biostudies-literatureUnknown8(2)Fundaun J<h4>Background</h4>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.<h4>Methods</h4>We recruited 42 healthy, right-handed adults (54.8% female, median age 37.3 JCSM communicationse70015https://www.ebi.ac.uk/biostudies/studies/S-EPMC12817650biostudies-literatureAutomated Segmentation of Forearm Muscles: Clinical Associations With Hand Function, Muscle Volume and Intramuscular Fat.PMC12817650Fundaun JWesselink EOElliott JMHastie TJSmith ZAChaudhari ASWeber KABerhe NDelp SLPfyffer DLynn BPLaw CSWBedard SKaptan MSmith ACMackey SOliva VPai S AMcKay MJRatliff JHu SSfalseAutomated Segmentation of Forearm Muscles: Clinical Associations With Hand Function, Muscle Volume and Intramuscular Fat.<h4>Background</h4>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.<h4>Methods</h4>We recruited 42 healthy, right-handed adults (54.8% female, median age 37.3 2025-01-01T00:00:00Z2025 Jul-Dec2026-06-06T19:45:44.848Z2026-06-04T03:12:32.665ZS-EPMC128176504156810110.1002/rco2.70015