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Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma

OBJECTIVE: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) using histogram analysis of apparent diffusion coefficients (ADC). METHODS: Breath-hold diffusion weighted imaging (DWI) was performed in 64 pa...

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Autores principales: Ma, Xiaohong, Ouyang, Han, Wang, Shuang, Wang, Meng, Zhou, Chunwu, Zhao, Xinming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513745/
https://www.ncbi.nlm.nih.gov/pubmed/31156307
http://dx.doi.org/10.21147/j.issn.1000-9604.2019.02.11
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author Ma, Xiaohong
Ouyang, Han
Wang, Shuang
Wang, Meng
Zhou, Chunwu
Zhao, Xinming
author_facet Ma, Xiaohong
Ouyang, Han
Wang, Shuang
Wang, Meng
Zhou, Chunwu
Zhao, Xinming
author_sort Ma, Xiaohong
collection PubMed
description OBJECTIVE: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) using histogram analysis of apparent diffusion coefficients (ADC). METHODS: Breath-hold diffusion weighted imaging (DWI) was performed in 64 patients (33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging (MRI) and follow-up computed tomography (CT) or MRI. The ADC values (ADC(10), ADC(30), ADC(median) and ADC(max)) were obtained from the histogram’s 10th, 30th, 50th and 100th percentiles. The ratios of ADC(10), ADC(30), ADC(median) and ADC(max) to the mean non-lesion area-ADC (RADC(10), RADC(30), RADC(median), and RADC(max)) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test. RESULTS: The ADC(30), ADC(median), ADC(max), RADC(30), RADC(median), and RADC(max) were significantly larger in the progressive group than in the stable group (P<0.05). The median progression-free survival (PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months, respectively. Univariate analysis indicated that RADC(10), RADC(30), and RADC(median) were significantly correlated with the PFS [hazard ratio (HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADC(median) was the only independent predictor of tumor progression (P=0.04). And the cutoff value of RADC(median) was 0.71. CONCLUSIONS: Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA.
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spelling pubmed-65137452019-05-31 Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma Ma, Xiaohong Ouyang, Han Wang, Shuang Wang, Meng Zhou, Chunwu Zhao, Xinming Chin J Cancer Res Original Article OBJECTIVE: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) using histogram analysis of apparent diffusion coefficients (ADC). METHODS: Breath-hold diffusion weighted imaging (DWI) was performed in 64 patients (33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging (MRI) and follow-up computed tomography (CT) or MRI. The ADC values (ADC(10), ADC(30), ADC(median) and ADC(max)) were obtained from the histogram’s 10th, 30th, 50th and 100th percentiles. The ratios of ADC(10), ADC(30), ADC(median) and ADC(max) to the mean non-lesion area-ADC (RADC(10), RADC(30), RADC(median), and RADC(max)) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test. RESULTS: The ADC(30), ADC(median), ADC(max), RADC(30), RADC(median), and RADC(max) were significantly larger in the progressive group than in the stable group (P<0.05). The median progression-free survival (PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months, respectively. Univariate analysis indicated that RADC(10), RADC(30), and RADC(median) were significantly correlated with the PFS [hazard ratio (HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADC(median) was the only independent predictor of tumor progression (P=0.04). And the cutoff value of RADC(median) was 0.71. CONCLUSIONS: Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA. AME Publishing Company 2019-04 /pmc/articles/PMC6513745/ /pubmed/31156307 http://dx.doi.org/10.21147/j.issn.1000-9604.2019.02.11 Text en Copyright © 2019 Chinese Journal of Cancer Research. All rights reserved. http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-Non Commercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Original Article
Ma, Xiaohong
Ouyang, Han
Wang, Shuang
Wang, Meng
Zhou, Chunwu
Zhao, Xinming
Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
title Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
title_full Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
title_fullStr Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
title_full_unstemmed Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
title_short Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
title_sort histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513745/
https://www.ncbi.nlm.nih.gov/pubmed/31156307
http://dx.doi.org/10.21147/j.issn.1000-9604.2019.02.11
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