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.
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