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Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis
Background and Aims: To investigate the impact of MR bias field correction on response determination and survival prediction using volumetric tumor enhancement analysis in patients with infiltrative hepatocellular carcinoma, after transcatheter arterial chemoembolization (TACE). Methods: This study...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
XIA & HE Publishing Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7562808/ https://www.ncbi.nlm.nih.gov/pubmed/33083252 http://dx.doi.org/10.14218/JCTH.2020.00054 |
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author | Liu, Cuihong Smolka, Susanne Papademetris, Xenophon Minh, Duc Do Gan, Geliang Deng, Yanhong Lin, MingDe Chapiro, Julius Wang, Ximing Georgiades, Christos Hong, Kelvin |
author_facet | Liu, Cuihong Smolka, Susanne Papademetris, Xenophon Minh, Duc Do Gan, Geliang Deng, Yanhong Lin, MingDe Chapiro, Julius Wang, Ximing Georgiades, Christos Hong, Kelvin |
author_sort | Liu, Cuihong |
collection | PubMed |
description | Background and Aims: To investigate the impact of MR bias field correction on response determination and survival prediction using volumetric tumor enhancement analysis in patients with infiltrative hepatocellular carcinoma, after transcatheter arterial chemoembolization (TACE). Methods: This study included 101 patients treated with conventional or drug-eluting beads TACE between the years of 2001 and 2013. Semi-automated 3D quantification software was used to segment and calculate the enhancing tumor volume (ETV) of the liver with and without bias-field correction on multi-phasic contrast-enhanced MRI before and 1-month after initial TACE. ETV (expressed as cm(3)) at baseline imaging and the relative change in ETV (as % change, ETV%) before and after TACE were used to predict response and survival, respectively. Statistical survival analyses included Kaplan-Meier curve generation and Cox proportional hazards modeling. Q statistics were calculated and used to identify the best cut-off value for ETV to separate responders and non-responders (ETV cm(3)). The difference in survival was evaluated between responders and non-responders using Kaplan-Meier and Cox models. Results: MR bias field correction correlated with improved response calculation from baseline MR as well as survival after TACE; using a 415 cm(3) cut-off for ETV at baseline (hazard ratio: 2.00, 95% confidence interval: 1.23-3.26, p=0.01) resulted in significantly improved response prediction (median survival in patients with baseline ETV <415 cm(3): 19.66 months vs. ≥415 cm(3): 9.21 months, p<0.001, log-rank test). A ≥41% relative decrease in ETV (hazard ratio: 0.58, 95%confidence interval: 0.37-0.93, p=0.02) was significant in predicting survival (ETV ≥41%: 19.20 months vs. ETV <41%: 8.71 months, p=0.008, log-rank test). Without MR bias field correction, response from baseline ETV could be predicted but survival after TACE could not. Conclusions: MR bias field correction improves both response assessment and accuracy of survival prediction using whole liver tumor enhancement analysis from baseline MR after initial TACE in patients with infiltrative hepatocellular carcinoma. |
format | Online Article Text |
id | pubmed-7562808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | XIA & HE Publishing Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75628082020-10-19 Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis Liu, Cuihong Smolka, Susanne Papademetris, Xenophon Minh, Duc Do Gan, Geliang Deng, Yanhong Lin, MingDe Chapiro, Julius Wang, Ximing Georgiades, Christos Hong, Kelvin J Clin Transl Hepatol Original Article Background and Aims: To investigate the impact of MR bias field correction on response determination and survival prediction using volumetric tumor enhancement analysis in patients with infiltrative hepatocellular carcinoma, after transcatheter arterial chemoembolization (TACE). Methods: This study included 101 patients treated with conventional or drug-eluting beads TACE between the years of 2001 and 2013. Semi-automated 3D quantification software was used to segment and calculate the enhancing tumor volume (ETV) of the liver with and without bias-field correction on multi-phasic contrast-enhanced MRI before and 1-month after initial TACE. ETV (expressed as cm(3)) at baseline imaging and the relative change in ETV (as % change, ETV%) before and after TACE were used to predict response and survival, respectively. Statistical survival analyses included Kaplan-Meier curve generation and Cox proportional hazards modeling. Q statistics were calculated and used to identify the best cut-off value for ETV to separate responders and non-responders (ETV cm(3)). The difference in survival was evaluated between responders and non-responders using Kaplan-Meier and Cox models. Results: MR bias field correction correlated with improved response calculation from baseline MR as well as survival after TACE; using a 415 cm(3) cut-off for ETV at baseline (hazard ratio: 2.00, 95% confidence interval: 1.23-3.26, p=0.01) resulted in significantly improved response prediction (median survival in patients with baseline ETV <415 cm(3): 19.66 months vs. ≥415 cm(3): 9.21 months, p<0.001, log-rank test). A ≥41% relative decrease in ETV (hazard ratio: 0.58, 95%confidence interval: 0.37-0.93, p=0.02) was significant in predicting survival (ETV ≥41%: 19.20 months vs. ETV <41%: 8.71 months, p=0.008, log-rank test). Without MR bias field correction, response from baseline ETV could be predicted but survival after TACE could not. Conclusions: MR bias field correction improves both response assessment and accuracy of survival prediction using whole liver tumor enhancement analysis from baseline MR after initial TACE in patients with infiltrative hepatocellular carcinoma. XIA & HE Publishing Inc. 2020-08-18 2020-09-28 /pmc/articles/PMC7562808/ /pubmed/33083252 http://dx.doi.org/10.14218/JCTH.2020.00054 Text en © 2020 Authors. http://creativecommons.org/licenses/by-nc/4.0/ This article has been published under the terms of Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), which permits noncommercial unrestricted use, distribution, and reproduction in any medium, provided that the following statement is provided. “This article has been published in Journal of Clinical and Translational Hepatology at DOI: 10.14218/JCTH.2020.00054 and can also be viewed on the Journal’s website at http://www.jcthnet.com”. |
spellingShingle | Original Article Liu, Cuihong Smolka, Susanne Papademetris, Xenophon Minh, Duc Do Gan, Geliang Deng, Yanhong Lin, MingDe Chapiro, Julius Wang, Ximing Georgiades, Christos Hong, Kelvin Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis |
title | Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis |
title_full | Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis |
title_fullStr | Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis |
title_full_unstemmed | Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis |
title_short | Predicting Infiltrative Hepatocellular Carcinoma Patient Outcome Post-TACE: MR Bias Field Correction Effect on 3D-quantitative Image Analysis |
title_sort | predicting infiltrative hepatocellular carcinoma patient outcome post-tace: mr bias field correction effect on 3d-quantitative image analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7562808/ https://www.ncbi.nlm.nih.gov/pubmed/33083252 http://dx.doi.org/10.14218/JCTH.2020.00054 |
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