Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evalua...

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Autores principales:	Qiang Wang, Changfeng Li, Jiaxing Zhang, Xiaojun Hu, Yingfang Fan, Kuansheng Ma, Ernesto Sparrelid, Torkel B. Brismar
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	radiomics microvascular invasion primary liver cancer prediction model systematic review Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/b45cf8284703422884bf3a22677bbf5b
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spelling	oai:doaj.org-article:b45cf8284703422884bf3a22677bbf5b2021-11-25T17:04:53ZRadiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment10.3390/cancers132258642072-6694https://doaj.org/article/b45cf8284703422884bf3a22677bbf5b2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-6694/13/22/5864https://doaj.org/toc/2072-6694Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evaluate their methodological quality. The methodological quality was assessed by the Radiomics Quality Score (RQS), and the risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Twenty-two studies using CT, MRI, or PET/CT for MVI prediction were included. All were retrospective studies, and only two had an external validation cohort. The AUC values of the prediction models ranged from 0.69 to 0.94 in the test cohort. Substantial methodological heterogeneity existed, and the methodological quality was low, with an average RQS score of 10 (28% of the total). Most studies demonstrated a low or unclear risk of bias in the domains of QUADAS-2. In conclusion, a radiomics model could be an accurate and effective tool for MVI prediction in HCC patients, although the methodological quality has so far been insufficient. Future prospective studies with an external validation cohort in accordance with a standardized radiomics workflow are expected to supply a reliable model that translates into clinical utilization.Qiang WangChangfeng LiJiaxing ZhangXiaojun HuYingfang FanKuansheng MaErnesto SparrelidTorkel B. BrismarMDPI AGarticleradiomicsmicrovascular invasionprimary liver cancerprediction modelsystematic reviewNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENCancers, Vol 13, Iss 5864, p 5864 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	radiomics microvascular invasion primary liver cancer prediction model systematic review Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	radiomics microvascular invasion primary liver cancer prediction model systematic review Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Qiang Wang Changfeng Li Jiaxing Zhang Xiaojun Hu Yingfang Fan Kuansheng Ma Ernesto Sparrelid Torkel B. Brismar Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
description	Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evaluate their methodological quality. The methodological quality was assessed by the Radiomics Quality Score (RQS), and the risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Twenty-two studies using CT, MRI, or PET/CT for MVI prediction were included. All were retrospective studies, and only two had an external validation cohort. The AUC values of the prediction models ranged from 0.69 to 0.94 in the test cohort. Substantial methodological heterogeneity existed, and the methodological quality was low, with an average RQS score of 10 (28% of the total). Most studies demonstrated a low or unclear risk of bias in the domains of QUADAS-2. In conclusion, a radiomics model could be an accurate and effective tool for MVI prediction in HCC patients, although the methodological quality has so far been insufficient. Future prospective studies with an external validation cohort in accordance with a standardized radiomics workflow are expected to supply a reliable model that translates into clinical utilization.
format	article
author	Qiang Wang Changfeng Li Jiaxing Zhang Xiaojun Hu Yingfang Fan Kuansheng Ma Ernesto Sparrelid Torkel B. Brismar
author_facet	Qiang Wang Changfeng Li Jiaxing Zhang Xiaojun Hu Yingfang Fan Kuansheng Ma Ernesto Sparrelid Torkel B. Brismar
author_sort	Qiang Wang
title	Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
title_short	Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
title_full	Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
title_fullStr	Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
title_full_unstemmed	Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment
title_sort	radiomics models for predicting microvascular invasion in hepatocellular carcinoma: a systematic review and radiomics quality score assessment
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b45cf8284703422884bf3a22677bbf5b
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_version_	1718412735226576896

Radiomics Models for Predicting Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Radiomics Quality Score Assessment

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