Effect of Tear Classification on Subscapularis Muscle Volume: A Deep Learning-based Semi-automatic Analysis of Pre- and Postoperative Changes in 246 Rotator Cuff Repair Patients With and Without First Facet Subscapularis Tears

  • Hwang, Kyosun; 
  • Lee, Jin Hyeok; 
  • Lim, Dongkyun; 
  • Yu, Kanghun; 
  • Jeong, Woong Kyo
Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

Background: Partial-thickness subscapularis (SSC) tendon tears, although less studied than full-thickness tears, are prevalent and clinically significant. Recent classifications have proposed subdivisions for these partial-thickness tears. However, their clinical implications and correlation with SSC muscle volume remain poorly understood. Purpose: To evaluate SSC muscle volume in relation to tendon tear classification and assess the changes in muscle volume both pre- and postoperatively using deep learning-based magnetic resonance imaging (MRI) segmentation in patients undergoing arthroscopic rotator cuff repair. Study Design: Cohort study; Level of evidence, 3. Methods: This study included 246 patients who underwent arthroscopic rotator cuff repair between January 2018 and December 2023. SSC tendon tears were classified using the Yoo and Rhee system. SSC muscle volumes were measured on preoperative MRIs and 6 months postoperatively using a validated deep learning segmentation tool. These volumes were normalized to the scapular volume. Results: Preoperative normalized SSC volume (nSSC) varied significantly across tear types (F = 7.21; P < .001). Patients with type 2B tears had a significantly lower mean nSSC (1.45 +/- 0.40) than those with no tears (1.68 +/- 0.37; P = .018) and type 2A tears (1.74 +/- 0.31; P = .023). Six months postoperatively, nSSC significantly decreased in patients with SSC tendon tears (nSSC = 1.48 +/- 0.34; Delta nSSC = -0.10 +/- 0.24; P < .001). For patients with type 2A or more severe tears, nSSC significantly decreased postoperatively in both the debridement (Delta nSSC = -0.13 +/- 0.18; P = .004) and repair (Delta nSSC = -0.12 +/- 0.29; P = .017) groups. However, the degree of volume change was not significantly different between the treatment groups. Conclusion: Even in partial-thickness tears affecting only the first facet, nSSC muscle volume decreases significantly with increasing tear severity. Furthermore, SSC muscle volume significantly decreases 6 months postoperatively in patients with SSC tendon tears, although the extent of this reduction does not vary among different treatment modalities.

키워드

deep learning; muscle volume; segmentation; shoulder; subscapularis tendon tear; FAT FRACTION
제목
Effect of Tear Classification on Subscapularis Muscle Volume: A Deep Learning-based Semi-automatic Analysis of Pre- and Postoperative Changes in 246 Rotator Cuff Repair Patients With and Without First Facet Subscapularis Tears
저자
Hwang, Kyosun; Lee, Jin Hyeok; Lim, Dongkyun; Yu, Kanghun; Jeong, Woong Kyo
DOI
10.1177/23259671251374303
발행일
2025-09
유형
Article
저널명
Orthopaedic Journal of Sports Medicine
권
13
호
9