TY - GEN
T1 - Reducing the Degrees of Freedom for Simultaneous Estimation of Ultrasonic Attenuation and Backscatter Coefficients
T2 - 2023 IEEE International Ultrasonics Symposium, IUS 2023
AU - Timaná, José
AU - Chahuara, Hector
AU - Basavarajappa, Lokesh
AU - Basarab, Adrian
AU - Hoyt, Kenneth
AU - Lavarello, Roberto
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Liver steatosis, a type of fatty liver disease, has been gaining significant attention in the medical field due to its global prevalence. Currently, large-scale evaluations of liver steatosis are hindered by the variability of the available non-invasive imaging tools. While conventional ultrasound often serves as the primary imaging modality for liver assessments, its accuracy is limited by its qualitative nature and operator dependency. To address these challenges, this study introduces a novel approach that reduces the degrees of freedom in simultaneously estimating ultrasonic backscatter (BSC) and attenuation (AC) coefficients. By exploiting the Rayleigh scattering behavior where the BSC trend remains approximately constant at lower frequencies, our method focuses on estimating just two parameters, offering increased precision. Ultrasound measurements were performed on a cohort of 29 Sprague-Dawley rats subjected to either a control or methionine and choline deficient diet. Postimaging, histological evaluations were conducted. Using support vector machine classification with leave-one-out cross-validation, our approach utilizing two degrees of freedom outperformed the three degrees of freedom method, achieving an accuracy of 96.6% compared to 72.4% in detecting liver steatosis. The findings indicate that this new method can significantly reduce estimation variability and enhance liver steatosis classification, paving the way for more consistent and reliable non-invasive liver assessments.
AB - Liver steatosis, a type of fatty liver disease, has been gaining significant attention in the medical field due to its global prevalence. Currently, large-scale evaluations of liver steatosis are hindered by the variability of the available non-invasive imaging tools. While conventional ultrasound often serves as the primary imaging modality for liver assessments, its accuracy is limited by its qualitative nature and operator dependency. To address these challenges, this study introduces a novel approach that reduces the degrees of freedom in simultaneously estimating ultrasonic backscatter (BSC) and attenuation (AC) coefficients. By exploiting the Rayleigh scattering behavior where the BSC trend remains approximately constant at lower frequencies, our method focuses on estimating just two parameters, offering increased precision. Ultrasound measurements were performed on a cohort of 29 Sprague-Dawley rats subjected to either a control or methionine and choline deficient diet. Postimaging, histological evaluations were conducted. Using support vector machine classification with leave-one-out cross-validation, our approach utilizing two degrees of freedom outperformed the three degrees of freedom method, achieving an accuracy of 96.6% compared to 72.4% in detecting liver steatosis. The findings indicate that this new method can significantly reduce estimation variability and enhance liver steatosis classification, paving the way for more consistent and reliable non-invasive liver assessments.
KW - Quantitative ultrasound
KW - attenuation coefficient
KW - backscatter coefficient
KW - liver steatosis
KW - murine animal model
KW - rayleigh scattering
KW - tissue characterization
UR - http://www.scopus.com/inward/record.url?scp=85178621852&partnerID=8YFLogxK
U2 - 10.1109/IUS51837.2023.10307954
DO - 10.1109/IUS51837.2023.10307954
M3 - Conference contribution
AN - SCOPUS:85178621852
T3 - IEEE International Ultrasonics Symposium, IUS
BT - IUS 2023 - IEEE International Ultrasonics Symposium, Proceedings
PB - IEEE Computer Society
Y2 - 3 September 2023 through 8 September 2023
ER -