PerioAI: A digital system for periodontal disease diagnosis from an intra-oral scan and cone-beam CT image.

IF 11.7 1区 医学 Q1 CELL BIOLOGY
Minhui Tan, Zhiming Cui, Yuan Li, Yu Fang, Lanzhuju Mei, Yue Zhao, Xinyu Wu, Hongchang Lai, Maurizio S Tonetti, Dinggang Shen
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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.

牙周病:一种通过口腔内扫描和锥形束CT图像诊断牙周病的数字系统。
牙周病的诊断和治疗计划是预防骨和牙齿脱落的关键。临床上,牙医用探针人工测量牙周袋深度,同时结合影像学的骨结构来评估牙周状态,这是一个主观的、侵入性的和认知负担的过程。本文提出了一种精确、自动、无创的直接测量龈骨距离(GBD)并以数字方式提供软硬组织信息的PerioAI系统。PerioAI是一个全栈过程,包括四个关键组件:口腔内扫描(IOS)分割、锥形束计算机断层扫描(CBCT)图像分割、多模态数据融合和数字探测测量。我们在包括2507名患者的多中心队列中评估了PerioAI。出色的IOS和CBCT分割性能确保了整个全栈过程的准确性。此外,数字探测精度显著,误差仅为0.040mm。这种方法有可能大大改善牙周病管理的临床工作流程,为诊断和治疗决策提供更精确,患者友好的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Reports Medicine
Cell Reports Medicine Biochemistry, 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.
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