肝癌血清炎症指标及影像特征与病理分级的相关性研究

目的:探讨术前血清炎症指标及肿瘤影像特征与肝细胞癌(HCC)病理分级的相关性,分析其对HCC病理分级的诊断效能.方法:搜集150例经术后病理证实并按照Edmondson分级法进行病理分级的H CC患者,回顾性分析其临床及影像资料.记录患者的术前血清炎症指标[碱性磷酸酶/淋巴细胞计数(ALR)、中性粒细胞计数/淋巴细胞计...

Correlation between serum inflammatory indicators,imaging features and the pathological grading of hepatocellular carcinoma

Objective:This paper aimed to explore the correlation between serum inflammatory indicators combined with tumor imaging features and the pathological grading of hepatocellular carcinoma(HCC),and analyze its diagnostic efficacy for the pathological grading.Methods:Retrospective study was conducted on 150 patients with HCC which confirmed by post-operative pathology, and graded according to Edmondson pathology.The preoperative serum inflammatory indicators [alkaline phosphatase-to-lymphocyte ratio(ALR),neutrophil-to-lymphocyte ratio(NLR),platelet-to-lymphocyte ratio(PLR),and aspartate aminotransferase-to-platelet ratio index(APRI)] and tumor imaging features(tumor maximum diameter, liver lobe involvement range, intra-tumoral necrosis, satellite nodules, tumor number and capsule) of these patients were analyzed.All the patients were divided into two groups: poorly differentiated group(grade Ⅲ-Ⅳ) and moderately to well differentiated group(grade Ⅰ-Ⅱ).Statistical analysis was conducted by using single-factor non-parametric Mann-Whitney U-rank sum test, Pearson Chi-square test and Fisher’s exact test to analyze the differences between two groups.Spearman rank correlation analysis was used to analyze the correlation between these indicators and different pathological grades.Receiver operating characteristic(ROC) curves were drawn to calculate areas under the ROC curve(AUCs) for evaluating the efficacy of single-indicator and multi-indicator combination in predicting the pathological grade of HCC.Results:ALR,NLR,APRI,tumor maximum diameter, capsule, satellite nodules, liver lobe involvement range, tumor number, and intra-tumoral necrosis were positively correlated with different pathological grades.And the ROC curve obtained the best cut-off values for predicting the poorly differentiated pathological grade were >63.6,>2.22,>0.19,and >5.2 cm for ALR(AUC:0.672),NLR(AUC:0.666),APRI(AUC:0.644),and tumor maximum diameter(AUC:0.810),respectively.In addition, the AUC of combining multi-indicators was 0.825,which was significantly higher than the above single index. Conclusion:It is feasible to use preoperative serum inflammatory indicators combined with tumor imaging features as effective predictors for HCC pathological grading, and the combination of multiple indicators for predicting pathological grading is significantly better than single indicator.