Abstract #3186

Training an Artificial Neural Network by Diffusion-Weighted MRI Data to Differentiate Between Prostate Cancer With High and With Low Gleason Score

Sebastiano Barbieri¹ and Harriet C Thoeny¹

¹Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University of Bern, Bern, Switzerland

We prospectively assess the feasibility of using DW-MRI data to train an artificial neural network which distinguishes between prostate cancer lesions with high (≥7) and with low (=6) Gleason scores in 84 patients. The accuracy of the artificial neural network is compared with the accuracy of classification based on apparent diffusion coefficient (ADC) values.

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