ReviewWorld journal of gastroenterology2020
New advances in radiomics of gastrointestinal stromal tumors.
Review in World journal of gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 32 citations in OpenAlex.
- A comprehensive review of immunotherapy in gastrointestinal tumors with a focus on the role of combination therapy with PARP inhibitors.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Review
- Radiomics model based on MRI to differentiate spinal multiple myeloma from metastases: A two-center study.Journal of bone oncology · 2024Article
- Article
- Identifying subtle differences : a radiomics model assessment for gastric schwannomas and gastrointestinal stromal tumors across risk grades.Frontiers in oncology · 2024Article
- Prediction of High-Risk Gastrointestinal Stromal Tumor Recurrence Based on Delta-CT Radiomics Modeling: A 3-Year Follow-up Study After Surgery.Clinical Medicine Insights. Oncology · 2024Article
- Computed tomography radiomics models of tumor differentiation in canine small intestinal tumors.Frontiers in veterinary science · 2024Article
- A radiomics-clinical combined nomogram-based on non-enhanced CT for discriminating the risk stratification in GISTs.Journal of cancer research and clinical oncology · 2023Article
- A combined radiomic model distinguishing GISTs from leiomyomas and schwannomas in the stomach based on endoscopic ultrasonography images.Journal of applied clinical medical physics · 2023Article
- Imaging of Gastrointestinal Tract Ailments.Journal of imaging · 2023Review
- Phenotyping the Histopathological Subtypes of Non-Small-Cell Lung Carcinoma: How Beneficial Is Radiomics?Diagnostics (Basel, Switzerland) · 2023Article
- The Neoplastic Side of the Abdominal Wall: A Comprehensive Pictorial Essay of Benign and Malignant Neoplasms.Diagnostics (Basel, Switzerland) · 2023Review
- Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers.Cancers · 2022Review
- Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview.World journal of gastroenterology · 2022Review
- Gastrointestinal stromal tumors: a comprehensive radiological review.Japanese journal of radiology · 2022Review
- Associations of CD34, Ki67, layer of invasion and clinical pathological characteristics, prognosis outcomes in gastrointestinal stromal tumors-a retrospective cohort study.Translational cancer research · 2022Article
- Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study.Frontiers in oncology · 2022Article
- New frontiers in liver ultrasound: From mono to multi parametricity.World journal of gastrointestinal oncology · 2021Review
- A deep look into radiomics.La Radiologia medica · 2021Review
- A novel CT-based radiomic nomogram for predicting the recurrence and metastasis of gastric stromal tumors.American journal of cancer research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastrointestinal stromal tumors (GISTs) are uncommon neoplasms of the gastrointestinal tract with peculiar clinical, genetic, and imaging characteristics. Preoperative knowledge of risk stratification and mutational status is crucial to guide the appropriate patients' treatment. Predicting the clinical behavior and biological aggressiveness of GISTs based on conventional computed tomography (CT) and magnetic resonance imaging (MRI) evaluation is challenging, unless the lesions have already metastasized at the time of diagnosis. Radiomics is emerging as a promising tool for the quantification of lesion heterogeneity on radiological images, extracting additional data that cannot be assessed by visual analysis. Radiomics applications have been explored for the differential diagnosis of GISTs from other gastrointestinal neoplasms, risk stratification and prediction of prognosis after surgical resection, and evaluation of mutational status in GISTs. The published researches on GISTs radiomics have obtained excellent performance of derived radiomics models on CT and MRI. However, lack of standardization and differences in study methodology challenge the application of radiomics in clinical practice. The purpose of this review is to describe the new advances of radiomics applied to CT and MRI for the evaluation of gastrointestinal stromal tumors, discuss the potential clinical applications that may impact patients' management, report limitations of current radiomics studies, and future directions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.