for one month. The test asks participants to identify and score visible lesions using interactive mpMRI images. After a formal review of the material, they completed a post-test. Participants also rated their diagnostic confidence on a scale of 1 to 10 before and after reviewing the ibook. The change in performance and confidence scores for each resident was compared using Wilcoxon Signed-Rank test.Eleven urology residents completed the pre-test, review session and post-test. The mean test score rose from 37% (median 40%) to 57% (median 58%) after reviewing the ibook. Improvement was significant (p=0.0039). Confidence scores also improved (p=0.001).We created an interactive ibook that teaches urologists how to evaluate prostate mpMRIs and demonstrated improved performance in interpretation amongst urology residents. This effective module can be incorporated into resident education on a national level and offered as a self-teaching resource for practicing urologists.
View details for DOI 10.1016/j.urology.2019.04.040
View details for PubMedID 31150691
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Performance of multiparametric MRI appears better when measured in patients who undergo radical prostatectomy.
Research and reports in urology
2018; 10: 233-235
Abstract
Utilization of pre-biopsy multiparametric MRI (mpMRI) is increasing. To optimize the usefulness of mpMRI, physicians should accurately quote patients a numerical risk of cancer based on their MRI. The Prostate Imaging Reporting and Data System (PIRADS) standardizes interpretation of mpMRI; however, reported rates of clinically significant prostate cancer (CSC) stratified by PIRADS score vary widely. While some publications use radical prostatectomy (RP) specimens as gold standard, others use biopsy. We hypothesized that much of the variation in CSC stems from differences in cancer prevalence in RP cohorts (100% prevalence) vs biopsy cohorts. To quantify the impact of this selection bias on cancer yield according to PIRADS score, we analyzed data from 614 men with 854 lesions who underwent targeted biopsy from 2014 to 2018. Of these, 125 men underwent RP. We compared the PIRADS detection rates of CSC (Gleason ≥7) on targeted biopsy between the biopsy-only and RP cohorts. For all PIRADS scores, CSC yield was much greater in patients who underwent RP. For example, CSC was found in 30% of PIRADS 3 lesions in men who underwent RP vs 7.6% in men who underwent biopsy. Our results show that mpMRI performance appears to be better in men who undergo RP compared with those who only receive biopsy. Physicians should understand the effect of this selection bias and its magnitude when discussing mpMRI results with patients considering biopsy, and take great caution in quoting CSC yields from publications using RP as gold standard.
View details for DOI 10.2147/RRU.S178064
View details for PubMedID 30538970
View details for PubMedCentralID PMC6254536
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The Research Implications of Prostate Specific Antigen Registry Errors: Data from the Veterans Health Administration
JOURNAL OF UROLOGY
2018; 200 (3): 541–47
View details for DOI 10.1016/j.juro.2018.03.127
View details for Web of Science ID 000441294600074
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Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging and Fusion Guided Targeted Biopsy Evaluated by Transperineal Template Saturation Prostate Biopsy for the Detection and Characterization of Prostate Cancer EDITORIAL COMMENT
JOURNAL OF UROLOGY
2018; 200 (2): 318
View details for Web of Science ID 000438718000081
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Gallium 68 PSMA-11 PET/MR Imaging in Patients with Intermediate- or High-Risk Prostate Cancer
RADIOLOGY
2018; 288 (2): 495–505
View details for DOI 10.1148/radiol.2018172232
View details for Web of Science ID 000441808100025
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Reduction of Muscle Contractions during Irreversible Electroporation Therapy Using High-Frequency Bursts of Alternating Polarity Pulses: A Laboratory Investigation in an Ex Vivo Swine Model
JOURNAL OF VASCULAR AND INTERVENTIONAL RADIOLOGY
2018; 29 (6): 893–98
View details for DOI 10.1016/j.jvir.2017.12.019
View details for Web of Science ID 000434906600020
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Gallium 68 PSMA-11 PET/MR Imaging in Patients with Intermediate- or High-Risk Prostate Cancer.
Radiology
2018: 172232
Abstract
Purpose To report the results of dual-time-point gallium 68 (68Ga) prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/magnetic resonance (MR) imaging prior to prostatectomy in patients with intermediate- or high-risk cancer. Materials and Methods Thirty-three men who underwent conventional imaging as clinically indicated and who were scheduled for radical prostatectomy with pelvic lymph node dissection were recruited for this study. A mean dose of 4.1 mCi ± 0.7 (151.7 MBq ± 25.9) of 68Ga-PSMA-11 was administered. Whole-body images were acquired starting 41-61 minutes after injection by using a GE SIGNA PET/MR imaging unit, followed by an additional pelvic PET/MR imaging acquisition at 87-125 minutes after injection. PET/MR imaging findings were compared with findings at multiparametric MR imaging (including diffusion-weighted imaging, T2-weighted imaging, and dynamic contrast material-enhanced imaging) and were correlated with results of final whole-mount pathologic examination and pelvic nodal dissection to yield sensitivity and specificity. Dual-time-point metabolic parameters (eg, maximum standardized uptake value [SUVmax]) were compared by using a paired t test and were correlated with clinical and histopathologic variables including prostate-specific antigen level, Gleason score, and tumor volume. Results Prostate cancer was seen at 68Ga-PSMA-11 PET in all 33 patients, whereas multiparametric MR imaging depicted Prostate Imaging Reporting and Data System (PI-RADS) 4 or 5 lesions in 26 patients and PI-RADS 3 lesions in four patients. Focal uptake was seen in the pelvic lymph nodes in five patients. Pathologic examination confirmed prostate cancer in all patients, as well as nodal metastasis in three. All patients with normal pelvic nodes in PET/MR imaging had no metastases at pathologic examination. The accumulation of 68Ga-PSMA-11 increased at later acquisition times, with higher mean SUVmax (15.3 vs 12.3, P < .001). One additional prostate cancer was identified only at delayed imaging. Conclusion This study found that 68Ga-PSMA-11 PET can be used to identify prostate cancer, while MR imaging provides detailed anatomic guidance. Hence, 68Ga-PSMA-11 PET/MR imaging provides valuable diagnostic information and may inform the need for and extent of pelvic node dissection.
View details for PubMedID 29786490
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Editorial Comment.
The Journal of urology
2018
View details for PubMedID 29684305
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The Research Implications of PSA Registry Errors: Data from the Veterans Health Administration.
The Journal of urology
2018
Abstract
INTRODUCTION: We sought to characterize the effects of PSA registry errors on clinical research by comparing cohorts based on cancer registry PSA values with those based directly on results in the electronic health record.METHODS: We defined example cohorts of men with prostate cancer using data from the Veterans Health Administration: those with a PSA values less than 4.0 ng/mL, 4.0 to 10.0 ng/mL, 10.0 to 20.0 ng/mL, and 20.0 to 98.0 ng/mL. We compared the composition of each cohort and overall patient survival when using PSA values from either the VA Central Cancer Registry versus the gold standard electronic health record laboratory file results.RESULTS: There was limited agreement between cohorts defined using either the cancer registry PSA values versus the laboratory file of the electronic health record. The least agreement was seen in patients with PSA values < 4.0 ng/mL (58%) and greatest among patients with PSA values between 4.0 and 10.0 ng/mL (89%). In each cohort, patients assigned to a cohort based only on the cancer registry PSA value had significantly different overall survival when compared with patients assigned based on both the registry and laboratory file PSA values.CONCLUSIONS: Cohorts based exclusively on cancer registry PSA values may have high rates of misclassification that can introduce concerning differences in key characteristics and result in measurable differences in clinical outcomes.
View details for PubMedID 29630980
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The impact of computed high b-value images on the diagnostic accuracy of DWI for prostate cancer: A receiver operating characteristics analysis.
Scientific reports
2018; 8 (1): 3409
Abstract
To evaluate the performance of computed high b value diffusion-weighted images (DWI) in prostate cancer detection. 97 consecutive patients who had undergone multiparametric MRI of the prostate followed by biopsy were reviewed. Five radiologists independently scored 138 lesions on native high b-value images (b = 1200 s/mm2), apparent diffusion coefficient (ADC) maps, and computed high b-value images (contrast equivalent to b = 2000 s/mm2) to compare their diagnostic accuracy. Receiver operating characteristic (ROC) analysis and McNemar's test were performed to assess the relative performance of computed high b value DWI, native high b-value DWI and ADC maps. No significant difference existed in the area under the curve (AUC) for ROCs comparing B1200 (b = 1200 s/mm2) to computed B2000 (c-B2000) in 5 readers. In 4 of 5 readers c-B2000 had significantly increased sensitivity and/or decreased specificity compared to B1200 (McNemar's p < 0.05), at selected thresholds of interpretation. ADC maps were less accurate than B1200 or c-B2000 for 2 of 5 readers (P < 0.05). This study detected no consistent improvement in overall diagnostic accuracy using c-B2000, compared with B1200 images. Readers detected more cancer with c-B2000 images (increased sensitivity) but also more false positive findings (decreased specificity).
View details for PubMedID 29467370
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EDITORIAL COMMENTS
JOURNAL OF UROLOGY
2018; 199 (1): 104–5
View details for DOI 10.1016/j.juro.2017.07.108
View details for Web of Science ID 000419429700071
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Performance of multiparametric MRI appears better when measured in patients who undergo radical prostatectomy
RESEARCH AND REPORTS IN UROLOGY
2018; 10: 233–35
View details for DOI 10.2147/RRU.S178064
View details for Web of Science ID 000451113100001
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Reduction of Muscle Contractions during Irreversible Electroporation Therapy Using High-Frequency Bursts of Alternating Polarity Pulses: A Laboratory Investigation in an ExVivo Swine Model.
Journal of vascular and interventional radiology : JVIR
2018; 29 (6): 893
Abstract
PURPOSE: To compare the intensity of muscle contractions in irreversible electroporation (IRE) treatments when traditional IRE and high-frequency IRE (H-FIRE) waveforms are used in combination with a single applicator and distal grounding pad (A+GP) configuration.MATERIALS AND METHODS: An exvivo in situ porcine model was used to compare muscle contractions induced by traditional monopolar IRE waveforms vs high-frequency bipolar IRE waveforms. Pulses with voltages between 200 and 5,000 V were investigated, and muscle contractions were recorded by using accelerometers placed on or near the applicators.RESULTS: H-FIRE waveforms reduced the intensity of muscle contractions in comparison with traditional monopolar IRE pulses. A high-energy burst of 2-mus alternating-polarity pulses energized for 200 mus at 4,500 V produced less intense muscle contractions than traditional IRE pulses, which were 25-100 mus in duration at 3,000 V.CONCLUSIONS: H-FIRE appears to be an effective technique to mitigate the muscle contractions associated with traditional IRE pulses. This may enable the use of voltages greater than 3,000 V necessary for the creation of large ablations invivo.
View details for PubMedID 29628296
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Ga-68 PSMA 11 PET/MRI in Patients with Newly Diagnosed Intermediate and High-Risk Prostate Cancers
SOC NUCLEAR MEDICINE INC. 2017
View details for Web of Science ID 000404949902137
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Mass spectrometric imaging of prostate biopsy samples: Cancer margin assessment from the distribution of small metabolites and lipids
AMER CHEMICAL SOC. 2017
View details for Web of Science ID 000430568500539
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Diagnosis of prostate cancer by desorption electrospray ionization mass spectrometric imaging of small metabolites and lipids
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2017; 114 (13): 3334-3339
Abstract
Accurate identification of prostate cancer in frozen sections at the time of surgery can be challenging, limiting the surgeon's ability to best determine resection margins during prostatectomy. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on 54 banked human cancerous and normal prostate tissue specimens to investigate the spatial distribution of a wide variety of small metabolites, carbohydrates, and lipids. In contrast to several previous studies, our method included Krebs cycle intermediates (m/z <200), which we found to be highly informative in distinguishing cancer from benign tissue. Malignant prostate cells showed marked metabolic derangements compared with their benign counterparts. Using the "Least absolute shrinkage and selection operator" (Lasso), we analyzed all metabolites from the DESI-MS data and identified parsimonious sets of metabolic profiles for distinguishing between cancer and normal tissue. In an independent set of samples, we could use these models to classify prostate cancer from benign specimens with nearly 90% accuracy per patient. Based on previous work in prostate cancer showing that glucose levels are high while citrate is low, we found that measurement of the glucose/citrate ion signal ratio accurately predicted cancer when this ratio exceeds 1.0 and normal prostate when the ratio is less than 0.5. After brief tissue preparation, the glucose/citrate ratio can be recorded on a tissue sample in 1 min or less, which is in sharp contrast to the 20 min or more required by histopathological examination of frozen tissue specimens.
View details for DOI 10.1073/pnas.1700677114
View details for Web of Science ID 000397607300049
View details for PubMedID 28292895
View details for PubMedCentralID PMC5380053
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Contemporary Use of Partial Nephrectomy: Are Older Patients With Impaired Kidney Function Being Left Behind?
UROLOGY
2017; 100: 65-71
View details for DOI 10.1016/j.urology.2016.08.044
View details for Web of Science ID 000397168900017
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Commentary regarding a recent collaborative consensus statement addressing prostate MRI and MRI-targeted biopsy in patients with a prior negative prostate biopsy
ABDOMINAL RADIOLOGY
2017; 42 (2): 346–49
View details for PubMedID 27670878
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Incident CKD after Radical or Partial Nephrectomy.
Journal of the American Society of Nephrology : JASN
2017
Abstract
The comparative effectiveness of partial nephrectomy versus radical nephrectomy to preserve kidney function has not been well established. We determined the risk of clinically significant (stage 4 and higher) CKD after radical or partial nephrectomy among veterans treated for kidney cancer in the Veterans Health Administration (2001-2013). Among patients with preoperative eGFR≥30 ml/min per 1.73 m(2), the incidence of CKD stage 4 or higher after radical (n=9759) or partial nephrectomy (n=4370) was 7.9% overall. The median time to stage 4 or higher CKD after surgery was 5 months, after which few patients progressed. In propensity score-matched cohorts, partial nephrectomy associated with a significantly lower relative risk of incident CKD stage 4 or higher (hazard ratio, 0.34; 95% confidence interval [95% CI], 0.26 to 0.43, versus radical nephrectomy). In a parallel analysis of patients with normal or near-normal preoperative kidney function (eGFR≥60 ml/min per 1.73 m(2)), partial nephrectomy was also associated with a significantly lower relative risk of incident CKD stage 3b or higher (hazard ratio, 0.15; 95% CI, 0.11 to 0.19, versus radical nephrectomy) in propensity score-matched cohorts. Competing risk regression models produced consistent results. Finally, patients treated with a partial nephrectomy had reduced risk of mortality (hazard ratio, 0.55; 95% CI, 0.49 to 0.62). In conclusion, compared with radical nephrectomy, partial nephrectomy was associated with a marked reduction in the incidence of clinically significant CKD and with enhanced survival. Postoperative decline in kidney function occurred mainly in the first year after surgery and appeared stable over time.
View details for PubMedID 29018140
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Prostate Magnetic Resonance Imaging Interpretation Varies Substantially Across Radiologists.
European urology focus
2017
Abstract
Multiparametric magnetic resonance imaging (mpMRI) interpreted by experts is a powerful tool for diagnosing prostate cancer. However, the generalizability of published results across radiologists of varying expertise has not been verified.To assess variability in mpMRI reporting and diagnostic accuracy across radiologists of varying experience in routine clinical care.Men who underwent mpMRI and MR-fusion biopsy between 2014-2016. Each MRI scan was read by one of nine radiologists using the Prostate Imaging Reporting and Data System (PIRADS) and was not re-read before biopsy. Biopsy histopathology was the reference standard.Outcomes were the PIRADS score distribution and diagnostic accuracy across nine radiologists. We evaluated the association between age, prostate-specific antigen, PIRADS score, and radiologist in predicting clinically significant cancer (Gleason ≥7) using multivariable logistic regression. We conducted sensitivity analyses for case volume and changes in accuracy over time.We analyzed data for 409 subjects with 503 MRI lesions. While the number of lesions (mean 1.2 lesions/patient) did not differ across radiologists, substantial variation existed in PIRADS distribution and cancer yield. The significant cancer detection rate was 3-27% for PIRADS 3 lesions, 23-65% for PIRADS 4, and 40-80% for PIRADS 5 across radiologists. Some 13-60% of men with a PIRADS score of <3 on MRI harbored clinically significant cancer. The area under the receiver operating characteristic curve varied from 0.69 to 0.81 for detection of clinically significant cancer. PIRADS score (p<0.0001) and radiologist (p=0.042) were independently associated with cancer in multivariable analysis. Neither individual radiologist volume nor study period impacted the results. MRI scans were not retrospectively re-read by all radiologists, precluding measurement of inter-observer agreement.We observed considerable variability in PIRADS score assignment and significant cancer yield across radiologists. We advise internal evaluation of mpMRI accuracy before widespread adoption.We evaluated the interpretation of multiparametric magnetic resonance imaging of the prostate in routine clinical care. Diagnostic accuracy depends on the Prostate Imaging Reporting and Data System score and the radiologist.
View details for PubMedID 29226826
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Contemporary Use of Partial Nephrectomy: Are Older Patients With Impaired Kidney Function Being Left Behind?
Urology
2016
Abstract
To assess whether patient factors, such as age and preoperative kidney function, were associated with receipt of partial nephrectomy in a national integrated healthcare system.We identified patients treated with a radical or partial nephrectomy from 2002 to 2014 in the Veterans Health Administration. We examined associations among patient age, sex, race or ethnicity, multimorbidity, baseline kidney function, tumor characteristics, and receipt of partial nephrectomy. We estimated the odds of receiving a partial nephrectomy and assessed interactions between covariates and the year of surgery to explore whether patient factors associated with partial nephrectomy changed over time.In our cohort of 14,186 patients, 4508 (31.2%) received a partial nephrectomy. Use of partial nephrectomy increased from 17% in 2002 to 32% in 2008 and to 38% in 2014. Patient race or ethnicity, age, tumor stage, and year of surgery were independently associated with receipt of partial nephrectomy. Black veterans had significantly increased odds of receipt of partial nephrectomy, whereas older patients had significantly reduced odds. Partial nephrectomy utilization increased for all groups over time, but older patients and patients with worse baseline kidney function showed the least increase in odds of partial nephrectomy.Although the utilization of partial nephrectomy increased for all groups, the greatest increase occurred in the youngest patients and those with the highest baseline kidney function. These trends warrant further investigation to ensure that patients at the highest risk of impaired kidney function are considered for partial nephrectomy whenever possible.
View details for DOI 10.1016/j.urology.2016.08.044
View details for PubMedID 27634733
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Production of Spherical Ablations Using Nonthermal Irreversible Electroporation: A Laboratory Investigation Using a Single Electrode and Grounding Pad.
Journal of vascular and interventional radiology
2016; 27 (9): 1432-1440 e3
Abstract
To mathematically model and test ex vivo a modified technique of irreversible electroporation (IRE) to produce large spherical ablations by using a single probe.Computed simulations were performed by using varying voltages, electrode exposure lengths, and tissue types. A vegetable (potato) tissue model was then used to compare ablations created by conventional and high-frequency IRE protocols by using 2 probe configurations: a single probe with two collinear electrodes (2EP) or a single electrode configured with a grounding pad (P+GP). The new P+GP electrode configuration was evaluated in ex vivo liver tissue.The P+GP configuration produced more spherical ablation volumes than the 2EP configuration in computed simulations and tissue models. In prostate tissue, computed simulations predicted ablation volumes at 3,000 V of 1.6 cm(3) for the P+GP configurations, compared with 0.94 cm(3) for the 2EP configuration; in liver tissue, the predicted ablation volumes were 4.7 times larger than those in the prostate. Vegetable model studies verify that the P+GP configuration produces larger and more spherical ablations than those produced by the 2EP. High-frequency IRE treatment of ex vivo liver with the P+GP configuration created a 2.84 × 2.21-cm ablation zone.Computer modeling showed that P+GP configuration for IRE procedures yields ablations that are larger than the 2EP configuration, creating substantial ablation zones with a single electrode placement. When tested in tissue models and an ex vivo liver model, the P+GP configuration created ablation zones that appear to be of clinically relevant size and shape.
View details for DOI 10.1016/j.jvir.2016.05.032
View details for PubMedID 27478129
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Prostate Magnetic Resonance Imaging and Magnetic Resonance Imaging Targeted Biopsy in Patients with a Prior Negative Biopsy: A Consensus Statement by AUA and SAR.
journal of urology
2016
Abstract
After an initial negative biopsy there is an ongoing need for strategies to improve patient selection for repeat biopsy as well as the diagnostic yield from repeat biopsies.As a collaborative initiative of the AUA (American Urological Association) and SAR (Society of Abdominal Radiology) Prostate Cancer Disease Focused Panel, an expert panel of urologists and radiologists conducted a literature review and formed consensus statements regarding the role of prostate magnetic resonance imaging and magnetic resonance imaging targeted biopsy in patients with a negative biopsy, which are summarized in this review.The panel recognizes that many options exist for men with a previously negative biopsy. If a biopsy is recommended, prostate magnetic resonance imaging and subsequent magnetic resonance imaging targeted cores appear to facilitate the detection of clinically significant disease over standardized repeat biopsy. Thus, when high quality prostate magnetic resonance imaging is available, it should be strongly considered for any patient with a prior negative biopsy who has persistent clinical suspicion for prostate cancer and who is under evaluation for a possible repeat biopsy. The decision of whether to perform magnetic resonance imaging in this setting must also take into account the results of any other biomarkers and the cost of the examination, as well as the availability of high quality prostate magnetic resonance imaging interpretation. If magnetic resonance imaging is done, it should be performed, interpreted and reported in accordance with PI-RADS version 2 (v2) guidelines. Experience of the reporting radiologist and biopsy operator are required to achieve optimal results and practices integrating prostate magnetic resonance imaging into patient care are advised to implement quality assurance programs to monitor targeted biopsy results.Patients receiving a PI-RADS assessment category of 3 to 5 warrant repeat biopsy with image guided targeting. While transrectal ultrasound guided magnetic resonance imaging fusion or in-bore magnetic resonance imaging targeting may be valuable for more reliable targeting, especially for lesions that are small or in difficult locations, in the absence of such targeting technologies cognitive (visual) targeting remains a reasonable approach in skilled hands. At least 2 targeted cores should be obtained from each magnetic resonance imaging defined target. Given the number of studies showing a proportion of missed clinically significant cancers by magnetic resonance imaging targeted cores, a case specific decision must be made whether to also perform concurrent systematic sampling. However, performing solely targeted biopsy should only be considered once quality assurance efforts have validated the performance of prostate magnetic resonance imaging interpretations with results consistent with the published literature. In patients with negative or low suspicion magnetic resonance imaging (PI-RADS assessment category of 1 or 2, respectively), other ancillary markers (ie PSA, PSAD, PSAV, PCA3, PHI, 4K) may be of value in identifying patients warranting repeat systematic biopsy, although further data are needed on this topic. If a repeat biopsy is deferred on the basis of magnetic resonance imaging findings, then continued clinical and laboratory followup is advised and consideration should be given to incorporating repeat magnetic resonance imaging in this diagnostic surveillance regimen.
View details for DOI 10.1016/j.juro.2016.06.079
View details for PubMedID 27320841
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Prostate Cancer Early Detection, Version 2.2016
JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK
2016; 14 (5): 509-519
Abstract
The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Prostate Cancer Early Detection provide recommendations for prostate cancer screening in healthy men who have elected to participate in an early detection program. The NCCN Guidelines focus on minimizing unnecessary procedures and limiting the detection of indolent disease. These NCCN Guidelines Insights summarize the NCCN Prostate Cancer Early Detection Panel's most significant discussions for the 2016 guideline update, which included issues surrounding screening in high-risk populations (ie, African Americans, BRCA1/2 mutation carriers), approaches to refine patient selection for initial and repeat biopsies, and approaches to improve biopsy specificity.
View details for Web of Science ID 000375888500007
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NCCN Guidelines Insights: Prostate Cancer Early Detection, Version 2.2016.
Journal of the National Comprehensive Cancer Network
2016; 14 (5): 509-519
Abstract
The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Prostate Cancer Early Detection provide recommendations for prostate cancer screening in healthy men who have elected to participate in an early detection program. The NCCN Guidelines focus on minimizing unnecessary procedures and limiting the detection of indolent disease. These NCCN Guidelines Insights summarize the NCCN Prostate Cancer Early Detection Panel's most significant discussions for the 2016 guideline update, which included issues surrounding screening in high-risk populations (ie, African Americans, BRCA1/2 mutation carriers), approaches to refine patient selection for initial and repeat biopsies, and approaches to improve biopsy specificity.
View details for PubMedID 27160230
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PROSTATE CANCER YIELD IN MRI LESIONS VARIES ACROSS RADIOLOGISTS
ELSEVIER SCIENCE INC. 2016: E42
View details for DOI 10.1016/j.juro.2016.02.1992
View details for Web of Science ID 000375278600096
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Accuracy of Prostate-Specific Antigen Values in Prostate Cancer Registries.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
2016
View details for PubMedID 27458297
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Prostate Cancer Early Detection, Version 2.2015 Clinical Practice Guidelines in Oncology
JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK
2015; 13 (12): 1534-1561
Abstract
Prostate cancer represents a spectrum of disease that ranges from nonaggressive, slow-growing disease that may not require treatment to aggressive, fast-growing disease that does. The NCCN Guidelines for Prostate Cancer Early Detection provide a set of sequential recommendations detailing a screening and evaluation strategy for maximizing the detection of prostate cancer that is potentially curable and that, if left undetected, represents a risk to the patient. The guidelines were developed for healthy men who have elected to participate in the early detection of prostate cancer, and they focus on minimizing unnecessary procedures and limiting the detection of indolent disease.
View details for Web of Science ID 000367021100010
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Gleason 6 Prostate Cancer: Translating Biology into Population Health
JOURNAL OF UROLOGY
2015; 194 (3): 626-634
Abstract
Gleason 6 (3+3) is the most commonly diagnosed prostate cancer among men with prostate specific antigen screening, the most histologically well differentiated and is associated with the most favorable prognosis. Despite its prevalence, considerable debate exists regarding the genetic features, clinical significance, natural history, metastatic potential and optimal management.Members of the Young Urologic Oncologists in the Society of Urologic Oncology cooperated in a comprehensive search of the peer reviewed English medical literature on Gleason 6 prostate cancer, specifically focusing on the history of the Gleason scoring system, histological features, clinical characteristics, practice patterns and outcomes.The Gleason scoring system was devised in the early 1960s, widely adopted by 1987 and revised in 2005 with a more restrictive definition of Gleason 6 disease. There is near consensus that Gleason 6 meets pathological definitions of cancer, but controversy about whether it meets commonly accepted molecular and genetic criteria of cancer. Multiple clinical series suggest that the metastatic potential of contemporary Gleason 6 disease is negligible but not zero. Population based studies in the U.S. suggest that more than 90% of men newly diagnosed with prostate cancer undergo treatment and are exposed to the risk of morbidity for a cancer unlikely to cause symptoms or decrease life expectancy. Efforts have been proposed to minimize the number of men diagnosed with or treated for Gleason 6 prostate cancer. These include modifications to prostate specific antigen based screening strategies such as targeting high risk populations, decreasing the frequency of screening, recommending screening cessation, incorporating remaining life expectancy estimates, using shared decision making and novel biomarkers, and eliminating prostate specific antigen screening entirely. Large nonrandomized and randomized studies have shown that active surveillance is an effective management strategy for men with Gleason 6 disease. Active surveillance dramatically reduces the number of men undergoing treatment without apparent compromise of cancer related outcomes.The definition and clinical relevance of Gleason 6 prostate cancer have changed substantially since its introduction nearly 50 years ago. A high proportion of screen detected cancers are Gleason 6 and the metastatic potential is negligible. Dramatically reducing the diagnosis and treatment of Gleason 6 disease is likely to have a favorable impact on the net benefit of prostate cancer screening.
View details for DOI 10.1016/j.juro.2015.01.126
View details for Web of Science ID 000359157200007
View details for PubMedCentralID PMC4551510
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Magnetic Resonance Imaging-Ultrasound Fusion Biopsy for Prediction of Final Prostate Pathology
JOURNAL OF UROLOGY
2014; 192 (5): 1367-1373
Abstract
We explored the impact of magnetic resonance imaging-ultrasound fusion prostate biopsy on the prediction of final surgical pathology.A total of 54 consecutive men undergoing radical prostatectomy at UCLA after fusion biopsy were included in this prospective, institutional review board approved pilot study. Using magnetic resonance imaging-ultrasound fusion, tissue was obtained from a 12-point systematic grid (mapping biopsy) and from regions of interest detected by multiparametric magnetic resonance imaging (targeted biopsy). A single radiologist read all magnetic resonance imaging, and a single pathologist independently rereviewed all biopsy and whole mount pathology, blinded to prior interpretation and matched specimen. Gleason score concordance between biopsy and prostatectomy was the primary end point.Mean patient age was 62 years and median prostate specific antigen was 6.2 ng/ml. Final Gleason score at prostatectomy was 6 (13%), 7 (70%) and 8-9 (17%). A tertiary pattern was detected in 17 (31%) men. Of 45 high suspicion (image grade 4-5) magnetic resonance imaging targets 32 (71%) contained prostate cancer. The per core cancer detection rate was 20% by systematic mapping biopsy and 42% by targeted biopsy. The highest Gleason pattern at prostatectomy was detected by systematic mapping biopsy in 54%, targeted biopsy in 54% and a combination in 81% of cases. Overall 17% of cases were upgraded from fusion biopsy to final pathology and 1 (2%) was downgraded. The combination of targeted biopsy and systematic mapping biopsy was needed to obtain the best predictive accuracy.In this pilot study magnetic resonance imaging-ultrasound fusion biopsy allowed for the prediction of final prostate pathology with greater accuracy than that reported previously using conventional methods (81% vs 40% to 65%). If confirmed, these results will have important clinical implications.
View details for DOI 10.1016/j.juro.2014.04.094
View details for Web of Science ID 000343856900015
View details for PubMedCentralID PMC4201866
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Magnetic resonance imaging-ultrasound fusion biopsy for prediction of final prostate pathology.
journal of urology
2014; 192 (5): 1367-1373
Abstract
We explored the impact of magnetic resonance imaging-ultrasound fusion prostate biopsy on the prediction of final surgical pathology.A total of 54 consecutive men undergoing radical prostatectomy at UCLA after fusion biopsy were included in this prospective, institutional review board approved pilot study. Using magnetic resonance imaging-ultrasound fusion, tissue was obtained from a 12-point systematic grid (mapping biopsy) and from regions of interest detected by multiparametric magnetic resonance imaging (targeted biopsy). A single radiologist read all magnetic resonance imaging, and a single pathologist independently rereviewed all biopsy and whole mount pathology, blinded to prior interpretation and matched specimen. Gleason score concordance between biopsy and prostatectomy was the primary end point.Mean patient age was 62 years and median prostate specific antigen was 6.2 ng/ml. Final Gleason score at prostatectomy was 6 (13%), 7 (70%) and 8-9 (17%). A tertiary pattern was detected in 17 (31%) men. Of 45 high suspicion (image grade 4-5) magnetic resonance imaging targets 32 (71%) contained prostate cancer. The per core cancer detection rate was 20% by systematic mapping biopsy and 42% by targeted biopsy. The highest Gleason pattern at prostatectomy was detected by systematic mapping biopsy in 54%, targeted biopsy in 54% and a combination in 81% of cases. Overall 17% of cases were upgraded from fusion biopsy to final pathology and 1 (2%) was downgraded. The combination of targeted biopsy and systematic mapping biopsy was needed to obtain the best predictive accuracy.In this pilot study magnetic resonance imaging-ultrasound fusion biopsy allowed for the prediction of final prostate pathology with greater accuracy than that reported previously using conventional methods (81% vs 40% to 65%). If confirmed, these results will have important clinical implications.
View details for DOI 10.1016/j.juro.2014.04.094
View details for PubMedID 24793118
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Initial experience with electronic tracking of specific tumor sites in men undergoing active surveillance of prostate cancer
UROLOGIC ONCOLOGY-SEMINARS AND ORIGINAL INVESTIGATIONS
2014; 32 (7): 952-957
Abstract
Targeted biopsy, using magnetic resonance (MR)-ultrasound (US) fusion, may allow tracking of specific cancer sites in the prostate. We aimed to evaluate the initial use of the technique to follow tumor sites in men on active surveillance of prostate cancer.A total of 53 men with prostate cancer (all T1c category) underwent rebiopsy of 74 positive biopsy sites, which were tracked and targeted using the Artemis MR-US fusion device (Eigen, Grass Valley, CA) from March 2010 through January 2013. The initial biopsy included 12 cores from a standard template (mapped by software) and directed biopsies from regions of interest seen on MR imaging (MRI). In the repeat biopsy, samples were taken from sites containing cancer at the initial biopsy. Outcomes of interest at second MR-US biopsy included (a) presence of any cancer and (b) presence of clinically significant cancer.All cancers on initial biopsy had either Gleason score 3+3 = 6 (n = 63) or 3+4 = 7 (n = 11). At initial biopsy, 23 cancers were within an MRI target, and 51 were found on systematic biopsy. Cancer detection rate on repeat biopsy (29/74, 39%) was independent of Gleason score on initial biopsy (P = not significant) but directly related to initial cancer core length (P<0.02). Repeat sampling of cancerous sites within MRI targets was more likely to show cancer than resampling of tumorous systematic sites (61% vs. 29%, P = 0.005). When initial cancer core length was≥4 mm within an MRI target, more than 80% (5/6) of follow-up tracking biopsies were positive. An increase of Gleason score was uncommon (9/74, 12%).Monitoring of specific prostate cancer-containing sites may be achieved in some men using an electronic tracking system. The chances of finding tumor on repeat specific-site sampling was directly related to the length of tumor in the initial biopsy core and presence of tumor within an MRI target; upgrading of Gleason score was uncommon. Further research is required to evaluate the potential utility of site-specific biopsy tracking for patients with prostate cancer on active surveillance.
View details for DOI 10.1016/j.urolonc.2014.04.003
View details for Web of Science ID 000343968900003
View details for PubMedCentralID PMC4254112
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Initial experience with electronic tracking of specific tumor sites in men undergoing active surveillance of prostate cancer.
Urologic oncology
2014; 32 (7): 952-957
Abstract
Targeted biopsy, using magnetic resonance (MR)-ultrasound (US) fusion, may allow tracking of specific cancer sites in the prostate. We aimed to evaluate the initial use of the technique to follow tumor sites in men on active surveillance of prostate cancer.A total of 53 men with prostate cancer (all T1c category) underwent rebiopsy of 74 positive biopsy sites, which were tracked and targeted using the Artemis MR-US fusion device (Eigen, Grass Valley, CA) from March 2010 through January 2013. The initial biopsy included 12 cores from a standard template (mapped by software) and directed biopsies from regions of interest seen on MR imaging (MRI). In the repeat biopsy, samples were taken from sites containing cancer at the initial biopsy. Outcomes of interest at second MR-US biopsy included (a) presence of any cancer and (b) presence of clinically significant cancer.All cancers on initial biopsy had either Gleason score 3+3 = 6 (n = 63) or 3+4 = 7 (n = 11). At initial biopsy, 23 cancers were within an MRI target, and 51 were found on systematic biopsy. Cancer detection rate on repeat biopsy (29/74, 39%) was independent of Gleason score on initial biopsy (P = not significant) but directly related to initial cancer core length (P<0.02). Repeat sampling of cancerous sites within MRI targets was more likely to show cancer than resampling of tumorous systematic sites (61% vs. 29%, P = 0.005). When initial cancer core length was≥4 mm within an MRI target, more than 80% (5/6) of follow-up tracking biopsies were positive. An increase of Gleason score was uncommon (9/74, 12%).Monitoring of specific prostate cancer-containing sites may be achieved in some men using an electronic tracking system. The chances of finding tumor on repeat specific-site sampling was directly related to the length of tumor in the initial biopsy core and presence of tumor within an MRI target; upgrading of Gleason score was uncommon. Further research is required to evaluate the potential utility of site-specific biopsy tracking for patients with prostate cancer on active surveillance.
View details for DOI 10.1016/j.urolonc.2014.04.003
View details for PubMedID 25027689
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Target detection: magnetic resonance imaging-ultrasound fusion-guided prostate biopsy.
Urologic oncology
2014; 32 (6): 903-911
Abstract
Recent advances in multiparametric magnetic resonance imaging (MRI) have enabled image-guided detection of prostate cancer. Fusion of MRI with real-time ultrasound (US) allows the information from MRI to be used to direct biopsy needles under US guidance in an office-based procedure. Fusion can be performed either cognitively or electronically, using a fusion device. Fusion devices allow superimposition (coregistration) of stored MRI images on real-time US images; areas of suspicion found on MRI can then serve as targets during US-guided biopsy. Currently available fusion devices use a variety of technologies to perform coregistration: robotic tracking via a mechanical arm with built-in encoders (Artemis/Eigen, BioJet/Geoscan); electromagnetic tracking (UroNav/Philips-Invivo, Hi-RVS/Hitachi); or tracking with a 3D US probe (Urostation/Koelis). Targeted fusion biopsy has been shown to identify more clinically significant cancers and fewer insignificant cancers than conventional biopsy. Fusion biopsy appears to be a major advancement over conventional biopsy because it allows (1) direct targeting of suspicious areas not seen on US and (2) follow-up biopsy of specific cancerous sites in men undergoing active surveillance.
View details for DOI 10.1016/j.urolonc.2013.08.006
View details for PubMedID 24239473
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Target detection: Magnetic resonance imaging-ultrasound fusion-guided prostate biopsy
UROLOGIC ONCOLOGY-SEMINARS AND ORIGINAL INVESTIGATIONS
2014; 32 (6): 903-911
Abstract
Recent advances in multiparametric magnetic resonance imaging (MRI) have enabled image-guided detection of prostate cancer. Fusion of MRI with real-time ultrasound (US) allows the information from MRI to be used to direct biopsy needles under US guidance in an office-based procedure. Fusion can be performed either cognitively or electronically, using a fusion device. Fusion devices allow superimposition (coregistration) of stored MRI images on real-time US images; areas of suspicion found on MRI can then serve as targets during US-guided biopsy. Currently available fusion devices use a variety of technologies to perform coregistration: robotic tracking via a mechanical arm with built-in encoders (Artemis/Eigen, BioJet/Geoscan); electromagnetic tracking (UroNav/Philips-Invivo, Hi-RVS/Hitachi); or tracking with a 3D US probe (Urostation/Koelis). Targeted fusion biopsy has been shown to identify more clinically significant cancers and fewer insignificant cancers than conventional biopsy. Fusion biopsy appears to be a major advancement over conventional biopsy because it allows (1) direct targeting of suspicious areas not seen on US and (2) follow-up biopsy of specific cancerous sites in men undergoing active surveillance.
View details for DOI 10.1016/j.urolonc.2013.08.006
View details for Web of Science ID 000340343400024
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Targeted Prostate Biopsy to Select Men for Active Surveillance: Do the Epstein Criteria Still Apply?
The Journal of urology
2014
Abstract
The Epstein histologic criteria (Gleason score <6, <2 cores positive, <50% of any core), established in 1994, have been widely used to select men for active surveillance. However, with the advent of targeted biopsy, which may be more accurate than conventional biopsy, we re-evaluated the likelihood of re-classification upon confirmatory re-biopsy using multi-parametric MRI-ultrasound fusion (mpMRI-US).We identified 113 subjects enrolled in the UCLA active surveillance meeting Epstein Criteria who subsequently underwent confirmatory, targeted biopsy via mpMRI-US. Median age was 64 years, PSA 4.2 ng/ml and prostate volume 46.8 cc. Targets, or regions of interest on mpMRI, were graded by level of suspicion and were biopsied at 3 mm intervals along their longest axis (median 10.5 mm). Additionally, 12 systematic cores were obtained during confirmatory re-biopsy. Our reporting is consistent with START criteria.Overall, confirmatory fusion biopsy resulted in re-classification for 41 men (36%), 26 (23%) due to Gleason grade >6, and 15 (13%) due to high volume Gleason 6 disease. When stratified by suspicion on mpMRI, the likelihood of reclassification was 24% to 29% for men with target grade 0 to 3, 45% for grade 4, and 100% for grade 5 (p=0.001). Men with grade 4 and 5 versus lower grade targets were >3 times (Odds Ratio 3.2, 95% Confidence Interval 1.4, 7.1, p=0.006) more likely to be reclassified.Upon confirmatory re-biopsy using mpMRI-US, men with high-suspicion mpMRI targets were frequently reclassified (45%-100%). Criteria for active surveillance should be re-evaluated when mpMRI-guided prostate biopsy is employed.
View details for DOI 10.1016/j.juro.2014.02.005
View details for PubMedID 24512956
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The role of magnetic resonance imaging in delineating clinically significant prostate cancer.
Urology
2014; 83 (2): 369-75
Abstract
To determine whether multiparametric magnetic resonance imaging might improve the identification of patients with higher risk disease at diagnosis and thereby reduce the incidence of undergrading or understaging.We retrospectively reviewed the clinical records of 115 patients who underwent multiparametric magnetic resonance imaging before radical prostatectomy. We used Epstein's criteria of insignificant disease with and without a magnetic resonance imaging (MRI) parameter (apparent diffusion coefficient) to calculate sensitivity, specificity, as well as negative and positive predictive values [NPV and PPV] across varying definitions of clinically significant cancer based on Gleason grade and tumor volume (0.2 mL, 0.5 mL, and 1.3 mL) on whole-mount prostate specimens. Logistic regression analysis was performed to determine the incremental benefit of MRI in delineating significant cancer.The majority had a prostate-specific antigen from 4.1-10.0 (67%), normal rectal examinations (90%), biopsy Gleason score ≤6 (68%), and ≤2 cores positive (55%). Of the 58 patients pathologically staged with Gleason 7 or pT3 disease at prostatectomy, Epstein's criteria alone missed 12 patients (sensitivity of 79% and NPV of 68%). Addition of apparent diffusion coefficient improved the sensitivity and NPV for predicting significant disease at prostatectomy to 93% and 84%, respectively. MRI improved detection of large Gleason 6 (≥1.3 mL, P = .006) or Gleason ≥7 lesions of any size (P <.001).Integration of MRI with existing clinical staging criteria helps identify patients with significant cancer. Clinicians should consider utilizing MRI in the decision-making process.
View details for DOI 10.1016/j.urology.2013.09.045
View details for PubMedID 24468511
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Deletions of chromosomes 3p and 14q molecularly subclassify clear cell renal cell carcinoma
CANCER
2013; 119 (8): 1547-1554
Abstract
The short arm of chromosome 3 (3p) harbors the von Hippel-Lindau (VHL) tumor suppressor gene, and the long arm of chromosome 14 (14q) harbors the hypoxia-inducible factor 1α (HIF-1α) gene. The objective of this study was to evaluate the significance of 3p loss (loss VHL gene) and 14q loss (loss HIF-1α gene) in clear cell renal cell carcinoma (ccRCC).In total, 288 ccRCC tumors underwent a prospective cytogenetic analysis for alterations in chromosomes 3p and 14q. Tumors were assigned to 1 of 4 possible chromosomal alterations: VHL +3p/+14q (VHL wild type [VHL-WT]), VHL +3p/-14q (VHL-WT plus HIF2α [WT/H2]), -3p/+14q (HIF1α and HIF2α [H1H2]), and -3p/-14q (HIF2α [H2]).Among patients who had loss of 3p, tumors with -3p/-14q (H2) alterations were larger (P = .002), had higher grade (P = .002) and stage (P = .001), and more often were metastatic (P = .029) than tumors that retained 14q (H1H2). All patients who had tumors with -3p/-14q (H2) had worse cancer-specific survival (P = .014), and patients who had localized disease (P = .012) and primary T1 (pT1) tumors (P = .008) had worse recurrence-free survival. In patients who had pT1 tumors, combined 3p/14q loss was an independent predictor of recurrence-free survival (hazard ratio, 11.19; 95% confidence interval, 1.91-65.63) and cancer-specific survival (hazard ratio, 15.93; 95% confidence interval, 3.09-82.16). The current investigation was limited by its retrospective design, single-center experience, and a lack of confirmatory protein analyses.Loss of chromosome 3p (the VHL gene) was associated with improved survival in patients with ccRCC, whereas loss of chromosome 14q (the HIF-1α gene) was associated with worse outcomes. The results of the current study support the hypothesis that HIF-1α functions as an important tumor suppressor gene in ccRCC.
View details for DOI 10.1002/cncr.27947
View details for Web of Science ID 000317618700014
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Targeted Biopsy in the Detection of Prostate Cancer Using an Office Based Magnetic Resonance Ultrasound Fusion Device
JOURNAL OF UROLOGY
2013; 189 (1): 86-91
Abstract
Targeted biopsy of lesions identified on magnetic resonance imaging may enhance the detection of clinically relevant prostate cancers. We evaluated prostate cancer detection rates in 171 consecutive men using magnetic resonance ultrasound fusion prostate biopsy.Subjects underwent targeted biopsy for active surveillance (106) or persistently increased prostate specific antigen but negative prior conventional biopsy (65). Before biopsy, each man underwent multiparametric magnetic resonance imaging at 3.0 Tesla. Lesions on magnetic resonance imaging were outlined in 3 dimensions and assigned increasing cancer suspicion levels (image grade 1 to 5) by a uroradiologist. A biopsy tracking system was used to fuse the stored magnetic resonance imaging with real-time ultrasound, generating a 3-dimensional prostate model on the fly. Working from the 3-dimensional model, transrectal biopsy of target lesions and 12 systematic biopsies were performed with the patient under local anesthesia in the clinic.A total of 171 subjects (median age 65 years) underwent targeted biopsy. At biopsy, median prostate specific antigen was 4.9 ng/ml and prostate volume was 48 cc. A targeted biopsy was 3 times more likely to identify cancer than a systematic biopsy (21% vs 7%). Prostate cancer was found in 53% of men, 38% of whom had Gleason grade 7 or greater cancer. Of the men with Gleason 7 or greater cancer 38% had disease detected only on targeted biopsies. Targeted biopsy findings correlated with level of suspicion on magnetic resonance imaging. Of 16 men 15 (94%) with an image grade 5 target (highest suspicion) had prostate cancer, including 7 with Gleason 7 or greater cancer.Prostate lesions identified on magnetic resonance imaging can be accurately targeted using magnetic resonance ultrasound fusion biopsy by a urologist in clinic. Biopsy findings correlate with level of suspicion on magnetic resonance imaging.
View details for DOI 10.1016/j.juro.2012.08.095
View details for Web of Science ID 000312604800029
View details for PubMedID 23158413
View details for PubMedCentralID PMC3561472
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Differing Perceptions of Quality of Life in Patients With Prostate Cancer and Their Doctors
JOURNAL OF UROLOGY
2013; 189 (1): S59-S65
Abstract
As the number of prostate cancer survivors increases, urologists must recognize their quality of life impairment. In the past physician ratings of patient symptoms did not correlate with patient self-assessments. We determined if urologists have improved their reporting of patient health related quality of life. We also investigated if urologists assessed health related quality of life more accurately in the short or long term.We identified 1,366 men from CaPSURE™, a national, prospective cohort, who had undergone prostatectomy, brachytherapy or external beam radiation therapy. At each visit urologists assessed fatigue, pain, and sexual, urinary and bowel dysfunction. Participants independently completed the SF-36™ and the UCLA-PCI. We contrasted the frequency of impairment reported by physicians and participants in select health related quality of life domains in the short (less than 1 year) and long (greater than 2 years) term. We also compared physician-patient concordance between the periods 1995 to 2000 and 2001 to 2007.In short-term and long-term followup, and for the 1995 to 2000 and 2001 to 2007 cohorts, physician and participant assessments differed in all analyzed domains. Urologists noted impairment in urinary and sexual function more often than fatigue or pain. Disagreement between physician and participant ratings did not vary dramatically from short-term to long-term followup, or from the earlier to the later cohort.In men treated for localized prostate cancer physician ratings of symptoms do not correlate well with patient self-assessments of health related quality of life. Physician reporting did not improve over time. It is increasingly important to recognize and address impairments in quality of life from prostate cancer and its treatment.
View details for DOI 10.1016/j.juro.2012.11.032
View details for Web of Science ID 000312100000016
View details for PubMedID 23234635
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Gain of chromosome 8q is associated with metastases and poor survival of patients with clear cell renal cell carcinoma.
Cancer
2012; 118 (23): 5777-5782
Abstract
The aim of this study was to evaluate the prevalence of chromosome 8q gain in clear cell renal cell carcinoma (CCRCC) and to correlate the findings with tumor phenotype and disease-specific survival (DSS).The tumor karyotypes of 336 consecutive patients with CCRCC were prospectively evaluated with classical cytogenetic analysis. Chromosome 8q status was correlated with clinicopathological variables, and its impact on DSS was evaluated.Gain of 8q occurred in 28 tumors (8.3%). Gain of 8q was associated with a higher risk of regional lymph node (21.4% vs 6.2%, P = .011) and distant metastases (50.0% vs 24.4%, P = .006), and greater tumor sizes (P = .030). Patients with gain of 8q had a 3.22-fold increased risk of death from CCRCC (P < .001). In multivariable analysis, gain of 8q was identified as an independent prognostic factor (hazard ratio, 2.37; P = .006). The concordance index of a multivariable base model increased significantly following inclusion of 8q gain (P = .0015).Gain of chromosome 8q occurs in a subset of CCRCCs and is associated with an increased risk of metastases and death from CCRCC. Because the proto-oncogene c-MYC is among the list of candidate genes located on 8q, our data suggest that these tumors may have unique pathways activated, which are associated with an aggressive tumor phenotype. If confirmed, defining tumors with gain of 8q may assist in identifying patients who would benefit for specific c-MYC inhibitors or agents that target the MAPK/ERK (mitogen-activated protein kinase) pathway.
View details for DOI 10.1002/cncr.27607
View details for PubMedID 22605478
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VALUE OF TARGETED BIOPSY IN DETECTING PROSTATE CANCER USING AN OFFICE-BASED MR-US FUSION DEVICE
Annual Meeting of the American-Urological-Association (AUA)
ELSEVIER SCIENCE INC. 2012: E829–E829
View details for Web of Science ID 000302912503350
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Systemic therapy for metastatic renal cell carcinoma: a review and update.
Reviews in urology
2012; 14 (3-4): 65-78
Abstract
An in-depth understanding of metastatic renal cell carcinoma (mRCC) is important so that practitioners can make informed evidenced-based decisions with patients to optimize not only quantity of life but quality of life as well. Therefore, this review focuses on the biology of mRCC as it relates to targets for therapy, as well as on the small molecules rationally designed with these targets in mind. In addition, anticipated emerging therapies are highlighted, including the new tyrosine kinase inhibitors axitinib and tivozanib, as well as new immune-based therapies such as dendritic cell-based vaccines and antibodies. We also briefly review recent reports from the emerging field of predicting drug response based on molecular markers. And finally, management of metastatic non-clear cell RCC histologies are discussed focusing on available evidence to direct decision making when assessing therapeutic options.
View details for PubMedID 23526579
View details for PubMedCentralID PMC3602729
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Dynamic Real-time Microscopy of the Urinary Tract Using Confocal Laser Endomicroscopy
UROLOGY
2011; 78 (1): 225-231
Abstract
To develop the diagnostic criteria for benign and neoplastic conditions of the urinary tract using probe-based confocal laser endomicroscopy (pCLE), a new technology for dynamic, in vivo imaging with micron-scale resolution. The suggested diagnostic criteria will formulate a guide for pCLE image interpretation in urology.Patients scheduled for transurethral resection of bladder tumor (TURBT) or nephrectomy were recruited. After white-light cystoscopy (WLC), fluorescein was administered as contrast. Different areas of the urinary tract were imaged with pCLE via direct contact between the confocal probe and the area of interest. Confocal images were subsequently compared with standard hematoxylin and eosin analysis.pCLE images were collected from 66 participants, including 2 patients who underwent nephrectomy. We identified key features associated with different anatomic landmarks of the urinary tract, including the kidney, ureter, bladder, prostate, and urethra. In vivo pCLE of the bladder demonstrated distinct differences between normal mucosa and neoplastic tissue. Using mosaicing, a post hoc image-processing algorithm, individual image frames were juxtaposed to form wide-angle views to better evaluate tissue microarchitecture.In contrast to standard pathologic analysis of fixed tissue with hematoxylin and eosin, pCLE provides real time microscopy of the urinary tract to enable dynamic interrogation of benign and neoplastic tissues in vivo. The diagnostic criteria developed in this study will facilitate adaptation of pCLE for use in conjunction with WLC to expedite diagnosis of urinary tract pathology, particularly bladder cancer.
View details for DOI 10.1016/j.urology.2011.02.057
View details for Web of Science ID 000292080300062
View details for PubMedID 21601243
View details for PubMedCentralID PMC4038103
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Electrochemical immunosensor detection of urinary lactoferrin in clinical samples for urinary tract infection diagnosis
BIOSENSORS & BIOELECTRONICS
2010; 26 (2): 649-654
Abstract
Urine is the most abundant and easily accessible of all body fluids and provides an ideal route for non-invasive diagnosis of human diseases, particularly of the urinary tract. Electrochemical biosensors are well suited for urinary diagnostics due to their excellent sensitivity, low-cost, and ability to detect a wide variety of target molecules including nucleic acids and protein biomarkers. We report the development of an electrochemical immunosensor for direct detection of the urinary tract infection (UTI) biomarker lactoferrin from infected clinical samples. An electrochemical biosensor array with alkanethiolate self-assembled monolayer (SAM) was used. Electrochemical impedance spectroscopy was used to characterize the mixed SAM, consisted of 11-mercaptoundecanoic acid and 6-mercapto-1-hexanol. A sandwich amperometric immunoassay was developed for detection of lactoferrin from urine, with a detection limit of 145 pg/ml. We validated lactoferrin as a biomarker of pyuria (presence of white blood cells in urine), an important hallmark of UTI, in 111 patient-derived urine samples. Finally, we demonstrated multiplex detection of urinary pathogens and lactoferrin through simultaneous detection of bacterial nucleic acid (16S rRNA) and host immune response protein (lactoferrin) on a single sensor array. Our results represent first integrated sensor platform capable of quantitative pathogen identification and measurement of host immune response, potentially providing clinical diagnosis that is not only more expeditious but also more informative than the current standard.
View details for DOI 10.1016/j.bios.2010.07.002
View details for Web of Science ID 000283804400056
View details for PubMedID 20667707
View details for PubMedCentralID PMC2946447
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DYNAMIC REAL TIME MICROSCOPY OF THE URINARY TRACT: AN IMAGING ATLAS BASED ON CONFOCAL LASER ENDOMICROSCOPY
MARY ANN LIEBERT INC. 2010: A278–A278
View details for Web of Science ID 000283864901225
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IS SURVEILLANCE FOR STAGE I SEMINOMA TRULY A LOW RISK OPTION?: ESTIMATING IMAGING RELATED RADIATION EXPOSURE AND THE RISK OF SECONDARY MALIGNANCY
ELSEVIER SCIENCE INC. 2010: E325–E326
View details for DOI 10.1016/j.juro.2010.02.2335
View details for Web of Science ID 000209829401682
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Differing Perceptions of Quality of Life in Patients With Prostate Cancer and Their Doctors
JOURNAL OF UROLOGY
2009; 182 (5): 2296-2302
Abstract
As the number of prostate cancer survivors increases, urologists must recognize their quality of life impairment. In the past physician ratings of patient symptoms did not correlate with patient self-assessments. We determined if urologists have improved their reporting of patient health related quality of life. We also investigated if urologists assessed health related quality of life more accurately in the short or long term.We identified 1,366 men from CaPSURE, a national, prospective cohort, who had undergone prostatectomy, brachytherapy or external beam radiation therapy. At each visit urologists assessed fatigue, pain, and sexual, urinary and bowel dysfunction. Participants independently completed the SF-36 and the UCLA-PCI. We contrasted the frequency of impairment reported by physicians and participants in select health related quality of life domains in the short (less than 1 year) and long (greater than 2 years) term. We also compared physician-patient concordance between the periods 1995 to 2000 and 2001 to 2007.In short-term and long-term followup, and for the 1995 to 2000 and 2001 to 2007 cohorts, physician and participant assessments differed in all analyzed domains. Urologists noted impairment in urinary and sexual function more often than fatigue or pain. Disagreement between physician and participant ratings did not vary dramatically from short-term to long-term followup, or from the earlier to the later cohort.In men treated for localized prostate cancer physician ratings of symptoms do not correlate well with patient self-assessments of health related quality of life. Physician reporting did not improve over time. It is increasingly important to recognize and address impairments in quality of life from prostate cancer and its treatment.
View details for DOI 10.1016/j.juro.2009.07.027
View details for Web of Science ID 000270756900063
View details for PubMedID 19758610
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Optical Biopsy of Human Bladder Neoplasia With In Vivo Confocal Laser Endomicroscopy
JOURNAL OF UROLOGY
2009; 182 (4): 1299-1305
Abstract
Confocal laser endomicroscopy is a new endoscopic imaging technology that could complement white light cystoscopy by providing in vivo bladder histopathology. We evaluated confocal laser endomicroscopy by imaging normal, malignant appearing and indeterminate bladder mucosa in a pilot study.Patients scheduled to undergo transurethral resection of bladder tumors were recruited during a 3-month period. After standard cystoscopy fluorescein was administered intravesically and/or intravenously as a contrast dye. A 2.6 mm probe based confocal laser endomicroscope was passed through a 26 Fr resectoscope to image normal and abnormal appearing areas. The images were collected with 488 nm excitation at 8 to 12 frames per second. The endomicroscopic images were compared with standard hematoxylin and eosin analysis of transurethral resection of bladder tumor specimens.Of the 27 recruited patients 8 had no cancer, 9 had low grade tumors, 9 had high grade tumors and 1 had a low grade tumor with a high grade focus. Endomicroscopic images demonstrated clear differences between normal mucosa, and low and high grade tumors. In normal urothelium larger umbrella cells are seen most superficially followed by smaller intermediate cells and the less cellular lamina propria. In contrast, low grade papillary tumors demonstrate densely arranged but normal-shaped small cells extending outward from fibrovascular cores. High grade tumors show markedly irregular architecture and cellular pleomorphism.We report the first study to our knowledge of in vivo confocal laser endomicroscopy in the urinary tract. Marked differences among normal urothelium, low grade tumors and high grade tumors were visualized. Pending further clinical investigation and technological improvement, confocal laser endomicroscopy may become a useful adjunct to conventional cystoscopy.
View details for DOI 10.1016/j.juro.2009.06.039
View details for Web of Science ID 000269764100016
View details for PubMedID 19683270
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OPTICAL BIOPSY OF HUMAN BLADDER NEOPLASIA WITH IN VIVO CONFOCAL LASER ENDOMICROSCOPY
104th Annual Meeting of the American-Urological-Association
ELSEVIER SCIENCE INC. 2009: 414–15
View details for Web of Science ID 000264448501254
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Fibered Confocal Microscopy of Bladder Tumors: An ex Vivo Study
JOURNAL OF ENDOUROLOGY
2009; 23 (2): 197-201
Abstract
The inadequacy of white-light cystoscopy to detect flat bladder tumors is well recognized. Great interest exists in developing other imaging technologies to augment or supplant conventional cystoscopy. Fibered confocal microscopy offers the promise of providing in vivo histopathologic information to help distinguish malignant from benign bladder lesions. We report the initial use of this technology to visualize tumors in the human bladder.We performed ex vivo fibered confocal imaging of fresh radical cystectomy specimens using the Mauna Kea Technologies Cellvizio system. The findings were compared with results from standard histopathology.The bladders of four patients were imaged using the fibered confocal microscope. Normal and neoplastic urothelium manifested differences in cellular and vascular density.This study demonstrates the feasibility of using fibered confocal microscopy to detect histologic differences between normal and neoplastic urothelium, and establishes a foundation for the use of fiber-based confocal microscopy in clinical studies.
View details for DOI 10.1089/end.2008.0524
View details for Web of Science ID 000263355500005
View details for PubMedID 19196063
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Estimating the Risk of Cancer Associated With Imaging Related Radiation During Surveillance for Stage I Testicular Cancer Using Computerized Tomography
JOURNAL OF UROLOGY
2009; 181 (2): 627-632
Abstract
Computerized tomography has a critical role in the surveillance of stage I nonseminomatous germ cell tumors of the testis. Some protocols call for up to 16 computerized tomography scans over 5 years, thereby exposing young patients to a significant amount of radiation. We estimated the lifetime risk of cancer incidence and cancer death from imaging related radiation received during surveillance of stage I nonseminomatous germ cell tumor.Using a model with a 64-slice computerized tomography scanner obtaining images of the abdomen and pelvis with or without chest in a standardized, phantom male patient, organ specific radiation doses were estimated using Monte Carlo simulation techniques. Lifetime attributable risks of cancer were estimated using the approach outlined in the Biological Effects of Ionizing Radiation VII Phase 2 report.With a 5-year surveillance protocol as suggested by the National Comprehensive Cancer Network, lifetime cancer risk ranged from 1 in 52 (1.9%) for an 18-year-old to 1 in 63 for a 40-year-old patient (1.2%). If chest computerized tomography is also performed the risk increases to 1 in 39 (2.6%) and 1 in 85 (1.6%), respectively. Lung and colon cancer accounted for most of the risk. The relative risk of a secondary malignancy with surveillance compared to a single scan after retroperitoneal lymph node dissection is approximately 15.2.Computerized tomography used in testicular cancer surveillance protocols imparts large radiation doses and is associated with a significant risk of cancer. This risk should be factored into counseling patients with stage I nonseminomatous germ cell tumor.
View details for DOI 10.1016/j.juro.2008.10.005
View details for Web of Science ID 000262419900070
View details for PubMedID 19091344
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Management of Wilms tumor: current standard of care
NATURE CLINICAL PRACTICE UROLOGY
2008; 5 (10): 551-560
Abstract
Wilms tumor is the most common renal malignancy in children. In the 1930s, overall survival for children with Wilms tumor was approximately 30%. Use of multidisciplinary therapy, guided by results from multi-institutional, randomized trials, has substantially improved overall survival to about 90%. Management of Wilms tumor differs substantially between Europe and the US. In Europe, the International Society of Pediatric Oncology protocols call for management of patients with presumptive Wilms tumor with neoadjuvant chemotherapy followed by nephrectomy and further chemotherapy. In the US, protocols developed by the National Wilms Tumor Study Group advise primary nephrectomy followed by a chemotherapy regimen tailored to the pathologic tumor stage. Despite these disparate strategies, overall survival is similar in patients managed according to European and US protocols. Patients with Wilms tumor now have excellent survival. Therefore, current goals aim to reduce the morbidity associated with therapy. Important complications of treatment for Wilms tumor include cardiomyopathy, renal failure, and increased risk of a secondary malignancy. Currently, the role of laparoscopic surgery in management of Wilms tumor remains extremely limited.
View details for DOI 10.1038/ncpuro1218
View details for Web of Science ID 000259638000010
View details for PubMedID 18836464
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Spirituality influences health related quality of life in men with prostate cancer
PSYCHO-ONCOLOGY
2006; 15 (2): 121-131
Abstract
Spirituality is interdependent with the biological, psychological, and interpersonal aspects of life. Although spirituality has been studied in breast cancer survivors, little work has been done in men with prostate cancer. We sought to determine whether lower spirituality in men with early stage prostate cancer is associated with worse general health-related quality of life (HRQOL), disease-specific HRQOL, or psychosocial health. Two hundred and twenty-two subjects were drawn from a state-funded program providing free prostate cancer treatment to indigent men. Validated instruments captured spirituality, general and disease-specific HRQOL, anxiety, symptom distress, and emotional well-being. We found a consistent relationship between spirituality and the outcomes assessed. Low spirituality was associated with significantly worse physical and mental health, sexual function and more urinary bother after controlling for covariates. All of the psychosocial variables studied reflected worse adjustment in the men with low spirituality. Because the likelihood of prostate cancer survivorship is high, interventions targeting spirituality could impact the physical and psychosocial health of many men.
View details for DOI 10.1002/pon.929
View details for Web of Science ID 000235490000004
View details for PubMedID 15880458
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Impact of diet on prostate cancer: a review
PROSTATE CANCER AND PROSTATIC DISEASES
2005; 8 (4): 304-310
Abstract
Epidemiological studies suggest that environmental factors may mediate the transformation of latent prostate cancer into clinically apparent tumors and that diet appears to influence this progression. Close correlations between average per capita fat intake and prostate cancer mortality internationally generated interest in underlying mechanisms for this link, such as through serum levels of androgens, free radicals, proinflammatory fatty acid metabolites, or insulin-like growth factor. Much interest currently lies in the potential of HMG-CoA reductase inhibitors (statins) to play a chemopreventative role in prostate cancer. Lycopene, a potent antioxidant found in tomatoes, may exert a protective effect in the prostate. Selenium and vitamin E have also been shown to decrease the risk of prostate cancer in some men. Calcium may support vitamin D-related antiproliferative effects in prostate cancer. Certain soy proteins, common in the Asian diet, have been shown to inhibit prostate cancer cell growth. Finally, green tea may also have a chemopreventive effect by inducing apoptosis. Despite confounding factors present in clinical studies assessing the effect of diet on cancer risk, the data remain compelling that a variety of nutrients may prevent the development and progression of prostate cancer.
View details for DOI 10.1038/sj.pcan.4500825
View details for Web of Science ID 000234418000002
View details for PubMedID 16130015
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Ethnic variation in health-related quality of life among low-income men with prostate cancer
ETHNICITY & DISEASE
2005; 15 (3): 461-468
Abstract
To describe and compare health-related quality of life (HRQOL) among Hispanic, African-American, and Caucasian men with localized prostate cancer.Observational study of low-income, ethnically diverse men with non-metastatic prostate cancer.Statewide public assistance program in California.208 men (51 Caucasian, 115 Hispanic, and 42 African-American men) with non-metastatic disease.Radical retropubic prostatectomy, radiation therapy, and hormonal therapy.Validated instruments measured general and disease-specific HRQOL, anxiety and fear of recurrence, spirituality, symptom distress, and self-efficacy.Hispanic men with prostate cancer were less educated, more often in significant relationships, and had more variable incomes compared with men of other ethnic/racial backgrounds. In univariate analyses, Caucasian men reported better physical function but less spirituality, while Hispanic men reported worse sexual function. Multivariate analysis revealed that Hispanic men had significantly worse physical function, bowel function, and bowel bother. African-American men experienced greater anxiety over recurrence. African-American and Hispanic men were more spiritual than Caucasian men.Greater attention to demographic variations in HRQOL may allow physicians to improve outcomes across ethnicities in low-income men with prostate cancer by offering more specialized counseling and providing referral to social support systems.
View details for Web of Science ID 000231199700015
View details for PubMedID 16108307