Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Personalized radiomics signature to screen for KIT-11 mutation genotypes among patients with gastrointestinal stromal tumors: a retrospective multicenter study.

Journal of translational medicine - 16 Oct 2023

Zhang Qing-Wei, Zhang Ran-Ying, Yan Zhi-Bo, Zhao Yu-Xuan, Wang Xin-Yuan, Jin Jing-Zheng, Qiu Qi-Xuan, Chen Jie-Jun, Xie Zhen-Hui, Lin Jiang, Cao Hui, Zhou Yan, Chen Hui-Min, Li Xiao-Bo

Abstract excerpt

OBJECTIVES: Gastrointestinal stromal tumors (GISTs) carrying different KIT exon 11 (KIT-11) mutations exhibit varying prognoses and responses to Imatinib. Herein, we aimed to determine whether computed tomography (CT) radiomics can accurately stratify KIT-11 mutation genotypes to benefit Imatinib therapy and GISTs monitoring. METHODS: Overall, 1143 GISTs from 3 independent centers were separated into a training...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Gastrointestinal Stromal Tumors
Share to Genotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Imatinib Mesylate

Share to Mutation

Share to Proto-Oncogene Proteins c-kit

Share to Receptor Protein-Tyrosine Kinases

Source

Open in PubMed Open full text

Identifiers

PMID: 37845765
DOI: 10.1186/s12967-023-04520-w
PMCID: PMC10577986

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Personalized radiomics signature to screen for KIT-11 mutation genotypes among patients with gastrointestinal stromal tumors: a retrospective multicenter study.PMID 37845765Read ↗

Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study.Semantic proximity Read ↗

Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center studySemantic proximity Read ↗

Gastrointestinal stromal tumors: associations between contrast-enhanced CT images and KIT exon 11 gene mutationSemantic proximity Read ↗

Predictive Value of a Radiomics Nomogram Model Based on Contrast-Enhanced Computed Tomography for KIT Exon 9 Gene Mutation in Gastrointestinal Stromal Tumors.Semantic proximity Read ↗

CT Radiogenomics for Differentiating KIT Exon 11 from non-KIT Exon 11 Gene Mutations in Small Intestinal Gastrointestinal Stromal TumorsSemantic proximity Read ↗

Prediction of Mutations and Outcome in Gastrointestinal Stromal Tumors with Deep Learning: A Multicenter, Multinational StudySemantic proximity Read ↗

Identification of D842V mutation in gastrointestinal stromal tumors based on CT radiomics: a multi-center study.Semantic proximity Read ↗

Deep Learning Predicts Mutations and Outcomes in Gastrointestinal Stromal Tumors.Semantic proximity Read ↗

Molecular Features of Gastrointestinal Stromal Tumors: A Single Referral Cancer Center Experience.Semantic proximity Read ↗

Preoperative prediction of KRAS mutation status in colorectal cancer using a CT-based radiomics nomogram.Semantic proximity Read ↗

Study on the Combined Prediction Model of c-KIT and PDGFRa Gene Mutation Status and Clinicopathological Features in 241 Patients with Gastrointestinal Stromal TumorsSemantic proximity Read ↗

Impact of Mutation Profile on Outcomes of Neoadjuvant Therapy in GISTSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.