AUTHOR=Villarreal-Haro Juan Luis , Gardier Remy , Canales-Rodríguez Erick J. , Fischi-Gomez Elda , Girard Gabriel , Thiran Jean-Philippe , Rafael-Patiño Jonathan TITLE=CACTUS: a computational framework for generating realistic white matter microstructure substrates JOURNAL=Frontiers in Neuroinformatics VOLUME=17 YEAR=2023 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2023.1208073 DOI=10.3389/fninf.2023.1208073 ISSN=1662-5196 ABSTRACT=

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.