TY - GEN
T1 - Improved quantitative contrast-enhanced ultrasound imaging of hepatocellular carcinoma response to transarterial chemoembolization
AU - Oezdemir, Ipek
AU - Shaw, Collette
AU - Eisenbrey, John R.
AU - Hoyt, Kenneth
N1 - Funding Information:
This work was supported in part by NIH grants R01CA194307, R21CA212851, K25EB017222 and Cancer Prevention and Research Institute of Texas (CPRIT) grant RP180670. The authors also acknowledge the Texas Advanced Computing Center (TACC) at the University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. URL: http://www.tacc.utexas.edu.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - The purpose of this research project was to improve the quantification of microvascular networks depicted in contrast-enhanced ultrasound (CEUS) images of human hepatocellular carcinoma (HCC). Due to limited anatomical information in CEUS images, grayscale B-mode ultrasound (US) data is preferred when estimating tissue motion. Transformation functions derived from the B-mode data are one solution for registering a dynamic sequence of CEUS images. Microvessel density (MVD) can then be calculated from both the original and motion corrected CEUS images as the ratio of the number of contrast-enhanced image pixels with a value greater than zero to the number of pixels of the entire tumor space. Using US images of HCC before and after treatment with transarterial chemoembolization, results revealed that affine and non-rigid motion correction improves visualization and quantitative analysis of clinical data. Using the correlation coefficient (CC) between CEUS frames as metric of tissue motion, our motion correction strategy produced a 20% increase in the average CC from motion corrected frames compared to the data before correction (p \lt 0.001). Furthermore, enhanced visualization of microvascular networks in the treated liver tumor space may improve determination of treatment efficacy and need for any repeat procedures.
AB - The purpose of this research project was to improve the quantification of microvascular networks depicted in contrast-enhanced ultrasound (CEUS) images of human hepatocellular carcinoma (HCC). Due to limited anatomical information in CEUS images, grayscale B-mode ultrasound (US) data is preferred when estimating tissue motion. Transformation functions derived from the B-mode data are one solution for registering a dynamic sequence of CEUS images. Microvessel density (MVD) can then be calculated from both the original and motion corrected CEUS images as the ratio of the number of contrast-enhanced image pixels with a value greater than zero to the number of pixels of the entire tumor space. Using US images of HCC before and after treatment with transarterial chemoembolization, results revealed that affine and non-rigid motion correction improves visualization and quantitative analysis of clinical data. Using the correlation coefficient (CC) between CEUS frames as metric of tissue motion, our motion correction strategy produced a 20% increase in the average CC from motion corrected frames compared to the data before correction (p \lt 0.001). Furthermore, enhanced visualization of microvascular networks in the treated liver tumor space may improve determination of treatment efficacy and need for any repeat procedures.
KW - Cancer
KW - Contrast-enhanced ultrasound
KW - Image registration, microbubble contrast agents, microvascular networks
KW - Motion correction
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U2 - 10.1109/ISBI.2019.8759238
DO - 10.1109/ISBI.2019.8759238
M3 - Conference contribution
AN - SCOPUS:85073912420
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 1737
EP - 1740
BT - ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
Y2 - 8 April 2019 through 11 April 2019
ER -