Keywords: Diagnosis/Prediction, Diagnosis/Prediction
Motivation: In recent years, artificial intelligence (AI) technology has emerged as a promising adjunctive tool for radiologists in detecting Bone metastasis (BM).
Goal(s): To explore the diagnostic performance of AI in detecting BM.
Approach: Two reviewers conducted a comprehensive search in eight databases to identify eligible articles from inception to July 2023. A meta-analysis employing a hierarchical model was performed to calculate pooled SE, SP, AUC, PLR, NLR, and DOR.
Results: We included 17 articles and extracted 70 lists of columns from 13 articles with a pooled SE of 0.89 (0.82-0.94), a pooled SP of 0.89 (0.83-0.93), a pooled AUC of 0.95 (0.93-0.97).
Impact: The present meta-analysis demonstrated the substantial diagnostic value of AI in identifying BM, with CT exhibiting superior performance compared to MR. However, further large-scale prospective studies are needed to validate the clinical utility of AI in managing BM.
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