ReviewInternational journal of radiation oncology, biology, physics2019
NCTN Assessment on Current Applications of Radiomics in Oncology.
Review in International journal of radiation oncology, biology, physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- The Role of PET Image Quantification in Modern Radiation Therapy.PET clinics · 2025Review
- Embracing the Future of Clinical Trials in Radiation Therapy: An NRG Oncology CIRO Technology Retreat Whitepaper on Pioneering Technologies and AI-Driven Solutions.International journal of radiation oncology, biology, physics · 2025Review
- Current and Future Applications of PET Radiomics in Radiation Oncology.PET clinics · 2025Review
- Impact of artificial intelligence-based and traditional image preprocessing and resampling on MRI-based radiomics for classification of papillary thyroid carcinoma.BJR artificial intelligence · 2025Article
- CT-based delta-radiomics nomogram to predict pathological complete response after neoadjuvant chemoradiotherapy in esophageal squamous cell carcinoma patients.Journal of translational medicine · 2024Article
- NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions.International journal of radiation oncology, biology, physics · 2024Article
- Synthesis of virtual monoenergetic images from kilovoltage peak images using wavelet loss enhanced CycleGAN for improving radiomics features reproducibility.Quantitative imaging in medicine and surgery · 2024Article
- The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics.Cancers · 2024Review
- The diagnostic value of a nomogram based on enhanced CT radiomics for differentiating between intrahepatic cholangiocarcinoma and early hepatic abscess.Frontiers in molecular biosciences · 2024Article
- Article
- Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI.Scientific reports · 2023Article
- Beyond Imaging and Genetic Signature in Glioblastoma: Radiogenomic Holistic Approach in Neuro-Oncology.Biomedicines · 2022Review
- Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies.Radiology · 2022Review
- Radiotherapy Standardisation and Artificial Intelligence within the National Cancer Institute's Clinical Trials Network.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2022Article
- Incremental Value of Radiomics in 5-Year Overall Survival Prediction for Stage II-III Rectal Cancer.Frontiers in oncology · 2022Article
- Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers.European radiology · 2021Article
- Implications of US radiomics signature for predicting malignancy in thyroid nodules with indeterminate cytology.European radiology · 2021Article
- Radiomic and radiogenomic modeling for radiotherapy: strategies, pitfalls, and challenges.Journal of medical imaging (Bellingham, Wash.) · 2021Review
- 4D radiomics: impact of 4D-CBCT image quality on radiomic analysis.Physics in medicine and biology · 2021Article
- The Potential Use of Radiomics with Pre-Radiation Therapy MR Imaging in Predicting Risk of Pseudoprogression in Glioblastoma Patients.Journal of imaging · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Radiomics is a fast-growing research area based on converting standard-of-care imaging into quantitative minable data and building subsequent predictive models to personalize treatment. Radiomics has been proposed as a study objective in clinical trial concepts and a potential biomarker for stratifying patients across interventional treatment arms. In recognizing the growing importance of radiomics in oncology, a group of medical physicists and clinicians from NRG Oncology reviewed the current status of the field and identified critical issues, providing a general assessment and early recommendations for incorporation in oncology studies.
Indexed as
Identifiers
What OpenQuestion holds
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.