Differential diagnosis and molecular stratification of gastrointestinal stromal tumors on CT images using a radiomics approach
This work addresses a challenging diagnostic and molecular stratification problem for clinicians treating rare gastrointestinal tumors, but it is incremental as it applies an existing radiomics method to new data with mixed results.
This study tackled the problem of distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and predicting molecular markers in GISTs using radiomics on CT images, achieving an AUC of 0.82 for tumor distinction, similar to radiologists, but failing to predict mutations or mitotic index effectively with AUCs around 0.52-0.56.
Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA,BRAF mutational status and mitotic index (MI). All 247 included patients (125 GISTS, 122 non-GISTs) underwent a contrast-enhanced venous phase CT. The GIST vs. non-GIST radiomics model, including imaging, age, sex and location, had a mean area under the curve (AUC) of 0.82. Three radiologists had an AUC of 0.69, 0.76, and 0.84, respectively. The radiomics model had an AUC of 0.52 for c-KIT, 0.56 for c-KIT exon 11, and 0.52 for the MI. Hence, our radiomics model was able to distinguish GIST from non-GISTS with a performance similar to three radiologists, but was not able to predict the c-KIT mutation or MI.