RESUMO
Purpose: We aimed to conduct a systematic review and meta-analysis of studies examining the performance of cone-beam computed tomography (CBCT) imaging in apical periodontitis (AP) prediction. This was done to address the contradictory results reported in the existing literature on this topic. Material and methods: We searched the Embase, PubMed, Cochrane library, and Scopus databases for literature published from inception to 30 June 2023 without language restriction using appropriate keywords. We included studies that reported the diagnostic accuracy values of CBCT in AP detection among humans by comparing AP diagnosis with a control group without lesions. We pooled the diagnostic accuracy values using a random effects model and presented the estimates as percentage and 95% confidence interval (CI). The heterogeneity between the surveys was explored by I2 statistic. Results: Out of 301 citations initially identified, a total of 8 eligible studies were finally included. According to the analyses, the overall pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) estimated for CBCT were 94.6% (95% CI: 90.2-97.1; I2 = 55.9%, p = 0.026), 91.2% (95% CI: 81.7-96.0; I2 = 81.6%, p < 0.001), 93.0% (95% CI: 87.4-96.2; I2 = 56.5%, p = 0.024), and 92.3% (95% CI: 82.3-96.8; I2 = 86.4%, p < 0.001), respectively. The overall pooled sensitivity, specificity, PPV, and NPV of digital radiography were 61.0% (95% CI: 38.3-79.8; I2 = 94.4%, p < 0.001), 97.3% (95% CI: 85.6-99.5; I2 = 86.7%, p < 0.001), 98.3% (95% CI: 92.0-99.6; I2 = 74.4%, p = 0.002), and 41.6% (95% CI: 28.0-56.6; I2 = 89.5%, p < 0.001), respectively. Conclusions: CBCT imaging has excellent diagnostic accuracy in AP prediction. Also, CBCT has better discriminant test performance for AP than digital radiography.
