■胰腺导管腺癌(PDAC)患者的区域淋巴结(LN)清扫没有统一的范围。不完整的局部LN夹层可导致术后复发,而区域LN夹层范围的盲目扩大会显着增加围手术期风险,而不会显着延长总生存期。我们旨在建立一种基于双层探测器能谱计算机断层扫描(DLCT)的无创可视化工具,以预测PDAC患者发生局部LN转移的可能性。
■对总共163个区域性LN进行了审查,并将其分为转移性队列(n=58个LN)和非转移性队列(n=105个LN)。在两个队列之间比较了DLCT定量参数以及区域LN的最长轴与最短轴(L/S)的节点比。DLCT定量参数包括动脉期碘浓度(APIC),动脉期标准化碘浓度(APNIC),动脉期有效原子序数(APZeff),动脉期归一化有效原子序数(APNZeff),动脉期频谱衰减曲线的斜率(APλHU),门静脉期碘浓度(PVPIC),门静脉期标准化碘浓度(PVPNIC),门静脉阶段的有效原子序数(PVPZeff),门静脉期归一化有效原子序数(PVPNZeff),以及门静脉期(PVPλHU)的光谱衰减曲线的斜率。采用基于曲线下面积(AUC)的Logistic回归分析对有意义的DLCT定量参数的诊断性能,L/S,以及将重要的DLCT定量参数和L/S相结合的模型。开发了基于具有最高诊断性能的模型的列线图作为预测指标。通过校准曲线和决策曲线分析(DCA)评估列线图的拟合优度和临床适用性。
■APNIC+L/S(APNIC+L/S)的组合型号在所有型号中具有最高的诊断性能,产生AUC,灵敏度,和0.878的特异性[95%置信区间(CI):0.825-0.931],分别为0.707和0.886。校准曲线表明APNIC-L/S列线图在预测概率和实际概率之间具有良好的一致性。同时,决策曲线表明,APNIC-L/S列线图可以产生比全部或不干预策略更大的净收益,阈值概率范围从0.0到0.75。
■作为一种有效且可视的非侵入性预测工具,在PDAC患者中,APNIC-L/S列线图对鉴别转移性LN具有良好的预测功效.
UNASSIGNED: There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete regional LN dissection can lead to postoperative recurrence, while blind expansion of the scope of regional LN dissection significantly increases the perioperative risk without significantly prolonging overall survival. We aimed to establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) to predict the probability of regional LN metastasis in patients with PDAC.
UNASSIGNED: A total of 163 regional LNs were reviewed and divided into a metastatic cohort (n=58 LNs) and nonmetastatic cohort (n=105 LNs). The DLCT quantitative parameters and the nodal ratio of the longest axis to the shortest axis (L/S) of the regional LNs were compared between the two cohorts. The DLCT quantitative parameters included the iodine concentration in the arterial phase (APIC), normalized iodine concentration in the arterial phase (APNIC), effective atomic number in the arterial phase (APZeff), normalized effective atomic number in the arterial phase (APNZeff), slope of the spectral attenuation curves in the arterial phase (APλHU), iodine concentration in the portal venous phase (PVPIC), normalized iodine concentration in the portal venous phase (PVPNIC), effective atomic number in the portal venous phase (PVPZeff), normalized effective atomic number in the portal venous phase (PVPNZeff), and slope of the spectral attenuation curves in the portal venous phase (PVPλHU). Logistic regression analysis based on area under the curve (AUC) was used to analyze the diagnostic performance of significant DLCT quantitative parameters, L/S, and the models combining significant DLCT quantitative parameters and L/S. A nomogram based on the models with highest diagnostic performance was developed as a predictor. The goodness of fit and clinical applicability of the nomogram were assessed through calibration curve and decision curve analysis (DCA).
UNASSIGNED: The combined model of APNIC + L/S (APNIC + L/S) had the highest diagnostic performance among all models, yielding an AUC, sensitivity, and specificity of 0.878 [95% confidence interval (CI): 0.825-0.931], 0.707, and 0.886, respectively. The calibration curve indicated that the APNIC-L/S nomogram had good agreement between the predicted probability and the actual probability. Meanwhile, the decision curve indicated that the APNIC-L/S nomogram could produce a greater net benefit than could the all- or-no-intervention strategy, with threshold probabilities ranging from 0.0 to 0.75.
UNASSIGNED: As a valid and visual noninvasive prediction tool, the APNIC-L/S nomogram demonstrated favorable predictive efficacy for identifying metastatic LNs in patients with PDAC.