A hybrid method for efficient and accurate simulations of diffusion compartment imaging signals

Gaëtan Rensonnet; Damien Jacobs; Benoît Macq; Maxime Taquet

doi:10.1117/12.2207890

22 December 2015 A hybrid method for efficient and accurate simulations of diffusion compartment imaging signals

Gaëtan Rensonnet, Damien Jacobs, Benoît Macq, Maxime Taquet

Proceedings Volume 9681, 11th International Symposium on Medical Information Processing and Analysis; 968107 (2015) https://doi.org/10.1117/12.2207890
Event: 11th International Symposium on Medical Information Processing and Analysis (SIPAIM 2015), 2015, Cuenca, Ecuador

Abstract

Diffusion-weighted imaging is sensitive to the movement of water molecules through the tissue microstructure and can therefore be used to gain insight into the tissue cellular architecture. While the diffusion signal arising from simple geometrical microstructure is known analytically, it remains unclear what diffusion signal arises from complex microstructural configurations. Such knowledge is important to design optimal acquisition sequences, to understand the limitations of diffusion-weighted imaging and to validate novel models of the brain microstructure. We present a novel framework for the efficient simulation of high-quality DW-MRI signals based on the hybrid combination of exact analytic expressions in simple geometric compartments such as cylinders and spheres and Monte Carlo simulations in more complex geometries. We validate our approach on synthetic arrangements of parallel cylinders representing the geometry of white matter fascicles, by comparing it to complete, all-out Monte Carlo simulations commonly used in the literature. For typical configurations, equal levels of accuracy are obtained with our hybrid method in less than one fifth of the computational time required for Monte Carlo simulations.

Citation Download Citation

Gaëtan Rensonnet, Damien Jacobs, Benoît Macq, and Maxime Taquet "A hybrid method for efficient and accurate simulations of diffusion compartment imaging signals", Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 968107 (22 December 2015); https://doi.org/10.1117/12.2207890

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