Quantifying the shape of the maximal expiratory flow–volume curve in mild COPD

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Highlights

  • The slope-ratio (SR) quantifies the shape of maximal expiratory flow–volume curves.

  • Compared to matched controls, COPD patients had a greater average SR.

  • Unlike controls, COPD patients had a SR that increased with lung volume.

  • The SR could be an additional metric to aid in COPD diagnosis.

Abstract

Maximal expiratory flow–volume (MEFV) curve evaluation using absolute and percent predicted values of flow and volume are used to diagnose respiratory disease, but the shape of the curve is rarely used. Three mathematical methods were used to quantify shape of MEFV curves in subjects with mild COPD (n = 19) and matched healthy controls (n = 15). Those with mild COPD had a significantly greater slope-ratio (SR) (1.90 ± 0.24 vs. 1.28 ± 0.32) and Beta-angle (160 ± 6.7 vs. 186 ± 15.0) compared to healthy individuals (p < 0.05). The flow-ratio method showed no difference between groups. A significant positive SR-volume relationship during expiration was observed in a greater number of mild COPD subjects (94%) compared to controls (20%) (p < 0.001). With its increased spatial resolution and the potential to discern etiology behind specific curvature, we suggest using the SR method when available. The change in SR throughout expiration could help identify those who fall within the lower limit of normal lung function and those who may have pathological obstruction.

Introduction

The maximal expiratory flow volume (MEFV) relationship conveys clinically important information pertaining to the respiratory system. Generating a MEFV curve is technically simple and commercially available equipment and software is inexpensive, accessible and the results are provided in standard spirometry reports. In health, a MEFV curve is reproducible within an individual, but often varies in shape and magnitude between subjects of similar demographics such as age, sex or height; these between-subject differences reflect normal biological variation and do not necessarily reflect pathology (Green et al., 1974, Tien et al., 1979). However, underlying pathologies will systematically change the magnitude and shape of the MEFV curve (Johnson et al., 1999). Therefore, MEFV curves are useful in diagnosing and managing respiratory disease. For example, chronic obstructive pulmonary disease (COPD) can lead to irreversible damage to the airways and lung parenchyma. Consequently, MEFV curves in COPD patients demonstrate a convexity to the volume axis, which is commonly referred to as “scooping”. The scooping is indicative of non-homogenous emptying of the lungs (Mead, 1978). Another example of changes in MEFV curve shape occurs during healthy aging, where changes in lung elastic tissue and stiffening of the chest-wall result in altered lung volumes (Johnson et al., 1994). Age-related changes are associated with structural changes to the airways which reduce maximal expiratory flows (Niewoehner and Kleinerman, 1974) and alter the shape of MEFV curves (Mead, 1978).

While the clinical interpretation of MEFV curves is widespread, only general information regarding absolute and relative (% predicted) volumes and flows are typically used. However, the shape of the MEFV curve provides additional information that is often overlooked, or qualitatively assessed by visual inspection. There are several methods for quantifying the shape of MEFV curves (Fig. 1) (Kapp et al., 1988, Mead, 1978, O’Donnell and Rose, 1990). Specifically, the slope-ratio (SR) index (Mead, 1978) quantifies the instantaneous slope at desired points along the MEFV curves. Since the SR index allows for multiple data points to be gathered, the change in SR throughout expiration can be determined. The Beta angle (β°) method (Kapp et al., 1988) calculates an angle around the flow at 50% vital capacity (VC). Thus, the β° gives an indication of the curvature of the whole MEFV curve. Lastly, the flow-ratio (FR) technique (O’Donnell and Rose, 1990) determines the percentage drop in expiratory flow from 50% to 25% of VC. The FR only determines curvature over a small portion of the MEFV curve, which may not be representative of the entire curve. Each method has the ability to identify population based trends or severe pathologies (Kapp et al., 1988, Mead, 1978, O’Donnell and Rose, 1990). The primary critique of the aforementioned methods is that severe obstructions are easily identifiable with standard pulmonary function tests (PFT), whereas milder forms are less apparent. For example, patients diagnosed with mild COPD are required to have a post-bronchodilator FEV1/FVC ratio <0.7 and FEV1  80% of predicted values, but this may simply reflect the lower end of healthy normal values due to aging, rather than a pathological state (Hansen et al., 2006, Hansen et al., 2007, Quanjer et al., 2011, Swanney et al., 2008). Therefore, if quantitative evaluation of MEFV curve shape can provide additional data that is not reliant on normal values, we may be able to better identify early stages of obstruction.

The purpose of this study was to determine which method of MEFV curve analysis could best identify unique characteristics of subjects with mild COPD. We hypothesized that, compared to healthy subjects, the SR index and β° would detect differences in MEFV curve shape in subjects with mild COPD, whereas the FR would not show any differences. Our hypothesis is based on the following observations. First, the SR and β° evaluate a greater aspect of the MEFV curve, whereas, the FR analysis only uses the latter 50%. Second, the SR evaluates the MEFV curve on a point-by-point basis allowing us to compare the average values, rather than relying on a set of discreet points.

Section snippets

Study participants

The study was a retrospective analysis of published (Guenette et al., 2014) and unpublished data (total n = 34, n = 15 male). All procedures received institutional ethical approval and informed consent was obtained from all subjects. Subjects were chosen in order to determine if the assessment of the shape of MEFV curves matched known alterations in lung and airway function in subjects with mild COPD and healthy controls. COPD severity was based on the GOLD guidelines (Rabe et al., 2007). The mild

Results

Descriptive characteristics are presented in Table 2. By design, subjects with GOLD I COPD were similar to the healthy subjects with respect to anthropometric variables, but differed in spirometric variables. The SR and β° method of curve quantification both detected differences in MEFV curvature between the healthy subjects and those with mild COPD (Table 3). The FR method did not detect differences between the groups (Table 3).

Fig. 2 displays the composite average MEFV curves and the

Discussion

The novel findings of this study are two-fold. First, using the SR and β° angle method allowed us to quantify differences in the shape of the MEFV curve between healthy subjects and those with mild COPD. This is in contrast to previous studies which have only identified curvature difference between healthy individuals and those with advanced lung disease (Jansen et al., 1980, Mead, 1978). Second, because the SR method permits analysis of the curve over a range of lung volumes, we can propose

Conclusions

The SR method of quantifying MEFV shape is able to detect subtle difference between healthy subjects and those with GOLD I COPD. The pattern of change in SR throughout expiration could be particularly useful in aiding the diagnosis of mild COPD when other measures (e.g., FEV1/FVC) may be detecting the effects of normal aging. Specifically, those with COPD have a SR ratio that increases with lung volume, whereas those who are elderly but healthy have a SR that decreases with lung volume. We

Acknowledgements

PBD was supported by a scholarship from the Natural Science and Engineering Council of Canada (NSERC). GEF was partly supported by (1) a focus on stroke fellowship funded by the Heart and Stroke Foundation of Canada, the Canadian Stroke Network, the Canadian Institutes of Health Research (CIHR) Institute of Circulatory and Respiratory Health, and the CIHR Institute of Aging; (2) A research award from the Michael Smith Foundation for Health Research (MSFHR); and (3) a fellowship from NSERC. JAG

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