ArticleTranslational cancer research2016
The emerging field of radiomics in esophageal cancer: current evidence and future potential.
Article in Translational cancer research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Radiomics diagnostic performance for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis.BMC medical imaging · 2024Pooled it
- Prediction of distant metastasis in esophageal cancer using a radiomics-clinical model.European journal of medical research · 2022Trial
- Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases.European radiology experimental · 2020Trial
- Magnetic resonance imaging-based radiomics signature for predicting preoperative staging of esophageal cancer.World journal of radiology · 2025Article
- Radiomics to predict PNI in ESCC.Abdominal radiology (New York) · 2025Article
- Prediction of lymphovascular invasion in esophageal squamous cell carcinoma by computed tomography-based radiomics analysis: 2D or 3D ?Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- The role of FDG PET/CT radiomics in the prediction of pathological response to neoadjuvant treatment in patients with esophageal cancer.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2024Article
- Computed tomography-based radiomic analysis for predicting pathological response and prognosis after neoadjuvant chemotherapy in patients with locally advanced esophageal cancer.Abdominal radiology (New York) · 2023Article
- Prognostic value of pre-therapeutic FDG-PET radiomic analysis in gastro-esophageal junction cancer.Scientific reports · 2023Article
- A radiomics nomogram based on contrast-enhanced CT for preoperative prediction of Lymphovascular invasion in esophageal squamous cell carcinoma.Frontiers in oncology · 2023Article
- Article
- Radiomic assessment of oesophageal adenocarcinoma: a critical review of 18F-FDG PET/CT, PET/MRI and CT.Insights into imaging · 2022Review
- PET/MRI and PET/CT Radiomics in Primary Cervical Cancer: A Pilot Study on the Correlation of Pelvic PET, MRI, and CT Derived Image Features.Molecular imaging and biology · 2022Article
- Computed tomography-based deep-learning prediction of lymph node metastasis risk in locally advanced gastric cancer.Frontiers in oncology · 2022Article
- A combined predicting model for benign esophageal stenosis after simultaneous integrated boost in esophageal squamous cell carcinoma patients (GASTO1072).Frontiers in oncology · 2022Article
- Computed tomography-based radiomic analysis for prediction of treatment response to salvage chemoradiotherapy for locoregional lymph node recurrence after curative esophagectomy.Journal of applied clinical medical physics · 2021Article
- Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study.World journal of gastroenterology · 2021Article
- Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma.Frontiers in oncology · 2021Article
- Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom.Tomography (Ann Arbor, Mich.) · 2019Article
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
'Radiomics' is the name given to the emerging field of extracting additional information from standard medical images using advanced feature analysis. This innovative form of quantitative image analysis appears to have future potential for clinical practice in patients with esophageal cancer by providing an additional layer of information to the standard imaging assessment. There is a growing body of evidence suggesting that radiomics may provide incremental value for staging, predicting treatment response, and predicting survival in esophageal cancer, for which the current work-up has substantial limitations. This review outlines the available evidence and future potential for the application of radiomics in the management of patients with esophageal cancer. In addition, an overview of the current evidence on the importance of reproducibility of image features and the substantial influence of varying smoothing scales, quantization levels, and segmentation methods is provided.
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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.