Dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) biomarkers are displaying significant promise as early indicators of therapeutic response in the modern clinic. As a consequence, they possess an evolving role in the current realm of individualized medicine. Challenges remain however regarding their application in cross-sectional contemporaneous or longitudinal studies - it is critical in these studies to decouple errors due to intra-scan patient motion or repositioning on the scanner from anatomical or functional changes occurring due to treatment that these biomarkers reflect. Tools that are capable of rapid, but reliable derivation of DCE-MRI biomarkers are therefore urgently needed. The GOAL of this proposed work is to develop, implement and validate three-dimensional image registration technology for enabling the rapid derivation of disease-associated biomarkers from clinical DCE-MRI. The focus is on the alignment of intra-subject anatomical images of body regions that involve both rigid (bone) and non-rigid (soft tissue) components. In our innovative registration scheme, pre-determined components such as bones deform in a rigid manner while soft tissue warps non-rigidly. We HYPOTHESIZE therefore that our method will provide better modeling of patient repositioning compared to currently clinically used technologies as well as state-of-the-art registration methods. In our SPECIFIC AIMS, we will: (1) develop the quasi-rigid, intra-subject registration method for MR image alignment, and (2) validate the registration method using MR images of adult patients with soft tissue sarcoma in a retrospective setting. Both computer-based and human observers will be used to compare the performance of the proposed method against conventional rigid and non-rigid registration methods. A novel system for radiologic scoring of the merits of image registration is devised and will be tested. The registration method will be developed as an open-source technique allowing easy distribution. DCE-MRI biomarkers are currently being evaluated as surrogate end-points in clinical trials of several novel drug treatments. The proposed registration method will enable rapid quantitative change analyses of DCE-MRI biomarkers over the treatment period. Physicians will be able to use this information to tailor therapeutic strategies according to the individual requirements of their patients. In this context, techniques developed in this proposal are applicable to a broad class of human diseases, e.g., oncologic (e.g., sarcomas, head and neck cancer, etc) or musculoskeletal disease (e.g., arthritis, etc). This work is a close collaboration with Robert Canter, a surgical oncologist who specializes in the clinical management of soft tissue sarcoma, Michael Buonocore, an MRI physicist whose expertise lies in clinical MRI protocol design and image analysis, Robert Boutin, a clinical radiologist with expertise in soft tissue sarcoma and consultant Wayne Monsky, an expert in cancer imaging biomarker development.

Public Health Relevance

Advanced imaging tools like magnetic resonance imaging (MRI) are playing a crucial role in combating serious human diseases like cancer and arthritis. The goal of this research is to develop open-source software to aid clinicians in rapidly analyzing MR images, enabling them to personalize therapeutic options for their patients.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Small Research Grants (R03)
Project #
Application #
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Pai, Vinay Manjunath
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California Davis
Schools of Medicine
United States
Zip Code
Foster, Brent; Joshi, Anand A; Borgese, Marissa et al. (2018) WRIST: A WRist Image Segmentation Toolkit for carpal bone delineation from MRI. Comput Med Imaging Graph 63:31-40
Foster, Brent; Boutin, Robert D; Lenchik, Leon et al. (2018) Skeletal Muscle Metrics on Clinical 18F-FDG PET/CT Predict Health Outcomes in Patients with Sarcoma. J Nat Sci 4:
Borgese, Marissa; Boutin, Robert D; Bayne, Christopher O et al. (2017) Association of lunate morphology, sex, and lunotriquetral interosseous ligament injury with radiologic measurement of the capitate-triquetrum joint. Skeletal Radiol 46:1729-1737
Mitra, A; Kundu-Raychaudhuri, S; Abria, C et al. (2017) In-vivo quantitative assessment of the therapeutic response in a mouse model of collagen-induced arthritis using 18 F-fluorodeoxyglucose positron emission tomography. Clin Exp Immunol 188:293-298
Abdelhafez, Yasser G; Hagge, Rosalie J; Badawi, Ramsey D et al. (2017) Early and Delayed 99mTc-MDP SPECT/CT Findings in Rheumatoid Arthritis and Osteoarthritis. Clin Nucl Med 42:e480-e481
Boutin, Robert D; Netto, Anuj P; Nakamura, David et al. (2017) ""Knuckle Cracking"": Can Blinded Observers Detect Changes with Physical Examination and Sonography? Clin Orthop Relat Res 475:1265-1271
Chaudhari, Abhijit J; Ferrero, Andrea; Godinez, Felipe et al. (2016) High-resolution (18)F-FDG PET/CT for assessing disease activity in rheumatoid and psoriatic arthritis: findings of a prospective pilot study. Br J Radiol 89:20160138
Corwin, Michael T; Fananapazir, Ghaneh; Chaudhari, Abhijit J (2016) MR Angiography of Renal Transplant Vasculature with Ferumoxytol:: Comparison of High-Resolution Steady-State and First-Pass Acquisitions. Acad Radiol 23:368-73
Joshi, Anand A; Leahy, Richard M; Badawi, Ramsey D et al. (2016) Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist. IEEE Trans Med Imaging 35:416-26
Zheng, Lin; Chaudhari, Abhijit J; Badawi, Ramsey D et al. (2014) Using global illumination in volume visualization of rheumatoid arthritis CT data. IEEE Comput Graph Appl 34:16-23

Showing the most recent 10 out of 15 publications