Gastrointestinal stromal tumors: associations between contrast-enhanced CT images and KIT exon 11 gene mutation

Xijiao Liu; Yuan Yin; Xiaozhou Wang; Caiwei Yang; Shang Wan; Xiaonan Yin; Tingfan Wu; Huijiao Chen; Zhongming Xu; Xin Li; Bin Song; Bo Zhang

doi:10.21037/atm-21-3811

Gastrointestinal stromal tumors: associations between contrast-enhanced CT images and KIT exon 11 gene mutation

Ann Transl Med. 2021 Oct;9(19):1496. doi: 10.21037/atm-21-3811.

Authors

Xijiao Liu^#¹, Yuan Yin^#², Xiaozhou Wang^#³, Caiwei Yang¹, Shang Wan¹, Xiaonan Yin², Tingfan Wu⁴, Huijiao Chen⁵, Zhongming Xu³, Xin Li⁶, Bin Song¹, Bo Zhang²

Affiliations

¹ Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
² Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, China.
³ Department of Radiology, Meishan People's Hospital, Meishan, China.
⁴ Clinical Education Team, GE Healthcare China, Shanghai, China.
⁵ Department of Pathology, West China Hospital, Sichuan University, Chengdu, China.
⁶ Global Research, GE Healthcare China, Shanghai, China.

^# Contributed equally.

Abstract

Background: Mutation screening for gastrointestinal stromal tumor (GIST) is crucial and the c kit gene (KIT) exon 11 mutation is the most common type. This study aimed to explore the associations between GIST with KIT exon 11 mutation and contrast-enhanced computed tomography (CT) images.

Methods: Pathologically proven GISTs with definitive genotype testing results in our hospital were retrospectively included. Abdominal contrast-enhanced CT images were analyzed. Conventional CT image features and radiomic features were recorded and extracted to build the following models: model _[CT], model _{[radiomic + clinic]} and model _{[CT + radiomic + clinic]}. The diagnostic performances of GISTs with KIT exon 11 mutation and KIT exon 11 deletion involving codons 557-558 were evaluated.

Results: In total, 327 GISTs (255 with KIT exon 11 mutation, and 73 with KIT exon 11 mutation deletion involving codons 557-558) were included. Significant CT features were found for GISTs with KIT exon 11 mutation. The area under curves (AUCs) of the models for KIT exon 11 mutation were 0.7158, 0.7530, and 0.8375 in the training cohort, and 0.6777, 0.7349, and 0.8105 in validation cohort, respectively. The AUCs of the models for KIT exon 11 mutation deletion involving codons 557-558 were 0.7155, 8621, and 0.8691 in the training cohort, and 0.7099, 0.8355, and 0.8488 in the validation cohort, respectively. The model _{[CT + radiomic + clinic]} demonstrated the highest AUCs for prediction of KIT exon 11 mutation and those with deletion involving codons 557-558 (P<0.05), respectively. The model _{[radiomic + clinic]} showed higher diagnostic performance than model _[CT] significantly.

Conclusions: Our results demonstrated the associations between GIST with KIT exon 11 mutation and contrast-enhanced CT images. We found combing conventional image analysis and texture analysis is a useful tool to distinguish GIST with KIT exon 11 mutation. CT radiogenomics exhibited good application potential in predict the KIT exon 11 mutation of GIST.

Keywords: Gastrointestinal stromal tumor (GIST); KIT exon 11; computed tomography; imaging genomics; mutation.