Department of Radiology and Diagnostic Imaging, Universidade Federal de São Paulo (UNIFESP), Rua Napoleão de Barros, 800, São Paulo, SP, 04024-002, Brazil.
Laboratório Delboni Auriemo - Grupo DASA, Av Juruá, 434, Barueri, SP, 06455-010, Brazil.
Eur Radiol. 2021 Nov;31(11):8498-8512. doi: 10.1007/s00330-021-07931-9. Epub 2021 Apr 21.
The aims of this review are to discuss the imaging modalities used to assess muscle changes in myopathies, to provide an overview of the inherited myopathies focusing on their patterns of muscle involvement in magnetic resonance imaging (MR), and to propose up-to-date imaging-based diagnostic algorithms that can help in the diagnostic workup.
Familiarization with the most common and specific patterns of muscular involvement in inherited myopathies is very important for radiologists and neurologists, as imaging plays a significant role in diagnosis and follow-up of these patients.
• Imaging is an increasingly important tool for diagnosis and follow-up in the setting of inherited myopathies. • Knowledge of the most common imaging patterns of muscle involvement in inherited myopathies is valuable for both radiologists and neurologists. • In this review, we present imaging-based algorithms that can help in the diagnostic workup of myopathies.
本文旨在讨论用于评估肌病肌肉变化的影像学方法,概述遗传性肌病,重点介绍磁共振成像(MRI)中的肌肉受累模式,并提出最新的基于影像学的诊断算法,以帮助诊断。
熟悉遗传性肌病中最常见和最具特异性的肌肉受累模式对放射科医生和神经科医生非常重要,因为影像学在这些患者的诊断和随访中起着重要作用。
影像学是遗传性肌病诊断和随访的重要工具。
了解遗传性肌病中最常见的肌肉受累影像学模式对放射科医生和神经科医生都有价值。
在本文中,我们提出了基于影像学的算法,可帮助诊断肌病。