Abstract
Introduction
The aim of this systematic review and meta-analysis was to investigate the overall
accuracy of deep learning models in detecting periapical (PA) radiolucent lesions
in dental radiographs, when compared to expert clinicians.
Methods
Electronic databases of Medline (via PubMed), Embase (via Ovid), Scopus, Google Scholar,
and arXiv were searched. Quality of eligible studies was assessed by using Quality
Assessment and Diagnostic Accuracy Tool-2. Quantitative analyses were conducted using
hierarchical logistic regression for meta-analyses on diagnostic accuracy. Subgroup
analyses on different image modalities (PA radiographs, panoramic radiographs, and
cone beam computed tomographic images) and on different deep learning tasks (classification,
segmentation, object detection) were conducted. Certainty of evidence was assessed
by using Grading of Recommendations Assessment, Development, and Evaluation system.
Results
A total of 932 studies were screened. Eighteen studies were included in the systematic
review, out of which 6 studies were selected for quantitative analyses. Six studies
had low risk of bias. Twelve studies had risk of bias. Pooled sensitivity, specificity,
positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of
included studies (all image modalities; all tasks) were 0.925 (95% confidence interval
[CI], 0.862–0.960), 0.852 (95% CI, 0.810–0.885), 6.261 (95% CI, 4.717–8.311), 0.087
(95% CI, 0.045–0.168), and 71.692 (95% CI, 29.957-171.565), respectively. No publication
bias was detected (Egger's test, P = .82). Grading of Recommendations Assessment, Development and Evaluationshowed a
“high” certainty of evidence for the studies included in the meta-analyses.
Conclusion
Compared to expert clinicians, deep learning showed highly accurate results in detecting
PA radiolucent lesions in dental radiographs. Most studies had risk of bias. There
was a lack of prospective studies.
Key Words
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Article info
Publication history
Published online: December 20, 2022
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© 2022 American Association of Endodontists.
