Department of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, No.225 Changhai, Shanghai, 200433, China.
Department of Organ Transplantation, Changhai Hospital, First Affiliated Hospital of Naval Medical University, Shanghai, 200433, China.
World J Surg Oncol. 2023 Feb 18;21(1):51. doi: 10.1186/s12957-023-02941-x.
The study aimed to explore the value of CT findings and inflammatory indicators in differentiating benign and malignant gallbladder polypoid lesions before surgery.
The study comprised a total of 113 pathologically confirmed gallbladder polypoid lesions with a maximum diameter ≥ 1 cm (68 benign and 45 malignant), all of which were enhanced CT-scanned within 1 month before surgery. The CT findings and inflammatory indicators of the patients were analyzed by univariate and multivariate logistic regression analysis to identify independent predictors of gallbladder polypoid lesions, and then a nomogram distinguishing benign and malignant gallbladder polypoid lesions was developed by combining these characteristics. The receiver operating characteristic (ROC) curve and decision curve were plotted to assess the performance of the nomogram.
Base status of the lesion (p < 0.001), plain CT value (p < 0.001), neutrophil-lymphocyte ratio (NLR) (p = 0.041), and monocyte-lymphocyte ratio (MLR) (p = 0.022) were independent predictors of malignant polypoid lesions of the gallbladder. The nomogram model established by incorporating the above factors had good performance in differentiating and predicting benign and malignant gallbladder polypoid lesions (AUC = 0.964), with sensitivity and specificity of 82.4% and 97.8%, respectively. The DCA demonstrated the important clinical utility of our nomogram.
CT findings combined with inflammatory indicators can effectively differentiate benign and malignant gallbladder polypoid lesions before surgery, which is valuable for clinical decision-making.
本研究旨在探讨 CT 表现和炎症指标在术前鉴别良恶性胆囊息肉样病变中的价值。
本研究共纳入 113 例经病理证实的最大直径≥1cm 的胆囊息肉样病变患者（68 例良性，45 例恶性），所有患者均在术前 1 个月内行增强 CT 扫描。通过单因素和多因素 logistic 回归分析，对患者的 CT 表现和炎症指标进行分析，以确定胆囊息肉样病变的独立预测因素，并结合这些特征建立鉴别良恶性胆囊息肉样病变的列线图。绘制受试者工作特征（ROC）曲线和决策曲线以评估列线图的性能。
病变基础状态（p<0.001）、平扫 CT 值（p<0.001）、中性粒细胞-淋巴细胞比值（NLR）（p=0.041）和单核细胞-淋巴细胞比值（MLR）（p=0.022）是胆囊恶性息肉样病变的独立预测因素。纳入上述因素的列线图模型在鉴别和预测良恶性胆囊息肉样病变方面具有良好的性能（AUC=0.964），其灵敏度和特异度分别为 82.4%和 97.8%。DCA 表明我们的列线图具有重要的临床实用价值。
CT 表现联合炎症指标可有效术前鉴别良恶性胆囊息肉样病变，有助于临床决策。
