Cargando…
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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |
_version_ | 1784743741207085056 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9267530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT liaochienchang ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT chengyufan ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT yuchunyen ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT tsangleungchitleo ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT chenchaolong ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT hsuhsienwen ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT changwanching ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT limweixiong ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT chuangyihsuan ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT huangpohsun ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT ouhsinyou ascoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT liaochienchang scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT chengyufan scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT yuchunyen scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT tsangleungchitleo scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT chenchaolong scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT hsuhsienwen scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT changwanching scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT limweixiong scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT chuangyihsuan scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT huangpohsun scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri AT ouhsinyou scoringsystemforpredictingmicrovascularinvasioninhepatocellularcarcinomabasedonquantitativefunctionalmri |