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Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma
BACKGROUND: Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radi...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594790/ https://www.ncbi.nlm.nih.gov/pubmed/37875815 http://dx.doi.org/10.1186/s12885-023-11491-0 |
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author | Zhao, Ying Zhang, Jian Wang, Nan Xu, Qihao Liu, Yuhui Liu, Jinghong Zhang, Qinhe Zhang, Xinyuan Chen, Anliang Chen, Lihua Sheng, Liuji Song, Qingwei Wang, Feng Guo, Yan Liu, Ailian |
author_facet | Zhao, Ying Zhang, Jian Wang, Nan Xu, Qihao Liu, Yuhui Liu, Jinghong Zhang, Qinhe Zhang, Xinyuan Chen, Anliang Chen, Lihua Sheng, Liuji Song, Qingwei Wang, Feng Guo, Yan Liu, Ailian |
author_sort | Zhao, Ying |
collection | PubMed |
description | BACKGROUND: Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. METHODS: A total of 138 patients with HCC who received TACE were retrospectively included and randomly divided into training and validation cohorts at a ratio of 7:3. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. The inter- and intraclass correlation coefficients, the spearman’s rank correlation test, and the gradient boosting decision tree algorithm were used for radiomics feature selection. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. RESULTS: The T-PTR radiomics models performed better than the TR and PTR models, and the T-PTR (3 mm) radiomics model demonstrated preferable performance with the AUCs of 0.884 (95%CI, 0.821–0.936) and 0.911 (95%CI, 0.825–0.975) in both training and validation cohorts. The T-PTR (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were fused to construct a combined nomogram. The combined nomogram [AUC: 0.910 (95%CI, 0.854–0.958) and 0.918 (95%CI, 0.831–0.986)] outperformed the clinical-radiological model [AUC: 0.789 (95%CI, 0.709–0.863) and 0.782 (95%CI, 0.660–0.902)] in the both cohorts and achieved good calibration capability and clinical utility. CONCLUSIONS: CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11491-0. |
format | Online Article Text |
id | pubmed-10594790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105947902023-10-25 Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma Zhao, Ying Zhang, Jian Wang, Nan Xu, Qihao Liu, Yuhui Liu, Jinghong Zhang, Qinhe Zhang, Xinyuan Chen, Anliang Chen, Lihua Sheng, Liuji Song, Qingwei Wang, Feng Guo, Yan Liu, Ailian BMC Cancer Research BACKGROUND: Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. METHODS: A total of 138 patients with HCC who received TACE were retrospectively included and randomly divided into training and validation cohorts at a ratio of 7:3. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. The inter- and intraclass correlation coefficients, the spearman’s rank correlation test, and the gradient boosting decision tree algorithm were used for radiomics feature selection. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. RESULTS: The T-PTR radiomics models performed better than the TR and PTR models, and the T-PTR (3 mm) radiomics model demonstrated preferable performance with the AUCs of 0.884 (95%CI, 0.821–0.936) and 0.911 (95%CI, 0.825–0.975) in both training and validation cohorts. The T-PTR (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were fused to construct a combined nomogram. The combined nomogram [AUC: 0.910 (95%CI, 0.854–0.958) and 0.918 (95%CI, 0.831–0.986)] outperformed the clinical-radiological model [AUC: 0.789 (95%CI, 0.709–0.863) and 0.782 (95%CI, 0.660–0.902)] in the both cohorts and achieved good calibration capability and clinical utility. CONCLUSIONS: CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11491-0. BioMed Central 2023-10-24 /pmc/articles/PMC10594790/ /pubmed/37875815 http://dx.doi.org/10.1186/s12885-023-11491-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zhao, Ying Zhang, Jian Wang, Nan Xu, Qihao Liu, Yuhui Liu, Jinghong Zhang, Qinhe Zhang, Xinyuan Chen, Anliang Chen, Lihua Sheng, Liuji Song, Qingwei Wang, Feng Guo, Yan Liu, Ailian Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
title | Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
title_full | Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
title_fullStr | Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
title_full_unstemmed | Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
title_short | Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
title_sort | intratumoral and peritumoral radiomics based on contrast-enhanced mri for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594790/ https://www.ncbi.nlm.nih.gov/pubmed/37875815 http://dx.doi.org/10.1186/s12885-023-11491-0 |
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