Disease duration and disability in dysfeRlinopathy can be described by muscle imaging using heatmaps and random forests

• Published in: Muscle & nerve Vol. 59; no. 4; pp. 436 - 444
• Main Authors: Gómez‐Andrés, David, Díaz, Jorge, Munell, Francina, Sánchez‐Montáñez, Ángel, Pulido‐Valdeolivas, Irene, Suazo, Lionel, Garrido, Cristián, Quijano‐Roy, Susana, Bevilacqua, Jorge A.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.04.2019
• Subjects: disability; dysferlin; heatmap; Infiltration; machine learning; Magnetic resonance imaging; Medical imaging; muscle imaging; Muscles; random forest; Thigh; heatmap; random forest; machine learning; dysferlin; disability; muscle imaging
• ISSN: 0148-639X; 1097-4598; 1097-4598
• DOI: 10.1002/mus.26403

ABSTRACT Introduction: The manner in which imaging patterns change over the disease course and with increasing disability in dysferlinopathy is not fully understood. Methods: Fibroadipose infiltration of 61 muscles was scored based on whole‐body MRI of 33 patients with dysferlinopathy and represented in a heatmap. We trained random forests to predict disease duration, Motor Function Measure dimension 1 (MFM‐D1), and modified Rankin scale (MRS) score based on muscle scoring and selected the most important muscle for predictions. Results: The heatmap delineated positive and negative fingerprints in dysferlinopathy. Disease duration was related to infiltration of infraspinatus, teres major–minor, and supraspinatus muscles. MFM‐D1 decreased with higher infiltration of teres major–minor, triceps, and sartorius. MRS related to infiltration of vastus medialis, gracilis, infraspinatus, and sartorius. Discussion: Dysferlinopathy shows a recognizable muscle MRI pattern. Fibroadipose infiltration in specific muscles of the thigh and the upper limb appears to be an important marker for disease progression. Muscle Nerve 59:436–444, 2019