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Location of medial collateral ligament tears: introduction to a magnetic resonance imaging-based classification

  • Fidelius von Rehlingen-Prinz,
  • Karthik R. Krishnan,
  • Sebastian Rilk,
  • Fabian Tomanek,
  • Gabriel C. Goodhart,
  • Victor Beckers,
  • Robert O’Brien,
  • Gregory S. DiFelice,
  • Douglas N. Mintz

摘要

Purpose

Despite established tear grade classifications, there is currently no radiological classification for sMCL tear locations. This study aims to establish a magnetic resonance imaging (MRI) tear location classification system for sMCL tears, to enhance understanding and guide treatment decisions by categorizing tear types.

Methods

A retrospective search in a single institution’s MRI database identified patients with acute, Grade III sMCL tears (< 30 days between injury and MRI) from January to December 2022. Non-acute and partial tears were excluded, and three observers assessed tear types based on the proposed sMCL MRI tear location system: type I (proximal 25%), Ib (proximal femoral bony avulsion), II (midsubstance, 25–75%), III (distal 25%), IIIb (distal tibial bony avulsion), IIIs (Stener-like lesion). The interclass correlation coefficient (ICC) was used to assess interrater and intrarater reliability for continuous data; Fleiss and Cohen’s kappa assessed interrater and intrarater reliability for categorical data.

Results

MRI scans of thirty patients with diagnosed sMCL injuries (53% female, mean age 37 ± 13 years, range 16–68 years) were included based on inclusion/exclusion criteria. Interrater reliability was excellent (ICC: 0.968, 95% CI, 0.933–0.985), and intrarater reliability was excellent (ICC: 0.938, 95% CI: 0.874–0.970 & 0.900, 95% CI, 0.789–0.952). Type I injuries were most common (60%), followed by type III (33.3%), type II (3.3%), type Ib (3.3%), type IIIb (0.0%), and type IIIs (0.0%).

Conclusion

The presented MRI-based sMCL tear location classification provides a reproducible system for grading high-grade sMCL injuries. We propose that this framework will significantly unify tear location understanding and support more informed treatment decisions.