Abstract #3503

Whole-brain diffusional variance decomposition (DIVIDE) in 8 minutes: Technical feasibility at 1.5, 3, and 7 T

Filip Szczepankiewicz¹, Jens Sjölund^2,3,4, Freddy Ståhlberg^1,5,6, Jimmy Lätt⁷, and Markus Nilsson^5,6

¹Medical Radiation Physics, Lund University, Lund, Sweden, ²Elekta Instrument AB, Kungstensgatan 18, Box 7593, SE-103 93 Stockholm, Stockholm, Sweden, ³Department of Biomedical Engineering, Linköping University, Linköping, Sweden, ⁴Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden, ⁵Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden, ⁶Lund University Bioimaging Center, Lund University, Lund, Sweden, ⁷Department of Imaging and Function, Skåne University Hospital, Lund, Sweden

Diffusion weighting along more than one direction at a time (tensor-valued encoding) can be used to probe features of the microstructure that are not accessible by conventional encoding. For example, it enables diffusional variance decomposition (DIVIDE) which can separate the effects of microscopic anisotropy, orientation dispersion, and heterogeneous isotropic diffusivity. Tensor-valued encoding is usually demanding with respect to gradient performance, limiting its applicability to high-performance MRI systems. However, a recent method for optimized encoding significantly reduced the demand on gradient performance, which warrants an investigation of the applicability of such encoding on a wider range of MRI hardware configurations. In this study, we demonstrate whole-brain diffusional variance decomposition (DIVIDE) in less than 8 minutes at a wide range of clinical MRI systems with different hardware configurations.

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