Quantitative Characterization of Tissue Microstructure in Concentrated Cell Pellet Biophantoms Based on the Structure Factor Model

被引:25
作者
Franceschini, Emilie [1 ]
de Monchy, Romain [1 ]
Mamou, Jonathan [2 ]
机构
[1] Aix Marseille Univ, Cent Marseille, LMA, CNRS,UPR 7051, F-13402 Marseille, France
[2] Riverside Res, FL Lizzi Ctr Biomed Engn, New York, NY 10038 USA
关键词
Backscatter coefficient; dense medium; Gaussian model; quantitative ultrasound; structure function; ultrasonic imaging; 3 SCATTERING MODELS; ULTRASONIC BACKSCATTER; SPECTRUM ANALYSIS; EX-VIVO; QUANTIFICATION; PARAMETERS; SPHERES; TUMORS;
D O I
10.1109/TUFFC.2016.2549273
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Quantitative ultrasound (QUS) methods based on the backscatter coefficient (BSC) are typically model-based. The BSC is estimated from experiments and is fit to a model. The fit parameters are often termed QUS estimates and are used to characterize the scattering properties of the tissue under investigation. Nevertheless, for physical interpretation of QUS estimates to be accurate, the scattering model chosen must also be accurate. The goal of this work was to investigate the use of the structure factor model (SFM) to take into account coherent scattering from high volume fractions of scatterers. The study focuses on comparing the performance of two sparse models (fluid-filled sphere and Gaussian) and one concentrated model (SFM) to estimate QUS parameters from simulations and cell pellet biophantoms with a range of scatterer volume fractions. Results demonstrated the superiority of the SFM for all investigated volume fractions (i.e., from 0.006 to 0.30). In particular, the sparse models underestimated scatterer size and overestimated acoustic concentration when the volume fraction was greater than 0.12. In addition, the SFM has the ability to provide the volume fraction and the relative impedance contrast (instead of only the acoustic concentration provided by the sparse models), which could have a great benefit for tissue characterization. This study demonstrates that the SFM could prove to be an invaluable tool for QUS and could help to more accurately characterize tissue from ultrasound measurements.
引用
收藏
页码:1321 / 1334
页数:14
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