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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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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. |
format | Online Article Text |
id | pubmed-7769358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
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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