Development and validation of a polyfit approach for assessing alveolar bone loss using panoramic radiography.

Abstract

Background: Panoramic radiographs (PAN) are one of the most common diagnostic tools in clinical practice. Periodontal disease, the second most prevalent oral disease, significantly impacts patients' quality of life. However, there is currently no standardized and quantitative image analysis method for periodontal diagnosis. This study aims to estimate alveolar bone loss in six sextants of the mouth using the Polyfit approach on panoramic radiography. This approach utilizes ratio and proportional measurements based on fixed anatomical points to improve the accuracy of assessing bone loss.

Methods: In this retrospective clinical study, we assessed alveolar bone loss (ABL) in 290 subjects. The subjects were divided into two groups, the resorption group (abbreviated to ABL) and non-resorption group (abbreviated to non-ABL), based on the presence of any ABL sextants. Each tooth was manually marked with reference anatomical landmarks using Anaconda-Labelme 5.2.1 software. To evaluate the proportionate bone resorption for each tooth, we employed the PAN-POL model based on the polyfit function to quantify bone loss across six dental sextants and the entire dental arch. For the reliability of measurements, Cone Beam Computed Tomography (CBCT) data from 30 patients were selected. Measurements were conducted in Mimics 21.0 and compared with the model's results to validate the ABL assessment. An independent sample t-test or the intergroup rank-sum test was used to evaluate the difference between resorption data from both classification methods, and ABL and non-ABL groups in each classification. Pearson's correlation analysis and linear regression analysis were used to test and verify the correlation between CBCT and panoramic radiography. P values of > 0.05 were considered not statistically significant.

Results: The PAN-POL model demonstrated effective differentiation between resorption and non-resorption groups, and the groups based on two classification achieving statistical significance (P < 0.05), and the ratio results were consistent with those from CBCT (P > 0.05), indicating no significant difference. The Intraclass Correlation Coefficient (ICC) results for reliability testing among two experts for both PAN and CBCT were steadily 0.83 ± 0.06 and 0.93 ± 0.06 (ICC>0.75).

Conclusion: In this study, the PAN-POL model accurately measured ABL in panoramic images by incorporating standard anatomical landmarks. This model aids in Periodontal Screening and Recording, serving as a novel, valuable and intuitive tool for initial periodontal diagnosis.