Shift Angle and Medial Retraction of the Deep Layer on Magnetic Resonance Imaging Are Associated With Intraoperative Reparability in Arthroscopic Rotator Cuff Repair
Year: 2026
Type: article
Study design: Observational Study
Abstract: Purpose: To determine whether magnetic resonance imaging-based measurements of the deep layer, specifically the shift angle and medial retraction, can predict intraoperative reparability of large-to-massive rotator cuff tears. Methods: This retrospective study included patients who underwent arthroscopic repair of large-to-massive rotator cuff tears between April 2015 and September 2019, with a minimum follow-up of 12 months. The shift angle was defined as the anteroposterior extent of the deep-layer tear on sagittal magnetic resonance imaging and medial retraction as the distance from the lateral edge of the deep-layer stump to the cartilage margins. Inter- and intraobserver reliabilities and predictive accuracy for reparability were assessed. Results: < .001) than the reparable group. Receiver operating characteristic analysis showed good diagnostic performance for predicting irreparability for both the shift angle (area under the curve, 0.861; cutoff, 98.0°) and medial retraction (area under the curve, 0.870; cutoff, 29.8 mm), comparable to or better than superficial tear-size measurements. Measurement reliability for both parameters was substantial to excellent (interobserver intraclass correlation coefficient = 0.862 and 0.769; intraobserver intraclass correlation coefficient = 0.896 and 0.889, respectively). Conclusions: Magnetic resonance imaging-based assessment of the deep layer using the shift angle and medial retraction showed good diagnostic performance and substantial reliability for predicting intraoperative reparability. Level of Evidence: Level III, retrospective cohort study.
DOI: 10.1002/ars2.70058
Authors: Hideya Yoshimura, Hiroko Ueki, Naoko Araya
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,000
OpenAlex ID: W7204127964