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Abstract #2463

Intra-compartmental kurtosis biases tensor-valued multidimensional diffusion

Rafael Neto Henriques1, Sune Nørhøj Jespersen2,3, and Noam Shemesh1
1Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, 2Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Clinical Institute, Aarhus University, Aarhus, Denmark, 3Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark

Multidimensional diffusion encoding (MDE) has been gaining attention for its potential to describe tissue microstructure with enhanced specificity by resolving kurtosis sources, albeit with significant assumptions (no time dependence, no intra-compartmental kurtosis). Correlation Tensor Imaging (CTI) has been introduced as a novel methodology capable of resolving kurtosis sources without relying on a-priori assumptions. Here, we harnessed CTI to validate the accuracy of tensor-valued MDE metrics and assess the importance of intra-compartmental kurtosis (Kintra) in tissues. Our results reveal that Kintra is non-negligible and skews the estimates of tensor-valued MDE approaches, even in the absence of detectable diffusion time dependence.

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