Esfandi Hadi, Javidan Mahshad, Anderson Rozalyn M, Pashaie Ramin
Electrical Engineering and Computer Science Department, Florida Atlantic University, Boca Raton, FL, USA.
Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA.
bioRxiv. 2024 Oct 11:2024.10.07.616950. doi: 10.1101/2024.10.07.616950.
Autoregulation and neurogliavascular coupling are key mechanisms that modulate myogenic tone (MT) in vessels to regulate cerebral blood flow (CBF) during resting state and periods of increased neural activity, respectively. To determine relative contributions of distinct vascular zones across different cortical depths in CBF regulation, we developed a simplified yet detailed and computationally efficient model of the mouse cerebrovasculature. The model integrates multiple simplifications and generalizations regarding vascular morphology, the hierarchical organization of mural cells, and potentiation/inhibition of MT in vessels. Our analysis showed that autoregulation is the result of the synergy between these factors, but achieving an optimal balance across all cortical depths and throughout the autoregulation range is a complex task. This complexity explains the non-uniformity observed experimentally in capillary blood flow at different cortical depths. In silico simulations of cerebral autoregulation support the idea that the cerebral vasculature does not maintain a plateau of blood flow throughout the autoregulatory range and consists of both flat and sloped phases. We learned that small-diameter vessels with large contractility, such as penetrating arterioles and precapillary arterioles, have major control over intravascular pressure at the entry points of capillaries and play a significant role in CBF regulation. However, temporal alterations in capillary diameter contribute moderately to cerebral autoregulation and minimally to functional hyperemia. In addition, hemodynamic analysis shows that while hemodynamics within capillaries remain relatively stable across all cortical depths throughout the entire autoregulation range, significant variability in hemodynamics can be observed within the first few branch orders of precapillary arterioles or transitional zone vessels. The computationally efficient cerebrovasculature model, proposed in this study, provides a novel framework for analyzing dynamics of the CBF regulation where hemodynamic and vasodynamic interactions are the foundation on which more sophisticated models can be developed.
自动调节和神经胶质血管耦合是关键机制，分别在静息状态和神经活动增加期间调节血管中的肌源性张力（MT）以调控脑血流量（CBF）。为了确定不同皮质深度的不同血管区域在CBF调节中的相对贡献，我们开发了一个简化但详细且计算高效的小鼠脑血管模型。该模型整合了关于血管形态、壁细胞的层次组织以及血管中MT的增强/抑制的多种简化和概括。我们的分析表明，自动调节是这些因素之间协同作用的结果，但要在所有皮质深度和整个自动调节范围内实现最佳平衡是一项复杂的任务。这种复杂性解释了在不同皮质深度的毛细血管血流中实验观察到的不均匀性。脑自动调节的计算机模拟支持这样的观点，即脑血管系统在整个自动调节范围内不会维持血流平稳，而是由平坦阶段和斜率阶段组成。我们了解到，具有大收缩性的小直径血管，如穿通小动脉和毛细血管前小动脉，对毛细血管入口处的血管内压力有主要控制作用，并且在CBF调节中起重要作用。然而，毛细血管直径的瞬时变化对脑自动调节的贡献适中，对功能性充血的贡献最小。此外，血流动力学分析表明，虽然在整个自动调节范围内所有皮质深度的毛细血管内血流动力学保持相对稳定，但在毛细血管前小动脉或过渡区血管的最初几个分支级别内可以观察到血流动力学的显著变化。本研究提出的计算高效的脑血管模型为分析CBF调节动力学提供了一个新框架，其中血流动力学和血管动力学相互作用是可以在此基础上开发更复杂模型的基础。
