ArticleScientific reports2021
MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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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
24 citing papers in PubMed.
- Apparent diffusion coefficient radiomics for differentiating benign and malignant PI-RADS 3-5 prostate lesions: external validation.International urology and nephrology · 2026Article
- Artificial intelligence-enabled MRI surveillance of prostate cancer: integrating PRECISE v2, PI-QUAL, and longitudinal biomarkers-a narrative review.Abdominal radiology (New York) · 2026Review
- Exploring the utility of artificial intelligence in identifying progression of prostate cancer during active surveillance: A systematic review.Prostate cancer and prostatic diseases · 2026Review
- Article
- Possible Role of Diffusion-Weighted Imaging in Prediction of Prostate Cancer Grade Group Upgrading: Insights from Biopsy to Radical Prostatectomy.Medicina (Kaunas, Lithuania) · 2026Article
- mpMRI-Based Risk Estimation to Optimize Prostate Cancer Patient Selection for Active Surveillance.Cancers · 2026Article
- Predictive models for biopsy upgrading in active surveillance for prostate cancer: a scoping review.World journal of urology · 2026Article
- Article
- Integrating multimodal data to predict the progression of hormone-sensitive prostate cancer.Clinical proteomics · 2025Article
- Prostate MRI and artificial intelligence during active surveillance: should we jump on the bandwagon?European radiology · 2024Review
- Biparametric MRI in prostate cancer during active surveillance: is it safe?European radiology · 2024Review
- [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Zone-specific computer-aided diagnosis system aimed at characterizing ISUP ≥ 2 prostate cancers on multiparametric magnetic resonance images: evaluation in a cohort of patients on active surveillance.World journal of urology · 2023Article
- The impact of pre-processing and disease characteristics on reproducibility of T2-weighted MRI radiomics features.Magma (New York, N.Y.) · 2023Article
- Review
- Stability of Multi-Parametric Prostate MRI Radiomic Features to Variations in Segmentation.Journal of personalized medicine · 2023Article
- mpMRI Interpretation in Active Surveillance for Prostate Cancer-An overview of the PRECISE score.Abdominal radiology (New York) · 2023Review
- Commentary: considering radiomics in the setting of prostate cancer active surveillance.European radiology · 2023Article
- Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance.European radiology · 2023Article
- Beyond diagnosis: is there a role for radiomics in prostate cancer management?European radiology experimental · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Nearly half of patients with prostate cancer (PCa) harbour low- or intermediate-risk disease considered suitable for active surveillance (AS). However, up to 44% of patients discontinue AS within the first five years, highlighting the unmet clinical need for robust baseline risk-stratification tools that enable timely and accurate prediction of tumour progression. In this proof-of-concept study, we sought to investigate the added value of MRI-derived radiomic features to standard-of-care clinical parameters for improving baseline prediction of PCa progression in AS patients. Tumour T
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