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Abstract #0146

Detection of Prostate Cancer using Diffusion-Relaxation Correlation Spectrum Imaging with Support Vector Machine Model – A Feasibility Study

Xiaobin Wei1, Guangyu Wu1, and Ke Xue2
1Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China, 2MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China


For clinical prostate examination, magnetic resonance imaging (MRI) is a significant imaging modality. In this study, the feasibility of diffusion-relaxation correlation spectrum imaging (DR-CSI) combined with a support vector machine (SVM) model for detecting PCa in vivo was initially explored, and its diagnostic performance was evaluated and compared with the Prostate Imaging-Reporting and Data System (PI-RADS) score based on multiparametric MRI (MP-MRI). The DR-CSI combined with SVM model may suggest additional clinical value and potential to improve the detection of PCa.

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