Diffusion MRI with double diffusion encoding and variable mixing times disentangles water exchange from transient kurtosis DOI Creative Commons
Arthur Chakwizira, Filip Szczepankiewicz, Markus Nilsson

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 13, 2025

Abstract Double diffusion encoding (DDE) makes MRI sensitive to a wide range of microstructural features, and the acquired data can be analysed using different approaches. Correlation tensor imaging (CTI) uses DDE resolve three components diffusional kurtosis: isotropic, anisotropic, microscopic kurtosis. The kurtosis is estimated from contrast between single (SDE) parallel signals at same b-value. Another approach multi-Gaussian exchange (MGE), which employs measure exchange. Sensitivity obtained by contrasting SDE CTI MGE exploit signal quantify exchange, this study investigates interplay these two quantities. We perform Monte Carlo simulations in geometries with varying levels behaviour parameters MGE. conclude that rate intercompartmental transient individual compartments are distinct sources In an attempt disentangle sources, we propose heuristic representation referred as tMGE (MGE incorporating kurtosis) accounts for both effects exploiting signatures mixing time: causes slow dependence on time while arguably has much faster dependence. find applying multiple times orthogonal may enable estimation well

Language: Английский

Diffusion MRI with double diffusion encoding and variable mixing times disentangles water exchange from transient kurtosis DOI Creative Commons
Arthur Chakwizira, Filip Szczepankiewicz, Markus Nilsson

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 13, 2025

Abstract Double diffusion encoding (DDE) makes MRI sensitive to a wide range of microstructural features, and the acquired data can be analysed using different approaches. Correlation tensor imaging (CTI) uses DDE resolve three components diffusional kurtosis: isotropic, anisotropic, microscopic kurtosis. The kurtosis is estimated from contrast between single (SDE) parallel signals at same b-value. Another approach multi-Gaussian exchange (MGE), which employs measure exchange. Sensitivity obtained by contrasting SDE CTI MGE exploit signal quantify exchange, this study investigates interplay these two quantities. We perform Monte Carlo simulations in geometries with varying levels behaviour parameters MGE. conclude that rate intercompartmental transient individual compartments are distinct sources In an attempt disentangle sources, we propose heuristic representation referred as tMGE (MGE incorporating kurtosis) accounts for both effects exploiting signatures mixing time: causes slow dependence on time while arguably has much faster dependence. find applying multiple times orthogonal may enable estimation well

Language: Английский

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