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 who...

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Bibliographic Details
Published in:Hepatology international 2022-04, Vol.16 (2), p.381-395
Main Authors: 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
Format: Article
Language:English
Subjects:
alpha-Fetoproteins - analysis
Biomarkers
Carcinoma, Hepatocellular - pathology
Colorectal Surgery
Digital imaging
Hepatocellular carcinoma
Hepatology
Humans
Liver cancer
Liver Neoplasms - pathology
Matching
Medical prognosis
Medicine
Medicine & Public Health
Microvasculature
Neoplasm Invasiveness
Neoplasm Recurrence, Local
Original
Original Article
Retrospective Studies
Risk analysis
Risk factors
Sampling
Surgery
Tumors
Vitamin K
α-Fetoprotein
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Summary: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  
ISSN:1936-0533
1936-0541
DOI:10.1007/s12072-022-10307-w