High-frequency intraoral ultrasonography for periodontal tissue characterization: a pilot study exploring echogenic...

To assess the feasibility and diagnostic potential of high-frequency intraoral ultrasonography for the real-time evaluation and characterization of periodontal tissues, including tissue echogenicity under both healthy and inflammatory conditions. Building on our prior preclinical validation of ultrasound for pocket depth measurement in a porcine model, this pilot study provides the first human application, focusing on a novel echogenicity-based 'atlas' for differentiating healthy and inflammatory periodontal tissues.

This prospective single-center pilot study included 13 patients diagnosed with periodontitis. Each participant underwent a standardized examination combining high frequency ultrasonographic imaging (20 MHz). A total of 1,987 ultrasonic ultrasonography measurements were recorded. Ultrasonographic images were analyzed using ImageJ to assess the mean and standard deviation of pixel intensity across several periodontal tissue types. Statistical analyses included Kruskal-Wallis testing, linear discriminant analysis (LDA), and K-means clustering to explore echogenicity-based tissue differentiation.

Ultrasound imaging enabled visualization of periodontal structures (enamel, cementum, alveolar bone, connective tissue, inflammatory tissue). Mean echogenicity values differed significantly across tissue types (p < 0.001), with enamel showing the highest mean pixel intensity (200 ± 15) and inflammatory tissue the lowest (50 ± 10). LDA achieved partial tissue separation, while K-means clustering identified six distinct echogenicity-based clusters. Real-time imaging detected subgingival calculus and deep tissue inflammation in 8 of 13 patients.

High-frequency intraoral ultrasonography is a feasible, non-invasive method for real-time periodontal tissue characterization. Echogenicity provides a robust marker for tissue differentiation and inflammation detection, but further studies with larger cohorts are needed to validate its clinical utility and automate diagnostic processes.

The study was approved by the Institutional Ethics Committee (Approval No. 22.04642.000161) and registered on the International Clinical Trials Registry Platform (ICTRP) under the identifier NCT05809427 (07/07/2023).