STTR Phase I: A Non-invasive Image­‐based Skeletal Muscle Analytics Tool

这个小型企业技术转移(STTR)第一阶段项目的更广泛的影响/商业潜力是提供一个新的工具，揭示关于骨骼肌力量和健康的重要信息。肌肉无力是我们整个社会普遍存在的问题，包括关节疾病患者、老年人、肥胖者和神经肌肉疾病患者。所有这些问题都以不同的和非直观的方式影响着全身的肌肉；然而，到目前为止，还没有市场上的技术允许在肌肉的基础上定量测量肌肉的大小。最初的目标客户是运动员组织，目标是利用这项技术为运动员的训练提供信息，以提高成绩，并为预测受伤易感性提供更多量化指标，并做出回归--？？]运动决策。然而，在渗透到运动员领域之后，最终目标是将这项技术发展到能够更广泛地应用于临床的诊断工具，用于预防、诊断和治疗与肌肉骨骼疾病和活动相关的健康状况，这将产生广泛的社会影响。拟议的项目将在基于图像的建模工具方面取得重大进展，以便能够对运动员整个下肢的肌肉进行高通量成像和分割。目前，物理治疗师、运动训练师以及力量和调理沙发上只有非常生硬的工具来评估每个人的力量。因此，培训和康复方法是通过经验和试错来开发的。同样，由于工具非常迟钝，目前还不清楚运动员的最佳肌肉特征是什么。这里提出的技术解决了这些问题，通过使用图像-？到-？]模型管道来量化整个下肢的肌肉大小。初步证据表明，这些新的测量为表型运动员提供了全新的衡量标准，确定了哪些肌肉特征能带来最大的表现(例如，速度、跳跃高度、灵活性)。目前在学术环境中开发的技术在市场翻译方面的潜力有限，因为：(I)它需要非常专门的磁共振成像方案，以及(Ii)分割时间限制了商业可行性。拟议的活动在开发解决这两个问题的创新方法方面具有很高的智力价值，最终将其从一种研究工具转变为一种商业上可行的服务。

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I 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 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. The initial targeted customers are athlete organizations, with the goal of using the technology to both inform training of athletes to improve performance as well as to provide more quantitative metrics for predicting injury susceptibility and make return--?]to--?]sport decisions. However, following penetration into the athlete sector, the ultimate goal is to advance the technology to the point where it can more broadly to used clinically as a diagnostic tool to be used in the prevention, diagnosis, and treatment of health conditions related to musculoskeletal disease and mobility, which will have wide spanning overall societal impact.The proposed project will provide a major advancement in image--?]based modeling tools in order to allow high--?]throughput imaging and segmentation of muscles of the entire lower limb of athletes. Currently, physical therapists, athletic trainers and strength and conditioning couches only have very blunt tools to assess each individual?fs strength. Therefore, training and rehabilitative approaches are developed via experience and trial and error. Similarly, because the tools have been very blunt, it is currently unknown what the optimal muscle characteristics of an athlete would be. The technology proposed here solves these problems by making using of an image--?]to--?]model pipeline to quantify muscle size across in the entire lower extremity. Preliminary evidence demonstrates that these new measurements provide entirely new metrics for phenotyping athletes, identifying which muscle profiles result in maximal performance (e.g., speed, jump height, agility). The current technology developed in the academic environment is limited in its potential to market translation because: (i) it requires a very specialized magnetic resonance imaging protocol, and (ii) segmentation time is prohibitive for commercial viability. The proposed activities have high intellectual merit in developing innovative approaches to solve both problems, ultimately transforming this from a research tool to a commercially viable service.