Davis Vigneault
Postdoctoral Medical Fellow, Radiology
Resident in Radiology
Bio
Davis is a resident in diagnostic radiology at Stanford, having received his medical degree from Tufts University School of Medicine and his DPhil in Biomedical Engineering from the University of Oxford through the NIH-Oxford Scholars and medical scientist training programs. For his graduate degree, worked on novel algorithms for measuring regional cardiac function from cardiac CT and MR, publishing in Radiology, Medical Image Analysis, and the Journal of Cardiovascular Magnetic Resonance, among others. In addition to cardiovascular imaging and deep learning, Davis has a strong interest in open source science, having been a frequent contributor of software to ITK and other libraries in the ITK ecosystem.
Honors & Awards
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Dr. Marc and Diane Homer Award in Diagnostic Radiology, Tufts University School of Medicine (2020)
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Best Poster in Cardiac Image Analysis, Functional Imaging and Modelling of the Heart (FIMH) (2017)
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NIH Graduate Symposium Travel Award, NIH-OxCam (2013)
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David F. Noonan Research Fellowship, Tufts University School of Medicine (2012)
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Howard Sample Prize in Physics, Tufts University College of Arts and Sciences (2010)
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Durkee Scholarship in Chemistry, Tufts University College of Arts and Sciences (2008)
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Nathan Gantcher Research Scholarship, Tufts University College of Arts and Sciences (2008)
Professional Education
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Doctor of Philosophy, University of Oxford (2017)
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Doctor of Medicine, Tufts University (2020)
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DPhil, University of Oxford, Biomedical Engineering (2020)
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MD, Tufts University School of Medicine (2020)
Current Clinical Interests
- Cardiovascular Imaging
All Publications
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Octree Representation Improves Data Fidelity of Cardiac CT Images and Convolutional Neural Network Semantic Segmentation of Left Atrial and Ventricular Chambers.
Radiology. Artificial intelligence
2021; 3 (6): e210036
Abstract
Purpose: To assess whether octree representation and octree-based convolutional neural networks (CNNs) improve segmentation accuracy of three-dimensional images.Materials and Methods: Cardiac CT angiographic examinations from 100 patients (mean age, 67 years ± 17 [standard deviation]; 60 men) performed between June 2012 and June 2018 with semantic segmentations of the left ventricular (LV) and left atrial (LA) blood pools at the end-diastolic and end-systolic cardiac phases were retrospectively evaluated. Image quality (root mean square error [RMSE]) and segmentation fidelity (global Dice and border Dice coefficients) metrics of the octree representation were compared with spatial downsampling for a range of memory footprints. Fivefold cross-validation was used to train an octree-based CNN and CNNs with spatial downsampling at four levels of image compression or spatial downsampling. The semantic segmentation performance of octree-based CNN (OctNet) was compared with the performance of U-Nets with spatial downsampling.Results: Octrees provided high image and segmentation fidelity (median RMSE, 1.34 HU; LV Dice coefficient, 0.970; LV border Dice coefficient, 0.843) with a reduced memory footprint (87.5% reduction). Spatial downsampling to the same memory footprint had lower data fidelity (median RMSE, 12.96 HU; LV Dice coefficient, 0.852; LV border Dice coefficient, 0.310). OctNet segmentation improved the border segmentation Dice coefficient (LV, 0.612; LA, 0.636) compared with the highest performance among U-Nets with spatial downsampling (Dice coefficients: LV, 0.579; LA, 0.592).Conclusion: Octree-based representations can reduce the memory footprint and improve segmentation border accuracy.Keywords CT, Cardiac, Segmentation, Supervised Learning, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021.
View details for DOI 10.1148/ryai.2021210036
View details for PubMedID 34870221
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M-SiSSR: Regional Endocardial Function Using Multilabel Simultaneous Subdivision Surface Registration.
Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH
2021; 12738: 242-252
Abstract
Quantification of regional cardiac function is a central goal of cardiology. Multiple methods, such as Coherent Point Drift (CPD) and Simultaneous Subdivision Surface Registration (SiSSR), have been used to register meshes to the endocardial surface. However, these methods do not distinguish between cardiac chambers during registration, and consequently the mesh may "slip" across the interface between two structures during contraction, resulting in inaccurate regional functional measurements. Here, we present Multilabel-SiSSR (M-SiSSR), a novel method for registering a "labeled" cardiac mesh (with each triangle assigned to a cardiac structure). We compare our results to the original, label-agnostic version of SiSSR and find both a visual and quantitative improvement in tracking of the mitral valve plane.
View details for DOI 10.1007/978-3-030-78710-3_24
View details for PubMedID 35287285
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Left Ventricular Strain Is Abnormal in Preclinical and Overt Hypertrophic Cardiomyopathy: Cardiac MR Feature Tracking
RADIOLOGY
2019; 290 (3): 640-648
Abstract
Purpose To evaluate myocardial strain and circumferential transmural strain difference (cTSD; the difference between epicardial and endocardial circumferential strain) in a genotyped cohort with hypertrophic cardiomyopathy (HCM) and to explore correlations between cTSD and other anatomic and functional markers of disease status. Left ventricular (LV) dysfunction may indicate early disease in preclinical HCM (sarcomere mutation carriers without LV hypertrophy). Cardiac MRI feature tracking may be used to evaluate myocardial strain in carriers of HCM sarcomere mutation. Materials and Methods Participants with HCM and their family members participated in a prospective, multicenter, observational study (HCMNet). Genetic testing was performed in all participants. Study participants underwent cardiac MRI with temporal resolution at 40 msec or less. LV myocardial strain was analyzed by using feature-tracking software. Circumferential strain was measured at the epicardial and endocardial surfaces; their difference yielded the circumferential transmural strain difference (cTSD). Multivariable analysis to predict HCM status was performed by using multinomial logistic regression adjusting for age, sex, and LV parameters. Results Ninety-nine participants were evaluated (23 control participants, 34 participants with preclinical HCM [positive for sarcomere mutation and negative for LV hypertrophy], and 42 participants with overt HCM [positive for sarcomere mutation and negative for LV hypertrophy]). The average age was 25 years ± 11 and 44 participants (44%) were women. Maximal LV wall thickness was 9.5 mm ± 1.4, 9.8 mm ± 2.2, and 16.1 mm ± 5.3 in control participants, participants with preclinical HCM (P = .496 vs control participants), and participants with overt HCM (P < .001 vs control participants), respectively. cTSD for control participants, preclinical HCM, and overt HCM was 14% ± 4, 17% ± 4, and 22% ± 7, respectively (P < .01 for all comparisons). In multivariable models (controlling for septal thickness and log-transformed N-terminal brain-type natriuretic peptide), cTSD was predictive of preclinical and overt HCM disease status (P < .01). Conclusion Cardiac MRI feature tracking identifies myocardial dysfunction not only in participants with overt hypertrophic cardiomyopathy, but also in carriers of sarcomere mutation without left ventricular hypertrophy, suggesting that contractile abnormalities are present even when left ventricular wall thickness is normal. © RSNA, 2018 Online supplemental material is available for this article.
View details for DOI 10.1148/radiol.2018180339
View details for Web of Science ID 000459261900008
View details for PubMedID 30561279
View details for PubMedCentralID PMC6394738
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Omega-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks
ELSEVIER. 2018: 95-106
Abstract
Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearance, orientation, and placement of the heart between patients, clinical views, scanners, and protocols makes fully automatic semantic segmentation a notoriously difficult problem. Here, we present Ω-Net (Omega-Net): A novel convolutional neural network (CNN) architecture for simultaneous localization, transformation into a canonical orientation, and semantic segmentation. First, an initial segmentation is performed on the input image; second, the features learned during this initial segmentation are used to predict the parameters needed to transform the input image into a canonical orientation; and third, a final segmentation is performed on the transformed image. In this work, Ω-Nets of varying depths were trained to detect five foreground classes in any of three clinical views (short axis, SA; four-chamber, 4C; two-chamber, 2C), without prior knowledge of the view being segmented. This constitutes a substantially more challenging problem compared with prior work. The architecture was trained using three-fold cross-validation on a cohort of patients with hypertrophic cardiomyopathy (HCM, N=42) and healthy control subjects (N=21). Network performance, as measured by weighted foreground intersection-over-union (IoU), was substantially improved for the best-performing Ω-Net compared with U-Net segmentation without localization or orientation (0.858 vs 0.834). In addition, to be comparable with other works, Ω-Net was retrained from scratch using five-fold cross-validation on the publicly available 2017 MICCAI Automated Cardiac Diagnosis Challenge (ACDC) dataset. The Ω-Net outperformed the state-of-the-art method in segmentation of the LV and RV bloodpools, and performed slightly worse in segmentation of the LV myocardium. We conclude that this architecture represents a substantive advancement over prior approaches, with implications for biomedical image segmentation more generally.
View details for DOI 10.1016/j.media.2018.05.008
View details for Web of Science ID 000442059700007
View details for PubMedID 29857330
View details for PubMedCentralID PMC7571050
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SiSSR: Simultaneous subdivision surface registration for the quantification of cardiac function from computed tomography in canines
MEDICAL IMAGE ANALYSIS
2018; 46: 215-228
Abstract
Recent improvements in cardiac computed tomography (CCT) allow for whole-heart functional studies to be acquired at low radiation dose (<2mSv) and high-temporal resolution (<100ms) in a single heart beat. Although the extraction of regional functional information from these images is of great clinical interest, there is a paucity of research into the quantification of regional function from CCT, contrasting with the large body of work in echocardiography and cardiac MR. Here we present the Simultaneous Subdivision Surface Registration (SiSSR) method: a fast, semi-automated image analysis pipeline for quantifying regional function from contrast-enhanced CCT. For each of thirteen adult male canines, we construct an anatomical reference mesh representing the left ventricular (LV) endocardium, obviating the need for a template mesh to be manually sculpted and initialized. We treat this generated mesh as a Loop subdivision surface, and adapt a technique previously described in the context of 3-D echocardiography to register these surfaces to the endocardium efficiently across all cardiac frames simultaneously. Although previous work performs the registration at a single resolution, we observe that subdivision surfaces naturally suggest a multiresolution approach, leading to faster convergence and avoiding local minima. We additionally make two notable changes to the cost function of the optimization, explicitly encouraging plausible biological motion and high mesh quality. Finally, we calculate an accepted functional metric for CCT from the registered surfaces, and compare our results to an alternate state-of-the-art CCT method.
View details for DOI 10.1016/j.media.2018.03.009
View details for Web of Science ID 000432615100015
View details for PubMedID 29627686
View details for PubMedCentralID PMC5942600
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Right ventricular strain by MR quantitatively identifies regional dysfunction in patients with arrhythmogenic right ventricular cardiomyopathy
JOURNAL OF MAGNETIC RESONANCE IMAGING
2016; 43 (5): 1132-1139
Abstract
Analysis of regional wall motion of the right ventricle (RV) is primarily qualitative with large interobserver variation in clinical practice. Thus, the purpose of this study was to use feature tracking to analyze regional wall motion abnormalities in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC).We enrolled 110 subjects (39 overt ARVC [mutation+/phenotype+] (35.5%), 40 preclinical ARVC [mutation+/phenotype-] (36.3%), and 31 control subjects (28.2%)). Cine steady state free precession cardiac MR was performed with temporal resolution ≤40 ms in the horizontal long axis (HLA), axial, and short axis directions. Regional strain was analyzed using feature tracking software and reproducibility was assessed by means of intraclass correlation coefficient. Dunnett's test was used in univariate analysis for comparisons to control subjects; cumulative odds logistic regression was used for minimally and fully adjusted multivariate models.Strain was significantly impaired in overt ARVC compared with control subjects both globally (P < 0.01) and regionally (all segments of HLA view, P < 0.01). In the HLA view, regional reproducibility was excellent within (intraclass correlation coefficient [ICC] = 0.81) and moderate between (ICC = 0.62) observers. Using a threshold of -31% subtricuspid strain in the HLA view, the sensitivity and specificity for overt ARVC were 75.0% and 78.2%, respectively. In multivariable analysis involving all three groups, subtricuspid strain less than -31% (beta = 1.38; P = 0.014) and RV end diastolic volume index (beta = 0.06; P = 0.001) were significant predictors of disease presence.RV strain can be reproducibly assessed with MR feature tracking, and regional strain is abnormal in overt ARVC compared with control subjects.
View details for DOI 10.1002/jmri.25068
View details for Web of Science ID 000375118400011
View details for PubMedID 26497822
View details for PubMedCentralID PMC4837004
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Non-Newtonian blood rheology impacts left atrial stasis in patient-specific simulations.
International journal for numerical methods in biomedical engineering
2022: e3597
Abstract
The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects are subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered when calculating patient-specific blood stasis indices by computational fluid dynamics.
View details for DOI 10.1002/cnm.3597
View details for PubMedID 35344280
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Vascular Landmark-Based Method for Highly Reproducible Measurement of Left Atrial Appendage Volume in Computed Tomography
CIRCULATION-CARDIOVASCULAR IMAGING
2019; 12 (12): e009075
Abstract
Modern computed tomographic scanning can produce 4-dimensional images of the left atrial appendage (LAA). LAA function and morphology can then be measured, to plan interventions such as occlusion and to evaluate LAA flow for thrombogenic risk analysis. A current problem here is defining a reproducible boundary between the LAA and the left atrium.This study used retrospectively gated 4-dimensional computed tomographic data from 25 implantation and coronary artery imaging patients. In each patient, the LAA ostium was defined at multiple time points during the RR interval. To examine the reproducibility of the definition of the LAA ostium, 3 observers analyzed all time frames in each patient 3 times. Five nonconsecutive time frames from each patient were then compared using intraclass correlation coefficients to quantify the precision of the method across patients. The correlation of LAA volumes for each time frame of each patient was determined across the different observers (interobserver) and within each observer's own data sets (intraobserver).The method was successful in 92% of patients. Two-way random-effect, absolute-agreement, single-measurement intraclass correlation coefficients for interobserver measurements were 0.984, 0.990, and 0.988, with intraobserver intraclass correlation coefficients of 0.989, 0.989, and 0.995. The intraclass correlation coefficient of all observations was 0.988.Classification of the LAA ostium using a stepwise procedure identifying the coumadin ridge and 2 vascular landmarks in ECG-gated computed tomography provides a viable method of establishing a highly reproducible boundary between the atrium and LAA needed to obtain LAA metrics useful for procedure planning and measuring LAA function.
View details for DOI 10.1161/CIRCIMAGING.119.009075
View details for Web of Science ID 000503252800002
View details for PubMedID 31842587
View details for PubMedCentralID PMC7685054
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Regional dynamics of fractal dimension of the left ventricular endocardium from cine computed tomography images
JOURNAL OF MEDICAL IMAGING
2019; 6 (4): 046002
Abstract
We present a method to leverage the high fidelity of computed tomography (CT) to quantify regional left ventricular function using topography variation of the endocardium as a surrogate measure of strain. 4DCT images of 10 normal and 10 abnormal subjects, acquired with standard clinical protocols, are used. The topography of the endocardium is characterized by its regional values of fractal dimension ( F D ), computed using a box-counting algorithm developed in-house. The average F D in each of the 16 American Heart Association segments is calculated for each subject as a function of time over the cardiac cycle. The normal subjects show a peak systolic percentage change in F D of 5.9 % ± 2 % in all free-wall segments, whereas the abnormal cohort experiences a change of 2 % ± 1.2 % ( p < 0.00001 ). Septal segments, being smooth, do not undergo large changes in F D . Additionally, a principal component analysis is performed on the temporal profiles of F D to highlight the possibility for unsupervised classification of normal and abnormal function. The method developed is free from manual contouring and does not require any feature tracking or registration algorithms. The F D values in the free-wall segments correlated well with radial strain and with endocardial regional shortening measurements.
View details for DOI 10.1117/1.JMI.6.4.046002
View details for Web of Science ID 000510163900020
View details for PubMedID 31737745
View details for PubMedCentralID PMC6838603
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Left Atrial structure and function in hypertrophic cardiomyopathy sarcomere mutation carriers with and without left ventricular hypertrophy
JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
2017; 19: 107
Abstract
Impaired left atrial (LA) function is an early marker of cardiac dysfunction and predictor of adverse cardiac events. Herein, we assess LA structure and function in hypertrophy in hypertrophic cardiomyopathy (HCM) sarcomere mutation carriers with and without left ventricular hypertrophy (LVH).Seventy-three participants of the HCMNet study who underwent cardiovascular magnetic resonance (CMR) imaging were studied, including mutation carriers with overt HCM (n = 34), preclinical mutation carriers without HCM (n = 24) and healthy, familial controls (n = 15).LA volumes were similar between preclinical, control and overt HCM cohorts after covariate adjustment. However, there was evidence of impaired LA function with decreased LA total emptying function in both preclinical (64 ± 8%) and overt HCM (59 ± 10%), compared with controls (70 ± 7%; p = 0.002 and p = 0.005, respectively). LA passive emptying function was also decreased in overt HCM (35 ± 11%) compared with controls (47 ± 10%; p = 0.006). Both LAtotal emptying function and LA passive emptying function were inversely correlated with the extent of late gadolinium enhancement (LGE; p = 0.005 and p < 0.05, respectively), LV mass (p = 0.02 and p < 0.001) and interventricular septal thickness (p < 0.001 for both) and serum NT-proBNP levels (p < 0.001 for both).LA dysfunction is detectable by CMR in preclinical HCM mutation carriers despite non-distinguishable LV wall thickness and LA volume. LA function appears most impaired in subjects with overt HCM and a greater extent of LV fibrosis.
View details for DOI 10.1186/s12968-017-0420-0
View details for Web of Science ID 000419010100002
View details for PubMedID 29284499
View details for PubMedCentralID PMC5745877
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Internal tissue references for (18)Fluorodeoxyglucose vascular inflammation imaging: Implications for cardiovascular risk stratification and clinical trials
PLOS ONE
2017; 12 (11): e0187995
Abstract
18Fluorodeoxyglucose (FDG) positron emission tomography (PET) uptake in the artery wall correlates with active inflammation. However, in part due to the low spatial resolution of PET, variation in the apparent arterial wall signal may be influenced by variation in blood FDG activity that cannot be fully corrected for using typical normalization strategies. The purpose of this study was to evaluate the ability of the current common methods to normalize for blood activity and to investigate alternative methods for more accurate quantification of vascular inflammation.The relationship between maximum FDG aorta wall activity and mean blood activity was evaluated in 37 prospectively enrolled subjects aged 55 years or more, treated for hyperlipidemia. Target maximum aorta standardized uptake value (SUV) and mean background reference tissue activity (blood, spleen, liver) were recorded. Target-to-background ratios (TBR) and arterial maximum activity minus blood activity were calculated. Multivariable regression was conducted, predicting uptake values based on variation in background reference and target tissue FDG uptake; adjusting for gender, age, lean body mass (LBM), blood glucose, blood pool activity, and glomerular filtration rate (GFR), where appropriate.Blood pool activity was positively associated with maximum artery wall SUV (β = 5.61, P<0.0001) as well as mean liver (β = 6.23, P<0.0001) and spleen SUV (β = 5.20, P<0.0001). Artery wall activity divided by blood activity (TBRBlood) or subtraction of blood activity did not remove the statistically significant relationship to blood activity. Blood pool activity was not related to TBRliver and TBRspleen (β = -0.36, P = NS and β = -0.58, P = NS, respectively).In otherwise healthy individuals treated for hyperlipidemia, blood FDG activity is associated with artery wall activity. However, variation in blood activity may mask artery wall signal reflective of inflammation, which requires normalization. Blood-based TBR and subtraction do not sufficiently adjust for blood activity. Warranting further investigation, background reference tissues with cellular uptake such as the liver and spleen may better adjust for variation in blood activity to improve assessment of vascular activity.
View details for DOI 10.1371/journal.pone.0187995
View details for Web of Science ID 000414997800036
View details for PubMedID 29131857
View details for PubMedCentralID PMC5683610
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Feature tracking CMR reveals abnormal strain in preclinical arrhythmogenic right ventricular dysplasia/cardiomyopathy: a multisoftware feasibility and clinical implementation study
JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
2017; 19: 66
Abstract
Regional right ventricular (RV) dysfunction is the hallmark of Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C), but is currently only qualitatively evaluated in the clinical setting. Feature Tracking Cardiovascular Magnetic Resonance (FT-CMR) is a novel quantitative method that uses cine CMR to calculate strain values. However, most prior FT-CMR studies in ARVD/C have focused on global RV strain using different software methods, complicating implementation of FT-CMR in clinical practice. We aimed to assess the clinical value of global and regional strain using FT-CMR in ARVD/C and to determine differences between commercially available FT-CMR software packages.We analyzed cine CMR images of 110 subjects (39 overt ARVD/C [mutation+/phenotype+], 40 preclinical ARVD/C [mutation+/phenotype-] and 31 control) for global and regional (subtricuspid, anterior, apical) RV strain in the horizontal longitudinal axis using four FT-CMR software methods (Multimodality Tissue Tracking, TomTec, Medis and Circle Cardiovascular Imaging). Intersoftware agreement was assessed using Bland Altman plots.For global strain, all methods showed reduced strain in overt ARVD/C patients compared to control subjects (p < 0.041), whereas none distinguished preclinical from control subjects (p > 0.275). For regional strain, overt ARVD/C patients showed reduced strain compared to control subjects in all segments which reached statistical significance in the subtricuspid region for all software methods (p < 0.037), in the anterior wall for two methods (p < 0.005) and in the apex for one method (p = 0.012). Preclinical subjects showed abnormal subtricuspid strain compared to control subjects using one of the software methods (p = 0.009). Agreement between software methods for absolute strain values was low (Intraclass Correlation Coefficient = 0.373).Despite large intersoftware variability of FT-CMR derived strain values, all four software methods distinguished overt ARVD/C patients from control subjects by both global and subtricuspid strain values. In the subtricuspid region, one software package distinguished preclinical from control subjects, suggesting the potential to identify early ARVD/C prior to overt disease expression.
View details for DOI 10.1186/s12968-017-0380-4
View details for Web of Science ID 000409127000001
View details for PubMedID 28863780
View details for PubMedCentralID PMC5581480
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Automatic high-resolution infarct detection using volumetric multiphase dual-energy CT
JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY
2017; 11 (4): 288-294
Abstract
Late contrast enhancement CT (LCE-CT) visualizes the presence of myocardial infarcts. Differentiation of the contrast-enhanced infarct from blood pool is challenging. We developed a novel method using data from first pass CT angiography (CTA) imaging to enable automatic infarct detection.A canine model of myocardial infarction was produced in 11 animals. Two months later, first pass CTA (90 kVp) and LCE-CT (dual energy 90 kVp/150 kVp tin filtered) were performed. Late gadolinium enhancement MRI was used as reference standard. The CTA and LCE-CT were co-registered using a fully automatic non-rigid method based on curved B-splines. The method allowed for limited elastic deformation and the considerable differences in attenuation between first-pass and delayed image. The blood pool was easily identified on the CTA image by high attenuation. Because CTA and LCE-CT were registered, the blood pool segmentation can be directly transferred to the LCE-CT - thereby solving the key problem of infarct/blood pool differentiation. The remaining segmentation of infarcted vs. noninfarcted myocardium was performed using a threshold. Automatic and MRI-guided expert segmentations of LCE-CT infarcts were compared to each other on volume and area basis (intraclass correlation coefficient, ICC) and on voxel basis (dice similarity coefficient, DSC between automatic and expert CT segmentation). CT infarct volumes were compared with the reference standard MRI.The infarcts were mainly subendocardial (81%) and relatively small (median MRI infarct mass 7.4 g). The automatic segmentation showed excellent agreement with expert segmentation on volume and area measurements (ICC = 0.96 and 0.87, respectively). DSC showed moderately good agreement (DSC = 0.47). Compared to MRI there was modest agreement (ICC = 0.62) and excellent correlation (R = 0.9). Manual interaction was less than 1 min per exam.We propose an automatic method for infarct segmentation on LCE-CT using multiphase CT information, which showed excellent agreement with expert readers and favorable correlation with MRI.
View details for DOI 10.1016/j.jcct.2017.04.006
View details for Web of Science ID 000404321500006
View details for PubMedID 28442244
View details for PubMedCentralID PMC5493020
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Coronary Plaque Burden at Coronary CT Angiography in Asymptomatic Men and Women
RADIOLOGY
2015; 277 (1): 73-80
Abstract
Purpose To assess the relationship between total, calcified, and noncalcified coronary plaque burdens throughout the entire coronary vasculature at coronary computed tomographic (CT) angiography in relationship to cardiovascular risk factors in asymptomatic individuals with low-to-moderate risk. Materials and Methods This HIPAA-compliant study had institutional review board approval, and written informed consent was obtained. Two hundred two subjects were recruited to an ongoing prospective study designed to evaluate the effect of HMG-CoA reductase inhibitors on atherosclerosis. Eligible subjects were asymptomatic individuals older than 55 years who were eligible for statin therapy. Coronary CT angiography was performed by using a 320-detector row scanner. Coronary wall thickness and plaque were evaluated in all epicardial coronary arteries greater than 2 mm in diameter. Images were analyzed by using dedicated software involving an adaptive lumen attenuation algorithm. Total plaque index (calcified plus noncalcified plaque) was defined as plaque volume divided by vessel length. Multivariable regression analysis was performed to determine the relationship between risk factors and plaque indexes. Results The mean age of the subjects was 65.5 years ± 6.9 (standard deviation) (36% women), and the median coronary artery calcium (CAC) score was 73 (interquartile range, 1-434). The total coronary plaque index was higher in men than in women (42.06 mm(2) ± 9.22 vs 34.33 mm(2) ± 8.35; P < .001). In multivariable analysis controlling for all risk factors, total plaque index remained higher in men than in women (by 5.01 mm(2); P = .03) and in those with higher simvastatin doses (by 0.44 mm(2)/10 mg simvastatin dose equivalent; P = .02). Noncalcified plaque index was positively correlated with systolic blood pressure (β = 0.80 mm(2)/10 mm Hg; P = .03), diabetes (β = 4.47 mm(2); P = .03), and low-density lipoprotein (LDL) cholesterol level (β = 0.04 mm(2)/mg/dL; P = .02); the association with LDL cholesterol level remained significant (P = .02) after additional adjustment for the CAC score. Conclusion LDL cholesterol level, systolic blood pressure, and diabetes were associated with noncalcified plaque burden at coronary CT angiography in asymptomatic individuals with low-to-moderate risk. (©) RSNA, 2015 Online supplemental material is available for this article.
View details for DOI 10.1148/radiol.2015142551
View details for Web of Science ID 000368434000009
View details for PubMedID 26035436
View details for PubMedCentralID PMC4613877
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Regional Strain Analysis with Multidetector CT in a Swine Cardiomyopathy Model: Relationship to Cardiac MR Tagging and Myocardial Fibrosis
RADIOLOGY
2015; 277 (1): 88-94
Abstract
To investigate the use of cine multidetector computed tomography (CT) to detect changes in myocardial function in a swine cardiomyopathy model.All animal protocols were in accordance with the Principles for the Utilization and Care of Vertebrate Animals Used in Testing Research and Training and approved by the University of Missouri Animal Care and Use Committee. Strain analysis of cine multidetector CT images of the left ventricle was optimized and analyzed with feature-tracking software. The standard of reference for strain was harmonic phase analysis of tagged cardiac magnetic resonance (MR) images at 3.0 T. An animal model of cardiomyopathy was imaged with both cardiac MR and 320-section multidetector CT at a temporal resolution of less than 50 msec. Three groups were evaluated: control group (n = 5), aortic-banded myocardial hypertrophy group (n = 5), and aortic-banded and cyclosporine A- treated cardiomyopathy group (n = 5). Histologic samples of the myocardium were obtained for comparison with strain results. Dunnett test was used for comparisons of the concentric remodeling group and eccentric remodeling group against the control group.Collagen volume fraction ranged from 10.9% to 14.2%; lower collagen fraction values were seen in the control group than in the cardiomyopathy groups (P < .05). Ejection fraction and conventional metrics showed no significant differences between control and cardiomyopathy groups. Radial strain for both cardiac MR and multidetector CT was abnormal in both concentric (cardiac MR 25.1% ± 4.2; multidetector CT 28.4% ± 2.8) and eccentric (cardiac MR 23.2% ± 2.0; multidetector CT 24.4% ± 2.1) remodeling groups relative to control group (cardiac MR 18.9% ± 1.9, multidetector CT 22.0% ± 1.7, P < .05, all comparisons). Strain values for multidetector CT versus cardiac MR showed better agreement in the radial direction than in the circumferential direction (r = 0.55, P = .03 vs r = 0.40, P = .13, respectively).Multidetector CT strain analysis has potential to identify regional wall-motion abnormalities in cardiomyopathy that is not otherwise detected using conventional metrics of myocardial function.
View details for DOI 10.1148/radiol.2015142339
View details for Web of Science ID 000368434000011
View details for PubMedID 25853636
View details for PubMedCentralID PMC4613883