ArticleEuropean radiology2023
Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Evolving role of biomarkers beyond prostate‑specific antigen in refining prostate cancer screening: From blood‑based tests to urinary and genetic markers (Review).Molecular medicine reports · 2026Review
- Integrating Artificial Intelligence into Prostate MR Imaging: Technical Foundations, Clinical Applications, and Workflow Implications.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Review
- AI-based prostate volume estimation from multi-planar MRI under variable acquisition protocols.European journal of radiology open · 2026Article
- Artificial intelligence-derived transition zone PSA density as a triage tool to reduce unnecessary prostate systematic biopsies in MRI-negative men.Insights into imaging · 2026Article
- Diagnostic Value of Transabdominal Ultrasound-based Versus Magnetic Resonance Imaging-based Prostate-specific Antigen Density for Clinically Significant Prostate Cancer.European urology open science · 2026Article
- Automated voxel-based prostate volumetry improves PSA density-based detection of clinically significant prostate cancer in the PSA gray zone: comparison with manual segmentation and the ellipsoid formula.Frontiers in digital health · 2026Article
- Changes in prostate volume during prostate SBRT delivered on an MR-Linac and correlation with acute toxicity.Clinical and translational radiation oncology · 2025Article
- An online national quality assessment survey of prostate MRI reading: interreader variability in prostate volume measurement and PI-RADS classification.European journal of radiology open · 2025Article
- Comparing AI and Manual Segmentation of Prostate MRI: Towards AI-Driven 3D-Model-Guided Prostatectomy.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- Impact of uncertainty quantification through conformal prediction on volume assessment from deep learning-based MRI prostate segmentation.Insights into imaging · 2024Article
- Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies.European radiology · 2024Article
- Comparison of data fusion strategies for automated prostate lesion detection using mpMRI correlated with whole mount histology.Radiation oncology (London, England) · 2024Article
- An Informative Review of Radiomics Studies on Cancer Imaging: The Main Findings, Challenges and Limitations of the Methodologies.Current oncology (Toronto, Ont.) · 2024Review
- Deep learning performance on MRI prostate gland segmentation: evaluation of two commercially available algorithms compared with an expert radiologist.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Three-Dimensional Measurement of the Uterus on Magnetic Resonance Images: Development and Performance Analysis of an Automated Deep-Learning Tool.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesProstate volume (PV) in combination with prostate specific antigen (PSA) yields PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time-consuming, radiologist-dependent task. The aim of this study was to assess whether a deep learning algorithm can replace PI-RADS 2.1 based ellipsoid formula (EF) for calculating PV.
methodsEight different measures of PV were retrospectively collected for each of 124 patients who underwent radical prostatectomy and preoperative MRI of the prostate (multicenter and multi-scanner MRI's 1.5 and 3 T). Agreement between volumes obtained from the deep learning algorithm (PV
resultsPV
conclusionDeep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI. KEY POINTS: • A commercially available deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI. • The deep-learning algorithm was previously untrained on this heterogenous multicenter day-to-day practice MRI data set.
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