ReviewScientific reports2017
PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology.
Review in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 98 papers, 4 of them syntheses that pooled it.
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.
Influence of PET/CT Radiomic Features on the Outcome of Lung Cancer Patients
Relationship Between Histopathological Features, Mutation Status, 18F-FDG PET/CT Radiomic Imaging Parameters as Well as Clinical Outcome in Patients With Treatment-naïve Non-small Cell Lung Cancer
Radiomic Features of Tumor and of Liver-Tumor Interface in Patients With Colorectal Liver Metastases. Identification of New Prognostic Biomarkers.
Who cites it
98 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Artificial intelligence-assisted PET imaging for predicting neoadjuvant chemotherapy response in breast cancer: a systematic review and meta-analysis.European journal of nuclear medicine and molecular imaging · 2026Pooled it
- Radiotherapy Planning and Molecular Imaging in Lung Cancer.Current radiopharmaceuticals · 2020Pooled it
- Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics.European journal of nuclear medicine and molecular imaging · 2019Pooled it
- Repeatability and Reproducibility of Radiomic Features: A Systematic Review.International journal of radiation oncology, biology, physics · 2018Pooled it
- Standard deviation of CT radiomic features among malignancies in each individual: prognostic ability in lung cancer patients.Journal of cancer research and clinical oncology · 2023Trial
- Trial
- Machine Learning-Driven Radiomics for an Early-Stage Predictive Model of Nodal Upstaging in Thoracic Oncology.Cancers · 2026Article
- The Role of Histology in Predicting Spread Through Air Spaces (STAS) in Non-Small Cell Lung Cancer.Journal of personalized medicine · 2026Article
- Long-axial field-of-view PET/CT improves radiomics feature reliability.European journal of nuclear medicine and molecular imaging · 2025Article
- The Role of Artificial Intelligence and Radiomics in the Management of Lymphomas by PET/CT: The Clairvoyance in Clinic.Cancer management and research · 2025Review
- Role of Textural Analysis Parameters Derived from FDG PET/CT in Diagnosing Cardiac Sarcoidosis.World journal of nuclear medicine · 2024Article
- Enhancing Survival Outcome Predictions in Metastatic Non-Small Cell Lung Cancer Through PET Radiomics Analysis.Cancers · 2024Article
- DSA Quantitative Analysis and Predictive Modeling of Obliteration in Cerebral AVM following Stereotactic Radiosurgery.AJNR. American journal of neuroradiology · 2024Article
- Premalignant Progression in the Lung: Knowledge Gaps and Novel Opportunities for Interception of Non-Small Cell Lung Cancer. An Official American Thoracic Society Research Statement.American journal of respiratory and critical care medicine · 2024Review
- Automated PD-L1 status prediction in lung cancer with multi-modal PET/CT fusion.Scientific reports · 2024Article
- Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence.Scientific reports · 2024Article
- Article
- Delta-radiomics in cancer immunotherapy response prediction: A systematic review.European journal of radiology open · 2023Article
- Impact of respiratory motion onJournal of applied clinical medical physics · 2023Article
- Radiomic analysis will add differential diagnostic value of benign and malignant pulmonary nodules: a hybrid imaging study based on [Insights into imaging · 2023Article
38 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Imaging with positron emission tomography (PET)/computed tomography (CT) is crucial in the management of cancer because of its value in tumor staging, response assessment, restaging, prognosis and treatment responsiveness prediction. In the last years, interest has grown in texture analysis which provides an "in-vivo" lesion characterization, and predictive information in several malignances including NSCLC; however several drawbacks and limitations affect these studies, especially because of lack of standardization in features calculation, definitions and methodology reporting. The present paper provides a comprehensive review of literature describing the state-of-the-art of FDG-PET/CT texture analysis in NSCLC, suggesting a proposal for harmonization of methodology.
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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.