Diagnostic Accuracy of Deep Learning for the Prediction of Osteoporosis Using Plain X-rays: A Systematic Review and Meta-Analysis

Tzu Yun Yen, Chan Shien Ho, Yueh Peng Chen, Yu-Cheng Pei*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations

Abstract

(1) Background: This meta-analysis assessed the diagnostic accuracy of deep learning model-based osteoporosis prediction using plain X-ray images. (2) Methods: We searched PubMed, Web of Science, SCOPUS, and Google Scholar from no set beginning date to 28 February 2023, for eligible studies that applied deep learning methods for diagnosing osteoporosis using X-ray images. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. The area under the receiver operating characteristic curve (AUROC) was used to quantify the predictive performance. Subgroup, meta-regression, and sensitivity analyses were performed to identify the potential sources of study heterogeneity. (3) Results: Six studies were included; the pooled AUROC, sensitivity, and specificity were 0.88 (95% confidence interval [CI] 0.85–0.91), 0.81 (95% CI 0.78–0.84), and 0.87 (95% CI 0.81–0.92), respectively, indicating good performance. Moderate heterogeneity was observed. Mega-regression and subgroup analyses were not performed due to the limited number of studies included. (4) Conclusion: Deep learning methods effectively extract bone density information from plain radiographs, highlighting their potential for opportunistic screening. Nevertheless, additional prospective multicenter studies involving diverse patient populations are required to confirm the applicability of this novel technique.

Original languageEnglish
Article number207
JournalDiagnostics
Volume14
Issue number2
DOIs
StatePublished - 18 01 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

  • X-ray
  • bone mineral density
  • convolutional neural network
  • deep learning
  • osteopenia
  • osteoporosis

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