Abstract #3588

Prostate Cancer Classification by Using Mono Exponential, Stretched Exponential and Kurtosis Model Parameters of Diffusion Signal Decay

Meltem Uyanik^1,2, Rolf Rieter², Michael Abern¹, Winnie Mar³, Virgilia Macias⁴, Hari T. Vigneswaran¹, and Richard L. Magin²

¹Department of Urology, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States, ²Richard and Loan Hill Department of Bioengineering, College of Engineering, University of Illinois at Chicago, Chicago, IL, United States, ³Department of Radiology, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States, ⁴Department of Pathology, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States

Prostate cancer is the most common solid cancer occurring among men in the US. Diffusion-weighted MR imaging plays a complementary role to T₂-weighted images in identifying regional changes in prostate tissue. Here, we fit the diffusion decay signal from patients using the stretched-exponential and the kurtosis models and compare the results with MR guided prostate biopsy histology. Our results showed that the kurtosis and stretched exponential models fit to multi-b values diffusion data have the potential to distinguish benign from malignant lesions. These model parameters identify tissue heterogeneity and structures that may be useful in the grading of prostate cancer.

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