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

Abstract 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.