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.

中文翻译：

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CACTUS：用于生成真实白质微结构基底的计算框架

蒙特卡罗扩散模拟是通过在受控环境中生成合成扩散加权磁共振图像 (DW-MRI) 来验证组织微观结构模型的强大工具。这对于理解微米级组织特性和毫米级测量的 DW-MRI 信号之间的联系、优化采集协议以瞄准感兴趣的微观结构特性以及探索估计方法的稳健性和准确性至关重要。然而，准确的模拟需要能够反映所研究组织的主要微观结构特征的基材。为了应对这一挑战，我们引入了一种新颖的计算工作流程 CACTUS（用于定制和超密基质的计算轴突配置器），用于生成合成白质基质。我们的方法允许构建比现有方法具有更高堆积密度、高达 95% 的轴突内体积分数以及高达 500μm 的更大体素尺寸的基底3具有丰富的纤维复杂性。CACTUS 生成的束具有角色散、束交叉以及沿纤维的内、外半径和 g 比的变化。我们通过引入一种新颖的全局成本函数和纤维径向生长方法来实现这一目标，该方法允许基材匹配预定义的目标特性并反映组织学研究中报告的特性。CACTUS 改进了复杂合成基底的开发，为微结构成像的未来应用铺平了道路。