Objective:To analyze the influencing factors of abnormal 15-minute retention rate of indocyanine green (ICG R15) (≥10%) in patients with hepatocellular carcinoma, and to construct a nomogram model, and to evaluate the prediction efficiency of the nomogram model.Methods:The clinical data of 190 patients with hepatocellular carcinoma in Zhengzhou University People's Hospital from December 2017 to June 2022 were retrospectively analyzed, including 148 males and 42 females, aged (57.8±9.9) years. According to ICG R15, the patients were divided into ICG R15 normal group ( n=134, ICG R15<10%) and ICG R15 abnormal group ( n=56, ICG R15≥10%). Univariate and multivariate logistic regression were used to analyze the influencing factors of abnormal ICG R15, and the nomogram model was established. The predictive ability of the model was evaluated by receiver operating characteristic (ROC) curve and C-index, and the model was verified by calibration curve and decision analysis curve. Results:Abnormal ICG R15 group the proportion of liver cirrhosis, albumin ≤35 g/L, hemoglobin ≤110 g/L, platelet count ≤100×10 9/L, prothrombin time >13 s, alanine aminotransferase >40 U/L, aspartate aminotransferase >40 U/L, total bilirubin >34.2 μmol/L, and the largest tumor diameter >5.0 cm, spleen volume >383.1 cm 3, spleen volume to of non-tumor liver volume (SNLR) >0.276 and liver tumor volume >117.2 cm 3 were higher than that of ICG R15 normal group, and the differences were statistically significant (all P<0.05). Logistic regression analysis showed that liver cirrhosis ( OR=3.89, 95% CI: 1.28-11.80, P=0.016), spleen volume >383.1 cm 3( OR=5.17, 95% CI: 1.38-19.38, P=0.015), SNLR >0.276 ( OR=5.54, 95% CI: 1.44-21.26, P=0.013) and total bilirubin >34.2 μmol/L( OR=10.20, 95% CI: 1.88-55.39, P=0.007) increased the risk of abnormal ICG R15. A nomogram model was constructed based on the above risk factors. The C-index of the model was 0.915 (95% CI: 0.872-0.957), and the area under the ROC curve predicted by the nomogram model was 0.915 (95% CI: 0.871-0.958). The calibration curve showed that the correlation index of the abnormal ICG R15 predicted by the nomogram was similar to actual situation. Decision analysis curve showed high returns. Conclusion:Liver cirrhosis, spleen volume >383.1 cm 3, SNLR>0.276 and total bilirubin >34.2 μmol/L were indepentlent risk factors for abnormal ICG R15 in patients with hepatocellur carcinoma. The clinical prediction model of ICG R15 abnormality constructed by nomogram has good prediction efficiency, which can provide a reference for evaluating preoperative liver reserve function of patients with hepatocellular carcinoma.

Objective:To investigate the influencing factors for microvascular invasion (MVI) in hepatocellular carcinoma based on three-dimensional visualization and the construction of its nomogram model.Methods:The retrospective cohort study method was conducted. The clinico-pathological data of 190 patients with hepatocellular carcinoma who were admitted to Henan University People′s Hospital from May 2018 to May 2021 were collected. There were 148 males and 42 females, aged (58±12)years. The 190 patients were randomly divided into the training set of 133 cases and the validation set of 57 cases by the method of random number table in the ratio of 7:3. The abdominal three-dimensional visualization system was used to characterize the tumor morphology and other imaging features. Observation indicators: (1) analysis of influencing factors for MVI in hepatocellular carcinoma; (2) construction and evaluation of nomogram model of MVI in hepatocellular carcinoma. Measurement data with normal distribution were expressed as Mean± SD, and independent sample t test was used for comparison between groups. Measurement data with skewed distribution were expressed as M( Q1, Q3), and non-parametric rank sum test was used for comparison between groups. Count data were expressed as absolute numbers, and the chi-square test was used for comparison between groups. Corresponding statistical methods were used for univariate analysis. Binary Logistic regression model was used for multivariate analysis. Receiver operator characteristic (ROC) curves were plotted, and the nomogram model was assessed by area under the curve (AUC), calibration curve, and decision curve. Results:(1) Analysis of influencing factors for MVI in hepatocellular carcinoma. Among 190 patients with hepatocellular carcinoma, there were 97 cases of positive MVI (including 63 cases in the training set and 34 cases in the validation set) and 93 cases of negative MVI (including 70 cases in the training set and 23 cases in the validation set). Results of multivariate analysis showed that alpha-fetoprotein, vascular endothelial growth factor, tumor volume, the number of tumors, and tumor morphology were independent factors affecting the MVI of patients with hepatocellular carcinoma ( odds ratio=5.06, 3.62, 1.00, 2.02, 2.59, 95% confidence interval as 1.61-15.90, 1.28-10.20, 1.00-1.01, 1.02-3.98, 1.03-6.52, P<0.05). (2) Construction and evaluation of nomogram model of MVI in hepatocellular carcinoma. The results of multivariate analysis were incorporated to construct a nomogram prediction model for MVI of hepatocellular carcinoma. ROC curves showed that the AUC of the training set of nomogram model was 0.85 (95% confidence interval as 0.79-0.92), the optimal fractional cutoff based on the Jordon′s index was 0.51, the sensitivity was 0.71, and the specificity was 0.84. The above indicators of validation set were 0.92 (95% confidence interval as 0.85-0.99), 0.50, 0.90, and 0.82, respectively. The higher total score of the training set suggested a higher risk of MVI in hepatocellular carcinoma. The calibration curves of both training and validation sets of nomogram model fitted well with the standard curves and have a high degree of calibration. The decision curve showed a high net gain of nomogram model. Conclusions:Alpha-fetoprotein, vascular endothelial growth factor, tumor volume, the number of tumors, and tumor morphology are independent influencing factors for MVI in patients with hepatocellular carcinoma. A nomogram model constructed based on three-dimensional visualized imaging features can predict MVI in hepatocellular carcinoma.

Objective:To study the impact of the age-adjusted Charlson comorbidity index (ACCI) on the prognosis of patients with hilar cholangiocarcinoma following laparoscopic surgical resection.Methods:Clinical data of 136 patients with hilar cholangiocarcinoma undergoing laparoscopic surgery at Zhengzhou University People's Hospital between January 2013 and January 2018 were retrospectively analyzed, including 81 males and 55 females, aged (63.6±9.8) years. Patients were divided into two groups based on the median ACCI score of 4.0: the high ACCI group (ACCI>4.0, n=49) and low ACCI group (ACCI≤4.0, n=87). The prognosis was compared between the two group. Univariate and multivariate Cox regression analyses were performed to analyze the effect of ACCI on survival after laparoscopic surgery. Results:The 1- and 3-year cumulative survival rates in low ACCI group were 87.4% and 48.3%, respectively, compared to 53.1% and 4.1% in high ACCI group ( χ2=27.97, P<0.001). Univariate Cox regression analysis indicated that ACCI >4.0 was associated with prognosis ( HR=3.73, 95% CI: 2.44-5.68, P<0.001). Multivariate Cox regression analysis also indicated that ACCI >4.0 was associated with an increased risk of postoperative mortality in patients with hilar cholangiocarcinoma ( HR=2.69, 95% CI: 1.65-4.37, P<0.001). Conclusion:The ACCI is a significant risk factor for survival of patients with hilar cholangiocarcinoma following laparoscopic surgery, which could facilitate a precise preoperative assessment of patient status and choice of surgical approach.