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Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma

To investigate whether MRI features could preoperatively predict local tumor progression (LTP) in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) as the first-line treatment and improve a novel predictive model through developing a nomogram including various c...

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Autores principales: Hu, Zhouchao, Yu, Nannan, Wang, Heping, Li, Shibo, Yan, Jingang, Zhang, Guoqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769358/
https://www.ncbi.nlm.nih.gov/pubmed/33350797
http://dx.doi.org/10.1097/MD.0000000000023924
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author Hu, Zhouchao
Yu, Nannan
Wang, Heping
Li, Shibo
Yan, Jingang
Zhang, Guoqiang
author_facet Hu, Zhouchao
Yu, Nannan
Wang, Heping
Li, Shibo
Yan, Jingang
Zhang, Guoqiang
author_sort Hu, Zhouchao
collection PubMed
description To investigate whether MRI features could preoperatively predict local tumor progression (LTP) in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) as the first-line treatment and improve a novel predictive model through developing a nomogram including various conventional MRI parameters. 105 patients with HCCs who had received RFA were enrolled. All patients had undergone conventional MRI before RFA. Uni- and multivariable analyses for LTP were assessing using a Cox proportional hazards model. The developed MRI-based nomogram was further designed based on multivariable logistic analysis in our study and the usefulness of the developed model was validated according to calibration curves and the C-index. Rim enhancement (hazard ratio: 2.689, P = .044) and the apparent diffusion coefficient (ADC) values (hazard ratio: 0.055, P = .038) were statistically significant independent predictors of LTP after RFA at multivariable analysis. The performance of the nomogram incorporating two MRI parameters (with a C-index of 0.782) was improved compared with that based on rim enhancement and ADC alone (with C-index values of 0.630 and 0.728, respectively). The calibration curve of the MRI-based nomogram showed good conformance between evaluation and observation at 0.5, 1, and 1.5 years after RFA. The preliminary predictive model based on MRI findings including rim enhancement and ADC value could be used preoperatively to estimate the risk of LTP of HCC after RFA as the first-line treatment.
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spelling pubmed-77693582020-12-29 Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma Hu, Zhouchao Yu, Nannan Wang, Heping Li, Shibo Yan, Jingang Zhang, Guoqiang Medicine (Baltimore) 6800 To investigate whether MRI features could preoperatively predict local tumor progression (LTP) in patients with hepatocellular carcinoma (HCC) treated with radiofrequency ablation (RFA) as the first-line treatment and improve a novel predictive model through developing a nomogram including various conventional MRI parameters. 105 patients with HCCs who had received RFA were enrolled. All patients had undergone conventional MRI before RFA. Uni- and multivariable analyses for LTP were assessing using a Cox proportional hazards model. The developed MRI-based nomogram was further designed based on multivariable logistic analysis in our study and the usefulness of the developed model was validated according to calibration curves and the C-index. Rim enhancement (hazard ratio: 2.689, P = .044) and the apparent diffusion coefficient (ADC) values (hazard ratio: 0.055, P = .038) were statistically significant independent predictors of LTP after RFA at multivariable analysis. The performance of the nomogram incorporating two MRI parameters (with a C-index of 0.782) was improved compared with that based on rim enhancement and ADC alone (with C-index values of 0.630 and 0.728, respectively). The calibration curve of the MRI-based nomogram showed good conformance between evaluation and observation at 0.5, 1, and 1.5 years after RFA. The preliminary predictive model based on MRI findings including rim enhancement and ADC value could be used preoperatively to estimate the risk of LTP of HCC after RFA as the first-line treatment. Lippincott Williams & Wilkins 2020-12-24 /pmc/articles/PMC7769358/ /pubmed/33350797 http://dx.doi.org/10.1097/MD.0000000000023924 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0
spellingShingle 6800
Hu, Zhouchao
Yu, Nannan
Wang, Heping
Li, Shibo
Yan, Jingang
Zhang, Guoqiang
Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma
title Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma
title_full Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma
title_fullStr Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma
title_full_unstemmed Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma
title_short Pre-radiofrequency ablation MRI imaging features predict the local tumor progression in hepatocellular carcinoma
title_sort pre-radiofrequency ablation mri imaging features predict the local tumor progression in hepatocellular carcinoma
topic 6800
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769358/
https://www.ncbi.nlm.nih.gov/pubmed/33350797
http://dx.doi.org/10.1097/MD.0000000000023924
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