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A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a histopathological marker and risk factor for HCC recurrence. We integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) image findings of tumors into a scoring system for predicting MVI. In total, 228 HCC patients wi...

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Autores principales: Liao, Chien-Chang, Cheng, Yu-Fan, Yu, Chun-Yen, Tsang, Leung-Chit Leo, Chen, Chao-Long, Hsu, Hsien-Wen, Chang, Wan-Ching, Lim, Wei-Xiong, Chuang, Yi-Hsuan, Huang, Po-Hsun, Ou, Hsin-You
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9267530/
https://www.ncbi.nlm.nih.gov/pubmed/35807074
http://dx.doi.org/10.3390/jcm11133789
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author Liao, Chien-Chang
Cheng, Yu-Fan
Yu, Chun-Yen
Tsang, Leung-Chit Leo
Chen, Chao-Long
Hsu, Hsien-Wen
Chang, Wan-Ching
Lim, Wei-Xiong
Chuang, Yi-Hsuan
Huang, Po-Hsun
Ou, Hsin-You
author_facet Liao, Chien-Chang
Cheng, Yu-Fan
Yu, Chun-Yen
Tsang, Leung-Chit Leo
Chen, Chao-Long
Hsu, Hsien-Wen
Chang, Wan-Ching
Lim, Wei-Xiong
Chuang, Yi-Hsuan
Huang, Po-Hsun
Ou, Hsin-You
author_sort Liao, Chien-Chang
collection PubMed
description Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a histopathological marker and risk factor for HCC recurrence. We integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) image findings of tumors into a scoring system for predicting MVI. In total, 228 HCC patients with pathologically confirmed MVI who underwent surgical resection or liver transplant between November 2012 and March 2021 were enrolled retrospectively. Patients were divided into a right liver lobe group (n = 173, 75.9%) as the model dataset and a left liver lobe group (n = 55, 24.1%) as the model validation dataset. Multivariate logistic regression identified two-segment involved tumor (Score: 1; OR: 3.14; 95% CI: 1.22 to 8.06; p = 0.017); ADC(min) ≤ 0.95 × 10(−3) mm(2)/s (Score: 2; OR: 10.88; 95% CI: 4.61 to 25.68; p = 0.000); and largest single tumor diameter ≥ 3 cm (Score: 1; OR: 5.05; 95% CI: 2.25 to 11.30; p = 0.000), as predictive factors for the scoring model. Among all patients, sensitivity was 89.66%, specificity 58.04%, positive predictive value 68.87%, and negative predictive value 84.41%. For validation of left lobe group, sensitivity was 80.64%, specificity 70.83%, positive predictive value 78.12%, and negative predictive value 73.91%. The scoring model using ADC(min), largest tumor diameter, and two-segment involved tumor provides high sensitivity and negative predictive value in MVI prediction for use in routine functional MR.
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spelling pubmed-92675302022-07-09 A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI Liao, Chien-Chang Cheng, Yu-Fan Yu, Chun-Yen Tsang, Leung-Chit Leo Chen, Chao-Long Hsu, Hsien-Wen Chang, Wan-Ching Lim, Wei-Xiong Chuang, Yi-Hsuan Huang, Po-Hsun Ou, Hsin-You J Clin Med Article Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a histopathological marker and risk factor for HCC recurrence. We integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) image findings of tumors into a scoring system for predicting MVI. In total, 228 HCC patients with pathologically confirmed MVI who underwent surgical resection or liver transplant between November 2012 and March 2021 were enrolled retrospectively. Patients were divided into a right liver lobe group (n = 173, 75.9%) as the model dataset and a left liver lobe group (n = 55, 24.1%) as the model validation dataset. Multivariate logistic regression identified two-segment involved tumor (Score: 1; OR: 3.14; 95% CI: 1.22 to 8.06; p = 0.017); ADC(min) ≤ 0.95 × 10(−3) mm(2)/s (Score: 2; OR: 10.88; 95% CI: 4.61 to 25.68; p = 0.000); and largest single tumor diameter ≥ 3 cm (Score: 1; OR: 5.05; 95% CI: 2.25 to 11.30; p = 0.000), as predictive factors for the scoring model. Among all patients, sensitivity was 89.66%, specificity 58.04%, positive predictive value 68.87%, and negative predictive value 84.41%. For validation of left lobe group, sensitivity was 80.64%, specificity 70.83%, positive predictive value 78.12%, and negative predictive value 73.91%. The scoring model using ADC(min), largest tumor diameter, and two-segment involved tumor provides high sensitivity and negative predictive value in MVI prediction for use in routine functional MR. MDPI 2022-06-30 /pmc/articles/PMC9267530/ /pubmed/35807074 http://dx.doi.org/10.3390/jcm11133789 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liao, Chien-Chang
Cheng, Yu-Fan
Yu, Chun-Yen
Tsang, Leung-Chit Leo
Chen, Chao-Long
Hsu, Hsien-Wen
Chang, Wan-Ching
Lim, Wei-Xiong
Chuang, Yi-Hsuan
Huang, Po-Hsun
Ou, Hsin-You
A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
title A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
title_full A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
title_fullStr A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
title_full_unstemmed A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
title_short A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI
title_sort scoring system for predicting microvascular invasion in hepatocellular carcinoma based on quantitative functional mri
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9267530/
https://www.ncbi.nlm.nih.gov/pubmed/35807074
http://dx.doi.org/10.3390/jcm11133789
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