ReviewFrontiers in oncology2023
The application of radiomics in esophageal cancer: Predicting the response after neoadjuvant therapy.
Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
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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
10 citing papers in PubMed, 13 citations in OpenAlex.
- Radiomics analysis of dual-layer spectral detector CT-derived iodine density maps for predicting the pathological complete response of esophageal squamous cell carcinoma after neoadjuvant chemoimmunotherapy.European journal of radiology open · 2026Article
- Article
- Magnetic resonance imaging-based radiomics signature for predicting preoperative staging of esophageal cancer.World journal of radiology · 2025Article
- Radiomics applications in the modern management of esophageal squamous cell carcinoma.Medical oncology (Northwood, London, England) · 2025Review
- Application of peritumoral radiomics based on simulated positioning CT images in the prognosis of intermediate-advanced esophageal cancer.Scientific reports · 2025Article
- Combining serum biomarkers and MRI radiomics to predict treatment outcome after thermal ablation in hepatocellular carcinoma.American journal of translational research · 2025Article
- Multi-channel multiphase CT-based deep learning and radiomics fusion model for noninvasive pathological grading of clear cell renal cell carcinoma.Frontiers in oncology · 2025Article
- Review
- The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy.Thoracic cancer · 2024Article
- Prediction of Neoadjuvant Chemoradiotherapy Sensitivity in Patients With Esophageal Squamous Cell Carcinoma Using CT-Based Radiomics Combined With Clinical Features.Dose-response : a publication of International Hormesis SocietyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Esophageal cancer (EC) is one of the fatal malignant neoplasms worldwide. Neoadjuvant therapy (NAT) combined with surgery has become the standard treatment for locally advanced EC. However, the treatment efficacy for patients with EC who received NAT varies from patient to patient. Currently, the evaluation of efficacy after NAT for EC lacks accurate and uniform criteria. Radiomics is a multi-parameter quantitative approach for developing medical imaging in the era of precision medicine and has provided a novel view of medical images. As a non-invasive image analysis method, radiomics is an inevitable trend in NAT efficacy prediction and prognosis classification of EC by analyzing the high-throughput imaging features of lesions extracted from medical images. In this literature review, we discuss the definition and workflow of radiomics, the advances in efficacy prediction after NAT, and the current application of radiomics for predicting efficacy after NAT.
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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.