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Abstract #3376

A Novel Framework for Simulating the In-Vivo Diffusion MRI Signal in Solid Tumours, Based on High-Resolution Optical Imaging Data from Real-World Tumours.

Ben Hipwell1, Tom Roberts1, Paul Sweeney2, Angela D'Esposito1, Morium Ali1, Eleftheria Panagiotaki3, Mark Lythgoe1, Daniel Alexander3, Rebecca Shipley2, and Simon Walker-Samuel1

1Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom, 2Mechanical Engineering, University College London, London, United Kingdom, 3Centre for Medical Image Computing and Computer Science, University College London, London, United Kingdom

We report the development of a novel in-silico modelling framework for probing the in-vivo diffusion MRI signal in tumours, based on high-resolution (5-10µm) optical imaging data from complete tumours. Blood flow in tissue substrates was estimated using fluid dynamical modelling. We then simulated the MRI signal using a Monte Carlo approach, and fitted the VERDICT model. VERDICT has previously been proposed as a method to noninvasively quantify histological features of tissue, including intracellular, extracellular and vascular volume fractions, cell radius and blood flow. We report preliminary findings of a good correspondence between the ground truth and measured values.

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