ArticleWorld journal of gastrointestinal oncology2024
Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor.
Article in World journal of gastrointestinal oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPreoperative knowledge of mutational status of gastrointestinal stromal tumors (GISTs) is essential to guide the individualized precision therapy.
aimTo develop a combined model that integrates clinical and contrast-enhanced computed tomography (CE-CT) features to predict gastric GISTs with specific genetic mutations, namely
methodsA total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio. The models were constructed using selected clinical features, conventional CT features, and radiomics features extracted from abdominal CE-CT images. Three models were developed: Model
resultsThe ROC analyses revealed that in the training cohort, the area under the curve (AUC) values for model
conclusionOur findings demonstrate that the combined model
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