Accuracy of Knee MRI Findings in Detecting Soft Tissue Injury, Taking Arthroscopy as the Gold Standard
DOI:
https://doi.org/10.51985/JBUMDC2025777Keywords:
Anterior Cruciate Ligament Injuries, Arthroscopy, Diagnostic Imaging, Knee Injuries,Abstract
Objective: To assess the diagnostic validity of Magnetic Resonance Imaging (MRI) in detecting soft tissue knee injuries
using arthroscopy as the gold standard.
Study Design and Setting: A cross-sectional validation study was conducted at Khyber Teaching Hospital, Peshawar.
Methodology: A total of 192 patients with clinical suspicion of soft tissue knee injury were enrolled using non-probability
consecutive sampling for six months from 1st January 2025 to 30th June 2025. Inclusion criteria involved patients aged
18–60 years presenting with knee pain (VAS >4) and a popping sound, with normal X-ray findings. MRI scans were
interpreted for the presence of soft tissue tears based on hyperintense signals on T2-weighted images and fiber discontinuity.
All patients subsequently underwent arthroscopic evaluation. The diagnostic accuracy of MRI was determined using
sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen’s Kappa for agreement.
Results: MRI showed high sensitivity for the medial meniscus (91.8%), anterior cruciate ligament (88.6%), and posterior
cruciate ligament (83.3%), while the lateral meniscus had moderate sensitivity (68.2%). Specificity ranged from 74.3%
(medial meniscus) to 86.7% (lateral meniscus). Agreement between MRI and arthroscopy was substantial for medial
meniscus injuries (ê = 0.81) and moderate for anterior cruciate ligament, posterior cruciate ligament, and lateral meniscus.
Conclusion: MRI has high diagnostic utility and a substantial agreement with arthroscopy, specifically for anterior cruciate
ligament and medial meniscus injuries. Given its non-invasive nature and strong predictive validity, MRI should be
considered an effective first-line diagnostic tool when evaluating soft tissue knee injuries.
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Copyright (c) 2026 Zeeshan Haider, Abbas Ali, Shehryar Khan, Luqman Khan, Ubaid Ullah, Waqas Ahmad (Author)
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