Trial reportMolecular imaging and biology2016
Robustness of Radiomic Features in [
Trial report in Molecular imaging and biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
69 citing papers in PubMed, 1 synthesis or guideline pooled it, 116 citations in OpenAlex.
- Repeatability and Reproducibility of Radiomic Features: A Systematic Review.International journal of radiation oncology, biology, physics · 2018Pooled it
- Invariant Texture Features to Gray Level Discretization.Journal of imaging informatics in medicine · 2026Article
- Multiparametric PET/CT Tensor Radiomics for Stability-Aware Machine Learning in Lung Cancer Survival Prediction.Journal of imaging informatics in medicine · 2026Article
- Impact of CT acquisition settings on the stability of radiomic features and the performance of pulmonary nodule classification models.Insights into imaging · 2026Article
- Radiomic-Based Machine Learning Classifiers for HPV Status Prediction in Oropharyngeal Cancer: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets: application to PET-based prediction of lung cancer subtypes.EJNMMI physics · 2025Article
- Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Myocardial perfusion SPECT radiomic features reproducibility assessment: Impact of image reconstruction and harmonization.Medical physics · 2025Article
- PET radiomics in lung cancer: advances and translational challenges.EJNMMI physics · 2024Review
- Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Mitigating the impact of image processing variations on tumour [Scientific reports · 2024Article
- Influence of image preprocessing on the segmentation-based reproducibility of radiomic features:Diagnostic and interventional radiology (Ankara, Turkey) · 2024Article
- Robustness of radiomic features in 123I-ioflupane-dopamine transporter single-photon emission computer tomography scan.PloS one · 2024Article
- A Critical Analysis of the Robustness of Radiomics to Variations in Segmentation Methods inDiagnostics (Basel, Switzerland) · 2023Article
- Multimodality radiomics analysis based on [European radiology · 2023Article
- Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [Sensors (Basel, Switzerland) · 2023Article
- Impact of Aggregation Methods for Texture Features on Their Robustness Performance: Application to NasopharyngealCancers · 2023Article
- A heterogeneous phantom study for investigating the stability of PET images radiomic features with varying reconstruction settings.Frontiers in nuclear medicine · 2023Article
- Development and verification of radiomics framework for computed tomography image segmentation.Medical physics · 2022Article
- The role of PET/CT in radiotherapy for nasopharyngeal carcinoma.Frontiers in oncology · 2022Review
9 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
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeRadiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging and to enable enhanced prediction of therapy response and outcome. An important ingredient to success in translation of radiomic features to clinical reality is to quantify and ascertain their robustness. In the present work, we studied the impact of segmentation and discretization on 88 radiomic features in 2-deoxy-2-[ PROCEDURES: Forty patients underwent [
resultsForty-four (50 %) and 55 (63 %) features depicted ICC ≥0.8 with respect to segmentation as obtained from [
conclusionsDiscretization generated larger effects on features than segmentation in both tracers. Features extracted from [
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.