ArticleAnnals of translational medicine2021
Development and validation of magnetic resonance imaging-based radiomics models for preoperative prediction of microsatellite instability in rectal cancer.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
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Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 46 citations in OpenAlex.
- Preoperative radiomics models using CT and MRI for microsatellite instability in colorectal cancer: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Diagnostic performance of radiomics models for preoperative prediction of microsatellite instability status in endometrial cancer: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Systematic review of machine learning-based radiomics approach for predicting microsatellite instability status in colorectal cancer.La Radiologia medica · 2023Pooled it
- Predicting Mismatch-Repair Status in Rectal Cancer Using Multiparametric MRI-Based Radiomics Models: A Preliminary Study.BioMed research international · 2022Trial
- Lymph node morphology as an MRI biomarker for microsatellite instability in rectal cancer.Abdominal radiology (New York) · 2026Observational
- Study on predicting microsatellite instability in rectal cancer using TCancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Interpretable intratumoral and peritumoral radiomics using SHAP for predicting microsatellite status in gastric adenocarcinoma: a dual-center study.Frontiers in oncology · 2026Article
- Preoperative CT-based radiomics model for predicting muscle invasion in patients with upper tract urothelial carcinoma below T3 stage.Abdominal radiology (New York) · 2025Article
- A radiomics model based on diffusion-weighted imaging developed using machine learning enables prediction of microsatellite instability in endometrial cancer.BMC medical imaging · 2025Article
- Multi-sequence MRI-based clinical-radiomics models for the preoperative prediction of microsatellite instability-high status in endometrial cancer.Precision radiation oncology · 2025Article
- Ensemble learning for predicting microsatellite instability in colorectal cancer using pretreatment colonoscopy images and clinical data.Frontiers in oncology · 2025Article
- Non-invasive CT radiomic biomarkers predict microsatellite stability status in colorectal cancer: a multicenter validation study.European radiology experimental · 2024Article
- A prediction model based on deep learning and radiomics features of DWI for the assessment of microsatellite instability in endometrial cancer.Cancer medicine · 2024Article
- A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer.Scientific reports · 2024Article
- An integrative clinical and CT-based tumoral/peritumoral radiomics nomogram to predict the microsatellite instability in rectal carcinoma.Abdominal radiology (New York) · 2024Article
- Predicting tumor deposits in rectal cancer: a combined deep learning model using T2-MR imaging and clinical features.Insights into imaging · 2023Article
- Review
- The Role of Radiomics in Rectal Cancer.Journal of gastrointestinal cancer · 2023Review
- Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study.European radiology · 2023Article
- Multisequence magnetic resonance imaging-based radiomics models for the prediction of microsatellite instability in endometrial cancer.La Radiologia medica · 2023Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicrosatellite instability (MSI) is a predictive biomarker for response to chemotherapy and a prognostic biomarker for clinical outcomes of rectal cancer. The purpose of this study was to develop and validate radiomics models for preoperative prediction of the MSI status of rectal cancer based on magnetic resonance (MR) images.
methodsThis study retrospectively recruited 491 rectal cancer patients with pathologically confirmed MSI status. Patients were randomly divided into a training cohort (n=327) and a validation cohort (n=164). The most predictive radiomics features were selected using intraclass correlation coefficient (ICC) analysis, the two-sample
resultsAmong the 491 rectal cancer patients, the prevalence of MSI was 10.39% (51/491). Following ICC analysis, two-sample
conclusionsRadiomics features based on preoperative T2-weighted MR imaging (MRI) are associated with the MSI status of rectal cancer. Combinational analysis of clinical factors and radiomics features may improve predictive performance and potentially contribute to noninvasive personalized therapy selection.
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