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Tong YX, Ye X, Chen YQ, You YR, Zhang HJ, Chen SX, Wang LL, Xue YJ, Chen LH. A nomogram model of spectral CT quantitative parameters and clinical characteristics predicting lymphovascular invasion of gastric cancer. Heliyon 2024; 10:e29214. [PMID: 38601586 PMCID: PMC11004867 DOI: 10.1016/j.heliyon.2024.e29214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 04/02/2024] [Accepted: 04/02/2024] [Indexed: 04/12/2024] Open
Abstract
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.
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Affiliation(s)
- 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
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