Objective analysis of partial three-dimensional rotator cuff muscle volume and fat infiltration across ages and sex from clinical MRI scans.
Objective analysis of partial three-dimensional rotator cuff muscle volume and fat infiltration across ages and sex from clinical MRI scans.
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DOI：
10.1038/s41598-023-41599-z
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发表时间：
2023-09-01
影响因子：
4.6
通讯作者：
中科院分区：
文献类型：
--
作者：
目的：临床MRI对肩袖（RC）萎缩和脂肪浸润（FI）的分析受到定性测量和肩胛骨覆盖范围变化的限制。本研究的目的是：开发/评估一种方法，通过临床mri（典型的侧位覆盖）量化RC肌肉的大小、萎缩和FI，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个全肩胛骨覆盖ct与匹配的临床mri，以纠正扫描捕获的变化，并确保测量RC的有效信息。利用该方法和自动化人工智能，对170例不同年龄和性别的健康临床肩部mri进行了分割，并对每个RC肌肉的大小、相对贡献和FI作为肩胛骨位置的函数进行了量化。采用双向方差分析来检验年龄和性别对RC肌肉组织的影响。分析显示，冈上肌、小圆肌和肩胛下肌的大小随着年龄的增长而减小（p < 0.05）；随着年龄的增长，冈上肌的相对贡献减少，冈下肌的相对贡献增加；冈下肌FI随年龄和女性增加。本研究表明，临床获得的mri可以用于RC的自动3D分析。这种方法不受覆盖范围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不同年龄的RC肌肉组织和不同性别的FI水平的差异。这个大型数据库可用于参考预期的肌肉特征，作为肩胛骨位置的函数，并最终可与提出的方法结合使用，用于患者群体的分析。
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.
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影响因子：
5.3
作者：
Iannotti, Joseph P.;Walker, Kyle;Ricchetti, Eric T.
通讯作者：
Ricchetti, Eric T.
影响因子：
3
作者：
Williams, Matthew D.;Laedermann, Alexandre;Walch, Gilles
通讯作者：
Walch, Gilles
DOI：
10.1148/ryai.220132
发表时间：
2023-03-01
期刊：
RADIOLOGY-ARTIFICIAL INTELLIGENCE
影响因子：
--
作者：
Riem, Lara;Feng, Xue;Blemker, Silvia S.
通讯作者：
Blemker, Silvia S.
从MRI进行深度学习的分割，并推断精度预测。
影响因子：
3.6
作者：
Hess, Hanspeter;Ruckli, Adrian C.;Burki, Finn;Gerber, Nicolas;Menzemer, Jennifer;Burger, Juergen;Schar, Michael;Zumstein, Matthias A.;Gerber, Kate
通讯作者：
Gerber, Kate
影响因子：
3.8
作者：
Santago AC 2nd;Vidt ME;Tuohy CJ;Poehling GG;Freehill MT;Jordan JH;Kraft RA;Saul KR
通讯作者：
Saul KR