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Abstract #4955

Prostate cancer detection with multiparametric MRI based computer-aided diagnosis: which sequence is the dominant technique

Ge Gao1, Xiaoying Wang, Chengyan Wang, and Jue Zhang

1Radiology, Peking University First Hospital, Beijing, People's Republic of China

Differ from PI-RADS v1, the updated PI-RADS v2 offers a decision process that puts the sequences as different role in scoring process and results in a final five-point score. However, the efficiency of each sequence in prostate cancer (PCa) detection in peripheral zone (PZ) and transition zone (TZ) is investigated by radiologists reading test preliminarily, which is highly depends on reader’s expertise and experience. This work applied a previous published machined learning model to investigate the weight of different sequences, including T2WI, DWI/ADC and DCE, in clinical significant PCa detection, and found that DWI/ADC performed the best both in PZ and TZ clinical significant PCa detection among these basic sequences which is recommended by PI-RADS v2

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