Periodontal Soft Tissue Characterization using Quantitative Ultrasound
Wednesday, April 10, 2024
8:34am – 8:41am
Location: 412
Authors: Sedigheh Poul, University of Michigan Amanda Rodriguez Betancourt, School of Dentistry, University of Michigan Ankita Samal, University of Iowa,College of Dentistry and Dental Clinics Hsun-Liang Chan, The Ohio State University Oliver Kripfgans, University of Michigan ,
Periodontal diseases are reported to affect approximately 42% of the adult populations in the United States. These diseases concern different components of oral soft tissues that support and surround teeth such as gingiva, alveolar mucosa, and alveolar bone. Among other diagnostic modalities for clinical assessments of periodontal soft tissues, bleeding on probing (invasive) and visual observation are two standard traditional methods for predicting inflammation, which are both qualitative and subjective. Characterizations of oral soft tissues (alveolar mucosa and gingiva) in ultrasound scans from the QUS approaches were investigated in this study. Employing the two-parameter Burr ultrasound speckle statistics model showed that the power-law and scale factor parameters are sensitive to differentiate healthy gingivae and alveolar mucosa (in vivo swine study). Thus, it is suggested that the two-parameter Burr model may have the potential to serve as an augmented tool for periodontal soft tissue characterization.