ArticleEuropean radiology2021
Advanced zoomed diffusion-weighted imaging vs. full-field-of-view diffusion-weighted imaging in prostate cancer detection: a radiomic features study.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Role of Artificial Intelligence in the Characterization and Outcome Prediction of Prostate Cancer: A Systematic Review.Tomography (Ann Arbor, Mich.) · 2026Pooled 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
- Microstructure imaging of prostate cancer by diffusion MRI.Magma (New York, N.Y.) · 2026Review
- Deep learning-based diffusion-weighted imaging vs. conventionally obtained diffusion-weighted imaging in prostate cancer extracapsular extension detection: a multicenter retrospective study.BMC medical imaging · 2025Article
- Automated machine learning for prostate cancer detection and Gleason score prediction using T2WI: a diagnostic multi-center study.BMC cancer · 2025Article
- Reduced Field-of-view Diffusion-Weighted Magnetic Resonance Imaging for Detecting Early Gastric Cancer: A Pilot Study Comparing Diagnostic Performance with MDCT and fFOV DWI.Current medical imaging · 2025Article
- Habitat analysis based on magnetic resonance imaging for the prediction of prostate cancer: a dual-center study.Quantitative imaging in medicine and surgery · 2025Article
- MRI radiomic study on prediction of nonenlarged lymph node metastasis of rectal cancer: reduced field-of-view versus conventional DWI.European radiology experimental · 2025Article
- Improved prostate cancer diagnosis: upgraded prostate imaging reporting and data system (PI-RADS) scores by zoomed diffusion-weighted imaging enhance deep-learning-based computer-aided diagnosis accuracy.Quantitative imaging in medicine and surgery · 2025Article
- Assessment of Prostate MR Image and Predictive Value for Benign Prostate Disease among Different DWI Sequences.Current medical imaging · 2025Article
- Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics.European radiology · 2025Article
- Exploring the value of arterial spin labeling and six diffusion MRI models in differentiating solid benign and malignant renal tumors.European radiology experimental · 2024Article
- Development and Validation of a Deep Learning Model to Reduce the Interference of Rectal Artifacts in MRI-based Prostate Cancer Diagnosis.Radiology. Artificial intelligence · 2024Article
- Article
- MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer.Journal of Zhejiang University. Science. B · 2023Review
- Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- Virtual biopsy in abdominal pathology: where do we stand?BJR open · 2023Review
- Adversarial training for prostate cancer classification using magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2022Article
- Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.International journal of molecular sciences · 2021Review
- Calculation of Apparent Diffusion Coefficients in Prostate Cancer Using Deep Learning Algorithms: A Pilot Study.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
objectivesWe aimed to compare the efficiency of prostate cancer (PCa) detection using a radiomics signature based on advanced zoomed diffusion-weighted imaging and conventional full-field-of-view DWI.
methodsA total of 136 patients, including 73 patients with PCa and 63 without PCa, underwent multi-parametric magnetic resonance imaging (mp-MRI). Radiomic features were extracted from prostate lesion areas segmented on full-field-of-view DWI with b-value = 1500 s/mm
resultsBoth z-DWI
conclusionRadiomics signatures based on the z-DWI technology had better diagnostic accuracy for PCa than that based on the f-DWI technology. The mixed model was better at diagnosing PCa and guiding clinical interventions for patients with suspected PCa compared with mp-MRI signatures and clinically independent risk factors. KEY POINTS: • Advanced zoomed DWI technology can improve the diagnostic accuracy of radiomics signatures for PCa. • Radiomics signatures based on z-calDWI
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