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从临床 MRI 扫描中分析不同年龄段和性别的部分三维旋转袖肌群体积和脂肪浸润的客观情况。

Objective analysis of partial three-dimensional rotator cuff muscle volume and fat infiltration across ages and sex from clinical MRI scans.

机构信息

Springbok Analytics, Charlottesville, VA, USA.

University of Virginia Medical School, Charlottesville, VA, USA.

出版信息

Sci Rep. 2023 Sep 1;13(1):14345. doi: 10.1038/s41598-023-41599-z.

Abstract

Objective analysis of rotator cuff (RC) atrophy and fatty infiltration (FI) from clinical MRI is limited by qualitative measures and variation in scapular coverage. The goals of this study were to: develop/evaluate a method to quantify RC muscle size, atrophy, and FI from clinical MRIs (with typical lateral only coverage) and then quantify the effects of age and sex on RC muscle. To develop the method, 47 full scapula coverage CTs with matching clinical MRIs were used to: correct for variation in scan capture, and ensure impactful information of the RC is measured. Utilizing this methodology and automated artificial intelligence, 170 healthy clinical shoulder MRIs of varying age and sex were segmented, and each RC muscle's size, relative contribution, and FI as a function of scapula location were quantified. A two-way ANOVA was used to examine the effect of age and sex on RC musculature. The analysis revealed significant (p < 0.05): decreases in size of the supraspinatus, teres minor, and subscapularis with age; decreased supraspinatus and increased infraspinatus relative contribution with age; and increased FI in the infraspinatus with age and in females. This study demonstrated that clinically obtained MRIs can be utilized for automatic 3D analysis of the RC. This method is not susceptible to coverage variation or patient size. Application of methodology in a healthy population revealed differences in RC musculature across ages and FI level between sexes. This large database can be used to reference expected muscle characteristics as a function of scapula location and could eventually be used in conjunction with the proposed methodology for analysis in patient populations.

摘要

目的 临床 MRI 对肩袖(RC)萎缩和脂肪浸润(FI)的客观分析受到定性测量和肩胛覆盖变化的限制。本研究的目的是:开发/评估一种从临床 MRI(典型的仅外侧覆盖)量化 RC 肌肉大小、萎缩和 FI 的方法,然后量化年龄和性别对 RC 肌肉的影响。为了开发该方法,使用了 47 个具有匹配临床 MRI 的全肩胛骨覆盖 CT 来:纠正扫描捕获的变化,并确保测量 RC 的重要信息。利用该方法和自动化人工智能,对 170 份不同年龄和性别的健康临床肩部 MRI 进行了分割,并量化了每个 RC 肌肉的大小、相对贡献和作为肩胛骨位置函数的 FI。使用双向方差分析来检查年龄和性别对 RC 肌肉的影响。分析显示,随着年龄的增长,冈上肌、小圆肌和肩胛下肌的大小显著(p < 0.05)减小;随着年龄的增长,冈上肌和冈下肌的相对贡献减少,而冈下肌的相对贡献增加;随着年龄的增长,冈下肌的 FI 增加,女性的 FI 也增加。本研究表明,临床获得的 MRI 可用于 RC 的自动 3D 分析。该方法不受覆盖变化或患者大小的影响。该方法在健康人群中的应用揭示了 RC 肌肉在不同年龄和 FI 水平之间的差异,以及性别之间的 FI 差异。这个大型数据库可以用作参考,根据肩胛骨位置预期的肌肉特征,并最终可以与提出的方法结合用于患者群体的分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/609a/10474276/466d51c8dcbb/41598_2023_41599_Fig1_HTML.jpg

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