Abstract #0704

Monte Carlo Simulation of Multiparameter Effects in Double Diffusion Encoding MRI

Rachawadee Trinate¹, David Berry², Jean-Philippe Galons³, Vitaly Galinsky⁴, Lawrence Frank⁴, and Elizabeth Hutchinson¹

¹Biomedical Engineering, The University of Arizona, Tucson, AZ, United States, ²Department of Orthopaedic Surgery, University of California San Diego, San Diego, CA, United States, ³Department of Medical Imaging, The University of Arizona, Tucson, AZ, United States, ⁴Center for Scientific and Computational Imaging, University of California San Diego, San Diego, CA, United States

Synopsis

Keywords: Microstructure, Microstructure

Motivation: Double Diffusion Encoding (DDE) MRI presents a promising approach for probing tissue microstructure, yet its clinical utility is challenged by the complexity of multiparameter optimization.

Goal(s): This study aims to investigate the effects of DDE encoding parameters and tissue microstructure and geometry on the diffusion signal.

Approach: Monte Carlo simulations using DifSim were conducted, varying τ_m and Δ across three fiber geometries: coherent, tilted, and crossing fibers.

Results: The pore sizes of coherent were extracted from diffusion signal. Sin(2θ) modulation was observed in both tilted and crossing fibers, allowing differentiation based on the ratio of their signal amplitudes.

Impact: Monte Carlo simulations demonstrate a promising method for studying the effects of parameters in DDE, aiding in the optimization of pulse sequences to obtain specific microstructural information and facilitating the translation to MRI scanners.

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