Morishima Ryo, Schoser Benedikt
Department of Neurology, Tokyo Metropolitan Neurological Hospital, Musashidai 2-6-1, Fuchu 183-0042, Tokyo, Japan.
Friedrich-Baur-Institute, Department of Neurology LMU Clinic Munich, Ziemssenstr. 1, 80336 Munich, Bavaria, Germany.
Muscles. 2023 Nov 8;2(4):374-388. doi: 10.3390/muscles2040029.
Skeletal muscle MRI studies in limb-girdle muscular dystrophy (LGMD) have increased over the past decades, improving the utility of MRI as a differential diagnostic tool. Nevertheless, the relative rarity of individual genotypes limits the scope of what each study can address, making it challenging to obtain a comprehensive overview of the MRI image of this splintered group. Furthermore, MRI studies have varied in their methods for assessing fat infiltration, which is essential in skeletal muscle MRI evaluation. It stayed problematic and impeded attempts to integrate multiple studies to cover the core MRI features of a distinct LGMD. In this study, we conducted a systematic review of LGMD in adults published until April 2023; 935 references were screened in PubMed and EMBASE, searches of the gray literature, and additional records were added during the screening process. Finally, 39 studies were included in our final analysis. We attempted to quantitatively synthesize the MRI data sets from the 39 individual studies. Finally, we illustrated ideal and simple MRI muscle involvement patterns of six representative LGMD genotypes. Our summary synthesis reveals a distinct distribution pattern of affected muscles by LGMD genotypes, which may be helpful for a quick first-tier differential diagnosis guiding genetic diagnostics.
在过去几十年中，针对肢带型肌营养不良症（LGMD）的骨骼肌MRI研究有所增加，提高了MRI作为鉴别诊断工具的效用。然而，单个基因型相对罕见，限制了每项研究能够涉及的范围，使得全面了解这一分类群体的MRI图像具有挑战性。此外，MRI研究在评估脂肪浸润的方法上存在差异，而脂肪浸润在骨骼肌MRI评估中至关重要。这仍然存在问题，并阻碍了整合多项研究以涵盖特定LGMD核心MRI特征的尝试。在本研究中，我们对截至2023年4月发表的成人LGMD研究进行了系统综述；在PubMed和EMBASE中筛选了935篇参考文献，搜索了灰色文献，并在筛选过程中添加了其他记录。最后，39项研究纳入了我们的最终分析。我们试图对这39项独立研究的MRI数据集进行定量综合。最后，我们展示了六种代表性LGMD基因型的理想且简单的MRI肌肉受累模式。我们的总结性综合分析揭示了LGMD基因型对受累肌肉的独特分布模式，这可能有助于快速进行一级鉴别诊断，指导基因诊断。
