Automated MRI-Based Quantification of Forearm Muscle Health and Associations with Hand Function

Motivation: Hand function is impaired in many conditions. MRI-derived muscle health markers may improve the evaluation of conditions affecting hand function. Traditional manual segmentation is time-consuming, necessitating automated approaches. Goal(s): Develop an accurate method to automatically assess forearm muscle health (muscle volume, intramuscular fat) and assess their relationship to hand function. Approach: We developed and tested a computer-vision model for automated forearm segmentation using fat-water MRI, then assessed associations between muscle health (volume, intramuscular fat) and hand function (grip strength, dexterity). Results: The computer-vision model achieved high accuracy and good-excellent reliability. Muscle volume was associated with BMI and grip strength. Impact: We developed an accurate, reliable computer-vision model to automatically segment forearm muscles, which will be made openly available. This method can improve clinical assessment of forearm muscle health leading to more efficient evaluation and management of conditions affecting hand function.