Participated · Seed · Apr 2023

Springbok builds AI and machine‑learning technology to automatically quantify rotator cuff muscle atrophy and fatty infiltration from standard clinical MRIs, producing 3D volumetric measurements and actionable reports for providers and patients. Its deep‑learning‑based algorithms were developed and validated in Phase I work and are trained on an extensive digital database of healthy and pathological rotator cuff scans. The technology aims to overcome limits of the qualitative Goutallier classification by providing objective, scalable, and faster quantitative analysis within clinical workflows. Springbok is working with research partners at the University of Virginia, the San Antonio Orthopaedic Group (TSAOG), and the University of Wisconsin to further develop and validate its methods. The company received a $1.7 million Phase II SBIR grant from the NIH to develop a commercially viable algorithm and complete product development. Completing Phase II is intended to enable an FDA 510(k) submission and move the product toward clinical commercialization to improve diagnosis, treatment planning, and surgical outcomes. Springbok Analytics, based in Charlottesville, VA, provides technology that converts standard 2D magnetic resonance image (MRI) data into precise, personalized 3D muscle visualizations. The company’s scans take less than 15 minutes and enable quantification of muscle volume, asymmetries, atrophy, soft tissue injuries, and scar tissue for athletic, performance, and health use cases. Led by CEO Scott Magargee, Springbok supports research and care for a range of musculoskeletal and neuromuscular conditions, including facioscapulohumeral muscular dystrophy (FSHD). The company was recently selected into the NBA’s Launchpad program to source, evaluate, and pilot technologies that advance soft tissue injury prevention and recovery. Springbok intends to use the $3M in seed funding to expand operations and broaden its business reach. The announcement does not disclose revenue or user metrics.