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.

翻译：蒙特卡洛扩散模拟通过在可控环境中生成合成扩散加权磁共振图像（DW-MRI），是验证组织微结构模型的强大工具。这对于理解微米级组织特性与毫米级DW-MRI信号之间的关联、优化针对特定微结构特性的采集协议，以及评估估计方法的鲁棒性和准确性具有基础性意义。然而，精确模拟需要能反映所研究组织主要微结构特征的基质。为解决这一挑战，我们提出了一种新型计算工作流程——CACTUS（定制超密基质的计算性轴突配置器），用于生成合成白质基质。我们的方法能够构建比现有方法更高填充密度的基质，轴突内体积分数可达95%，同时支持最大(500微米)³的体素尺寸并具备丰富的纤维复杂性。CACTUS可生成具有角度分散、束交叉以及沿纤维方向内径、外径和g-比值变化的纤维束。我们通过引入新型全局代价函数和纤维径向生长方法实现这一目标，使基质能够匹配预定义的靶向特性，并复现组织学研究中报告的特征。CACTUS推动了复杂合成基质的发展，为微结构成像的未来应用铺平了道路。