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Abstract #0708

Improved characterization of prostate tumors through multi-compartmental analysis of restriction spectrum imaging data

Christopher C Conlin1, Christine H Feng2, Ana E Rodriguez-Soto1, Roshan A Karunamuni2, Joshua M Kuperman1, Dominic Holland1, Rebecca Rakow-Penner1, Tyler M Seibert2, Anders M Dale1,3, and Michael E Hahn1
1Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, United States, 2Department of Radiation Medicine and Applied Science, UC San Diego School of Medicine, La Jolla, CA, United States, 3Department of Neurosciences, UC San Diego School of Medicine, La Jolla, CA, United States

Restriction spectrum imaging (RSI) is an advanced multi-shell diffusion technique that models the diffusion-weighted signal as a linear combination of exponential decays. While RSI shows promise for assessing prostate cancer, an optimal RSI model that effectively characterizes the diffusion properties of both normal and cancerous prostate tissue is essential to ensuring an accurate evaluation of prostate cancer lesions. In this study, we determined optimal ADC values for several RSI models of the prostate and assessed the number of tissue compartments required to best describe diffusion in both normal and cancerous prostate tissue.

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