Osteoarthritis (OA) affects over 50 million Americans and has a substantial impact on the US economy and the health care system. Currently, there is no cure for this debilitating disease and the effective treatment is, at best, focused on symptomatic relief. The conventional MR techniques have shown promise for the identification of more subtle morphologic alterations as determined by cartilage volume, or surface fibrillation. However, even the more innovative of these conventional techniques have not been consistent in predicting the knee OA progression. Therefore, there is a high demand for reliable, objective, non-invasive and quantitative imaging markers that identifies the risk population at early stage. The long-term objective of this grant application is to develop a more effective means of identifying individuals at higher risk for knee OA progression via quantitative knee joint assessment of cartilage, trabecular bone and bone marrow. High- resolution, multi-nuclear [sodium (23Na) and proton (1H)] MR imaging approaches, novel image post- processing and visualization methods at ultra-high field system (7T) will significantly impact the objective assessment of OA pathology. OA may be aggravated by many risk factors such as joint malalignment, obesity, trauma, meniscal abnormalities or cruciate ligament tears, biochemical, biomechanical, genetic, and environmental. Specifically, we will use novel sodium and proton micro-MRI, image-processing and visualization technologies employing fuzzy distance transform (FDT), digital topological analysis (DTA) and tensor analysis. We will acquire high resolution sodium and proton MRI of age-and gender matched OA subjects in a longitudinal fashion to determine whether baseline combined risk profile can predict risk population for severe knee OA progression over 30 months period. Finally, we will identify which interactions (cartilage-bone, bone-marrow or cartilage-marrow or combination of all three etc) at baseline exam will better predict the potential risk factor for severe knee OA progression over 30 months period. Once developed and validated in human knee joint, these studies will profoundly affect not only to diagnose OA in its earliest stages but also possibly identifies the risk population at early stage. We anticipate that the quantitative interactions among the cartilage, bone and marrow and their combined interactions may be useful to design a risk profile for knee OA progression rather than individual approach. We plan to address these close interactions between cartilage, bone and marrow in OA patients with external collaboration through subcontract (Dr. Punam Saha, Department of Electrical &Computer Engineering and Radiology, University of Iowa). The focus of the grant application is consistent with the mission of the NIBIB/NIAMS (NIH) bioengineering research grant (BRG) program.
Osteoarthritis (OA) affects ~6% of the US adult population and ~12-13% of those aged 60 and over. It has a substantial negative impact on the economy and the health care system. The current R01 proposal will develop a more effective means of identifying individuals at higher risk for OA progression via quantitative assessment of whole knee joint via ultra high field (7T) MRI system.
|Lee, Jae-Seung; Xia, Ding; Jerschow, Alexej et al. (2016) In vitro study of endogenous CEST agents at 3 T and 7 T. Contrast Media Mol Imaging 11:4-14|
|Chen, Cheng; Jin, Dakai; Liu, Yinxiao et al. (2016) Trabecular bone characterization on the continuum of plates and rods using in vivo MR imaging and volumetric topological analysis. Phys Med Biol 61:N478-N496|
|Wang, Ligong; Regatte, Ravinder R (2015) Tâ‚Ï MRI of human musculoskeletal system. J Magn Reson Imaging 41:586-600|
|Wang, Ligong; Regatte, Ravinder R (2015) Investigation of regional influence of magic-angle effect on t2 in human articular cartilage with osteoarthritis at 3 T. Acad Radiol 22:87-92|
|Chang, Gregory; Honig, Stephen; Liu, Yinxiao et al. (2015) 7Â Tesla MRI of bone microarchitecture discriminates between women without and with fragility fractures who do not differ by bone mineral density. J Bone Miner Metab 33:285-93|
|Madelin, Guillaume; Poidevin, Frederick; Makrymallis, Antonios et al. (2015) Classification of sodium MRI data of cartilage using machine learning. Magn Reson Med 74:1435-48|
|Lee, Jae-Seung; Xia, Ding; Ge, Yulin et al. (2014) Concurrent saturation transfer contrast in in vivo brain by a uniform magnetization transfer MRI. Neuroimage 95:22-8|
|Parasoglou, Prodromos; Xia, Ding; Chang, Gregory et al. (2014) Three-dimensional saturation transfer Â³Â¹P-MRI in muscles of the lower leg at 3.0 T. Sci Rep 4:5219|
|Wang, Ligong; Salibi, Nouha; Chang, Gregory et al. (2014) Evaluation of subchondral bone marrow lipids of acute anterior cruciate ligament (ACL)-injured patients at 3 T. Acad Radiol 21:758-66|
|Wang, Ligong; Chang, Gregory; Bencardino, Jenny et al. (2014) T1rho MRI of menisci in patients with osteoarthritis at 3 Tesla: a preliminary study. J Magn Reson Imaging 40:588-95|
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