ArticleThe ultrasound journal2026
Diagnostic accuracy of ultrasound in assessing medial collateral ligament and medial meniscus injuries? A systematic review and meta-analysis.
Article in The ultrasound journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMedial Collateral Ligament (MCL) and Medial Meniscus (MM) injuries are common medial knee pathologies. While MRI and arthroscopy are gold-standard diagnostic modalities, they are costly, invasive, and often delayed. Ultrasound is fast, inexpensive, and non-invasive, with growing use clinically, particularly point-of-care ultrasound (POCUS). This systematic review and meta-analysis aims were to evaluate ultrasound's diagnostic performance for MCL and MM injuries, both as standalone modalities and initial screening tools.
methodsA systematic search of PubMed, Cochrane, Embase, CINAHL, and Google Scholar identified studies between 1st October 2014 and 31st October 2024. Fourteen studies (1,259 patients) met inclusion criteria. Methodological quality was assessed using validated tools.
resultsOverall risk of bias was low, with moderate certainty of evidence for MCL and low certainty for MM injuries. Nine studies (713 patients) evaluated MCL injuries. Bivariate meta-analysis showed pooled sensitivity 0.83 (95% CI: 0.76-0.88), specificity 0.96 (95% CI: 0.91-0.98), diagnostic odds ratio (DOR) 117.8, and area under the SROC curve (AUC) 0.90. Heterogeneity was minimal (I² = 0%). Twelve studies (969 patients) evaluated MM injuries, with pooled sensitivity 0.85 (95% CI: 0.82-0.88), specificity 0.89 (95% CI: 0.81-0.94), DOR 45, and AUC 0.88. Heterogeneity was low for sensitivity but substantial for specificity (I² = 70.6%).
conclusionsUltrasound demonstrated high specificity for MCL and moderate sensitivity for MM injuries. It may serve as a valuable modality for MCL injuries in POCUS settings and as an initial screening tool for MM injuries. As POCUS utilisation expands, it may support diagnostic pathways.
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