ReviewNuclear medicine and molecular imaging2019
Radiomics in Oncological PET/CT: a Methodological Overview.
Review in Nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
75 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Application of artificial intelligence and radiomics in the prediction of lymph node metastasis and tumour grading of oral cancer - a systematic review and meta analysis.BMC oral health · 2026Pooled it
- Current progress and quality of radiomic studies for predicting EGFR mutation in patients with non-small cell lung cancer using PET/CT images: a systematic review.The British journal of radiology · 2021Pooled it
- Current status and quality of radiomics studies in lymphoma: a systematic review.European radiology · 2020Pooled it
- The prognostic value of radiomic features from pre- and post-treatmentScientific reports · 2023Trial
- Radiomic analysis for predicting prognosis of colorectal cancer from preoperativeJournal of translational medicine · 2022Trial
- Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer.European journal of nuclear medicine and molecular imaging · 2022Trial
- Inter- and intra-quartile comparison of multi-tracer PET/CT and liquid biopsy molecular markers in cancer: a futuristic perspective on evolving a "stepped care" model for individualized precision theranostics through AI/ML.European journal of nuclear medicine and molecular imaging · 2026Article
- Inter-Observer Reproducibility of [18F]FDG PET/CT Radiomic Features in Primary Breast Carcinoma.Journal of imaging · 2026Article
- [Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Pseudotime-Based derivation of a PET-Based metabolic progression index for prognostic stratification in Extensive-Stage SCLC.Annals of nuclear medicine · 2026Article
- A study on 18F-FDG PET/CT imaging assessment of the anti-aging efficacy of BMMSCs in the macaque brain.Stem cells translational medicine · 2026Article
- Radiomics-Based Differential Diagnosis of Radicular Cysts and Apical Granulomas on CBCT Images Using RadC-CNN Architecture.Diagnostics (Basel, Switzerland) · 2026Article
- Mitigating bladder signal inEJNMMI physics · 2026Article
- Article
- Predicting recurrence of prostate cancer after radical treatment using AI models based on PET/CT radiomics: a dual-center study.Frontiers in oncology · 2026Article
- Voxel-based dosimetry for predicting treatment response to transarterial radioembolization in hepatocellular carcinoma: significance of intratumoral dose distribution.EJNMMI physics · 2025Article
- Article
- Article
- Integrating PET and MRI Radiomics for Staging and Prognostic Stratification in Anal Canal Cancer.Cancers · 2025Article
- Review
15 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics is a medical imaging analysis approach based on computer-vision. Metabolic radiomics in particular analyses the spatial distribution patterns of molecular metabolism on PET images. Measuring intratumoral heterogeneity via image is one of the main targets of radiomics research, and it aims to build a image-based model for better patient management. The workflow of radiomics using texture analysis follows these steps: 1) imaging (image acquisition and reconstruction); 2) preprocessing (segmentation & quantization); 3) quantification (texture matrix design & texture feature extraction); and 4) analysis (statistics and/or machine learning). The parameters or conditions at each of these steps are effect on the results. In statistical testing or modeling, problems such as multiple comparisons, dependence on other variables, and high dimensionality of small sample size data should be considered. Standardization of methodology and harmonization of image quality are one of the most important challenges with radiomics methodology. Even though there are current issues in radiomics methodology, it is expected that radiomics will be clinically useful in personalized medicine for oncology.
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.