Abstract #3999

A Data-Driven Sequential Backward Selection Framework to Accelerate Diffusion-Relaxation Prostate Microstructure Mapping

Zhaohuan Zhang¹, Sohrab Afshari Mirak¹, Melina Hosseiny¹, Afshin Azadikhah¹, Amir Bajgiran¹, Alan Priester², Kyunghyun Sung¹, Anthony E Sisk³, Robert E Reiter², Steven Raman¹, Dieter R Enzmann¹, and Holden H Wu¹

¹Department of Radiology, UCLA, Los Angeles, CA, United States, ²Department of Urology, UCLA, Los Angeles, CA, United States, ³Department of Pathology, UCLA, Los Angeles, CA, United States

Synopsis

Diffusion-Relaxation Correlation Spectrum Imaging (DR-CSI) can provide unique microstructural information for prostate cancer characterization, but requires longer scan times for two-dimensional encoding of TE and b-values. This study developed a data-driven sequential backward selection framework that determined subsampled encoding schemes for DR-CSI, achieving 70% reduction of scan time to 6min while maintaining accurate ex vivo prostate microstructure mapping.

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