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Abstract #3465

Non-invasive quantification of prostate cancer using AMICO framework for VERDICT MRI

Elisenda Bonet-Carne1, Alessandro Daducci2,3, Eleftheria Panagiotaki1, Edward Johnston4, Nicola Stevens4, David Atkinson4, Shonit Punwani4, and Daniel C Alexander1

1Centre for Medical Image Computing, University College London, London, United Kingdom, 2Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 3University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 4Centre for Medical Imaging, University College London, London, United Kingdom

The aim of this study is to extend the AMICO framework to the VERDICT model-based diffusion-weighted MRI (DW-MRI) technique and to evaluate its performance to prostate cancer imaging. DW-MRI was acquired for 4 subjects and the VERDICT model was fitted to the data using both fitting procedures. In both cases similar differences in parameter values between tumour and normal tissue were found. The AMICO formulation reduces the computation time for VERDICT and produces parameter maps that are more homogeneous than those obtained with the original fitting. The AMICO formulation reflects the microstructural differences in a clinically practical time.

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