Ultrasound Characterization of Oral Soft Tissues in vivo Using the Burr Speckle Model

Abstract

Periodontal diseases, reportedly affect 4 out of 10 adults in the USA. The standard of care for clinical assessments of these diseases is invasive, subjective and semi-qualitative. Thus, research on proposing alternate noninvasive modalities for clinical assessments of periodontal tissues is crucial. Quantitative Ultrasound (QUS) has shown promises in noninvasive assessments of various diseases in soft biological tissues; however, it has not been employed in periodontology. Here as the first step, we focused on QUS-based characterization of two very adjacent oral soft tissues of alveolar mucosa and attached gingiva in an in vivo animal study. We investigated first order ultrasonic speckle statistics using the two-parameter Burr model (b and l). Our QUS analysis was compared with the Masson$'$s Trichrome histology images of the two oral tissue types quantitatively using the RGB color thresholding. QUS study included 10 swine and US scanning was performed at the first and second molars, resulting in 80 scans. US scan data was acquired at the frequency of 24 MHz. Results at both oral sites (molar 1 and molar 2) showed that difference between the two tissue types using Burr parameters were statistically significant (p$<0.0001$). The average Burr b was reported higher in attached gingiva while the average Burr l was lower compared to mucosa. The color thresholding of these images confirmed that the percent of blue, which stains collagenous regions, was at least two times higher in gingiva compared with alveolar mucosa. It was suggested that the elevated Burr b (related to potential scatterer densities) in gingiva could be aligned with findings from histology. This study showed a promising potential of QUS for clinical assessment of periodontal soft tissues.