ArticleAnnals of surgical oncology2019
Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer.
Article in Annals of surgical oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.
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Who cites it
70 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Tissue-Based Markers as a Tool to Assess Response to Neoadjuvant Radiotherapy in Rectal Cancer-Systematic Review.International journal of molecular sciences · 2022Pooled it
- Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer.Journal of translational medicine · 2021Trial
- A cfDNA fragmentomics-based machine learning model for predicting treatment response and recurrence in locally advanced rectal cancer after neoadjuvant chemoradiotherapy.The journal of liquid biopsy · 2026Article
- Multi-parametric MRI radiomics to predict sensitivity to neoadjuvant chemoradiotherapy based on multi-regions of interest in locally advanced rectal cancer: a multicenter study.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Article
- Radiomics analysis of restaging MRI for detection of pathological complete response in locally advanced rectal cancer.European journal of radiology open · 2026Article
- Personalized neoadjuvant treatment regimen selection in locally advanced rectal cancer based on regimen-specific response modeling.NPJ digital medicine · 2026Article
- Integrating CT-Based Radiomics Analysis With Serum CEA Level to Predict Neoadjuvant Chemoradiotherapy Response in Colorectal Cancer.The Kaohsiung journal of medical sciences · 2026Article
- MRI-Based Radiomics to Predict Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer: A Retrospective Study.Journal of personalized medicine · 2026Article
- MRI-based multiregional radiomics for pretreatment prediction of pathologic complete response to neoadjuvant chemoradiation therapy in locally advanced rectal cancer: a bicenter study.Abdominal radiology (New York) · 2026Article
- MRI-based habitat analysis for pathologic response prediction after neoadjuvant chemoradiotherapy in rectal cancer: a multicenter study.European radiology · 2026Article
- Multi-parametric MRI radiomics predicts different HER2 expression in breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI.Abdominal radiology (New York) · 2025Review
- Enhancing the role of MRI in rectal cancer: advances from staging to prognosis prediction.European radiology · 2025Review
- Development and Cross-Institutional Validation of a Comprehensive Machine Learning Model Predicting Response to Neoadjuvant Therapy for Rectal Cancer.Cancer management and research · 2025Article
- A clinical-radiomics nomogram based on automated segmentation of chest CT to discriminate PRISm and COPD patients.European journal of radiology open · 2024Article
- Visualization analysis of research hotspots and trends in MRI-based artificial intelligence in rectal cancer.Heliyon · 2024Article
- Multiparametric MRI-based radiomic nomogram for predicting HER-2 2+ status of breast cancer.Heliyon · 2024Article
- Performance and Dimensionality of Pretreatment MRI Radiomics in Rectal Carcinoma Chemoradiotherapy Prediction.Journal of clinical medicine · 2024Article
- Prediction of pathologic complete response to neoadjuvant chemoradiation in locally advanced rectal cancer.Frontiers in oncology · 2024Article
10 more citing papers are in PubMed but not listed here.
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Funding
Abstract
objectiveThe aim of this study was to investigate whether pretherapeutic, multiparametric magnetic resonance imaging (MRI) radiomic features can be used for predicting non-response to neoadjuvant therapy in patients with locally advanced rectal cancer (LARC).
methodsWe retrospectively enrolled 425 patients with LARC [allocated in a 3:1 ratio to a primary (n = 318) or validation (n = 107) cohort] who received neoadjuvant therapy before surgery. All patients underwent T1-weighted, T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted MRI scans before receiving neoadjuvant therapy. We extracted 2424 radiomic features from the pretherapeutic, multiparametric MR images of each patient. The Wilcoxon rank-sum test, Spearman correlation analysis, and least absolute shrinkage and selection operator regression were successively performed for feature selection, whereupon a multiparametric MRI-based radiomic model was established by means of multivariate logistic regression analysis. This feature selection and multivariate logistic regression analysis was also performed on all single-modality MRI data to establish four single-modality radiomic models. The performance of the five radiomic models was evaluated by receiver operating characteristic (ROC) curve analysis in both cohorts.
resultsThe multiparametric, MRI-based radiomic model based on 16 features showed good predictive performance in both the primary (p < 0.01) and validation (p < 0.05) cohorts, and performed better than all single-modality models. The area under the ROC curve of this multiparametric MRI-based radiomic model achieved a score of 0.822 (95% CI 0.752-0.891).
conclusionsWe demonstrated that pretherapeutic, multiparametric MRI radiomic features have potential in predicting non-response to neoadjuvant therapy in patients with LARC.
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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.