Evidence map›Paper›PMID 41665701›Full record

ArticleArchives of orthopaedic and trauma surgery2026

Meniscus and ligament injuries associated with tibial plateau fractures cannot be predicted from CT scans, even with high surgical experience.

Stephanie Schneider, Johanna Ludwig, Alexander Hönning, Wiebke Käckenmester, Denis Guembel, Axel Ekkernkamp, Philipp-Johannes Braun, Theresa Diermeier

Abstract read
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Article in Archives of orthopaedic and trauma surgery, 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Stephanie SchneiderSana Klinikum Lichtenberg, Berlin, Germany. mail@drstephanieschneider.de.
Johanna LudwigUnfallkrankenhaus Berlin, Berlin, Germany.
Alexander HönningUnfallkrankenhaus Berlin, Berlin, Germany.
Wiebke KäckenmesterUnfallkrankenhaus Berlin, Berlin, Germany.
Denis GuembelUnfallkrankenhaus Berlin, Berlin, Germany.
Axel EkkernkampUnfallkrankenhaus Berlin, Berlin, Germany.
Philipp-Johannes BraunUnfallkrankenhaus Berlin, Berlin, Germany.
Theresa DiermeierUnfallkrankenhaus Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTibial plateau fractures are associated with a range of meniscal and ligamentous injuries that are relevant to the outcome. Standard diagnostics include radiographs and computed tomography (CT). Magnetic resonance imaging (MRI) is not routinely recommended, although it visualizes meniscal and ligamentous injuries with high sensitivity and specificity. The aim of the study was to analyze tibial plateau fractures for meniscal and ligamentous injuries and to determine whether predictability could be achieved using CT. The study also examined whether the detection of meniscal and ligamentous injuries depended on the experience of the trauma surgeon.

methodInitially, 30 CT scans and subsequently 30 MRIs were evaluated by three residents and three consultants. To prevent rater recall of MRI–CT findings for a given patient, findings were presented in a randomized order with a two-week interval between CT and MRI assessments. A standardized questionnaire was used to evaluate soft-tissue injuries, fracture classification, surgical strategy, and the treatment of associated meniscal and ligamentous injuries for each CT and MRI. The radiologists’ MRI report was defined as the reference standard.

resultsThe incidence of meniscal and ligamentous injuries associated with tibial plateau fractures was 93% (n=30). The regions most affected by soft-tissue injuries were the posterolateral corner, the anterior cruciate ligament, and both collateral ligaments. Sixty additional soft-tissue injuries were identified upon evaluation of MRI scans. The greatest improvement in diagnostic accuracy for meniscal and ligamentous injuries due to MRI was observed in cases of posterior cruciate ligament tears. Differences between consultants and residents were particularly evident in the detection of soft-tissue injuries in the lateral meniscus (63% vs. 48%, n=30, p=0.036) and the collateral ligament (70% vs. 56%, n=30, p=0.045).

conclusionPredicting meniscal and ligamentous injuries in tibial plateau fractures based solely on CT scans is insufficient, irrespective of the surgeon’s experience. The benefit and indication for MRI should be assessed on an individualized basis. The fracture extent, suspicion of soft-tissue injury, the treatment goal, and patient factors all influence this decision.

Indexed as

Ligaments, ArticularTibial FracturesTibial Meniscus InjuriesTibial Plateau FracturesTomography, X-Ray ComputedAdultAgedFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedCTLigamentous injuriesMeniscal injuriesMRISoft tissueTibial plateau fracture

Identifiers

PMID41665701
PMCPMC12891015

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.