ReviewDiagnostics (Basel, Switzerland)2021
A Systematic Review of PET Textural Analysis and Radiomics in Cancer.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 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.
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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
37 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Current insights on PSMA PET/CT in intermediate-risk prostate cancer: a literature review.Annals of nuclear medicine · 2025Pooled it
- A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.Cancer medicine · 2023Pooled it
- Joint EANM/SNMMI guideline on radiomics in nuclear medicine : Jointly supported by the EANM Physics Committee and the SNMMI Physics, Instrumentation and Data Sciences Council.European journal of nuclear medicine and molecular imaging · 2023Guideline
- Habitat-based CT radiomics profiling spatial-temporal heterogeneity in resectable NSCLC predict pathological response to neoadjuvant chemoimmunotherapy: a multi-center study.NPJ precision oncology · 2026Article
- Preoperative Prediction of Spread Through Air Spaces in Lung Cancer UsingDiagnostics (Basel, Switzerland) · 2026Article
- Differentiating the differentiation degree of gastric cancer based on MRI radiomics.BMC medical imaging · 2025Article
- Texture analysis and metabolic parameters ofEuropean journal of nuclear medicine and molecular imaging · 2025Article
- The Role of [18F]FDG PET-Based Radiomics and Machine Learning for the Evaluation of Cardiac Sarcoidosis: A Narrative Literature Review.Medicina (Kaunas, Lithuania) · 2025Review
- Texture Analysis of 68Ga-DOTATOC PET/CT Images for the Prediction of Outcome in Patients with Neuroendocrine Tumors.Biomedicines · 2025Article
- Practical use of radiomic features as a metric for image quality discrimination in [EJNMMI reports · 2025Article
- 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
- Illuminating the Shadows: Innovation in Advanced Imaging Techniques for Myeloma Precursor Conditions.Diagnostics (Basel, Switzerland) · 2025Review
- On the robustness of [18F]-FDG-PET radiomic features to variations in image acquisition and reconstruction settings: A phantom study.PloS one · 2025Article
- Clinical scoring systems, molecular subtypes and baseline [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- Enhancing Survival Outcome Predictions in Metastatic Non-Small Cell Lung Cancer Through PET Radiomics Analysis.Cancers · 2024Article
- Coefficient of variation and texture analysis of 18F-FDG PET/CT images for the prediction of outcome in patients with multiple myeloma.Annals of hematology · 2024Article
- Mitigating the impact of image processing variations on tumour [Scientific reports · 2024Article
- Article
- 2-[Medicina (Kaunas, Lithuania) · 2024Article
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundAlthough many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies.
methodsPubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted.
resultsA total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20-1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1-286).
conclusionsPET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.
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Registered trials
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