ArticleOncotarget2016
Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 2 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.
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.
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Who cites it
68 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
- Radiomics in prostate cancer imaging for a personalized treatment approach - current aspects of methodology and a systematic review on validated studies.Theranostics · 2021Pooled it
- Trial
- 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
- A New Radiotranscriptomic Approach to Analyze Combined Sets of T3b Stage-Specific Genes and Radiomic Features in Prostate Cancer.Cancer reports (Hoboken, N.J.) · 2025Article
- Assessing the Molecular Heterogeneity of Prostate Cancer Biopsy Sampling: Insights from the MAST Trial.European urology focus · 2025Article
- Intrinsic Gene Expression Correlates of the Biophysically Modeled Diffusion Magnetic Resonance Imaging Signal.Biological psychiatry global open science · 2025Article
- Clinical-radiomics hybrid modeling outperforms conventional models: machine learning enhances stratification of adverse prognostic features in prostate cancer.Frontiers in oncology · 2025Article
- Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer.Gland surgery · 2023Review
- Review
- Clinical-Genomic Risk Group Classification of Suspicious Lesions on Prostate Multiparametric-MRI.Cancers · 2023Article
- Predicting cervical lymph node metastasis in OSCC based on computed tomography imaging genomics.Cancer medicine · 2023Article
- Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET-MRI data.Nature biomedical engineering · 2023Article
- Radiogenomics Analysis Linking Multiparametric MRI and Transcriptomics in Prostate Cancer.Cancers · 2023Article
- Inflammation and Prostate Cancer: A Multidisciplinary Approach to Identifying Opportunities for Treatment and Prevention.Cancers · 2022Review
- Overview of radiomics in prostate imaging and future directions.The British journal of radiology · 2022Review
- Non-Invasive Profiling of Advanced Prostate Cancer via Multi-Parametric Liquid Biopsy and Radiomic Analysis.International journal of molecular sciences · 2022Article
- Personalized management of prostate cancer: from molecular and imaging markers to radiogenomics.Polish journal of radiology · 2022Review
- Network Analysis Integrating microRNA Expression Profiling with MRI Biomarkers and Clinical Data for Prostate Cancer Early Detection: A Proof of Concept Study.Biomedicines · 2021Article
- Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.International journal of molecular sciences · 2021Review
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective was to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues.Global gene expression profiles were generated from 17 mpMRI-directed diagnostic prostate biopsies using an Affimetrix platform. Spatially distinct imaging areas ('habitats') were identified on MRI/3D-Ultrasound fusion. Radiomic features were extracted from biopsy regions and normal appearing tissues. We correlated 49 radiomic features with three clinically available gene signatures associated with adverse outcome. The signatures contain genes that are over-expressed in aggressive prostate cancers and genes that are under-expressed in aggressive prostate cancers. There were significant correlations between these genes and quantitative imaging features, indicating the presence of prostate cancer prognostic signal in the radiomic features. Strong associations were also found between the radiomic features and significantly expressed genes. Gene ontology analysis identified specific radiomic features associated with immune/inflammatory response, metabolism, cell and biological adhesion. To our knowledge, this is the first study to correlate radiogenomic parameters with prostate cancer in men with MRI-guided biopsy.
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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.