Rochefort Gaël Y, Denis Frédéric, Renaud Matthieu
Faculty of Odontology, Tours University, 37000 Tours, France.
Department of Medicine and Bucco-Dental Surgery, Tours University Hospital, 37044 Tours, France.
Dent J (Basel). 2025 Jul 29;13(8):349. doi: 10.3390/dj13080349.
: This pilot study evaluates the correlation between periodontal pocket depth (PPD) measurements obtained by manual probing and those derived from an AI-coupled ultrasound imaging device in periodontitis patients. : Thirteen patients with periodontitis underwent ultrasonic probing with an AI engine for automated PPD measurements, followed by routine manual probing. : A total of 2088 manual and 1987 AI-based PPD measurements were collected. The mean PPD was 4.2 mm (range: 2-8 mm) for manual probing and 4.5 mm (range: 2-9 mm) for AI-based ultrasound, with a Pearson correlation coefficient of 0.68 (95% CI: 0.62-0.73). Discrepancies were noted in cases with inflammation or calculus. AI struggled to differentiate pocket depths in complex clinical scenarios. : Ultrasound imaging offers non-invasive, real-time visualization of periodontal structures, but AI accuracy requires further training to address image artifacts and clinical variability. : The ultrasound device shows promise for non-invasive periodontal diagnostics but is not yet a direct alternative to manual probing. Further AI optimization and validation are needed. : This technology could enhance patient comfort and enable frequent monitoring, pending improvements in AI reliability.
本初步研究评估了牙周炎患者中通过手动探查获得的牙周袋深度（PPD）测量值与源自人工智能耦合超声成像设备的测量值之间的相关性。13名牙周炎患者使用人工智能引擎进行超声探查以自动测量PPD，随后进行常规手动探查。共收集了2088次手动PPD测量值和1987次基于人工智能的PPD测量值。手动探查的平均PPD为4.2毫米（范围：2 - 8毫米），基于人工智能的超声测量为4.5毫米（范围：2 - 9毫米），皮尔逊相关系数为0.68（95%置信区间：0.62 - 0.73）。在有炎症或牙结石的病例中发现了差异。在复杂的临床场景中，人工智能难以区分牙周袋深度。超声成像可提供牙周结构的非侵入性实时可视化，但人工智能的准确性需要进一步训练以解决图像伪影和临床变异性问题。该超声设备在非侵入性牙周诊断方面显示出前景，但尚不能直接替代手动探查。需要进一步优化和验证人工智能。在人工智能可靠性得到改善之前，这项技术可以提高患者舒适度并实现频繁监测。
