Funded Projects
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Project # | Project Title | Research Focus Area | Research Program | Administering IC | Institution(s) | Investigator(s) | Location(s) | Year Awarded |
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1UH2AR076724-01
Show Summary |
Technology Research Site for Advanced, Faster Quantitative Imaging for BACPAC | Clinical Research in Pain Management | Back Pain Consortium Research Program | NIAMS | UNIVERSITY OF CALIFORNIA, SAN FRANCISCO | MAJUMDAR, SHARMILA | San Francisco, CA | 2019 |
NOFO Title: HEAL Initiative: Back Pain Consortium (BACPAC) Research Program Technology Research Sites (UH2/UH3 Clinical Trial Optional)
NOFO Number: RFA-AR-19-028 Summary: Despite the significance of spine disorders, there are few reliable methods to determine appropriate patient care and evaluate intervention effectiveness. The research and tool development take the critical next step in the clinical translation of faster, quantitative magnetic resonance imaging (MR) of patients with lower back pain. The multidisciplinary Technology Research Site (Tech Site) of BACPAC will develop Phase IV (i.e., technology optimization) technologies and/or methods (TTMs) to leverage two key technical advancements: development of machine learning-based, faster MR acquisition methods and machine learning for image segmentation and extraction of objective disease related features from images. The team will develop, validate, and deploy end-to-end deep learning-based technologies (TTMs) for accelerated image reconstruction, tissue segmentation, and detection of spinal degeneration to facilitate automated, robust assessment of structure-function relationships between spine characteristics, neurocognitive pain response, and patient-reported outcomes. |