ReviewThe British journal of radiology2016
Imaging genomics in cancer research: limitations and promises.
Review in The British journal of radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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
60 citing papers in PubMed.
- Metastatic Colorectal Cancer Treatment Response Evaluation by Ultra-Deep Sequencing of Cell-Free DNA and Matched White Blood Cells.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Trial
- MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis.European radiology · 2018Trial
- Radiological signature of HER2-Positive gallbladder cancer: analysis of CT features.Abdominal radiology (New York) · 2026Article
- Early Enhancement in Contrast-Enhanced Computed Tomography Is an Index ofVeterinary sciences · 2025Article
- The impact of radiogenomics on breast cancer.American journal of cancer research · 2025Review
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases.Journal of the anus, rectum and colon · 2025Article
- Cancer treatment monitoring using cell-free DNA fragmentomes.Nature communications · 2024Article
- BTK Expression Level Prediction and the High-Grade Glioma Prognosis Using Radiomic Machine Learning Models.Journal of imaging informatics in medicine · 2024Article
- Role of Artificial Intelligence in Surgical Decision-Making: A Comprehensive Review.Galen medical journal · 2024Review
- Bridging the Gap Between Imaging and Molecular Characterization: Current Understanding of Radiomics and Radiogenomics in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2024Review
- Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics.Cancer medicine · 2023Article
- Article
- Machine learning with multimodal data for COVID-19.Heliyon · 2023Review
- Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer.Scientific reports · 2023Article
- Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects.International journal of molecular sciences · 2023Review
- Radiomics models based on multi-sequence MRI for preoperative evaluation of MUC4 status in pancreatic ductal adenocarcinoma: a preliminary study.Quantitative imaging in medicine and surgery · 2022Article
- Artificial intelligence in breast cancer imaging: risk stratification, lesion detection and classification, treatment planning and prognosis-a narrative review.Exploration of targeted anti-tumor therapy · 2022Review
- Article
- Radiomic signatures based on multiparametric MR images for predicting Ki-67 index expression in medulloblastoma.Annals of translational medicine · 2021Article
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.
Funding
Abstract
Recently, radiogenomics or imaging genomics has emerged as a novel high-throughput method of associating imaging features with genomic data. Radiogenomics has the potential to provide comprehensive intratumour, intertumour and peritumour information non-invasively. This review article summarizes the current state of radiogenomic research in tumour characterization, discusses some of its limitations and promises and projects its future directions. Semi-radiogenomic studies that relate specific gene expressions to imaging features will also be briefly reviewed.
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.