SynthesisInternational journal of molecular sciences2019
TCGA-TCIA Impact on Radiogenomics Cancer Research: A Systematic Review.
Synthesis in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 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
53 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- What Genetics Can Do for Oncological Imaging: A Systematic Review of the Genetic Validation Data Used in Radiomics Studies.International journal of molecular sciences · 2022Pooled it
- Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review.Journal of medical Internet research · 2021Pooled it
- Transformer-Based PET/CT Fusion Enables Preoperative Prediction and Prognostic Stratification of Spread Through Air Spaces in Lung Adenocarcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- A novel signature of palmitoylation for predicting prognosis and therapeutic response of hepatocellular carcinoma.Discover oncology · 2026Article
- Machine learning-based signature for prognosis and drug sensitivity in hepatocellular carcinoma using glycolysis-related gene.Oncology letters · 2026Article
- From Radiomics to Radiogenomics: Decoding Renal Cell Carcinoma Biology for Precision Medicine-a narrative review.Insights into imaging · 2025Review
- Machine learning-based quantitative prediction of spread through air spaces in primary lung adenocarcinoma using intratumoural heterogeneity scores.International journal of surgery (London, England) · 2025Article
- Phenotypic stratification of Low-grade Glioma using multimodal MRI via outcome-weighted integrative clustering.BMC neurology · 2025Article
- Multimodal radiomics in glioma: predicting recurrence in the peritumoural brain zone using integrated MRI.BMC medical imaging · 2025Article
- Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.Scientific reports · 2025Article
- Annexin A1-FPR1 Interaction in dendritic cells promotes immune microenvironment modulation in Thyroid Cancer.Cell biology and toxicology · 2025Article
- From manual clinical criteria to machine learning algorithms: Comparing outcome endpoints derived from diverse electronic health record data modalities.PLOS digital health · 2025Article
- Imaging genomics of cancer: a bibliometric analysis and review.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Review
- Ultrasound-based radiogenomics: status, applications, and future direction.Ultrasonography (Seoul, Korea) · 2025Article
- A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma.Frontiers in immunology · 2025Article
- Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.Frontiers in medicine · 2025Article
- Radiomics models to predict axillary lymph node metastasis in breast cancer and analysis of the biological significance of radiomic features.Frontiers in oncology · 2025Article
- Determinants of community-acquired pneumonia among under-five children in Awi Zone, Northwest Ethiopia.Frontiers in public health · 2025Article
- Constructing and exploring neuroimaging projects: a survey from clinical practice to scientific research.Insights into imaging · 2024Review
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
In the last decade, the development of radiogenomics research has produced a significant amount of papers describing relations between imaging features and several molecular 'omic signatures arising from next-generation sequencing technology and their potential role in the integrated diagnostic field. The most vulnerable point of many of these studies lies in the poor number of involved patients. In this scenario, a leading role is played by The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA), which make available, respectively, molecular 'omic data and linked imaging data. In this review, we systematically collected and analyzed radiogenomic studies based on TCGA-TCIA data. We organized literature per tumor type and molecular 'omic data in order to discuss salient imaging genomic associations and limitations of each study. Finally, we outlined the potential clinical impact of radiogenomics to improve the accuracy of diagnosis and the prediction of patient outcomes in 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.