Abstract #4330

Automatic sodium maps reconstruction using PatchMatch algorithm for phantom detection

Ferran Prados^1,2, Bhavana S Solanky², Patricia Alves Da Mota², Manuel Jorge Cardoso¹, Wallace J Brownlee², Niamh Cawley², David H Miller², Xavier Golay³, Sebastien Ourselin¹, and Claudia Angela Michela Gandini Wheeler-Kingshott^2,4

¹Translational Imaging Group, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom, ³Brain Repair & Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom, ⁴Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy

Quantitative sodium magnetic resonance imaging (²³Na-MRI) enables the non-invasive measurement of in vivo total ²³Na concentration (TSC) in the human brain. This involves a complex process of reconstructing datasets acquired to calculate a TSC map. Quantitative TSC map calibration relies on external reference phantoms with known concentration for linear calibration. This commonly involves manually segmenting the phantoms by trained raters, hindering automatic image analysis, and presenting a bottleneck in the TSC computation. We propose to substitute the manual segmentation by OPAL, a novel, fast, robust and reliable technique for segmenting sodium phantoms that allows fully-automatic reconstruction of TSC maps.

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