NSF Award
1152716
This Small Business Innovation Research (SBIR) Phase II project proposes to develop a real-time ultrasound system for evaluating musculoskeletal soft tissue conditions by implementing the novel ultrasound post-processing software developed in Phase I into a programmable platform ultrasound system. Today, radiologists diagnose most musculoskeletal diseases by observing static MRI or conventional ultrasound images and considering key factors that support only qualitative, subjective assessments. Developing an efficient, real-time, quantitative method for diagnosing soft tissue (e.g., tendons and ligaments) injuries and monitoring healing can lead to more accurate diagnoses and reduce re-injury of incompletely healed tissues. The project will enhance the novel software technology's clinical utility and workflow efficiency. The original software will be enhanced by improving the software to automatically detect a region of interest with the ultrasound image. The registered regions of interest can be matched precisely from one patient visit to the next. Developing data mining software will further increase efficiency and accuracy by leveraging machine learning to assist with diagnostic decisions. These software improvements will be integrated with the platform ultrasound system to improve clinical workflow. The integrated product will both match the work flow efficiency of standard ultrasound and dramatically advance the utility of ultrasound within the musculoskeletal arena. <br/><br/>The broader impact/commercial potential of this project, if successful, will dramatically improve clinicians' ability to care for soft tissue injuries and will position the company to capitalize on (1) pressure to reduce medical imaging costs, (2) musculoskeletal specialists' growing interest in ultrasound, especially portable instruments, (3) a major ultrasound manufacturer's focus on the large and relatively untapped musculoskeletal ultrasound market, and (4) the recent emergence of quantitative ultrasound for non-musculoskeletal applications. This Phase II project will produce an efficient, real-time, quantitative method for diagnosing soft tissue injuries and monitoring healing. In the US alone, overuse injuries (strains, sprains) are the most frequently reported musculoskeletal injuries. Annually, 18.4 million such injuries cost approximately $92 B. Patients suffering from musculoskeletal injuries currently face three challenges at diagnosis, care, and outcome. First, current diagnostic methods, including MRI, ultrasound, or physical manipulation, rely on highly subjective and observer-dependent interpretation, so accuracy varies. Second, MRI is still the standard of care, but is far more costly than ultrasound. Substituting ultrasound for MRI, where appropriate for initially diagnosing musculoskeletal conditions, could save Medicare $736 M/year. Third, the lack of an objective monitoring method to determine when a patient can safely return to activity means patients risk missing unnecessary work time or re-injury.
