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

Author:

Wang Ping1,Chen Kaige1,Han Ying1,Zhao Min2,Abiyasi Nanding1,Peng Haiyong1,Yan Shaolei1,Shang Jiming1,Shang Naijian1,Meng Wei1ORCID

Affiliation:

1. Radiology Department, Harbin Medical University, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, Heilongjiang, 150081, China

2. Pharmaceutical Diagnostics, GE Healthcare, Beijing, China, 1#Tongji South Road, Daxing District, Beijing, 100176, China

Abstract

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.

Publisher

Future Medicine Ltd

Subject

Cancer Research,Oncology,General Medicine

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