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Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma

This study explored the potential of computed tomography (CT) textural feature analysis for the stratification of single large hepatocellular carcinomas (HCCs) > 5 cm, and the subsequent determination of patient suitability for liver resection (LR) or transcatheter arterial chemoembolization (TAC...

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Autores principales: Li, Meng, Fu, Sirui, Zhu, Yanjie, Liu, Zaiyi, Chen, Shuting, Lu, Ligong, Liang, Changhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914356/
https://www.ncbi.nlm.nih.gov/pubmed/26910890
http://dx.doi.org/10.18632/oncotarget.7467
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author Li, Meng
Fu, Sirui
Zhu, Yanjie
Liu, Zaiyi
Chen, Shuting
Lu, Ligong
Liang, Changhong
author_facet Li, Meng
Fu, Sirui
Zhu, Yanjie
Liu, Zaiyi
Chen, Shuting
Lu, Ligong
Liang, Changhong
author_sort Li, Meng
collection PubMed
description This study explored the potential of computed tomography (CT) textural feature analysis for the stratification of single large hepatocellular carcinomas (HCCs) > 5 cm, and the subsequent determination of patient suitability for liver resection (LR) or transcatheter arterial chemoembolization (TACE). Wavelet decomposition was performed on portal-phase CT images with three bandwidth responses (filter 0, 1.0, and 1.5). Nine textural features of each filter were extracted from regions of interest. Wavelet-2-H (filter 1.0) in LR and wavelet-2-V (filter 0 and 1.0) in TACE were related to survival. Subsequently, LR and TACE patients were divided based on the wavelet-2-H and wavelet-2-V median at filter 1.0 into two subgroups (+ or −). LR+ patients showed the best survival, followed by LR-, TACE+, and TACE-. We estimated that LR+ patients treated using TACE would exhibit a survival similar to TACE- patients and worse than TACE+ patients, with a severe compromise in overall survival. LR was recommended for TACE- patients, whereas TACE was preferred for LR- and TACE+ patients. Independent of tumor size, CT textural features showed positive and negative correlations with survival after LR and TACE, respectively. Although further validation is needed, texture analysis demonstrated the feasibility of using HCC patient stratification for determining the suitability of LR vs. TACE.
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spelling pubmed-49143562016-07-11 Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma Li, Meng Fu, Sirui Zhu, Yanjie Liu, Zaiyi Chen, Shuting Lu, Ligong Liang, Changhong Oncotarget Clinical Research Paper This study explored the potential of computed tomography (CT) textural feature analysis for the stratification of single large hepatocellular carcinomas (HCCs) > 5 cm, and the subsequent determination of patient suitability for liver resection (LR) or transcatheter arterial chemoembolization (TACE). Wavelet decomposition was performed on portal-phase CT images with three bandwidth responses (filter 0, 1.0, and 1.5). Nine textural features of each filter were extracted from regions of interest. Wavelet-2-H (filter 1.0) in LR and wavelet-2-V (filter 0 and 1.0) in TACE were related to survival. Subsequently, LR and TACE patients were divided based on the wavelet-2-H and wavelet-2-V median at filter 1.0 into two subgroups (+ or −). LR+ patients showed the best survival, followed by LR-, TACE+, and TACE-. We estimated that LR+ patients treated using TACE would exhibit a survival similar to TACE- patients and worse than TACE+ patients, with a severe compromise in overall survival. LR was recommended for TACE- patients, whereas TACE was preferred for LR- and TACE+ patients. Independent of tumor size, CT textural features showed positive and negative correlations with survival after LR and TACE, respectively. Although further validation is needed, texture analysis demonstrated the feasibility of using HCC patient stratification for determining the suitability of LR vs. TACE. Impact Journals LLC 2016-02-17 /pmc/articles/PMC4914356/ /pubmed/26910890 http://dx.doi.org/10.18632/oncotarget.7467 Text en Copyright: © 2016 Li et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Clinical Research Paper
Li, Meng
Fu, Sirui
Zhu, Yanjie
Liu, Zaiyi
Chen, Shuting
Lu, Ligong
Liang, Changhong
Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
title Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
title_full Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
title_fullStr Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
title_full_unstemmed Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
title_short Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
title_sort computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma
topic Clinical Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914356/
https://www.ncbi.nlm.nih.gov/pubmed/26910890
http://dx.doi.org/10.18632/oncotarget.7467
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