Department of Physiology, Anatomy and Genetics, University of Oxford , Oxford , United Kingdom.
Department of Computer Science, University of Oxford , Oxford , United Kingdom.
J Appl Physiol (1985). 2018 Mar 1;124(3):615-631. doi: 10.1152/japplphysiol.00745.2017. Epub 2017 Oct 26.
Inhomogeneity in the lung impairs gas exchange and can be an early marker of lung disease. We hypothesized that highly precise measurements of gas exchange contain sufficient information to quantify many aspects of the inhomogeneity noninvasively. Our aim was to explore whether one parameterization of lung inhomogeneity could both fit such data and provide reliable parameter estimates. A mathematical model of gas exchange in an inhomogeneous lung was developed, containing inhomogeneity parameters for compliance, vascular conductance, and dead space, all relative to lung volume. Inputs were respiratory flow, cardiac output, and the inspiratory and pulmonary arterial gas compositions. Outputs were expiratory and pulmonary venous gas compositions. All values were specified every 10 ms. Some parameters were set to physiologically plausible values. To estimate the remaining unknown parameters and inputs, the model was embedded within a nonlinear estimation routine to minimize the deviations between model and data for CO, O, and N flows during expiration. Three groups, each of six individuals, were studied: young (20-30 yr); old (70-80 yr); and patients with mild to moderate chronic obstructive pulmonary disease (COPD). Each participant undertook a 15-min measurement protocol six times. For all parameters reflecting inhomogeneity, highly significant differences were found between the three participant groups ( P < 0.001, ANOVA). Intraclass correlation coefficients were 0.96, 0.99, and 0.94 for the parameters reflecting inhomogeneity in deadspace, compliance, and vascular conductance, respectively. We conclude that, for the particular participants selected, highly repeatable estimates for parameters reflecting inhomogeneity could be obtained from noninvasive measurements of respiratory gas exchange. NEW & NOTEWORTHY This study describes a new method, based on highly precise measures of gas exchange, that quantifies three distributions that are intrinsic to the lung. These distributions represent three fundamentally different types of inhomogeneity that together give rise to ventilation-perfusion mismatch and result in impaired gas exchange. The measurement technique has potentially broad clinical applicability because it is simple for both patient and operator, it does not involve ionizing radiation, and it is completely noninvasive.
肺部不均匀会影响气体交换，并且可能是肺部疾病的早期标志物。我们假设，对气体交换的高精度测量包含了足够的信息，可以无创地量化不均匀性的许多方面。我们的目的是探讨一种肺不均匀性参数化方法是否既能拟合这些数据，又能提供可靠的参数估计。我们开发了一个不均匀肺部气体交换的数学模型，其中包含顺应性、血管导纳和死腔的不均匀性参数，这些参数均相对于肺容积。输入是呼吸流量、心输出量以及吸气和肺动脉气体组成。输出是呼气和肺静脉气体组成。所有值每 10ms 指定一次。一些参数被设定为生理上合理的值。为了估计其余未知的参数和输入，模型被嵌入到一个非线性估计例程中，以最小化模型和数据在呼气期间 CO、O 和 N 流之间的偏差。三个组，每组 6 人，分别为：年轻（20-30 岁）；老年（70-80 岁）；和轻度至中度慢性阻塞性肺疾病（COPD）患者。每位参与者进行了 6 次 15 分钟的测量方案。对于反映不均匀性的所有参数，三组参与者之间存在非常显著的差异（P<0.001，方差分析）。反映死腔、顺应性和血管导纳不均匀性的参数的组内相关系数分别为 0.96、0.99 和 0.94。我们得出结论，对于所选的特定参与者，可以从呼吸气体交换的无创测量中获得反映不均匀性的参数的高度可重复估计。本研究描述了一种新方法，该方法基于对气体交换的高精度测量，可量化与肺固有相关的三种分布。这些分布代表了三种根本不同类型的不均匀性，它们共同导致通气-灌注不匹配，并导致气体交换受损。该测量技术具有广泛的临床应用潜力，因为它对患者和操作人员都简单，不涉及电离辐射，并且完全无创。
