CHARLOTTESVILLE, Va., March 17, 2025 /PRNewswire/ - Springbok Analytics (www.springbokanalytics.com), a leader in AI-powered muscle analysis, today announced its role in MOVE Peds, the first large-scale clinical study focused on pediatric facioscapulohumeral muscular dystrophy (FSHD; NCT06847282). The study, led by top neuromuscular experts and funded by the NIH, aims to fill critical gaps in understanding how FSHD progresses in children and will set the foundation for future drug trials.
FSHD is one of the most common muscular dystrophies, but its progression in children remains poorly defined due to a lack of large-scale natural history data. With drug developers beginning to shift their focus to pediatric FSHD, MOVE Peds will provide essential information to refine clinical trial strategies, validate outcome measures, optimize inclusion criteria, and solidify MRI's role as a predictive biomarker—paving the way for accelerated regulatory review and wider physician adoption of emerging therapies.
"For drug developers looking at pediatric FSHD, the data from MOVE Peds will be essential," said Jeff Statland, MD, the overall study PI at the University of Kansas Medical Center. "Building on our adult studies focused on predicting progression of MRI and functional tests and being able to understand how children change as they grow will be essential to accurately interpreting hopeful treatment effects."
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Springbok's AI-Powered MRI Analysis: Advancing Pediatric FSHD Research
Springbok Analytics is bringing its cutting-edge, AI-driven muscle health analysis to MOVE Peds, providing a fully integrated, turnkey solution for MRI data acquisition, processing, and analysis. Springbok's contributions include:
Speed & Efficiency: The protocol is designed for rapid scanning (less than 45 minutes for whole body coverage including both muscle and inflammation specific assessments), minimizing the time children spend in the MRI scanner—a critical factor for pediatric studies.
Comprehensive Muscle Analytics: Unlike alternative MRI analytic methods, Springbok's acquisition and AI-methods generate data for all individual muscles and bone. This ensures a complete picture of disease impact, over-time adjustment for developmental growth, and allows optimal comparison of MRI data to functional test performance.
Quantifying Fat & STIR Signals: Springbok quantifies Short Tau Inversion Recovery (STIR), a key marker of muscle inflammation and early disease activity—critical for tracking disease progression and treatment effects, which may vary more in children.
