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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


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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