Key result
Whole-body MRI identified a selective pattern of muscle involvement in pediatric LMNA-related dystrophy that was differentiated from SEPN1-related myopathy using machine learning.
Why the study?
Can whole-body MRI combined with machine learning differentiate pediatric LMNA-related dystrophy from SEPN1-related myopathy?
Observational (n=17)
Can whole-body MRI combined with machine learning differentiate pediatric LMNA-related dystrophy from SEPN1-related myopathy?
Whole-body MRI reveals a distinct pattern of skeletal muscle involvement in pediatric LMNA-related dystrophy that can be differentiated from SEPN1-related myopathy using machine learning.
Answers are grounded in this paper and cite their sources.
May aid differential diagnosis of pediatric LMNA- and SEPN1-related myopathies; hypothesis-generating pending prospective validation.
INTRODUCTION: We sought to define the whole-body MRI (WB-MRI) fingerprint of muscle involvement in pediatric LMNA-related dystrophy (LMNA-RD) and to compare it with SEPN1-related myopathy (SEPN1-RM). METHODS: Signal abnormality and atrophy in 109 muscles were scored by semiquantitative scales in 8 children with LMNA-RD and represented by heatmaps. These features were compared with those from 9 SEPN1-RM patients by random forests. RESULTS: LMNA-RD showed predominant signal abnormalities in erector spinae, serratus anterior, subscapularis, gluteus medius and minimus, vastii, adductor magnus and longus, semimembranosus, medial gastrocnemius, and soleus muscles. Psoas, sternocleidomastoid, gracilis, and sartorius muscles often had normal signal but showed atrophy. Cranial, flexor digitorum longus, and tibialis posterior muscles were spared. According to random forests, atrophied semimembranosus in SEPN1-RM was the most relevant feature to distinguish these patients from LMNA-RD. CONCLUSIONS: A selective pattern in WB-MRI for pediatric LMNA-RD exists and can be differentiated from SEPN1-RM by machine learning. Muscle Nerve 54: 192-202, 2016.
No takes yet. Share an insight, caveat, or question.
Gómez‐Andrés et al. (2015) conducted an observational in Pediatric LMNA-related dystrophy and SEPN1-related myopathy (n=17). LMNA-related dystrophy vs. SEPN1-related myopathy was evaluated on Differentiation of muscle signal abnormality and atrophy patterns using random forests. Whole-body MRI identified a selective pattern of muscle involvement in pediatric LMNA-related dystrophy that was differentiated from SEPN1-related myopathy using machine learning.
Synapse has enriched 10 related papers. Consider them for comparative context: