Abstract
Background & Aim
Plaque-induced gingivitis, if not treated, may advance to periodontitis, which is one of the major causes of tooth loss. Early diagnosis and intervention are needed for the prevention of periodontitis. Current diagnostic methods largely rely on clinical and radiographic parameters that reflect the sequelae of the disease instead of the ongoing inflammatory process. Manual periodontal probing, which is the current standard method for measuring clinical attachment loss (CAL) and periodontal pocket depth (PPD), has some limitations. The aim of this research was to evaluate the utility of ultrasound and digital colour analysis as non-invasive tools to monitor periodontal tissue changes during the induction and resolution of experimental gingivitis. The study also sought to explore correlations between ultrasound parameters, colorimetric measurements, and conventional clinical indices to assess their potential in periodontal diagnostics.
Methods
Nineteen undergraduate dental students from the University of Otago participated in the study. Customised stents were placed on their maxillary left posterior teeth (teeth 24, 25, and 26) for 21 days to induce experimental gingivitis. Weekly ultrasound measurements were taken using the UltraD3 (Periomedic, Tauranga, New Zealand) ultrasound device, alongside clinical indices such as the Plaque Index (PI), Gingival Index (GI), Gingival Bleeding Index (GBI), CAL, and PPD. Colorimetric measurements were recorded at weeks 1, 4, and 7. Spearman’s correlation coefficient was used to analyse relationships between ultrasound/colorimetric measurements and clinical indices. Kruskal-Wallis tests with Dunn’s post hoc comparisons assessed the ability of ultrasound parameters to distinguish clinical severity. Receiver Operating Characteristic (ROC) analysis evaluated the diagnostic accuracy.
Results
Significant differences were observed between the mean PI, GI, and GBI scores of test and control teeth across weeks 1, 2, and 3 (p < 0.0001). Ultrasound parameters exhibited weak to moderate correlations with clinical indices, particularly during the resolution phase (r = -0.25 to 0.35), suggesting greater sensitivity to tissue recovery than acute inflammation. Colorimetric analysis showed stronger correlations with CAL (mean |r| = 0.132), especially in buccal sites, indicating its potential as an indirect marker of attachment loss. ROC analysis revealed poor to moderate diagnostic accuracy for ultrasound (AUC: 0.45 – 0.55). Multivariate analysis improved diagnostic performance slightly, with AUC values reaching 0.731 for tracking of disease resolution.
Conclusions
The novel UltraD3 device marks a promising advancement in periodontal diagnostics by using an ultrasound to assess real-time gingival elasticity. Its non-invasive nature reduced patient discomfort and minimised examiner variability, offering several advantages over traditional probing. However, the limited sensitivity to inflammation and lack of standardised thresholds currently restrict widespread clinical adoption. Future improvements, such as reducing acquisition time, refining the probe tip design, and standardisation, may enhance its clinical effectiveness and accuracy.