Abstract #3131

High-Resolution Diffusion Kurtosis Imaging (DKI) Enabled by Segmented Position Orientation Adaptive Smoothing (POAS)

Siawoosh Mohammadi¹, Karsten Tabelow², Thorsten Feiweier³, Joerg Polzehl², Nikolaus Weiskopf¹

¹Wellcome Trust Centre for Neuroimaging at UCL, ION UCL, UCL, London, United Kingdom; ²Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany; ³Healthcare Sector, Siemens AG, Erlangen, Bayern, Germany

Recent studies suggest that Diffusion Kurtosis Imaging (DKI) is more sensitive to gray microstructure than the well-known diffusion tensor imaging (DTI). However, DKI suffers from a low signal-to-noise ratio (SNR), since it is based on multiple and high b-value data. Thus, in-vivo high-resolution DKI with small voxel sizes has not been available on clinical scanners. We aimed to overcome the low SNR issue by using a novel version of the position orientation adaptive smoothing (POAS), which is separately applied on grey and white matter masks.