ReviewNature reviews. Clinical oncology2025
Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine.
Review in Nature reviews. Clinical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 3 of them syntheses that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Predicting T790M mutation status in non-small cell lung cancer based on radiomics: A systematic review and meta-analysis.PloS one · 2026Pooled it
- CT-based radiomics in predicting the efficacy of preoperative neoadjuvant chemoimmunotherapy for non-small cell lung cancer: a systematic review and meta-analysis.Frontiers in immunology · 2026Pooled it
- Diagnostic accuracy of AI-augmented renal ultrasound for degenerative kidney disorders: a systematic review and meta-analysis.Future science OA · 2026Review
- Tools for providing information to patients about high-tech medical resources for treatment of cancer.Acta oncologica (Stockholm, Sweden) · 2026Review
- Automated Deauville Score computation from baseline [¹⁸F]FDG PET/CT predicts progression-free survival in multiple myeloma: a radiogenomic framework.European journal of nuclear medicine and molecular imaging · 2026Article
- Cardiac Magnetic Resonance Radiomics for Diagnosis, Phenotyping and Risk Stratification of Cardiomyopathies.Healthcare (Basel, Switzerland) · 2026Review
- The Role of Artificial Intelligence in Optimizing Diagnosis in Prostate Cancer-A Narrative Review.Journal of clinical medicine · 2026Review
- Externally validated yet undertrained: sample size deficits in machine learning-based radiomics.European radiology · 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
- Undertraining is the floor, not the ceiling: when statistical and validation failures compound in radiomics.European radiology · 2026Article
- Imaging the hallmarks of cancer.Nature reviews. Cancer · 2026Review
- Development and validation of an interpretable medical deep foundation model for predicting occult lymph node metastasis in early-stage small cell lung cancer: a multicenter retrospective diagnostic study.Translational lung cancer research · 2026Article
- Artificial Intelligence for Personalized Prediction of Post-TIPS Outcomes: Integrating Clinical, Biochemical, and Radiomics Data-A Narrative Review.Journal of clinical medicine · 2026Review
- Machine Learning for Radiomics in Oncology: Challenges, Limitations, and Future Directions.Sensors (Basel, Switzerland) · 2026Article
- Why Radiomics Rarely Reaches the Clinic: Reproducibility, Validation, and Evidence Gap-A Critical Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Comparison of clinical-radiological and radiomics features for predicting pulmonary nodule malignancy in a multicenter study of mixed clinical and surveillance populations.European radiology · 2026Article
- Repeatability and reproducibility of MRI-derived radiomics on a 0.35 T MR-Linac using a tissue-mimicking phantom.Physics and imaging in radiation oncology · 2026Article
- Methodological quality of cardiac CT and MRI radiomics studies assessed using METRICS and RQS by human readers and ChatGPT 5.1 Thinking.European radiology experimental · 2026Article
- Deep learning-based CT slice synthesis improves radiomic feature reproducibility and discriminative performance in lung nodule assessment.Insights into imaging · 2026Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics is a tool for medical imaging analysis that could have a relevant role in precision oncology by offering precise quantitative support for clinical decision-making. The Radiomics Quality Score (RQS) is a tool developed to assess the rigour of radiomics studies that has now been widely adopted by researchers. Although RQS version 1.0 established a benchmark, an updated framework is required to account for evolving knowledge and ensure optimal evaluation of the quality of radiomics studies through the inclusion of fairness, explainability, rigorous quality control and harmonization. In this Review, we introduce the updated RQS 2.0, which maintains the scientific rigour of its predecessor and addresses these contemporary needs, and therefore could potentially accelerate clinical translation. Moreover, we introduce the radiomics readiness levels, inspired by the technology readiness level framework, which are integrated in RQS 2.0 and reflect nine distinct levels of incremental improvement in radiomics research with the ultimate aim of clinical implementation. We also detail anticipated future directions in radiomics, outlining a strategic vision to advance precision oncology, which is the ultimate aim of RQS 2.0.
Indexed as
Identifiers
40903523What 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.