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Abstract #0842

Enhanced Non-invasive Characterisation of Renal Tumour Microstructure with VERDICT-MRI

Snigdha Sen1, Lorna Smith2, Lucy Caselton2, Joey Clemente2, Maxine Tran3, Shonit Punwani2, David Atkinson2, Richard L Hesketh2, and Eleftheria Panagiotaki1
1Centre for Medical Image Computing, University College London, London, United Kingdom, 2Centre for Medical Imaging, University College London, London, United Kingdom, 3Department of Surgical Biotechnology, University College London, London, United Kingdom

Synopsis

Keywords: Kidney, Kidney, Microstructure Imaging

Motivation: Diffusion-weighted (DW)-MRI may characterise renal cell carcinoma (RCC) by reflecting cellularity, but results using the apparent diffusion coefficient (ADC) model are inconclusive.

Goal(s): Use advanced modelling with VERDICT-MRI to characterise renal tissue in two different grades and subtypes of RCC, and compare performance to ADC.

Approach: Fit VERDICT and ADC models to DW-MRI data from two patients and compare performance in terms of accuracy of fitted signal and parameter estimates.

Results: The VERDICT model captures the DW-MRI signal more accurately than ADC. It discriminates between tissue types, and shows high cellularity and low vasculature in the grade 3 tumour, agreeing with independent CT.

Impact: We show that VERDICT-MRI can be used to accurately characterise tumour and benign tissue microstructure in two patients with RCC of different grade and subtype, improving performance over ADC and reflecting histological tissue properties such as cellularity and vasculature.

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Keywords