SBIR Phase II: A Non-invasive Image-based Skeletal Muscle Analytics Tool

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to provide a new tool revealing important information regarding skeletal muscle strength and health. Muscle weakness is a pervasive problem across our society, including people with joint disease, aging people, obese people, and people with neuromuscular disorders. All of these problems affect muscles across the body in different and non-intuitive ways; however, to date there has not been marketed technology that allows for quantitative measurement of muscle size on a muscle-by-muscle basis and specific analysis to address the muscle weakness problem. Due to the current high cost, the initial targeted customers will be elite athlete organizations, with the goal of using the technology to improve performance as well as to provide more quantitative metrics for predicting injury susceptibility and make return-to-sport decisions. However, with research and development to bring down the cost, the ultimate goal is to make a broadly used clinical tool for prevention, diagnosis, and treatment of health conditions related to musculoskeletal disease and mobility, which will have broad societal impact. The proposed project will provide a major advancement in image-based modeling and data analysis tools in order to allow high-throughput imaging, rapid and accurate segmentation of muscles and efficient data analysis. Currently, physical therapists, athletic trainers and strength and conditioning coaches only have very blunt tools to assess each individual?s strength and very limited information about the optimal muscle profile. Therefore, training and rehabilitative approaches are developed via experience and trial and error. The technology proposed here solves these problems by making using of an image-to-model pipeline to quantify muscle size and provide valuable and actionable information based on the quantification. However, the obstacles for a wide adoption of this technology include specific magnetic resonance imaging (MRI) protocols and lengthy image segmentation process. In the previous funding cycle these two problems have been addressed with substantial technology advancements. The proposed activities in this funding cycle will continue the technical development process to further bring down the cost with improved image segmentation process and provide additional value with advanced data analysis. It will ultimately be a revolutionary tool to improve muscle health.