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First Standard Quantification of Ultrasound Attenuation in Healthy Periodontal Soft Tissues In Vivo
Daria Poul1, Amanda Rodriguez Betancourt2, Ankita Samal3
1Department of Radiology, University of Michigan, Ann Arbor, MI, USA.
Objective:
Periodontal diseases affect 46% of adults aged ≥30 years in the United States, yet current clinical diagnostic approaches are subjective, semi-quantitative and late-stage indicators. This gap highlights a critical unmet need for alternative biomarkers. Ultrasonography is emerging to fill this gap as a surrogate for non-invasive and quantitative assessments of oral diseases. This study presents the first quantification of the ultrasound attenuation coefficient slope (ACS) as a key acoustic property and potential biomarker of oral tissues, using standard techniques.
Methods:
In a swine cohort (N = 10), we characterized the high-frequency (24 MHz) ACSs of healthy periodontal tissues (gingiva) in vivo using the spectral difference method. First, we validated the technique using custom tissue-mimicking phantoms with known ACSs. Five interproximal oral sites from each of the oral quadrants were enrolled and imaged: Premolar 3 - Mesial, Premolar 3 - Distal, Premolar 4 - Distal, Molar 1 - Distal and Molar 2 - Distal. A total of 162 oral sites were analyzed after applying exclusion criteria.
Results:
The respective median (first quartile|third quartile) ACSs for the five oral sites were 1.66 (1.25|1.99), 1.37 (1.06|1.64), 0.99 (0.8|1.25), 1.08 (0.89|1.47) and 1.28 (0.94|1.24) dB/MHz.cm. The gingival ACS mean at Premolar 3 - Mesial was significantly higher than any other oral site (p ≤ 0.05), while the rest of the sites showed a non-significant difference in their means. The average ACS was 1.17 (±0.48) dB/MHz.cm across non-significant oral sites.
Conclusion:
The high-frequency ultrasound ACSs of periodontal soft tissues were quantified in vivo using standardized techniques. This work not only characterizes an important acoustic property of oral tissues for the first time, but also contributes to the future development of quantitative ultrasound biomarkers for dental healthcare that rely on attenuation knowledge.