Li Yuan, Cao Yingying, Zhang Yaping, Zhou Tao, Xia Fan, Ren Shuai, Wang Zhongqiu
Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China.
J Cancer. 2025 Jun 12;16(9):2812-2821. doi: 10.7150/jca.111548. eCollection 2025.
The distinction between pancreatic ductal adenocarcinoma (PDAC) and benign pancreatic lesions remains challenging. This study aimed to evaluate the utility of computed tomography (CT) imaging features and clinical characteristics in differentiating PDAC from benign pancreatic lesions. In this retrospective study, a total of 97 patients with PDAC and 90 patients with benign pancreatic lesions were included. Various imaging features and clinical characteristics were assessed. Univariable and multivariable logistic regression analyses were conducted, and receiver operating characteristic (ROC) curves and their corresponding areas under the curve (AUCs) were assessed. The optimal cut-off value for D-dimer was determined using the Youden index. The DeLong test was employed to compare the AUCs of the ROC curves between different prediction models. The clinical and radiologic models achieved AUCs of 0.86 and 0.85, respectively. Moreover, the combined model demonstrated superior predictive performance compared to either model alone. This overall model included two significant clinical predictors (D-dimer and CA19-9) and three radiological predictors (lymph node enlargement, pancreatic atrophy, and cystic components). It yielded an AUC of 0.92 (95% CI: 0.88-0.95), with a sensitivity of 83.5% and specificity of 82.2%. In addition, the optimal cut-off value of D-dimer for differentiating PDAC from benign pancreatic lesions was found to be 0.84 mg/L. The overall model including clinical and radiologic variables (e.g., serum D-dimer, CA19-9, lymph node enlargement, pancreatic atrophy, and cystic components) demonstrated higher sensitivity and specificity in differentiating PDAC from benign pancreatic lesions. Serum D-dimer may serve as a valuable adjunctive biomarker in the diagnosis of pancreatic cancer and may further enhance the diagnostic performance of CA19-9 when used in combination.
胰腺导管腺癌(PDAC)与胰腺良性病变之间的鉴别仍然具有挑战性。本研究旨在评估计算机断层扫描(CT)成像特征和临床特征在区分PDAC与胰腺良性病变中的作用。在这项回顾性研究中,共纳入了97例PDAC患者和90例胰腺良性病变患者。评估了各种成像特征和临床特征。进行了单变量和多变量逻辑回归分析,并评估了受试者操作特征(ROC)曲线及其相应的曲线下面积(AUC)。使用尤登指数确定D-二聚体的最佳截断值。采用德龙检验比较不同预测模型的ROC曲线的AUC。临床模型和放射学模型的AUC分别为0.86和0.85。此外,联合模型显示出比单独任何一个模型都更好的预测性能。这个整体模型包括两个重要的临床预测指标(D-二聚体和CA19-9)和三个放射学预测指标(淋巴结肿大、胰腺萎缩和囊性成分)。其AUC为0.92(95%CI:0.88-0.95),敏感性为83.5%,特异性为82.2%。此外,发现区分PDAC与胰腺良性病变的D-二聚体最佳截断值为0.84mg/L。包括临床和放射学变量(如血清D-二聚体、CA19-9、淋巴结肿大、胰腺萎缩和囊性成分)的整体模型在区分PDAC与胰腺良性病变方面显示出更高的敏感性和特异性。血清D-二聚体可能作为胰腺癌诊断中有价值的辅助生物标志物,与CA19-9联合使用时可能进一步提高诊断性能。