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Background: Postoperative recurrence impedes the curability of early-stage hepatocellular carcinoma (E-HCC). We aimed to establish a novel recurrencerelated pathological prognosticator with artificial intelligence, and investigate the relationship between pathological features and the local immunological microenvironment. Methods: A total of 576 whole-slide images (WSIs) were collected from 547 patients with E-HCC in the Zhongshan cohort, which was randomly divided into a training cohort and a validation cohort. The external validation cohort comprised 147 Tumor Node Metastasis (TNM) stage I patients from The Cancer Genome Atlas (TCGA) database. Six types of HCC tissues were identified by a weakly supervised convolutional neural network. A recurrence-related histological score (HS) was constructed and validated. The correlation between immune microenvironment and HS was evaluated through extensive immunohistochemical data. Results: The overall classification accuracy of HCC tissues was 94.17%. The Cindexes of HS in the training, validation and TCGA cohorts were 0.804, 0.739 and 0.708, respectively. Multivariate analysis showed that the HS (HR= 4.05, 95% CI: 3.40-4.84) was an independent predictor for recurrence-free survival. Patients in HS high-risk group had elevated preoperative alpha-fetoprotein levels, poorer tumor differentiation and a higher proportion of microvascular invasion. The immunohistochemistry data linked the HS to local immune cell infiltration. HS was positively correlated with the expression level of peritumoral CD14+ cells (p= 0.013), and negatively with the intratumoral CD8+ cells (p< 0.001). Conclusions: The study established a novel histological score that predicted short-term and long-term recurrence for E-HCCs using deep learning, which could facilitate clinical decision making in recurrence prediction and management. [ABSTRACT FROM AUTHOR]

Background: Whether perioperative blood transfusions (PBTs) adversely influence oncological outcomes for intrahepatic cholangiocarcinoma (ICC) patients after curative resection remains undetermined.Methods: Of the 605 patients who underwent curative liver resection for ICC between 2000 and 2012, 93 received PBT. We conducted Cox regression and variable selection logistic regression analyses to identify confounding factors of PBT. Propensity score matching (PSM) and Cox regression analyses were used to compare the overall survival (OS) and disease-free survival (DFS) between the patients with or without PBT.Results: After exclusion, 93 eligible patients (15.4%) received PBT, compared with 512 (84.6%) who did not receive PBT; the groups were highly biased in terms of the propensity score (PS) analysis (0.096 ± 0.104 vs. 0.479 ± 0.372, p < 0.001). PBT was associated with an increased risk of OS (HR: 1.889, 95% CI: 1.446-2.468, p < 0.001) and DFS (HR: 1.589, 95% CI: 1.221-2.067, p < 0.001) in the entire cohort. After propensity score matching (PSM), no bias was observed between the groups (PS,0.136 ± 0.117 VS. 0.193 ± 0.167, p = 0.785). In the multivariate Cox analysis, PBT was not associated with increased risks of OS (HR: 1.172, 95% CI: 0.756-1.816, p = 0.479) and DFS (HR: 0.944, 95% CI: 0.608-1.466, p = 0.799). After propensity score adjustment, PBT was still not associated with OS or DFS after ICC curative resection.Conclusions: The present study found that PBT did not affect DFS and OS after curative resection of ICC. [ABSTRACT FROM AUTHOR]