ArticleRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology2018
Development and validation of an MRI-based model to predict response to chemoradiotherapy for rectal cancer.
Article in Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 28 citations in OpenAlex.
- Improving prediction of ypT0-1N0 response in rectal cancer: the added value of gross tumor type to magnetic resonance tumor regression grade after chemoradiotherapy in a retrospective cohort study.Annals of surgical treatment and research · 2026Article
- A machine learning model for the early prediction of Gram-negative bloodstream infection in ICU patients.BMC medical informatics and decision making · 2026Article
- Predicting cardiac resynchronization therapy response: development and validation of a single photon emission computed tomography-based nomogram.Quantitative imaging in medicine and surgery · 2025Article
- Delayed surgery for more than 9 weeks induces worse survival outcomes in locally advanced rectal cancer patients with poor response to neoadjuvant chemoradiotherapy: a propensity score matched cohort study.Gastroenterology report · 2025Article
- 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
- Radiomic and Volumetric Measurements as Clinical Trial Endpoints-A Comprehensive Review.Cancers · 2022Review
- Pretreatment blood biomarkers combined with magnetic resonance imaging predict responses to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.Frontiers in oncology · 2022Article
- Role of tumor cell senescence in non-professional phagocytosis and cell-in-cell structure formation.BMC molecular and cell biology · 2020Article
- Carcinoembryonic Antigen Improves the Performance of Magnetic Resonance Imaging in the Prediction of Pathologic Response after Neoadjuvant Chemoradiation for Patients with Rectal Cancer.Cancer research and treatment · 2020Article
- A Deep Learning Model to Predict the Response to Neoadjuvant Chemoradiotherapy by the Pretreatment Apparent Diffusion Coefficient Images of Locally Advanced Rectal Cancer.Frontiers in oncology · 2020Article
- Predicting the tumor response to chemoradiotherapy for rectal cancer: Model development and external validation using MRI radiomics.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2020Article
- Modern MR Imaging Technology in Rectal Cancer; There Is More Than Meets the Eye.Frontiers in oncology · 2020Review
- Accurate outcome prediction after neo-adjuvant radio-chemotherapy for rectal cancer based on a TCP-based early regression index.Clinical and translational radiation oncology · 2019Article
- Development and validation of radiomic signatures of head and neck squamous cell carcinoma molecular features and subtypes.EBioMedicine · 2019Article
- Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer.Annals of surgical oncology · 2019Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
Abstract
background and purposeTo safely implement organ preserving treatment strategies for patients with rectal cancer, well-considered selection of patients with favourable response is needed. In this study, we develop and validate an MRI-based response predicting model.
methodsA multivariate model using T2-volumetric and DWI parameters before and 6 weeks after chemoradiation (CRT) was developed using a cohort of 85 rectal cancer patients and validated in an external cohort of 55 patients that underwent preoperative CRT.
resultsTwenty-two patients (26%) achieved ypT0-1N0 response in the development cohort versus 13 patients (24%) in the validation cohort. Two T2-volumetric parameters (ΔVolume% and Sphere_post) and two DWI parameters (ADC_avg_post and ADCratio_avg) were retained in a model predicting (near-)complete response (ypT0-1N0). In the development cohort, this model had a good predictive performance (AUC = 0.89; 95% CI 0.80-0.98). Validation of the model in an external cohort resulted in a similar performance (AUC = 0.88 95% CI 0.79-0.98).
conclusionAn MRI-based prediction model of (near-)complete pathological response following CRT in rectal cancer patients, shows a high predictive performance in an external validation cohort. The clinically relevant features in the model make it an interesting tool for implementation of organ-preserving strategies in 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.