Reduced-order modeling and analysis of dynamic cerebral autoregulation via diffusion maps.
Reduced-order modeling and analysis of dynamic cerebral autoregulation via diffusion maps.
复制标题
通过扩散图进行动态大脑自动调节的降阶建模和分析。
DOI：
10.1088/1361-6579/acc780
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发表时间：
2023
影响因子：
3.2
通讯作者：
Kougioumtzoglou,IA
中科院分区：
文献类型：
--
作者：
DosSantos,KRM;Katsidoniotaki,MI;Miller,EC;Petersen,NH;Marshall,RS;Kougioumtzoglou,IA
目的基于扩散图的概念，开发了一种数据驱动技术，用于动态大脑自动调节（DCA）的简约建模和分析。具体来说，首先，基于动脉血压、脑血流速度及其时间导数考虑DCA动力学的状态空间描述。接下来，对数据集域上的图上的随机游走的马尔可夫矩阵进行特征值分析，产生内在动力学的低维表示。通过仅考虑两个最重要的特征值，可以进一步降低维度。它们的比率值表明基础系统是受活跃还是低活跃动态控制，分别表明 DCA 功能健康或受损。我们通过考虑健康个体和单侧颈内动脉 (ICA) 狭窄或闭塞的患者来评估该技术的可靠性。我们使用 McNemar 的卡方检验计算了该技术的灵敏度，以检测第二组 DCA 功能中假定的侧对侧差异（假设闭塞或狭窄侧的动态减退）。将结果与传递函数分析（TFA）进行比较。还在缺失数据的假设下比较了两种方法的性能。主要结果扩散图和 TFA 均表明 ICA 狭窄或闭塞患者的 DCA 存在生理性左右差异，敏感性分别为 81% 和 71%。此外，这两种方法都表明了闭塞或狭窄一侧与健康组任意两侧之间的差异。然而，扩散图捕捉到了未遮挡侧和健康组之间的额外差异，而 TFA 则没有。此外，与 TFA 相比，扩散图在缺失数据时表现出优越的性能。 意义 使用扩散图技术导出的特征值比可潜在用作可靠且稳健的生物标志物，用于评估自动调节的内在动态有多活跃，并指示健康与受损的 DCA 功能。
ObjectiveA data-driven technique for parsimonious modeling and analysis of dynamic cerebral autoregulation (DCA) is developed based on the concept of diffusion maps. Specifically, first, a state-space description of DCA dynamics is considered based on arterial blood pressure, cerebral blood flow velocity, and their time derivatives. Next, an eigenvalue analysis of the Markov matrix of a random walk on a graph over the dataset domain yields a low-dimensional representation of the intrinsic dynamics. Further dimension reduction is made possible by accounting only for the two most significant eigenvalues. The value of their ratio indicates whether the underlying system is governed by active or hypoactive dynamics, indicating healthy or impaired DCA function, respectively. We assessed the reliability of the technique by considering healthy individuals and patients with unilateral internal carotid artery (ICA) stenosis or occlusion. We computed the sensitivity of the technique to detect the presumed side-to-side difference in the DCA function of the second group (assuming hypoactive dynamics on the occluded or stenotic side), using McNemar's chi square test. The results were compared with transfer function analysis (TFA). The performance of the two methods was also compared under the assumption of missing data.Main resultsBoth diffusion maps and TFA suggested a physiological side-to-side difference in the DCA of ICA stenosis or occlusion patients with a sensitivity of 81% and 71%, respectively. Further, both two methods suggested the difference between the occluded or stenotic side and any two sides of the healthy group. However, the diffusion maps captured additional difference between the unoccluded side and the healthy group, that TFA did not. Furthermore, compared to TFA, diffusion maps exhibited superior performance when subject to missing data.SignificanceThe eigenvalues ratio derived using the diffusion maps technique can be potentially used as a reliable and robust biomarker for assessing how active the intrinsic dynamics of the autoregulation is and for indicating healthy versus impaired DCA function.