Automated Segmentation of Forearm Muscles: Clinical Associations With Hand Function, Muscle Volume and Intramuscular Fat.

ABSTRACT:

Background

Hand function is critical for daily activities and declines early in many diseases, conditions or disorders affecting the musculoskeletal and neurologic systems. Muscle health markers derived from clinically available magnetic resonance imaging (MRI) scans are strongly associated with functional capacity, may enhance clinical assessment and inform management options. However, traditional muscle MRI assessments require time-intensive manual segmentations. Here, we aim to develop and test a computer-vision model for automated forearm muscle segmentation and investigate associations between MRI-derived muscle markers and age, sex, BMI, functional grip strength and dexterity measures.

Methods

We recruited 42 healthy, right-handed adults (54.8% female, median age 37.3 

SUBMITTER: Fundaun J 

PROVIDER: S-EPMC12817650 | biostudies-literature | 2025 Jul-Dec

REPOSITORIES: biostudies-literature