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Published on: January 12, 2019
Muscle MRI Pattern in Dysferlinopathy and its Correlation with Dysferlin Gait
Tanushree Chawla1, Dipti Baskar1, Kiran Polavarapu1,2
1Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bengaluru, Karnataka, India.
Background And Objectives:
Magnetic resonance imaging (MRI) in dysferlinopathy has consistently demonstrated a particular pattern of affliction. We aimed to study muscle MRI characteristics of lower limbs in limb girdle muscular dystrophy (LGMD)-R2 phenotypes and correlate them with the gait pattern.
Methods:
Forty genetically and/or biopsy-proven cases of dysferlinopathy underwent muscle MRI of the lower limbs. The pattern and extent of fatty infiltration and edema were recorded. Spearman's correlation analysis was used to find the correlation between muscle involvement and demographics, duration of illness, Muscular Dystrophy Functional Rating Scale (MDFRS), genotype, and gait pattern.
Results:
Mean age at onset and duration of illness at evaluation were 21.5 ± 6.3 years and 7.15 ± 4.95 years, respectively. Male: Female of patients was 2:1. Long head of biceps femoris was most severely involved with relative sparing of short head. Specific MRI pattern was noted based on phenotype, though no genotypic correlation was observed. Adductor magnus and semimembranosus were more severely involved in LGMD and proximodistal (PD) forms compared to Miyoshi muscular dystrophy type 1 phenotype. In addition, tibialis posterior and extensor hallucis longus were more severely involved in PD compared to MM and LGMD phenotypes. MDFRS mobility domain and duration of illness correlated with MRI findings. Gait pattern analysis revealed more severe involvement of flexor hallucis longus compared to extensor hallucis longus.
Conclusions:
Muscle involvement differed based on the phenotype. Characteristic great toe extension in PD phenotype showed an imaging correlation with more severe involvement of flexor hallucis longus compared to extensor hallucis longus. Thus, imaging can be a potential biomarker to study the evolution and severity of disease in dysferlinopathy.
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