Tong Yong-Xiu, Ye Xiao, Chen Yong-Qin, You Ya-Ru, Zhang Hui-Juan, Chen Shu-Xiang, Wang Li-Li, Xue Yun-Jing, Chen Li-Hong
Department of Radiology, Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, China.
Department of Radiology, Fujian Provincial Geriatric Hospital, Fuzhou, 350001, China.
Heliyon. 2024 Apr 3;10(7):e29214. doi: 10.1016/j.heliyon.2024.e29214. eCollection 2024 Apr 15.
The study established a nomogram based on quantitative parameters of spectral computed tomography (CT) and clinical characteristics, aiming to evaluate its predictive value for preoperative lymphovascular invasion (LVI) in gastric cancer (GC).
From December 2019 to December 2021, 171 patients with pathologically confirmed GC were retrospectively collected with corresponding clinical data and spectral CT quantitative data. Patients were divided into LVI-positive and LVI-negative groups based on their pathological results. The univariate and multivariate logistic regression analyses were used to identify the risk factors and construct a nomogram. The calibration curve and receiver operating characteristic (ROC) curve were adopted to evaluate the predictive accuracy of nomogram.
Four clinical characteristics or spectral CT quantitative parameters, including Borrmann classification ( = 0.039), CA724 ( = 0.007), tumor thickness ( = 0.031), and iodine concentration in the venous phase (VIC) ( = 0.004) were identified as independent factors for LVI in GC patients. The nomogram was established based on the four factors, which had a potent predictive accuracy in the training, internal validation and external validation cohorts, with the area under the ROC curve (AUC) of 0.864 (95% CI, 0.798-0.930), 0.964 (95% CI, 0.903-1.000) and 0.877 (95% CI, 0.759-0.996), respectively.
This study constructed a comprehensive nomogram consisting spectral CT quantitative parameters and clinical characteristics of GC, which exhibited a robust efficiency in predicting LVI in GC patients.
本研究基于光谱计算机断层扫描（CT）的定量参数和临床特征建立了一种列线图，旨在评估其对胃癌（GC）术前淋巴管侵犯（LVI）的预测价值。
回顾性收集2019年12月至2021年12月期间171例经病理确诊的GC患者的相应临床资料和光谱CT定量数据。根据病理结果将患者分为LVI阳性组和LVI阴性组。采用单因素和多因素逻辑回归分析确定危险因素并构建列线图。采用校准曲线和受试者工作特征（ROC）曲线评估列线图的预测准确性。
四个临床特征或光谱CT定量参数，包括Borrmann分型（P = 0.039）、CA724（P = 0.007）、肿瘤厚度（P = 0.031）和静脉期碘浓度（VIC）（P = 0.004）被确定为GC患者LVI的独立因素。基于这四个因素建立了列线图，其在训练队列、内部验证队列和外部验证队列中均具有较强的预测准确性，ROC曲线下面积（AUC）分别为0.864（95%CI，0.798 - 0.930）、0.964（95%CI，0.903 - 1.000）和0.877（95%CI，0.759 - 0.996）。
本研究构建了一个综合列线图，包含GC的光谱CT定量参数和临床特征，在预测GC患者LVI方面表现出强大的效能。
