Ultrasound Imaging: Advancing the Diagnosis of Periodontal Disease

Abstract

<b>Objectives</b>: 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. <b>Materials and Methods</b>: Thirteen patients with periodontitis underwent ultrasonic probing with an AI engine for automated PPD measurements, followed by routine manual probing. <b>Results</b>: 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. <b>Discussion</b>: Ultrasound imaging offers non-invasive, real-time visualization of periodontal structures, but AI accuracy requires further training to address image artifacts and clinical variability. <b>Conclusions</b>: 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. <b>Clinical Relevance</b>: This technology could enhance patient comfort and enable frequent monitoring, pending improvements in AI reliability.

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