LAUSR

OBJECTIVE To evaluate CT texture analysis as a tool to differentiate gastrointestinal stromal tumors (GISTs) without KIT exon 11 mutation. MATERIALS AND METHODS This study consisted of a study group of 69 GISTs and a validation group of 17 GISTs. Clinical information of the patients were collected and analyzed. Two-dimensional and three-dimensional texture analysis was performed. The textural parameters were evaluated in the study group and were validated in the validation group. The repeatability of the textural parameters on the single region of interest (single-ROI), double-ROI, and whole volume of interest (whole-VOI) was analyzed. The independent predictor for the GIST genotypes was analyzed with logistic regression models. The support vector machine (SVM) classifiers were also trained and 6-fold cross validation ROC curves were computed. Subjective heterogeneity scores of each lesion on enhanced CT images were given by radiologists and the corresponding difference of the heterogeneity rating was evaluated. RESULTS The non-gastric location, lower CD34_stain level and higher textural parameter standard Deviation (stdDeviation) were associated with the GISTs without KIT exon 11 mutation in the study group. The cross validation SVM classifiers achieved with combination of stdDeviation, anatomic location and CD34_stain level demonstrated medium to good prediction efficiency (AUC = 0.864-0.904) regarding the GIST genotypes. The stdDeviation was an independent predictor of GISTs without KIT exon 11 mutation, and had a medium correlation with the GIST genotypes in the study group (AUC = 0.726-0.750). The stdDeviation showed good performance (AUC = 0.904-0.962) when validated in the validation group. The double-ROIs improved the performances of single-ROIs, decreasing the variances of single-ROIs brought by section-selection, and demonstrating excellent agreements between ROIs and whole-VOI. Subjective heterogeneity scores had no statistically significant differences between GIST genotypes. CONCLUSION CT texture analysis can potentially help to differentiate GISTs without KIT exon 11 mutation from those GISTs with KIT exon 11 mutation on enhanced CT images.