Department of Bioengineering, University of Washington, Seattle, WA, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
J Mol Cell Cardiol. 2019 Mar;128:117-128. doi: 10.1016/j.yjmcc.2019.01.010. Epub 2019 Jan 22.
Cardiac conduction disturbances are linked with arrhythmia development. The concept of safety factor (SF) has been derived to describe the robustness of conduction, but the usefulness of this metric has been constrained by several limitations. For example, due to the difficulty of measuring the necessary input variables, SF calculations have only been applied to synthetic data. Moreover, quantitative validation of SF is lacking; specifically, the practical meaning of particular SF values is unclear, aside from the fact that propagation failure (i.e., conduction block) is characterized by SF < 1. This study aims to resolve these limitations for our previously published SF formulation and explore its relationship to relevant electrophysiological properties of cardiac tissue. First, HL-1 cardiomyocyte monolayers were grown on multi-electrode arrays and the robustness of propagation was estimated using extracellular potential recordings. SF values reconstructed purely from experimental data were largely between 1 and 5 (up to 89.1% of sites characterized). This range is consistent with values derived from synthetic data, proving that the formulation is sound and its applicability is not limited to analysis of computational models. Second, for simulations conducted in 1-, 2-, and 3-dimensional tissue blocks, we calculated true SF values at locations surrounding the site of current injection for sub- and supra-threshold stimuli and found that they differed from values estimated by our SF formulation by <10%. Finally, we examined SF dynamics under conditions relevant to arrhythmia development in order to provide physiological insight. Our analysis shows that reduced conduction velocity (Θ) caused by impaired intrinsic cell-scale excitability (e.g., due to sodium current a loss-of-function mutation) is associated with less robust conduction (i.e., lower SF); however, intriguingly, Θ variability resulting from modulation of tissue scale conductivity has no effect on SF. These findings are supported by analytic derivation of the relevant relationships from first principles. We conclude that our SF formulation, which can be applied to both experimental and synthetic data, produces values that vary linearly with the excess charge needed for propagation. SF calculations can provide insights helpful in understanding the initiation and perpetuation of cardiac arrhythmia.
心脏传导障碍与心律失常的发生有关。安全系数（SF）的概念已经被用来描述传导的稳健性，但由于几个限制，该指标的实用性受到了限制。例如，由于难以测量必要的输入变量，SF 的计算仅应用于合成数据。此外，SF 的定量验证也缺乏；具体来说，除了传播失败（即传导阻滞）的特征是 SF < 1 之外，特定 SF 值的实际意义尚不清楚。本研究旨在解决我们之前发表的 SF 公式的这些限制，并探索其与心脏组织相关电生理特性的关系。首先，HL-1 心肌细胞单层在多电极阵列上生长，并使用细胞外电势记录来估计传播的稳健性。仅从实验数据重建的 SF 值主要在 1 到 5 之间（高达 89.1%的位点特征）。该范围与从合成数据得出的值一致，证明该公式是合理的，其适用性不仅限于分析计算模型。其次，对于在 1、2 和 3 维组织块中进行的模拟，我们计算了在电流注入部位周围亚阈值和超阈值刺激下的真实 SF 值，并发现它们与我们的 SF 公式估计的值相差<10%。最后，我们研究了与心律失常发展相关的条件下的 SF 动态，以提供生理见解。我们的分析表明，由于内在细胞尺度兴奋性受损（例如，由于钠电流功能丧失突变）导致的传导速度（Θ）降低与传导稳定性降低（即 SF 降低）有关；然而，有趣的是，由于组织尺度电导率调制引起的 Θ 变化对 SF 没有影响。这些发现得到了从第一原理推导出的相关关系的分析支持。我们得出结论，我们的 SF 公式可应用于实验和合成数据，产生的数值与传播所需的额外电荷线性相关。SF 计算可以提供有助于理解心脏心律失常的发生和持续的见解。
