Development and Validation of a Novel Nomogram for Predicting Vessels that Encapsulate Tumor Cluster in Hepatocellular Carcinoma

Abstract

Background Vessels that encapsulate tumor cluster (VETC) is associated with poor prognosis in hepatocellular carcinoma (HCC). Vessels that encapsulate tumor cluster estimation before initial treatment is helpful for clinical doctors. We aimed to construct a novel predictive model for VETC, using preoperatively accessible clinical parameters and imagine features. Methods Totally, 365 HCC patients who received curative hepatectomy in the Sun Yat-Sen University Cancer Center from 2013 to 2014 were enrolled in this study. Vessels that encapsulate tumor cluster pattern was confirmed by immunochemistry staining. 243 were randomly assigned to the training cohort while the rest was assigned to the validation cohort. Independent predictive factors for VETC estimation were determined by univariate and multivariate logistic analysis. We further constructed a predictive nomogram for VETC in HCC. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curve, and calibration curve. Besides, the decision curve was plotted to evaluate the clinical usefulness. Ultimately, Kaplan–Meier survival curves were utilized to confirm the association between the nomogram and survival. Results Immunochemistry staining revealed VETC in 87 patients (23.8%). lymphocyte to monocyte ratio (>7.75, OR = 4.06), neutrophil (>7, OR = 4.48), AST to ALT ratio (AAR > .86, OR = 2.16), ALT to lymphocyte ratio index (BLRI > 21.73, OR = 2.57), alpha-fetoprotein (OR = 1.1), and tumor diameter (OR = 2.65) were independent predictive factors. The nomogram incorporating these predictive factors performed well with an area under the curve (AUC) of .746 and .707 in training and validation cohorts, respectively. Calibration curves indicated the predicted probabilities closely corresponded with the actual VETC status. Moreover, the decision curve proved our nomogram could provide clinical benefits with patients. Finally, low probability of VETC group had significantly longer recurrence free survival (RFS) and overall survival (OS) than the high probability of the VETC group (all P < .001). Conclusion A novel predictive nomogram integrating clinical indicators and image characteristics shows strong predictive VETC performance and might provide standardized net clinical benefits.

Clinical significance of mechanistic target of rapamycin expression in vessels that encapsulate tumor cluster‐positive hepatocellular carcinoma patients who have undergone living donor liver transplantation

“…The concept of VETC was first reported by Fang et al factor in HCC. [17][18][19] In the present study, 20.1% of HCC patients who underwent LDLT for HCC had VETC(+) tumors; this figure is in agreement with previous reports. VETC(+) HCC is highly malignant and its occurrence is correlated with programmed cell death ligand 1 (PD-L1) and vascular endothelial growth factor expression.…”

“…The concept of VETC was first reported by Fang et al 6 VETC is present in 16.9%–23.8% of HCC patients and is a poor prognostic factor in HCC 17–19 . In the present study, 20.1% of HCC patients who underwent LDLT for HCC had VETC(+) tumors; this figure is in agreement with previous reports.…”

Vessels that encapsulate tumour clusters vascular pattern in hepatocellular carcinoma

“… 27 Finally, several studies adopted a value of ≥55% tumour area as the “optimal” cut-off to define VETC-positive vs. VETC-negative phenotypes to predict prognosis. 24 , 26 , [28] , [29] , [30] , [31] , [32] However, the original reference for this cut-off comes from a study which evaluated VETC using tissue microarrays 24 which may not have the same applicability in the other studies which used whole sections. Indeed, the true prevalence and severity of VETC can only be quantified using resection or explant specimens and not tissue microarrays or liver biopsies (discussed later).…”

Deep Learning Radiomics Model of Dynamic Contrast‐Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma

“…However, evaluating VETC patterns preoperatively remains challenging because VETC can only be diagnosed by surgical specimens. Some studies have tried to use preoperative imaging to noninvasive evaluate VETC 8–12 . Computed tomography (CT) or MRI features, such as types of enhancement pattern, intratumoral necrosis, tumor size, and non‐rim diffuse and heterogeneous arterial phase hyperenhancement (non‐rim dh‐APHE), have been reported to be associated with VETC 8–11 .…”

“…[8][9][10][11][12] Computed tomography (CT) or MRI features, such as types of enhancement pattern, intratumoral necrosis, tumor size, and non-rim diffuse and heterogeneous arterial phase hyperenhancement (non-rim dh-APHE), have been reported to be associated with VETC. [8][9][10][11] Yu et al predicted the preoperative VETC and prognosis of HCC patients based on radiomics features of the hepatobiliary phase (HBP) of gadolinium-ethoxybenzyldiethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI. 12 However, the criteria for preoperative imaging diagnosis of VETC have not been widely accepted, and more robust evidence is needed.…”