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.
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.
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