{"title":"PerioAI: A digital system for periodontal disease diagnosis from an intra-oral scan and cone-beam CT image.","authors":"Minhui Tan, Zhiming Cui, Yuan Li, Yu Fang, Lanzhuju Mei, Yue Zhao, Xinyu Wu, Hongchang Lai, Maurizio S Tonetti, Dinggang Shen","doi":"10.1016/j.xcrm.2025.102186","DOIUrl":null,"url":null,"abstract":"<p><p>Periodontal disease diagnosis and treatment planning are critical for preventing bone and tooth loss. Clinically, dentists manually measure periodontal pocket depth with probes while integrating bone structure from imaging to assess periodontal status, a process that is subjective, invasive, and cognitively burdensome. Here, we propose PerioAI, an accurate, automatic, and non-invasive system that directly measures the gingiva-bone distance (GBD) and provides soft and hard tissue information digitally. PerioAI is a full-stack process comprising four key components: intra-oral scan (IOS) segmentation, cone-beam computed tomography (CBCT) image segmentation, multimodal data fusion, and digital probing measurement. We evaluated PerioAI on multicenter cohorts comprising 2,507 patients. Outstanding IOS and CBCT segmentation performances ensure accuracy throughout the full-stack process. Moreover, digital probing achieves remarkable precision with only 0.040mm error. This approach has the potential to substantially improve clinical workflows in periodontal disease management, offering a more precise, patient-friendly method for diagnosis and treatment decision-making.</p>","PeriodicalId":9822,"journal":{"name":"Cell Reports Medicine","volume":"6 6","pages":"102186"},"PeriodicalIF":11.7000,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Reports Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.xcrm.2025.102186","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Periodontal disease diagnosis and treatment planning are critical for preventing bone and tooth loss. Clinically, dentists manually measure periodontal pocket depth with probes while integrating bone structure from imaging to assess periodontal status, a process that is subjective, invasive, and cognitively burdensome. Here, we propose PerioAI, an accurate, automatic, and non-invasive system that directly measures the gingiva-bone distance (GBD) and provides soft and hard tissue information digitally. PerioAI is a full-stack process comprising four key components: intra-oral scan (IOS) segmentation, cone-beam computed tomography (CBCT) image segmentation, multimodal data fusion, and digital probing measurement. We evaluated PerioAI on multicenter cohorts comprising 2,507 patients. Outstanding IOS and CBCT segmentation performances ensure accuracy throughout the full-stack process. Moreover, digital probing achieves remarkable precision with only 0.040mm error. This approach has the potential to substantially improve clinical workflows in periodontal disease management, offering a more precise, patient-friendly method for diagnosis and treatment decision-making.
Cell Reports MedicineBiochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
15.00
自引率
1.40%
发文量
231
审稿时长
40 days
期刊介绍:
Cell Reports Medicine is an esteemed open-access journal by Cell Press that publishes groundbreaking research in translational and clinical biomedical sciences, influencing human health and medicine.
Our journal ensures wide visibility and accessibility, reaching scientists and clinicians across various medical disciplines. We publish original research that spans from intriguing human biology concepts to all aspects of clinical work. We encourage submissions that introduce innovative ideas, forging new paths in clinical research and practice. We also welcome studies that provide vital information, enhancing our understanding of current standards of care in diagnosis, treatment, and prognosis. This encompasses translational studies, clinical trials (including long-term follow-ups), genomics, biomarker discovery, and technological advancements that contribute to diagnostics, treatment, and healthcare. Additionally, studies based on vertebrate model organisms are within the scope of the journal, as long as they directly relate to human health and disease.