AUTHOR=Sabharwal Amarpreet , Kavthekar Neil , Miecznikowski Jeffrey , Glogauer Michael , Maddi Abhiram , Sarder Pinaki TITLE=Integrating Image Analysis and Dental Radiography for Periodontal and Peri-Implant Diagnosis JOURNAL=Frontiers in Dental Medicine VOLUME=Volume 3 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/dental-medicine/articles/10.3389/fdmed.2022.840963 DOI=10.3389/fdmed.2022.840963 ISSN=2673-4915 ABSTRACT=The recent change in classification of periodontal and peri-implant diseases includes objective evaluation of intra-oral radiographs and quantification of bone loss for disease staging and grading. Progression of periodontal disease requires standardized deduction of bone loss in a longitudinal manner, and its interpretation as a percentage of bone loss in relation to tooth root and as a function of the patient's age. Similarly, bone loss around dental implants, after accounting for initial remodeling, is central for determining diagnosis, severity and progression of peri-implantitis. Additionally, bone gain secondary to periodontal regeneration can be measured using standardized dental radiography techniques and compared to baseline morphology to determine treatment success. Since treatment outcomes are central to patient engagement, computational annotation of treatment-related improvements in radiographic images can yield powerful mechanisms for communication. Computational image analysis, including machine learning (ML), has potential to develop quantitative measures of tooth, implant, and bone volumes, and predict disease progression. The developed algorithms need to be standardized while considering pre- and post-analytical factors for successful translation to clinic. This review will discuss general and radiographic criteria for periodontal and peri-implant diagnosis, staging and grading. Additionally, machine learning algorithms, their ease of use and potential for assisted diagnosis will be discussed in the context of dental radiographic image analysis for periodontitis and peri-implantitis diagnosis.