  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, optimising 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 (500um) 3 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.
