Deep Learning Approach to Measure Alveolar Bone Loss After COVID-19

Severity of periodontal disease may be determined by measurement of alveolar crestal height (ACH) on dental bitewing radiographs; however, the prevailing method of assessment is through visualization which is time consuming and not a direct measure. The primary objective of this manuscript is to create and validate a deep learning technique for precise evaluation of alveolar bone loss in bitewing radiographs. Additionally, surveys were conducted with dental professionals to determine accuracy of visualized measures of ACH for severe periodontal disease versus the deep learning program and to determine the acceptability of utility of the program among diverse dental professionals. Lastly, the deep learning program was utilized in research to evaluate the role of COVID on periodontal disease through longitudinal measures of bitewing radiograph ACH from patients during the: "pre-pandemic" (Feb 2017 - Feb 2020) and "post-pandemic" (Feb 2020 - Feb 2023) periods. The pre-pandemic group had a mean percentage loss of ACH of -1.74 + 16.5%, representing a gain in alveolar bone. In contrast, the post-pandemic group had a gain in ACH of 2.46 + 14.6%, representing a loss in alveolar bone. There remained a trend for greater annualized percent change in ACH in the post-pandemic vs pre-pandemic group (1.33 + 11.9% vs -0.94 + 12.5%, p=0.07), after accounting for differences in duration between xrays. Overall, this study demonstrates the successful training and validation of a deep learning program for ACH measurement as well as its utility and acceptability among dental professionals for clinical and research. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by the Columbia Biomedical Engineering Technology Accelerator (BiomedX) Program. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the Columbia University International Review Board, reference number AAAT2272. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.