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Die Erkennung von Zahnpathologien auf apikalen Röntgenaufnahmen. Ergebnisse einer Reliabilitätsstudie
Die Erkennung von Zahnpathologien auf apikalen Röntgenaufnahmen. Ergebnisse einer Reliabilitätsstudie
The goal of the presented study was to illustrate the inter- and intra-examiner reliability of pathologies on apical radiographs and compare them with similar studies. Specifically, the differences between diagnostic categories, evaluation rounds and the professional experience of the examiner were studied to check for statistical relevance. For the detection of pathologies, variating Cohens Kappa (CK) values were recorded in the moderate to perfect range, indicating a significant difference in the assessment of the diagnostic categories and the experience of the examiner. In contrast, CK values were consistently in the perfect range regardless of the professional experience of the examiner and categories for the detection of restorative measures on periapical radiographs, as evidenced in the study by Wülk et al. (2023). Endo-perio-lesions had the best CK values of 0,840 CK and were thus rated most reliable, whereas periapical lesions and periodontal bone loss scored the least with CK values of 0,435 and 0,454 respectively. Additionally, the odds ratios (OR) indicate a large disparity between the experienced and less experienced examiners, while showing almost identical values across the evaluation rounds. The hypothesis that there is no difference in the reliability of assessment between diagnostic categories and the experience of examiners was therefore rejected in this study, while it was confirmed in the research by Wülk et al. (2023). A main driver for this discrepancy could be that pathologies are generally more difficult to assess in radiographs requiring a higher level of experience in the examiner than restorative measures. Differences between evaluation rounds were not detected in both studies, ensuring the replicability of the studies. The results suggest that enhanced university teaching is recommended to improve education and training programs for the detection of pathologies on apical radiographs, especially for periapical lesions and periodontal bone loss. Additional research on the quality of detection for additional diagnostic categories on apical radiographs, OPGs and bitewings is recommended to aid the identification and elimination of further uncertainties. The additional research should also address all potential weaknesses in radiological diagnostics to support automated and standardized results. With the rapid advancements in artificial intelligence (AI) use-cases in dentistry, the generation of high-quality data for AI models must be ensured.
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Meusburger, Theresa
2023
German
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Meusburger, Theresa (2023): Die Erkennung von Zahnpathologien auf apikalen Röntgenaufnahmen: Ergebnisse einer Reliabilitätsstudie. Dissertation, LMU München: Faculty of Medicine
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Abstract

The goal of the presented study was to illustrate the inter- and intra-examiner reliability of pathologies on apical radiographs and compare them with similar studies. Specifically, the differences between diagnostic categories, evaluation rounds and the professional experience of the examiner were studied to check for statistical relevance. For the detection of pathologies, variating Cohens Kappa (CK) values were recorded in the moderate to perfect range, indicating a significant difference in the assessment of the diagnostic categories and the experience of the examiner. In contrast, CK values were consistently in the perfect range regardless of the professional experience of the examiner and categories for the detection of restorative measures on periapical radiographs, as evidenced in the study by Wülk et al. (2023). Endo-perio-lesions had the best CK values of 0,840 CK and were thus rated most reliable, whereas periapical lesions and periodontal bone loss scored the least with CK values of 0,435 and 0,454 respectively. Additionally, the odds ratios (OR) indicate a large disparity between the experienced and less experienced examiners, while showing almost identical values across the evaluation rounds. The hypothesis that there is no difference in the reliability of assessment between diagnostic categories and the experience of examiners was therefore rejected in this study, while it was confirmed in the research by Wülk et al. (2023). A main driver for this discrepancy could be that pathologies are generally more difficult to assess in radiographs requiring a higher level of experience in the examiner than restorative measures. Differences between evaluation rounds were not detected in both studies, ensuring the replicability of the studies. The results suggest that enhanced university teaching is recommended to improve education and training programs for the detection of pathologies on apical radiographs, especially for periapical lesions and periodontal bone loss. Additional research on the quality of detection for additional diagnostic categories on apical radiographs, OPGs and bitewings is recommended to aid the identification and elimination of further uncertainties. The additional research should also address all potential weaknesses in radiological diagnostics to support automated and standardized results. With the rapid advancements in artificial intelligence (AI) use-cases in dentistry, the generation of high-quality data for AI models must be ensured.