Abstract #3765

UKRIN Kidney Analysis Toolbox (UKAT): A Framework for Harmonized Quantitative Renal MRI Analysis

Alexander J Daniel¹, Fabio Nery², João Sousa³, Charlotte E Buchanan¹, Hao Li⁴, Andrew N Priest^4,5, Steven Sourbron³, David L Thomas^6,7,8, and Susan T Francis¹

¹Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, ²Great Ormond Street Institute of Child Health, University College London, London, United Kingdom, ³Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom, ⁴Department of Radiology, University of Cambridge, Cambridge, United Kingdom, ⁵Department of Radiology, Addenbrooke’s Hospital, Cambridge, United Kingdom, ⁶Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, ⁷Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, ⁸Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom

Multicentre validation studies are key to the clinical translation of renal MRI and as such, the development of harmonised, cross vendor protocols is crucial. To process data acquired from these protocols, the UK Renal Imaging Network Kidney Analysis Toolbox (UKAT) has been developed. This open-source, vendor agnostic and easy to use Python package can be used for image registration, field mapping, relaxometry and diffusion mapping. UKATs combination of robust software, documented methodological decisions and easy to follow tutorials means we envisage this as a useful tool for the renal and abdominal imaging community.

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