{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T06:38:15Z","timestamp":1791527895320,"version":"4.3.4"},"reference-count":41,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:00:00Z","timestamp":1739923200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Our study aimed to determine the accuracy of the artificial intelligence-based Diagnocat system (DC) in detecting periapical lesions (PL) on panoramic radiographs (PRs). Methods: 616 teeth were selected from 357 panoramic radiographs, including 308 teeth with clearly visible periapical radiolucency and 308 without any periapical lesion. Three groups were generated: teeth with radiographic signs of caries (Group 1), teeth with coronal restoration (Group 2), and teeth with root canal filling (Group 3). The PRs were uploaded to the Diagnocat system for evaluation. The performance of the convolutional neural network in detecting PLs was assessed by its sensitivity, specificity, and positive and negative predictive values, as well as the diagnostic accuracy value. We investigated the possible effect of the palatoglossal air space (PGAS) on the evaluation of the AI tool. Results: DC identified periapical lesions in 240 (77.9%) cases out of the 308 teeth with PL and detected no PL in 68 (22.1%) teeth with PL. The AI-based system detected no PL in any of the groups without PL. The overall sensitivity, specificity, and diagnostic accuracy of DC were 0.78, 1.00, and 0.89, respectively. Considering these parameters for each group, Group 2 showed the highest values at 0.84, 1.00, and 0.95, respectively. Fisher\u2019s Exact test showed that PGAS does not significantly affect (p = 1) the detection of PL in the upper teeth. The AI-based system showed lower probability values for detecting PL in the case of central incisors, wisdom teeth, and canines. The sensitivity and diagnostic accuracy of DC for detecting PL on canines showed lower values at 0.27 and 0.64, respectively. Conclusions: The CNN-based Diagnocat system can support the diagnosis of PL on PRs and serves as a decision-support tool during radiographic assessments.<\/jats:p>","DOI":"10.3390\/diagnostics15040510","type":"journal-article","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T11:49:27Z","timestamp":1739965767000},"page":"510","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Deep Learning-Based Periapical Lesion Detection on Panoramic Radiographs"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2718-451X","authenticated-orcid":false,"given":"Viktor","family":"Szab\u00f3","sequence":"first","affiliation":[{"name":"Department of Oral Diagnostics, Faculty of Dentistry, Semmelweis University, 47 Szentkiralyi Str., 1088 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6768-0176","authenticated-orcid":false,"given":"Kaan","family":"Orhan","sequence":"additional","affiliation":[{"name":"Department of Oral Diagnostics, Faculty of Dentistry, Semmelweis University, 47 Szentkiralyi Str., 1088 Budapest, Hungary"},{"name":"Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Ankara University, Ankara 06100, Turkey"},{"name":"Medical Design Application, and Research Center (MEDITAM), Ankara University, Ankara 06100, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9530-7926","authenticated-orcid":false,"given":"Csaba","family":"Dob\u00f3-Nagy","sequence":"additional","affiliation":[{"name":"Department of Oral Diagnostics, Faculty of Dentistry, Semmelweis University, 47 Szentkiralyi Str., 1088 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9687-3556","authenticated-orcid":false,"given":"D\u00e1niel S\u00e1ndor","family":"Veres","sequence":"additional","affiliation":[{"name":"Department of Biophysics and Radiation Biology, Semmelweis University, 1088 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Manulis","sequence":"additional","affiliation":[{"name":"Diagnocat Inc., San Francisco, CA 94102, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matvey","family":"Ezhov","sequence":"additional","affiliation":[{"name":"Diagnocat Inc., San Francisco, CA 94102, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Sanders","sequence":"additional","affiliation":[{"name":"Diagnocat Inc., San Francisco, CA 94102, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5933-3956","authenticated-orcid":false,"given":"Bence Tam\u00e1s","family":"Szab\u00f3","sequence":"additional","affiliation":[{"name":"Department of Oral Diagnostics, Faculty of Dentistry, Semmelweis University, 47 Szentkiralyi Str., 1088 Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Erdelyi, R.A., Duma, V.F., Sinescu, C., Dobre, G.M., Bradu, A., and Podoleanu, A. 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