Quantitative Ultrasound Perfusion Biomarker: Cross-Modality Validation with Laser Speckle Imaging
Abstract
Rationale and Objectives: Tooth extraction can cause alveolar bone resorption and variable healing despite socket preservation. Current perfusion assessment relies largely on visual evaluation, limiting objective monitoring of socket healing. We developed and validated a quantitative color flow ultrasound framework to reduce sensitivity to imaging settings and motion artifacts. Materials and Methods: Color flow ultrasound data were acquired longitudinally in 30 patients undergoing tooth extraction and grafting. Velocity- and power-weighted color pixel density (CPDvel and CPDpwr) were derived from complex-valued color flow (TRI) data at 0-1.5 mm beneath the epithelial surface. Gain robustness was assessed using a Quantitative Imaging Biomarker Alliance (QIBA) flow phantom. Concurrent laser speckle contrast imaging (LASCA) provided in vivo comparison. Results: Phantom velocity estimates remained stable across color gain settings of 20-100 a.u. at flow rates of 2, 4, 6, and 8 mL/s. Perfusion metrics decreased over approximately 2-30 weeks after extraction. Nonlinear fits yielded R2 values of 0.74 for CPDvel, 0.45 for CPDpwr, and 0.66 for LASCA. Exponential half-decay times were 60.3, 92.4, and 48.3 days, respectively, relative to the first post-extraction measurement. LASCA correlated linearly with ultrasound-derived velocity (R2 = 0.68) and power (R2 = 0.74; both p < 0.05). Conclusions: The framework supports noninvasive, quantitative monitoring of superficial perfusion during socket healing with reduced sensitivity to color gain. Direct analysis of TRI data provides depth-specific perfusion metrics and may improve consistency across imaging sessions. Further validation is needed to determine its ability to identify compromised healing and inform clinical decisions.
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BibTeX
@misc{tai2026quantitative,
title = {{Quantitative Ultrasound Perfusion Biomarker: Cross-Modality Validation with Laser Speckle Imaging}},
author = {Haowei Tai and Oscar Duran-Garnica and Karen Villarreal and Hsun-Liang Chan and Oliver D. Kripfgans},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.39069},
eprint = {2610.39069},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.39069},
}
RIS
TY - UNPB
TI - Quantitative Ultrasound Perfusion Biomarker: Cross-Modality Validation with Laser Speckle Imaging
AU - Haowei Tai
AU - Oscar Duran-Garnica
AU - Karen Villarreal
AU - Hsun-Liang Chan
AU - Oliver D. Kripfgans
PY - 2026
DA - 2026/10/29
PB - arXiv
DO - 10.48550/arxiv.2610.39069
UR - https://arxiv.org/abs/2610.39069
AB - Rationale and Objectives: Tooth extraction can cause alveolar bone resorption and variable healing despite socket preservation. Current perfusion assessment relies largely on visual evaluation, limiting objective monitoring of socket healing. We developed and validated a quantitative color flow ultrasound framework to reduce sensitivity to imaging settings and motion artifacts. Materials and Methods: Color flow ultrasound data were acquired longitudinally in 30 patients undergoing tooth extraction and grafting. Velocity- and power-weighted color pixel density (CPDvel and CPDpwr) were derived from complex-valued color flow (TRI) data at 0-1.5 mm beneath the epithelial surface. Gain robustness was assessed using a Quantitative Imaging Biomarker Alliance (QIBA) flow phantom. Concurrent laser speckle contrast imaging (LASCA) provided in vivo comparison. Results: Phantom velocity estimates remained stable across color gain settings of 20-100 a.u. at flow rates of 2, 4, 6, and 8 mL/s. Perfusion metrics decreased over approximately 2-30 weeks after extraction. Nonlinear fits yielded R2 values of 0.74 for CPDvel, 0.45 for CPDpwr, and 0.66 for LASCA. Exponential half-decay times were 60.3, 92.4, and 48.3 days, respectively, relative to the first post-extraction measurement. LASCA correlated linearly with ultrasound-derived velocity (R2 = 0.68) and power (R2 = 0.74; both p < 0.05). Conclusions: The framework supports noninvasive, quantitative monitoring of superficial perfusion during socket healing with reduced sensitivity to color gain. Direct analysis of TRI data provides depth-specific perfusion metrics and may improve consistency across imaging sessions. Further validation is needed to determine its ability to identify compromised healing and inform clinical decisions.
ER -