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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