Prediction model based on radiomics and clinical features for preoperative lymphovascular invasion in gastric cancer patients

被引:5
作者
Wang, Ping [1 ]
Chen, Kaige [1 ]
Han, Ying [1 ]
Zhao, Min [2 ,3 ]
Abiyasi, Nanding [1 ]
Peng, Haiyong [1 ]
Yan, Shaolei [1 ]
Shang, Jiming [1 ]
Shang, Naijian [1 ]
Meng, Wei [1 ]
机构
[1] Harbin Med Univ, Harbin Med Univ Canc Hosp, Radiol Dept, 150 Haping Rd, Harbin 150081, Heilongjiang, Peoples R China
[2] GE Healthcare, Pharmaceut Diagnost, Beijing, Peoples R China
[3] 1Tongji South Rd,Daxing Dist, Beijing 100176, Peoples R China
关键词
contrast-enhanced computed tomography; gastric cancer; Lauren classification; lymphovascular invasion; radiomics; LYMPH-NODE METASTASIS; CT; ADENOCARCINOMA; PARAMETERS; MRI;
D O I
10.2217/fon-2022-1025
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: We explored whether a model based on contrast-enhanced computed tomography radiomics features and clinicopathological factors can evaluate preoperative lymphovascular invasion (LVI) in patients with gastric cancer (GC) with Lauren classification. Methods: Based on clinical and radiomic characteristics, we established three models: Clinical + Arterial phase_Radcore, Clinical + Venous phase_Radcore and a combined model. The relationship between Lauren classification and LVI was analyzed using a histogram. Results: We retrospectively analyzed 495 patients with GC. The areas under the curve of the combined model were 0.8629 and 0.8343 in the training and testing datasets, respectively. The combined model showed a superior performance to the other models. Conclusion: CECT-based radiomics models can effectively predict preoperative LVI in GC patients with Lauren classification. Tweetable abstractContrast-enhanced computed tomography-based radiomics models can effectively predict the preoperative lymphovascular invasion status in patients with gastric cancer with Lauren classification.
引用
收藏
页码:1613 / 1626
页数:14
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