AIMC Topic: Gastrointestinal Stromal Tumors
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An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.
BMC gastroenterology
Apr 9, 2025
BACKGROUND: Gastric stromal tumors (GSTs) and gastric leiomyomas (GLs) represent the primary subtypes of gastric submucosal tumors (SMTs) characterized by distinct biological characteristics and treatment modalities. The accurate differentiation betw...
Next questions on gastrointestinal stromal tumors: unresolved challenges and future directions.
Current opinion in oncology
Apr 4, 2025
PURPOSE OF REVIEW: Despite remarkable progress in the management of gastrointestinal stromal tumors (GISTs), critical challenges persist. Key aspects such as risk stratification, the optimal duration of adjuvant therapy, and strategies to enhance the...
A deep-learning model for predicting tyrosine kinase inhibitor response from histology in gastrointestinal stromal tumor.
The Journal of pathology
Feb 14, 2025
Over 90% of gastrointestinal stromal tumors (GISTs) harbor mutations in KIT or PDGFRA that can predict response to tyrosine kinase inhibitor (TKI) therapies, as recommended by NCCN (National Comprehensive Cancer Network) guidelines. However, gene seq...
Receptor, Platelet-Derived Growth Factor alpha
Gastrointestinal Neoplasms
Gastrointestinal Stromal Tumors
Imatinib Mesylate
Pyrazoles
Middle Aged
Protein Kinase Inhibitors
Triazines
Humans
Pyrroles
Deep Learning
Proto-Oncogene Proteins c-kit
Treatment Outcome
Tyrosine Kinase Inhibitors
Mutation
Female
Aged
Male
Interpretable machine learning model based on CT semantic features and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors.
Scientific reports
Nov 26, 2024
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...
Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Oct 22, 2024
BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies according to risk. However, no specific protocols exist for preoperative assessment of the malignant potential of gastric GISTs (gGISTs). This study ai...
Imatinib adherence prediction using machine learning approach in patients with gastrointestinal stromal tumor.
Cancer
Sep 6, 2024
BACKGROUND: Nonadherence to imatinib is common in patients with gastrointestinal stromal tumor (GIST), which is associated with poor prognosis and financial burden. The primary aim of this study was to investigate the adherence rate in patients with ...
Interpretable artificial intelligence to optimise use of imatinib after resection in patients with localised gastrointestinal stromal tumours: an observational cohort study.
The Lancet. Oncology
Jul 5, 2024
BACKGROUND: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We ...
Deep learning analysis for differential diagnosis and risk classification of gastrointestinal tumors.
Scandinavian journal of gastroenterology
Jul 1, 2024
OBJECTIVES: Recently, artificial intelligence (AI) has been applied to clinical diagnosis. Although AI has already been developed for gastrointestinal (GI) tract endoscopy, few studies have applied AI to endoscopic ultrasound (EUS) images. In this st...
Differentiating Gastrointestinal Stromal Tumors From Leiomyomas of Upper Digestive Tract Using Convolutional Neural Network Model by Endoscopic Ultrasonography.
Journal of clinical gastroenterology
Jul 1, 2024
BACKGROUND: Gastrointestinal stromal tumors (GISTs) and leiomyomas are the most common submucosal tumors of the upper digestive tract, and the diagnosis of the tumors is essential for their treatment and prognosis. However, the ability of endoscopic ...
Preoperative CT-based radiomics and deep learning model for predicting risk stratification of gastric gastrointestinal stromal tumors.
Medical physics
Jun 27, 2024
BACKGROUND: Gastrointestinal stromal tumors (GISTs) are clinically heterogeneous with various malignant potential in different individuals. It is crucial to explore a reliable method for preoperative risk stratification of gastric GISTs noninvasively...
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