Abstract #2865

Assessment of an automated method for AIF voxel selection for renal filtration rate estimation from DCE-MRI data.

Anita Banerji¹, Derek Magee², Constantina Chrysochou³, Philip Kalra³, David Buckley¹, and Steven Sourbron¹

¹Department of Biomedical Imaging, The University of Leeds, Leeds, United Kingdom, ²School of Computing, The University of Leeds, Leeds, United Kingdom, ³Department of Renal Medicine, Salford Royal hospital NHS foundation trust, Salford, United Kingdom

In this work we present an automated arterial input function voxel selection method for estimation of glomerular filtration rate (GFR) from renal DCE-MRI data. We assessed the agreement of GFR values estimated using the automated method with values estimated using semi-automatic expert selection and nuclear medicine techniques using 16 acquired data sets. The automated method successfully selected voxels within the aorta in all cases. The agreement between the expert and automated method was in some cases poor. However, the agreement of the automated method with the nuclear medicine results was similar to that of the expert method.

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