The value of CT-based radiomics nomogram in differential diagnosis of different histological types of gastric cancer.

ABSTRACT: To establish and verify a nomogram based on computed tomography (CT) radiomics analysis to predict the histological types of gastric cancer preoperatively for patients with surgical indications. A sum of 171 patients with gastric cancer were included into this retrospective study. The least absolute shrinkage and selection operator (LASSO) was used for feature selection while the multivariate Logistic regression method was used for radiomics model and nomogram building. The area under curve (AUC) was used for performance evaluation in this study. The radiomics model got AUCs of 0.755 (95% CI 0.650-0.859), 0.71 (95% CI 0.543-0.875) and 0.712 (95% CI 0.500-0.923) for histological prediction in the training, the internal and external verification cohorts. The radiomics nomogram based on radio

SUBMITTER: Huang H 

PROVIDER: S-EPMC9747822 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature