ReviewInternational journal of molecular sciences2021
Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.
Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 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
65 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- MRI/Transrectal Ultrasound Fusion-Guided Targeted Biopsy and Transrectal Ultrasound-Guided Systematic Biopsy for Diagnosis of Prostate Cancer: A Systematic Review and Meta-analysis.Frontiers in oncology · 2022Pooled it
- Inter-reader agreement of the prostate imaging reporting and data system version v2.1 for detection of prostate cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- AnCurrent radiopharmaceuticals · 2024Trial
- Prediction of distant metastasis in esophageal cancer using a radiomics-clinical model.European journal of medical research · 2022Trial
- Prostatic artery embolization and imaging-based biomarkers: current tools in monitoring treatment response and emerging strategies.Abdominal radiology (New York) · 2026Review
- Biomarkers for Precision Prognosis in Prostate Cancer: Imaging, Molecular, and Integrated Approaches.Cancers · 2026Review
- Artificial intelligence and multi-omics integration in liquid biopsy for genitourinary cancers: a systematic scoping review.International urology and nephrology · 2026Article
- Machine learning-DeepSurv prediction model integrating mpMRI radiomics and genomic biomarkers for BCR-free survival and tumor response in prostate radiotherapy.Journal of radiation research · 2026Article
- Radiomics-based machine learning models for predicting genomic alterations in metastatic prostate cancer using PSMA PET imaging: a pilot study.EJNMMI reports · 2025Article
- Redefining Prostate Cancer Precision: Radiogenomics, Theragnostics, and AI-Driven Biomarkers.Cancers · 2025Review
- Impact of magnetic resonance imaging visibility of prostate cancer on partial gland ablation.BJUI compass · 2025Article
- Precise prediction of bone metastases and metastatic burden using exosomal mirnas and radiomics: a multi-center study.Journal of translational medicine · 2025Article
- Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care.Diagnostics (Basel, Switzerland) · 2025Review
- Ultrasound-based radiogenomics: status, applications, and future direction.Ultrasonography (Seoul, Korea) · 2025Article
- Advancements in molecular imaging probes for precision diagnosis and treatment of prostate cancer.Journal of Zhejiang University. Science. B · 2025Review
- Empowering health care consumers & understanding patients' perspectives on AI integration in oncology and surgery: A perspective.Health science reports · 2024Article
- Diagnostic Accuracy of Molecular Imaging Techniques for Detecting Prostate Cancer: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- Using active surveillance for Gleason 7 (3+4) prostate cancer: A narrative review.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2024Review
- The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer.Journal of personalized medicine · 2024Review
- Article
5 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
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.
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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.