Berman Avery J L, Chaussé Jacob, Hartung Grant, Polimeni Jonathan R, Chen J Jean
Department of Physics, Carleton University, Ottawa, ON, Canada.
University of Ottawa Institute of Mental Health Research at The Royal, Ottawa, ON, Canada.
bioRxiv. 2025 Sep 4:2025.08.29.673098. doi: 10.1101/2025.08.29.673098.
Biophysical simulations have guided the development of blood oxygenation level-dependent (BOLD) functional MRI (fMRI) acquisitions and signal models that relate the BOLD signal to the underlying physiology, such as calibrated BOLD and vascular fingerprinting. Numerous simulation techniques have been developed, however, few of them have been directly compared, thus limiting the assessment of the accuracy and interchangeability of these methods as well as the accuracy of the quantitative techniques derived from them. In this work, we compared the accuracy and computational demands of eight previously published simulation approaches that adopt different geometries (ranging from infinite cylinders to synthetic vascular anatomical networks (VANs)), field offset calculations (analytical and Fourier-based), and water diffusion implementations (Monte Carlo and convolution-based), all of which are available in an open-source Python toolkit, . The reference simulation approach for comparison used three-dimensional infinite cylinders, analytical field offsets, and Monte Carlo diffusion. When compared with the reference approach, most of the simulations, including two- and three-dimensional geometries, were in excellent agreement when assuming the intravascular signal contribution was small. Two commonly employed simulation approaches were notably biased; both used two-dimensional geometries with overly simplified vasculature or field offset calculations. In general, the simulated intravascular signal was the least consistent across approaches, thus potentially resulting in larger errors when the intravascular signal contribution is large. Lastly, the VAN results were in good agreement with the reference but they diverged slightly, yet systematically, from each other at smaller radii , primarily driven by intravascular signal differences. We conclude, therefore, that the reference approach is an attractive option for exploratory simulations in the many cases where anatomical and hemodynamic realism is not needed, balancing ease of implementation, accessibility, versatility, computational efficiency, accuracy of results, and interpretability. These findings help pave the way for a broader adoption of forward modelling of the BOLD signal and more reliable interpretations of biophysical simulations aiming to develop quantitative models of the BOLD signal.
生物物理模拟指导了血氧水平依赖（BOLD）功能磁共振成像（fMRI）采集和信号模型的发展，这些模型将BOLD信号与潜在生理过程相关联，如校准BOLD和血管指纹识别。尽管已经开发了许多模拟技术，但很少有技术被直接比较，这限制了对这些方法的准确性和互换性以及从中衍生的定量技术准确性的评估。在这项工作中，我们比较了八种先前发表的模拟方法的准确性和计算需求，这些方法采用了不同的几何形状（从无限圆柱体到合成血管解剖网络（VANs））、场偏移计算（解析法和基于傅里叶的方法）以及水扩散实现方式（蒙特卡罗法和基于卷积的方法），所有这些方法都可在一个开源Python工具包中获取。用于比较的参考模拟方法使用三维无限圆柱体、解析场偏移和蒙特卡罗扩散。与参考方法相比，在假设血管内信号贡献较小时，大多数模拟（包括二维和三维几何形状）都具有很好的一致性。两种常用的模拟方法存在明显偏差；它们都使用了二维几何形状，且血管系统或场偏移计算过于简化。一般来说，不同方法之间模拟的血管内信号一致性最差，因此当血管内信号贡献较大时，可能会导致更大的误差。最后，VAN结果与参考结果吻合良好，但在较小半径处它们彼此之间略有但系统性的偏差，主要是由血管内信号差异驱动的。因此，我们得出结论，在许多不需要解剖和血流动力学真实性的情况下，参考方法是探索性模拟的一个有吸引力的选择，它在实现的简易性、可及性、通用性、计算效率、结果准确性和可解释性之间取得了平衡。这些发现有助于为更广泛地采用BOLD信号正向建模以及更可靠地解释旨在开发BOLD信号定量模型的生物物理模拟铺平道路。
