Abstract
The aim of this study was to test the hypothesis that the Computer Aided UltraSound (CAUS) method developed by the authors [1-4] for the estimation of UltraSound Tissue Characteristics (UTC) parameters on transcutaneous (Transc) ultrasound (US) images can predict the liver fat content with similar accuracy and precision as with intraoperative (Intraop) US. A large animal study in post partum dairy cows (N=151) was performed to test these hypotheses. Five Transc B-Mode US liver image were acquired before surgery. During abomasal displacement surgery five Intraop US B-Mode liver images and a liver biopsy was taken. In liver tissue samples, triacylglycerol (TAG) content was measured by biochemical analysis. Firstly the equipment preset, which was kept fixed during whole study time, was carefully calibrated[5]. For the echo level calibration a TMP was used, and all UTC parameters were expressed relatively to those of the phantom. Prior to UTC parameters estimation several pre-processing steps were performed: Back-Scan Conversion (BSC); Look Up Table (LUT) correction; superficial tissue layers (Fat layer) attenuation correction and Automatic Gain Correction (AGC) were performed. Also several postprocessing steps were incorporated like: Automatic segmentation and residual attenuation correction were performed. Stepwise multiple linear regression analysis on a training set (N=76) was performed. In all cases the Residual Attenuation coefficient (ResAtt, R=0.81) was the only selected parameter. The results were tested on the residual cows (test set N=75) to predict the TAG content in the liver. Receiver Operating Characteristics (ROC) analysis then was applied to estimate the Area Under the Curve (AUC) and the sensitivity and specificity of the CAUS method. Equivalent high predictive values for AUC (95%), sensitivity(87%) and specificity (83%) for Intraop and Transc applications were found. Consequently, it can be concluded, applied Fat layer attenuation correction to Transc US images was performed adequately.
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