Honors & Awards

  • CVIS Fellow, Stanford University
  • Edward J. Hoffman Graduate Fellowship, University of California, Los Angeles (September 2012)
  • Alavi-Mandell Prize for Outstanding Original Article, Journal of Nuclear Medicine (June 2011)
  • Sylvia Sorkin Greenfield Award, David Geffen School of Medicine at UCLA (October 2009)
  • Nuclear Oncology Council Young Investigator Award, First Place, Society of Nuclear Medicine (June 2009)
  • Brain Imaging Council Young Investigator Award, First Place, Society of Nuclear Medicine (June 2008)
  • Fred S. Grodins Award for Academic Excellence in Biomedical Engineering, University of Southern California (May 2005)
  • Summa Cum Laude, University of Southern California (December 2004)
  • Elected to Tau Beta Pi Engineering Honor Society, University of Southern California (December 2002)

Professional Education

  • Bachelor of Science, University of Southern California (2004)
  • Master of Science, University of California Los Angeles (2011)
  • Doctor of Philosophy, University of California Los Angeles (2013)

Stanford Advisors

All Publications

  • Specific Imaging of Bacterial Infection using 6'' -(18)F-Fluoromaltotriose: A Second Generation PET Tracer Targeting the Maltodextrin Transporter in Bacteria. Journal of nuclear medicine : official publication, Society of Nuclear Medicine Gowrishankar, G., Hardy, J., Wardak, M., Namavari, M., Reeves, R., Neofytou, E., Srinivasan, A., Wu, J., Contag, C., Gambhir, S. 2017


    Purpose: 6"-(18)F-fluoromaltotriose is a novel positron emission tomography (PET) tracer that can potentially be used to image and localize most bacterial infections, much like 2-deoxy-2-(18)F-fluoro-D-glucose ((18)F-FDG) has been used to image and localize many cancers. However, unlike (18)F-FDG, 6"-(18)F-fluoromaltotriose is not taken up by inflammatory lesions and appears to be specific to bacterial infections by targeting the maltodextrin transporter that is expressed in most Gram-positive and Gram-negative strains of bacteria. Materials and Methods: 6"-(18)F-fluoromaltotriose was synthesized with high radiochemical purity and evaluated in several clinically relevant bacterial strains incultures in vitro and in living mice. Results: 6"-(18)F-fluoromaltotriose was taken up in both Gram-positive and Gram-negative bacterial strains. 6"-[(18)F]-fluoromaltotriose was also able to detect Pseudomonas aeruginosa in a clinically relevant mouse model of wound infection. The utility of 6"-(18)F-fluoromaltotriose to help monitor antibiotic therapies was also evaluated in rats. Conclusion: 6"-(18)F-fluoromaltotriose is a promising new tracer that has significant diagnostic utility, with the potential to change the clinical management of patients suffering from infectious diseases of bacterial origin.

    View details for DOI 10.2967/jnumed.117.191452

    View details for PubMedID 28490473

  • Automated Movement Correction for Dynamic PET/CT Images: Evaluation with Phantom and Patient Data PLOS ONE Ye, H., Wong, K., Wardak, M., Dahlbom, M., Kepe, V., Barrio, J. R., Nelson, L. D., Small, G. W., Huang, S. 2014; 9 (8)


    Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers.

    View details for DOI 10.1371/journal.pone.0103745

    View details for Web of Science ID 000341105100021

    View details for PubMedID 25111700

  • F-18-FLT and F-18-FDOPA PET kinetics in recurrent brain tumors EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING Wardak, M., Schiepers, C., Cloughesy, T. F., Dahlbom, M., Phelps, M. E., Huang, S. 2014; 41 (6): 1199-1209


    In this study, kinetic parameters of the cellular proliferation tracer (18)F-3'-deoxy-3'-fluoro-L-thymidine (FLT) and the amino acid probe 3,4-dihydroxy-6-(18)F-fluoro-L-phenylalanine (FDOPA) were measured before and early after the start of therapy, and were used to predict the overall survival (OS) of patients with recurrent malignant glioma using multiple linear regression (MLR) analysis.High-grade recurrent brain tumors in 21 patients (11 men and 10 women, age range 26 - 76 years) were investigated. Each patient had three dynamic PET studies with each probe: at baseline and after 2 and 6 weeks from the start of treatment. Treatment consisted of biweekly cycles of bevacizumab (an angiogenesis inhibitor) and irinotecan (a chemotherapeutic agent). For each study, about 3.5 mCi of FLT (or FDOPA) was administered intravenously and dynamic PET images were acquired for 1 h (or 35 min for FDOPA). A total of 126 PET scans were analyzed. A three-compartment, two-tissue model was applied to estimate tumor FLT and FDOPA kinetic rate constants using a metabolite- and partial volume-corrected input function. MLR analysis was used to model OS as a function of FLT and FDOPA kinetic parameters for each of the three studies as well as their relative changes between studies. An exhaustive search of MLR models using three or fewer predictor variables was performed to find the best models.Kinetic parameters from FLT were more predictive of OS than those from FDOPA. The three-predictor MLR model derived using information from both probes (adjusted R(2) = 0.83) fitted the OS data better than that derived using information from FDOPA alone (adjusted R(2) = 0.41), but was only marginally different from that derived using information from FLT alone (adjusted R(2) = 0.82). Standardized uptake values (either from FLT alone, FDOPA alone, or both together) gave inferior predictive results (best adjusted R(2) = 0.25).For recurrent malignant glioma treated with bevacizumab and irinotecan, FLT kinetic parameters obtained early after the start of treatment (absolute values and their associated changes) can provide sufficient information to predict OS with reasonable confidence using MLR. The slight increase in accuracy for predicting OS with a combination of FLT and FDOPA PET information may not warrant the additional acquisition of FDOPA PET for therapy monitoring in patients with recurrent glioma.

    View details for DOI 10.1007/s00259-013-2678-2

    View details for Web of Science ID 000335572600018

    View details for PubMedID 24604590

  • Automated VOI Analysis in FDDNP PET Using Structural Warping: Validation through Classification of Alzheimer's Disease Patients. International journal of Alzheimer's disease Wilks, M. Q., Protas, H., Wardak, M., Kepe, V., Small, G. W., Barrio, J. R., Huang, S. 2012; 2012: 512069-?


    We evaluate an automated approach to the cortical surface mapping (CSM) method of VOI analysis in PET. Although CSM has been previously shown to be successful, the process can be long and tedious. Here, we present an approach that removes these difficulties through the use of 3D image warping to a common space. We test this automated method using studies of FDDNP PET in Alzheimer's disease and mild cognitive impairment. For each subject, VOIs were created, through CSM, to extract regional PET data. After warping to the common space, a single set of CSM-generated VOIs was used to extract PET data from all subjects. The data extracted using a single set of VOIs outperformed the manual approach in classifying AD patients from MCIs and controls. This suggests that this automated method can remove variance in measurements of PET data and can facilitate accurate, high-throughput image analysis.

    View details for DOI 10.1155/2012/512069

    View details for PubMedID 22482071

  • Discriminant Analysis of F-18-Fluorothymidine Kinetic Parameters to Predict Survival in Patients with Recurrent High-Grade Glioma CLINICAL CANCER RESEARCH Wardak, M., Schiepers, C., Dahlbom, M., Cloughesy, T., Chen, W., Satyamurthy, N., Czernin, J., Phelps, M. E., Huang, S. 2011; 17 (20): 6553-6562


    The primary objective of this study was to investigate whether changes in 3'-deoxy-3'-[¹⁸F]fluorothymidine (¹⁸F-FLT) kinetic parameters, taken early after the start of therapy, could predict overall survival (OS) and progression-free survival (PFS) in patients with recurrent malignant glioma undergoing treatment with bevacizumab and irinotecan.High-grade recurrent brain tumors were investigated in 18 patients (8 male and 10 female), ages 26 to 76 years. Each had 3 dynamic positron emission tomography (PET) studies as follows: at baseline and after 2 and 6 weeks from the start of treatment, ¹⁸F-FLT (2.0 MBq/kg) was injected intravenously, and dynamic PET images were acquired for 1 hour. Factor analysis generated factor images from which blood and tumor uptake curves were derived. A three-compartment, two-tissue model was applied to estimate tumor ¹⁸F-FLT kinetic rate constants using a metabolite- and partial volume-corrected input function. Different combinations of predictor variables were exhaustively searched in a discriminant function to accurately classify patients into their known OS and PFS groups. A leave-one-out cross-validation technique was used to assess the generalizability of the model predictions.In this study population, changes in single parameters such as standardized uptake value or influx rate constant did not accurately classify patients into their respective OS groups (<1 and ≥ 1 year; hit ratios ≤ 78%). However, changes in a set of ¹⁸F-FLT kinetic parameters could perfectly separate these two groups of patients (hit ratio = 100%) and were also able to correctly classify patients into their respective PFS groups (<100 and ≥ 100 days; hit ratio = 88%).Discriminant analysis using changes in ¹⁸F-FLT kinetic parameters early during treatment seems to be a powerful method for evaluating the efficacy of therapeutic regimens.

    View details for DOI 10.1158/1078-0432.CCR-10-3290

    View details for Web of Science ID 000296359400021

    View details for PubMedID 21868765

  • Quantitative analysis of [F-18]FDDNP PET using subcortical white matter as reference region EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING Wong, K., Wardak, M., Shao, W., Dahlbom, M., Kepe, V., Liu, J., Satyamurthy, N., Small, G. W., Barrio, J. R., Huang, S. 2010; 37 (3): 575-588


    Subcortical white matter is known to be relatively unaffected by amyloid deposition in Alzheimer's disease (AD). We investigated the use of subcortical white matter as a reference region to quantify [(18)F]FDDNP binding in the human brain.Dynamic [(18)F]FDDNP PET studies were performed on 7 control subjects and 12 AD patients. Population efflux rate constants (k(')(2)) from subcortical white matter (centrum semiovale) and cerebellar cortex were derived by a simplified reference tissue modeling approach incorporating physiological constraints. Regional distribution volume ratio (DVR) estimates were derived using Logan and simplified reference tissue approaches, with either subcortical white matter or cerebellum as reference input. Discriminant analysis with cross-validation was performed to classify control subjects and AD patients.The population estimates of k(')(2) in subcortical white matter did not differ significantly between control subjects and AD patients but the variability of individual estimates of k(')(2) determined in white matter was lower than that in cerebellum. Logan DVR showed dependence on the efflux rate constant in white matter. The DVR estimates in the frontal, parietal, posterior cingulate, and temporal cortices were significantly higher in the AD group (p<0.01). Incorporating all these regional DVR estimates as predictor variables in discriminant analysis yielded accurate classification of control subjects and AD patients with high sensitivity and specificity, and the results agreed well with those using the cerebellum as the reference region.Subcortical white matter can be used as a reference region for quantitative analysis of [(18)F]FDDNP with the Logan method which allows more accurate and less biased binding estimates, but a population efflux rate constant has to be determined a priori.

    View details for DOI 10.1007/s00259-009-1293-8

    View details for Web of Science ID 000274544600016

    View details for PubMedID 19882153

  • Movement Correction Method for Human Brain PET Images: Application to Quantitative Analysis of Dynamic F-18-FDDNP Scans JOURNAL OF NUCLEAR MEDICINE Wardak, M., Wong, K., Shao, W., Dahlbom, M., Kepe, V., Satyamurthy, N., Small, G. W., Barrio, J. R., Huang, S. 2010; 51 (2): 210-218


    Head movement during a PET scan (especially a dynamic scan) can affect both the qualitative and the quantitative aspects of an image, making it difficult to accurately interpret the results. The primary objective of this study was to develop a retrospective image-based movement correction (MC) method and evaluate its implementation on dynamic 2-(1-{6-[(2-(18)F-fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile ((18)F-FDDNP) PET images of cognitively intact controls and patients with Alzheimer's disease (AD).Dynamic (18)F-FDDNP PET images, used for in vivo imaging of beta-amyloid plaques and neurofibrillary tangles, were obtained from 12 AD patients and 9 age-matched controls. For each study, a transmission scan was first acquired for attenuation correction. An accurate retrospective MC method that corrected for transmission-emission and emission-emission misalignments was applied to all studies. No restriction was assumed for zero movement between the transmission scan and the first emission scan. Logan analysis, with the cerebellum as the reference region, was used to estimate various regional distribution volume ratio (DVR) values in the brain before and after MC. Discriminant analysis was used to build a predictive model for group membership, using data with and without MC.MC improved the image quality and quantitative values in (18)F-FDDNP PET images. In this subject population, no significant difference in DVR value was observed in the medial temporal (MTL) region of controls and patients with AD before MC. However, after MC, significant differences in DVR values in the frontal, parietal, posterior cingulate, MTL, lateral temporal (LTL), and global regions were seen between the 2 groups (P < 0.05). In controls and patients with AD, the variability of regional DVR values (as measured by the coefficient of variation) decreased on average by more than 18% after MC. Mean DVR separation between controls and patients with AD was higher in frontal, MTL, LTL, and global regions after MC. Group classification by discriminant analysis based on (18)F-FDDNP DVR values was markedly improved after MC.The streamlined and easy-to-use MC method presented in this work significantly improves the image quality and the measured tracer kinetics of (18)F-FDDNP PET images. The proposed MC method has the potential to be applied to PET studies on patients having other disorders (e.g., Down syndrome and Parkinson's disease) and to brain PET scans with other molecular imaging probes.

    View details for DOI 10.2967/jnumed.109.063701

    View details for Web of Science ID 000274152800022

    View details for PubMedID 20080894