ReviewDiagnostics (Basel, Switzerland)2021
Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
32 citing papers in PubMed, 53 citations in OpenAlex.
- Cancer of unknown primary: the evolution of tissue of origin identification in the artificial intelligence era.Biomarker research · 2026Review
- Fusion of MRI-radiomics and clinical features to improve pathological T-stage prediction of rectal cancer: a multicenter study.BMC cancer · 2026Article
- Article
- Review
- Image Analysis as tool for Predicting Colorectal Cancer Molecular Alterations: A Scoping Review.Molecular imaging and radionuclide therapy · 2025Article
- A Machine Learning Model Based on MRI Radiomics to Predict Response to Chemoradiation Among Patients with Rectal Cancer.Life (Basel, Switzerland) · 2024Article
- A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer.Abdominal radiology (New York) · 2024Article
- 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
- Computed Tomography-Based Radiomics for Long-Term Prognostication of High-Risk Localized Prostate Cancer Patients Received Whole Pelvic Radiotherapy.Journal of personalized medicine · 2023Article
- Radiomics in colorectal cancer patients.World journal of gastroenterology · 2023Review
- Development and Validation of Artificial-Intelligence-Based Radiomics Model Using Computed Tomography Features for Preoperative Risk Stratification of Gastrointestinal Stromal Tumors.Journal of personalized medicine · 2023Article
- Article
- Radiomics in Lung Metastases: A Systematic Review.Journal of personalized medicine · 2023Review
- Virtual biopsy in abdominal pathology: where do we stand?BJR open · 2023Review
- Primary Tumor Radiomic Model for Identifying Extrahepatic Metastasis of Hepatocellular Carcinoma Based on Contrast Enhanced Computed Tomography.Diagnostics (Basel, Switzerland) · 2022Article
- Total Neoadjuvant Therapy Is a Predictor for Complete Pathological Response in Patients Undergoing Surgery for Rectal Cancer.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2022Article
- Radiomic Cancer Hallmarks to Identify High-Risk Patients in Non-Metastatic Colon Cancer.Cancers · 2022Article
- Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases.La Radiologia medica · 2022Article
- Automated Prediction of the Response to Neoadjuvant Chemoradiotherapy in Patients Affected by Rectal Cancer.Cancers · 2022Article
- Article
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While cross-sectional imaging has seen continuous progress and plays an undiscussed pivotal role in the diagnostic management and treatment planning of patients with rectal cancer, a largely unmet need remains for improved staging accuracy, assessment of treatment response and prediction of individual patient outcome. Moreover, the increasing availability of target therapies has called for developing reliable diagnostic tools for identifying potential responders and optimizing overall treatment strategy on a personalized basis. Radiomics has emerged as a promising, still fully evolving research topic, which could harness the power of modern computer technology to generate quantitative information from imaging datasets based on advanced data-driven biomathematical models, potentially providing an added value to conventional imaging for improved patient management. The present study aimed to illustrate the contribution that current radiomics methods applied to magnetic resonance imaging can offer to managing 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.