ArticleCancer research and treatment2020
Magnetic Resonance-Based Texture Analysis Differentiating KRAS Mutation Status in Rectal Cancer.
Article in Cancer research and treatment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
49 citing papers in PubMed, 2 syntheses or guidelines pooled it, 80 citations in OpenAlex.
- Performance of Machine Learning in Diagnosing KRAS (Kirsten Rat Sarcoma) Mutations in Colorectal Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Repeatability of radiomics studies in colorectal cancer: a systematic review.BMC gastroenterology · 2023Pooled it
- KRAS status predicted by pretreatment MRI radiomics was associated with lung metastasis in locally advanced rectal cancer patients.BMC medical imaging · 2023Trial
- Radiomics model based on multi-sequence MR images for predicting preoperative immunoscore in rectal cancer.La Radiologia medica · 2022Trial
- Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer.Journal of translational medicine · 2021Trial
- Preoperative prediction of KRAS mutation in rectal cancer using a combined T2-weighted imaging radiomics and volumetric apparent diffusion coefficient histogram model.Abdominal radiology (New York) · 2026Article
- Development and evaluation of an explainable machine learning selection pipeline for predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.Journal of translational medicine · 2026Article
- Assessment of prognostic indicators and KRAS mutations in rectal cancer using a fractional-order calculus MR diffusion model: whole tumor histogram analysis.Abdominal radiology (New York) · 2025Article
- Differentiating small intestinal stromal tumors from primary small intestinal lymphomas using contrast-enhanced CT and texture analysis: a diagnostic study.Frontiers in oncology · 2025Article
- Research progress on predicting KRAS gene mutations in colorectal cancer by combining radiomics and multimodal medical imaging.Frontiers in oncology · 2025Review
- CT-based radiomics integrated model for brain metastases in stage III/IV ALK-positive lung adenocarcinoma patients.Frontiers in oncology · 2025Article
- The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer.Cancers · 2024Review
- A multicenter study: predicting KRAS mutation and prognosis in colorectal cancer through a CT-based radiomics nomogram.Abdominal radiology (New York) · 2024Article
- Review
- The Role of Radiomics in Rectal Cancer.Journal of gastrointestinal cancer · 2023Review
- Investigating the Feasibility of Predicting KRAS Status, Tumor Staging, and Extramural Venous Invasion in Colorectal Cancer Using Inter-Platform Magnetic Resonance Imaging Radiomic Features.Diagnostics (Basel, Switzerland) · 2023Article
- Construction of prediction model for KRAS mutation status of colorectal cancer based on CT radiomics.Japanese journal of radiology · 2023Article
- Radiomics and Radiogenomics in Pelvic Oncology: Current Applications and Future Directions.Current oncology (Toronto, Ont.) · 2023Review
- Association between Dynamic Contrast-Enhanced MRI Parameters and Prognostic Factors in Patients with Primary Rectal Cancer.Current oncology (Toronto, Ont.) · 2023Article
- Rectal MRI Interpretation After Neoadjuvant Therapy.Journal of magnetic resonance imaging : JMRI · 2023Review
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
purposeMutation of the Kirsten Ras (KRAS) oncogene is present in 30%-40% of colorectal cancers and has prognostic significance in rectal cancer. In this study, we examined the ability of radiomics features extracted from T2-weighted magnetic resonance (MR) images to differentiate between tumors with mutant KRAS and wild-type KRAS. MATERIALS AND
methodsSixty patients with primary rectal cancer (25 with mutant KRAS, 35 with wild-type KRAS) were retrospectively enrolled. Texture analysis was performed in all regions of interest on MR images, which were manually segmented by two independent radiologists. We identified potentially useful imaging features using the two-tailed t test and used them to build a discriminant model with a decision tree to estimate whether KRAS mutation had occurred.
resultsThree radiomic features were significantly associated with KRASmutational status (p < 0.05). The mean (and standard deviation) skewness with gradient filter value was significantly higher in the mutant KRAS group than in the wild-type group (2.04±0.94 vs. 1.59±0.69). Higher standard deviations for medium texture (SSF3 and SSF4) were able to differentiate mutant KRAS (139.81±44.19 and 267.12±89.75, respectively) and wild-type KRAS (114.55±29.30 and 224.78±62.20). The final decision tree comprised three decision nodes and four terminal nodes, two of which designated KRAS mutation. The sensitivity, specificity, and accuracy of the decision tree was 84%, 80%, and 81.7%, respectively.
conclusionUsing MR-based texture analysis, we identified three imaging features that could differentiate mutant from wild-type KRAS. T2-weighted images could be used to predict KRAS mutation status preoperatively in patients with rectal cancer.
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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.