A nomogram model of spectral CT quantitative parameters and clinical characteristics predicting lymphovascular invasion of gastric cancer
Yong-Xiu Tong,
Xiao Ye,
Yong-Qin Chen,
Ya-ru You,
Hui-Juan Zhang,
Shu-Xiang Chen,
Li-Li Wang,
Yun-Jing Xue,
Li-Hong Chen
Affiliations
Yong-Xiu Tong
Department of Radiology, Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, China
Xiao Ye
Department of Radiology, Fujian Provincial Geriatric Hospital, Fuzhou, 350001, China
Yong-Qin Chen
Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, 350001, China
Ya-ru You
Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China
Hui-Juan Zhang
Department of Radiology, Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, China
Shu-Xiang Chen
Department of Radiology, Provincial Clinical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, China
Li-Li Wang
Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China; Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors (Fujian Medical University), Fuzhou, 350001, China
Yun-Jing Xue
Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China; Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors (Fujian Medical University), Fuzhou, 350001, China
Li-Hong Chen
Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China; Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors (Fujian Medical University), Fuzhou, 350001, China; Corresponding author. Department of Radiology, Fujian Medical University Union Hospital, Fuzhou 350001, China.
Objective: 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). Methods: 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. Results: Four clinical characteristics or spectral CT quantitative parameters, including Borrmann classification (P = 0.039), CA724 (P = 0.007), tumor thickness (P = 0.031), and iodine concentration in the venous phase (VIC) (P = 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. Conclusion: 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.
