MP-MRI is a critical component in active surveillance (AS) of prostate cancer (PCa) because of a high negative predictive value for clinically significant tumours. This review illustrates pitfalls of MP-MRI and how to recognise and avoid them. The anterior fibromuscular stroma and central zone are low signal on T2W-MRI/apparent diffusion coefficient (ADC), resembling PCa. Location, progressive enhancement and low signal on b ≥1000 mm²/s echo-planar images (EPI) are differentiating features. BPH can mimic PCa. Glandular BPH shows increased T2W/ADC signal, cystic change and progressive enhancement; however, stromal BPH resembles transition zone (TZ) PCa. A rounded morphology, low T2 signal capsule and posterior/superior location favour stromal BPH. Acute/chronic prostatitis mimics PCa at MP-MRI, with differentiation mainly on clinical grounds. Visual analysis of diffusion-weighted MRI must include EPI and appropriate windowing of ADC. Quantitative ADC analysis is limited by lack of standardization; the ADC ratio and ADC histogram analysis are alternatives to mean values. DCE lacks standardisation and has limited utility in the TZ, where T2W/DWI are favoured. Targeted TRUS-guided biopsies of MR-detected lesions are challenging. Lesions detected on MP-MRI may not be perfectly targeted with TRUS and this must be considered when faced with a suspicious lesion on MP-MRI and a negative targeted TRUS biopsy histopathological result.Keypoints• Multi-parametric MRI plays a critical role in prostate cancer active surveillance.• Low T2W signal intensity structures appear dark on ADC, potentially simulating cancer.• Stromal BPH mimics cancer at DWI and DCE.• Long b value trace EPI should be reviewed• Targeted biopsy of MR-detected lesions using TRUS guidance may be challenging.
• AMLwvf are difficult to prospectively diagnose with imaging. • MRI findings associated with AMLwvf overlap with various RCC subtypes. • T2W-SI combined with chemical-shift SI-index is specific for AMLwvf but lacks sensitivity. • T2W-SI combined with AUC CE-MRI is sensitive and specific for AMLwvf. • Models incorporating two or more findings are more accurate than univariate analysis.
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