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Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma

BACKGROUND: Microvascular invasion (MVI) is a prominent risk factor of postoperative recurrence for hepatocellular carcinoma (HCC). The MVI detection rate of conventional pathological examination approaches is relatively low and unsatisfactory. METHODS: By integrating pathological macro-slide with w...

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Autores principales: Yu, Hong-Ming, Wang, Kang, Feng, Jin-Kai, Lu, Lei, Qin, Yu-Chen, Cheng, Yu-Qiang, Guo, Wei-Xing, Shi, Jie, Cong, Wen-Ming, Lau, Wan Yee, Dong, Hui, Cheng, Shu-Qun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013327/
https://www.ncbi.nlm.nih.gov/pubmed/35294742
http://dx.doi.org/10.1007/s12072-022-10307-w
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author Yu, Hong-Ming
Wang, Kang
Feng, Jin-Kai
Lu, Lei
Qin, Yu-Chen
Cheng, Yu-Qiang
Guo, Wei-Xing
Shi, Jie
Cong, Wen-Ming
Lau, Wan Yee
Dong, Hui
Cheng, Shu-Qun
author_facet Yu, Hong-Ming
Wang, Kang
Feng, Jin-Kai
Lu, Lei
Qin, Yu-Chen
Cheng, Yu-Qiang
Guo, Wei-Xing
Shi, Jie
Cong, Wen-Ming
Lau, Wan Yee
Dong, Hui
Cheng, Shu-Qun
author_sort Yu, Hong-Ming
collection PubMed
description BACKGROUND: Microvascular invasion (MVI) is a prominent risk factor of postoperative recurrence for hepatocellular carcinoma (HCC). The MVI detection rate of conventional pathological examination approaches is relatively low and unsatisfactory. METHODS: By integrating pathological macro-slide with whole-mount slide imaging, we first created a novel pathological examination method called image-matching digital macro-slide (IDS). Surgical samples from eligible patients were collected to make IDS. The MVI detection rates, tumor recurrence rates and recurrence-free survival were compared among conventional 3-Point and 7-Point baseline sampling protocols and IDS. Additionally, biomarkers to recognize MVI false negative patients were probed via combining conventional pathological sampling protocols and IDS. Receiver operating characteristic curve (ROC) analysis was used to obtain the optimal cutoff of biomarkers to distinguish MVI false negative patients. RESULTS: The MVI detection rates were 21.98%, 32.97% and 63.74%, respectively, in 3-Point, 7-Point baseline sampling protocols and IDS (p < 0.001). Tumor recurrence rate of patients with MVI negative status in IDS (6.06%) was relatively lower than that of patients with MVI negative status in 3-Point (16.90%) and 7-Point (16.39%) sampling protocols. Alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II) were selected as potential biomarkers to distinguish MVI false negative patients. CONCLUSIONS: Our study demonstrated that IDS can help enhance the detection rate of MVI in HCC and refine the prediction of HCC prognosis. Alpha-fetoprotein is identified as a suitable and robust biomarker to recognize MVI false-negative patients in conventional pathological protocols. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12072-022-10307-w.
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spelling pubmed-90133272022-05-02 Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma Yu, Hong-Ming Wang, Kang Feng, Jin-Kai Lu, Lei Qin, Yu-Chen Cheng, Yu-Qiang Guo, Wei-Xing Shi, Jie Cong, Wen-Ming Lau, Wan Yee Dong, Hui Cheng, Shu-Qun Hepatol Int Original Article BACKGROUND: Microvascular invasion (MVI) is a prominent risk factor of postoperative recurrence for hepatocellular carcinoma (HCC). The MVI detection rate of conventional pathological examination approaches is relatively low and unsatisfactory. METHODS: By integrating pathological macro-slide with whole-mount slide imaging, we first created a novel pathological examination method called image-matching digital macro-slide (IDS). Surgical samples from eligible patients were collected to make IDS. The MVI detection rates, tumor recurrence rates and recurrence-free survival were compared among conventional 3-Point and 7-Point baseline sampling protocols and IDS. Additionally, biomarkers to recognize MVI false negative patients were probed via combining conventional pathological sampling protocols and IDS. Receiver operating characteristic curve (ROC) analysis was used to obtain the optimal cutoff of biomarkers to distinguish MVI false negative patients. RESULTS: The MVI detection rates were 21.98%, 32.97% and 63.74%, respectively, in 3-Point, 7-Point baseline sampling protocols and IDS (p < 0.001). Tumor recurrence rate of patients with MVI negative status in IDS (6.06%) was relatively lower than that of patients with MVI negative status in 3-Point (16.90%) and 7-Point (16.39%) sampling protocols. Alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II) were selected as potential biomarkers to distinguish MVI false negative patients. CONCLUSIONS: Our study demonstrated that IDS can help enhance the detection rate of MVI in HCC and refine the prediction of HCC prognosis. Alpha-fetoprotein is identified as a suitable and robust biomarker to recognize MVI false-negative patients in conventional pathological protocols. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12072-022-10307-w. Springer India 2022-03-16 /pmc/articles/PMC9013327/ /pubmed/35294742 http://dx.doi.org/10.1007/s12072-022-10307-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) .
spellingShingle Original Article
Yu, Hong-Ming
Wang, Kang
Feng, Jin-Kai
Lu, Lei
Qin, Yu-Chen
Cheng, Yu-Qiang
Guo, Wei-Xing
Shi, Jie
Cong, Wen-Ming
Lau, Wan Yee
Dong, Hui
Cheng, Shu-Qun
Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
title Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
title_full Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
title_fullStr Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
title_full_unstemmed Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
title_short Image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
title_sort image-matching digital macro-slide—a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013327/
https://www.ncbi.nlm.nih.gov/pubmed/35294742
http://dx.doi.org/10.1007/s12072-022-10307-w
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