Abstract
BackgroundThis meta-analysis assessed the efficacy of dual-energy computed tomography (DECT) in the diagnosis of anterior cruciate ligament (ACL) injuries.MethodsThe literature search was performed up to December 8, 2023, and included a comprehensive examination of several databases: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP. Diagnostic metrics sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and a summary receiver operating characteristic (SROC) were determined using a bivariate model analysis. Heterogeneity within the data was explored through subgroup analyses, which considered variables including geographical region, use of magnetic resonance imaging (MRI), arthroscopy, and study design.ResultsThe analysis included ten studies encompassing 544 patients. DECT demonstrated substantial diagnostic utility for ACL injuries of the knee, with a sensitivity of 0.91 (95% confidence interval [CI]: 0.88–0.94), a specificity of 0.90 (95% CI: 0.81–0.95), a PLR of 9.20 (95% CI: 4.50–19.00), a NLR of 0.10 (95% CI: 0.06–0.14), a DOR of 97.00 (95% CI: 35.00–268.00), and an area under the curve (AUC) of 0.95 (95% CI: 0.93–0.97). The subgroup analyses consistently showed high diagnostic precision for ACL injuries across Asian population (sensitivity: 0.91, specificity: 0.91, PLR: 9.90, NLR: 0.09, DOR: 105.00, AUC: 0.96), in MRI subgroup (sensitivity: 0.85, specificity: 0.94, PLR: 9.57, NLR: 0.18, DOR: 56.00, AUC: 0.93), in arthroscopy subgroup (sensitivity: 0.92, specificity: 0.89, PLR: 8.40, NLR: 0.09, DOR: 94.00, AUC: 0.95), for prospective studies (sensitivity: 0.92, specificity: 0.88, PLR: 7.40, NLR: 0.09, DOR: 78.00, AUC: 0.95), and for retrospective studies (sensitivity: 0.91, specificity: 0.93, AUC: 0.93).ConclusionDECT exhibits a high value in diagnosing ACL injuries. The significant diagnostic value of DECT provides clinicians with a powerful tool that enhances the accuracy and efficiency of diagnosis and optimizes patient management and treatment outcomes.
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