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Updated: Apr 10, 2026
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Muscle Magnetic Resonance Imaging Phenotyping and Pattern Recognition in Genetically Confirmed Myopathies: A
Shariq Ahmad Shah1, Venugopalan Y Vishnu2, Leve Joseph Devaranjan Sebastian1
1Department of Neuroimaging and Interventional Neuroradiology, All India Institute of Medical Sciences, New Delhi, India.
Background And Objectives:
Diagnosing myopathy subtypes is challenging due to clinical and genetic heterogeneity. While muscle magnetic resonance imaging (MRI) enables pattern recognition, standardized imaging data from India are lacking. This study aimed to define MRI patterns in myopathies, compare semi-quantitative scores with fat fraction (FF) analysis, and derive a diagnostic algorithm.
Methods:
In this study, a total of 102 patients with confirmed dystrophic or inflammatory myopathies underwent 3T MRI of the pelvic girdle and lower limbs, combining conventional sequences with Dixon-based fat quantification. Analysis used a modified Mercuri T1 scale and Stramare T2 edema scoring, along with FF measurements across 6,180 muscles. Disease patterns, correlations between imaging and clinical variables, and associations between qualitative and quantitative metrics were analyzed.
Results:
MRI patterns were distinct for each myopathy. Facioscapulohumeral dystrophy showed hamstring involvement with low asymmetry (5%). Dystrophinopathies exhibited a "trefoil with single fruit" sign (68%). Calpainopathy showed symmetrical end-stage involvement of the gluteal, adductor, and hamstring muscles, while dysferlinopathy affected the gluteus minimus and posterior compartment. Glucosamine-N-acetyl Epimerase (GNE) myopathy showed severe involvement of the gluteus minimus, sartorius, gracilis, and tibialis anterior muscles. In inflammatory myopathies, dermatomyositis showed edema (62%) without a fixed pattern, whereas inclusion body myositis affected the gastrocnemius and gluteal muscles. Disease duration correlated with T1 scores (r = 0.3, P = 0.001) and FF (r = 0.4, P = 0.003). A significant association ( P < 0.001) was observed between T1 scores and FF categories.
Conclusions:
Combined semi-quantitative scoring and FF MRI distinguished myopathy subtypes, correlated with disease duration, and supported the use of MRI as a biomarker. Our muscle atlas defines disease-specific imaging phenotypes and serves as a reference for diagnostic evaluation in diverse populations.
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