CACTUS: a computational framework for generating realistic white matter microstructure substrates

Frontiers in Neuroinformatics

Neuroscience

Remy Gardier¹  Juan Luis Villarreal-Haro¹  Erick J. Canales-Rodríguez¹  Jean-Philippe Thiran²  Elda Fischi-Gomez²  Gabriel Girard³  Jonathan Rafael-Patiño⁴ 

[1] Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland;Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland;CIBM Center for Biomedical Imaging, Lausanne, Switzerland;Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland;Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland;CIBM Center for Biomedical Imaging, Lausanne, Switzerland;Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland;Department of Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada;Signal Processing Laboratory (LTS5), École Polytechnique Frale de Lausanne (EPFL), Lausanne, Switzerland;Radiology Department, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland;

关键词: microstructure imaging;    diffusion MRI;    brain imaging;    white matter;    Monte-Carlo simulations;    numerical phantom;    synthetic substrates;    high packing density;   

DOI  :  10.3389/fninf.2023.1208073

 received in 2023-04-18, accepted in 2023-07-13,  发布年份 2023

来源: Frontiers

【 摘 要 】

Monte-Carlo diffusion simulations are a powerful tool for validating tissue microstructure models by generating synthetic diffusion-weighted magnetic resonance images (DW-MRI) in controlled environments. This is fundamental for understanding the link between micrometre-scale tissue properties and DW-MRI signals measured at the millimetre-scale, optimizing acquisition protocols to target microstructure properties of interest, and exploring the robustness and accuracy of estimation methods. However, accurate simulations require substrates that reflect the main microstructural features of the studied tissue. To address this challenge, we introduce a novel computational workflow, CACTUS (Computational Axonal Configurator for Tailored and Ultradense Substrates), for generating synthetic white matter substrates. Our approach allows constructing substrates with higher packing density than existing methods, up to 95% intra-axonal volume fraction, and larger voxel sizes of up to 500μm3 with rich fibre complexity. CACTUS generates bundles with angular dispersion, bundle crossings, and variations along the fibres of their inner and outer radii and g-ratio. We achieve this by introducing a novel global cost function and a fibre radial growth approach that allows substrates to match predefined targeted characteristics and mirror those reported in histological studies. CACTUS improves the development of complex synthetic substrates, paving the way for future applications in microstructure imaging.

【 授权许可】

Unknown   
Copyright © 2023 Villarreal-Haro, Gardier, Canales-Rodríguez, Fischi-Gomez, Girard, Thiran and Rafael-Patiño.