Health Technology/clinical-trials

AI-Powered Detection of Periapical Lesions on Panoramic Radiographs: French Multicentre Study Seeks to Redefine Diagnostic Thresholds in Endodontic Imaging

247 Health News Editorial

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9 July 2026

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5 min read

·clinical-trials

A French multicentre study is enrolling 2,000 patients to validate a deep learning algorithm capable of detecting periapical lesions on dental panoramic radiographs, using CBCT as the reference standard. With panoramic imaging detecting as few as 20% of periapical lesions compared to 69% for CBCT, an accurate AI-assisted tool could transform diagnostic workflows in general dental practice worldwide.

Originally reported by ClinicalTrials.gov

References

  1. 1.Centre Hospitalier Régional Metz-Thionville. (2023). Detection of periapical lesions on dental panoramic images based on artificial intelligence using cone beam computed tomography (NCT05888935). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT05888935
  2. 2.Leonardi Dutra, K., Haas, L., Porporatti, A. L., Flores-Mir, C., Nascimento Santos, J., Mezzomo, L. A., Corrêa, M., & De Luca Canto, G. (2016). Diagnostic accuracy of cone-beam computed tomography and conventional radiography on apical periodontitis: A systematic review and meta-analysis. Journal of Endodontics, 42(3), 356–364. https://doi.org/10.1016/j.joen.2015.12.015
  3. 3.Ekert, T., Krois, J., Meinhold, L., Elhennawy, K., Emara, R., Golla, T., & Schwendicke, F. (2019). Deep learning for the radiographic detection of apical lesions. Journal of Endodontics, 45(7), 917–922. https://doi.org/10.1016/j.joen.2019.03.016
  4. 4.Bender, I. B., & Seltzer, S. (2003). Roentgenographic and direct observation of experimental lesions in bone: I and II. Journal of Endodontics, 29(11), 702–706. https://doi.org/10.1097/00004770-200301000-00002
  5. 5.Pak, J. G., Fayazi, S., & White, S. N. (2012). Prevalence of periapical radiolucency and root canal treatment: A systematic review of cross-sectional studies. Journal of Endodontics, 38(9), 1170–1176. https://doi.org/10.1016/j.joen.2011.10.020
  6. 6.Schwendicke, F., Golla, T., Dreher, M., & Krois, J. (2019). Convolutional neural network for detecting jaw lesions in panoramic radiographs. Journal of Dentistry, 92, 103099. https://doi.org/10.1016/j.jdent.2019.103099
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