Evaluation of Multiparametric Magnetic Resonance Imaging in Detection and Prediction of Prostate Cancer

BACKGROUND - Although European Society of Urogenital Radiology proposed the potential of multiparametric magnetic resonance imaging (MP-MRI) as a tool in the diagnostic pathway for prostate cancer (PCa) and published a unified scoring system named Prostate Imaging Reporting and Data System (PI-RADS version 1), these still need to be validated by real-life studies.

OBJECTIVE - To evaluate the role of MP-MRI in detection and prediction of PCa.

METHODS - Patients with clinical suspicion of PCa who underwent prebiopsy MP-MRI from 2002 to 2009 were recruited. MP-MRI results were retrospectively assigned as overall scores using PI-RADS by two radiologists. Patients were followed and the end point was the diagnosis of PCa. Receiver operating characteristics (ROC) curve was performed to test diagnostic efficacy of MP-MRI, under results of biopsy within three months. The cox proportional hazards model was used to identify independent variables for the detection of PCa.

RESULTS - Finally, 1113 of the 1806 enrolled patients were included for analysis. The median follow-up was 56.0 months (1-137 mo). For 582 patients biopsied within three months, area under the curve for the detection of PCa with MP-MRI was 0.88 (95% confidence interval [CI], 0.75-1.00) in group of baseline prostate specific antigen (PSA) 0.01-4.00 ng/ml (n = 31), 0.90 (95% CI, 0.84-0.95) in PSA 4.01-10.00 ng/ml (n = 142), and 0.91 (95% CI, 0.87-0.94) in PSA >10.00 ng/ml (n = 409), respectively. In the cox model adjusted for age and baseline PSA level, for the detection rate of PCa, compared with PI-RADS 1-2 (reference), the hazard ratio was 6.43 (95% CI, 4.29-9.65) for PI-RADS 3, 18.58 (95% CI, 13.36-25.84) for PI-RADS 4-5 (p < 0.001).

CONCLUSIONS - Prebiopsy MP-MRI with PI-RADS is demonstrated as a valuable diagnostic and predictive tool for PCa.

PLoS One. 2015 Jun 12;10(6):e0130207. doi: 10.1371/journal.pone.0130207. eCollection 2015.

Wang R1, Wang H1, Zhao C1, Hu J2, Jiang Y1, Tong Y3, Liu T4, Huang R5, Wang X1.

1 Department of Radiology, Peking University First Hospital, Beijing, China.
2 Department of Radiology, First Affiliated Hospital of Kunming Medical University, YunNan, China.
3 Department of Radiology, Aerospace Central Hospital, Beijing, China.
4 Department of Radiology, Dongzhimen Hospital, Beijing, China.
5 Department of Radiology, Peking University Shenzhen Hospital, Guangdong, China.


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