Abstract: 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.
CITATION STYLE
Quon, J. S., Moosavi, B., Khanna, M., Flood, T. A., Lim, C. S., & Schieda, N. (2015, August 29). False positive and false negative diagnoses of prostate cancer at multi-parametric prostate MRI in active surveillance. Insights into Imaging. Springer Verlag. https://doi.org/10.1007/s13244-015-0411-3
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