SynthesisFrontiers in oncology2025
MRI-based radiomics for predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review and meta-analysis.
Synthesis in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence Models Using Magnetic Resonance Imaging to Predict Response to Chemoradiotherapy in Rectal Cancer: A Systematic Review.ANZ journal of surgery · 2026Pooled it
- Photoacoustic-ultrasound endoscopy for assessment of rectal cancer treatment response: A prospective study with T2-weighted MRI radiomics comparison.Photoacoustics · 2026Article
- Clinical target volume radiomics from planning CT for pretreatment response prediction in rectal cancer undergoing chemoradiotherapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 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
- Macro Habitat-Based T2-Weighted MRI Radiomics and Deep Learning Fusion for Predicting Treatment Response and Prognosis After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.Cancer medicine · 2026Article
- Article
- Multimodal radiomics for precision management of colorectal cancer.Discover oncology · 2026Review
- Development and validation of an MRI radiomics-based model for predicting progression risk in prostate cancer after endocrine therapy.Translational andrology and urology · 2026Article
- Predictive imaging in abdominal oncology: current trends and future directions.Japanese journal of radiology · 2026Review
- Radiomics and deep learning in upper tract urothelial carcinoma: advancing preoperative risk stratification and clinical decision-making.Frontiers in oncology · 2026Review
- Delta-Radiomics Biomarker in Colorectal Cancer Liver Metastases Treated with Cetuximab Plus Avelumab (CAVE Trial).Diagnostics (Basel, Switzerland) · 2025Article
- Predicting pathological complete response after neoadjuvant chemoradiotherapy in rectal cancer: beyond morphologic MRI.International journal of colorectal disease · 2025Article
- Neoadjuvant Treatment for Locally Advanced Rectal Cancer: Current Status and Future Directions.Cancers · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate the value of MRI-based radiomics for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer (LARC) through a systematic review and meta-analysis. Methods: A systematic literature search was conducted in PubMed, Embase, Proquest, Cochrane Library, and Web of Science databases, covering studies up to July 1st, 2024, on the diagnostic accuracy of MRI radiomics for predicting pCR in LARC patients following NCRT. Two researchers independently evaluated and selected studies using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and the Radiomics Quality Score (RQS) tool. A random-effects model was employed to calculate the pooled sensitivity, specificity, and diagnostic odds ratio (DOR) for MRI radiomics in predicting pCR. Meta-regression and subgroup analyses were performed to explore potential sources of heterogeneity. Statistical analyses were performed using RevMan 5.4, Stata 17.0, and Meta-Disc 1.4. Results: A total of 35 studies involving 9,696 LARC patients were included in this meta-analysis. The average RQS score of the included studies was 13.91 (range 9.00-24.00), accounting for 38.64% of the total score. According to QUADAS-2, there were risks of bias in patient selection and flow and timing domain, though the overall quality of the studies was acceptable. MRI-based radiomics showed no significant threshold effect in predicting pCR (Spearman correlation coefficient=0.119, P=0.498) but exhibited high heterogeneity (I Conclusions: MRI-based radiomics demonstrates high efficacy for predicting pCR in LARC patients following NCRT, holding significant promise for informing clinical decision-making processes and advancing individualized treatment in rectal cancer patients. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024611733.
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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 Socratic graph.