The applicant's original training is in engineering, computer science, and physics with a background in computational modeling of porous media. He plans to integrate his strengths in quantitative analysis and current postdoctoral experience in finite-element analysis with NIH-relevant research. His long-term career goal is to advance the understanding, diagnosis, and management of diseases through non-invasive imaging and multi-disciplinary approaches. The short-term objective through this coordinated program of mentored research/training in quantitative MRI and biomechanics is to complete the preparation of the applicant as an independent researcher of osteoporotic fractures and further his capacity to establish new directions for biomedical research through multi-disciplinary collaborations. To achieve these goals, the mentored research outlined in this proposal will be complemented by a formal training program involving didactic coursework;participation at conferences, seminars, and workshops;and regular interactions with other investigators, collaborators, and trainees. The applicant will be mentored by world renowned scientists on MR techniques for bone imaging (Prof. Felix W. Wehrli, Ph.D.), endocrinological aspects of metabolic bone diseases (Prof. Peter J. Snyder, M.D.), and image-based biomechanical modeling and mechanical testing (Prof. X. Edward Guo, Ph.D.). The proposed research involves the development of a biomechanical framework for early prediction of vertebral fractures, which are among the most common outcomes of osteoporosis affecting the elderly. The early detection of vertebral deformities is important because patients with such deformities are known to be at elevated risk for further fractures. Lateral radiographic projections of the spine, an approach which has many limitations, are still used as the clinical standard for diagnosis of these deformities. The hypothesis that the impaired mechanical competence at the spine parallels similar changes at distal skeletal sites and the vertebral fracture status can be predicted on the basis of biomechanical analysis via in-vivo high-resolution magnetic resonance (mMR) images of distal extremities will be tested. The proposed study makes use of mMR images of distal radius and distal tibia and midline-sagittal spine MR images in ninety eight patients with osteoporosis. The specific objectives involve 1) validation of parameters relating to bone's mechanical properties derived from mMRI-based finite-element modeling using cadaveric human tibia, 2) expansion of capabilities of the mMRI-based FE-technology developed previously to analyze mMR images of distal radius and distal tibia in patients, and 3) development of a framework to predict vertebral fracture status by exploring the hypothesized association between spinal deformity and MRI-derived parameters relating to bone quality at distal extremities. The proposed research holds the potential to provide an improved technique for early prediction of vertebral fractures and will serve well as a launching pad for the applicant to become an independent researcher.

Public Health Relevance

The proposed research describes a non-invasive method to identify subjects who are at elevated risk of getting vertebral fractures. This approach holds the potential to improve the accuracy of early diagnosis and assessment of treatment efficacy in osteoporosis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
5K25AR060283-02
Application #
8206657
Study Section
Arthritis and Musculoskeletal and Skin Diseases Special Grants Review Committee (AMS)
Program Officer
Lester, Gayle E
Project Start
2010-12-15
Project End
2014-11-30
Budget Start
2011-12-01
Budget End
2012-11-30
Support Year
2
Fiscal Year
2012
Total Cost
$125,359
Indirect Cost
$8,096
Name
University of Pennsylvania
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Zhang, Ning; Magland, Jeremy F; Song, Hee Kwon et al. (2015) Registration-based autofocusing technique for automatic correction of motion artifacts in time-series studies of high-resolution bone MRI. J Magn Reson Imaging 41:954-63
Rajapakse, C S; Phillips, E A; Sun, W et al. (2014) Vertebral deformities and fractures are associated with MRI and pQCT measures obtained at the distal tibia and radius of postmenopausal women. Osteoporos Int 25:973-82
Al Mukaddam, Mona; Rajapakse, Chamith S; Bhagat, Yusuf A et al. (2014) Effects of testosterone and growth hormone on the structural and mechanical properties of bone by micro-MRI in the distal tibia of men with hypopituitarism. J Clin Endocrinol Metab 99:1236-44
Seifert, Alan C; Li, Cheng; Rajapakse, Chamith S et al. (2014) Bone mineral (31)P and matrix-bound water densities measured by solid-state (31)P and (1)H MRI. NMR Biomed 27:739-48
Zhang, Ning; Magland, Jeremy F; Rajapakse, Chamith S et al. (2013) Assessment of trabecular bone yield and post-yield behavior from high-resolution MRI-based nonlinear finite element analysis at the distal radius of premenopausal and postmenopausal women susceptible to osteoporosis. Acad Radiol 20:1584-91
Chang, G; Rajapakse, C S; Diamond, M et al. (2013) Micro-finite element analysis applied to high-resolution MRI reveals improved bone mechanical competence in the distal femur of female pre-professional dancers. Osteoporos Int 24:1407-17
Zhang, Ning; Magland, Jeremy F; Rajapakse, Chamith S et al. (2013) Potential of in vivo MRI-based nonlinear finite-element analysis for the assessment of trabecular bone post-yield properties. Med Phys 40:052303
Rajapakse, Chamith S; Leonard, Mary B; Bhagat, Yusuf A et al. (2012) Micro-MR imaging-based computational biomechanics demonstrates reduction in cortical and trabecular bone strength after renal transplantation. Radiology 262:912-20