Computer quantification of “angle of collapse” on maximum expiratory flow volume curve for diagnosing asthma-COPD overlap syndrome

Abstract

BackgroundIn a previous study, we demonstrated that asthma patients with signs of emphysema on quantitative computed tomography (CT) fulfill the diagnosis of asthma-COPD overlap syndrome (ACOS). However, quantitative CT measurements of emphysema are not routinely available for patients with chronic airway disease, which limits their application. Spirometry was a widely used examination tool in clinical settings and shows emphysema as a sharp angle in the maximum expiratory flow volume (MEFV) curve, called the “angle of collapse (AC)”. The aim of this study was to investigate the value of the AC in the diagnosis of emphysema and ACOS.MethodsThis study included 716 participants: 151 asthma patients, 173 COPD patients, and 392 normal control subjects. All the participants underwent pulmonary function tests. COPD and asthma patients also underwent quantitative CT measurements of emphysema. The AC was measured using computer models based on Matlab software. The value of the AC in the diagnosis of emphysema and ACOS was evaluated using receiver-operating characteristic (ROC) curve analysis.ResultsThe AC of COPD patients was significantly lower than that of asthma patients and control subjects. The AC was significantly negatively correlated with emphysema index (EI; r=−0.666, P<0.001), and patients with high EI had a lower AC than those with low EI. The ROC curve analysis showed that the AC had higher diagnostic efficiency for high EI (area under the curve =0.876) than did other spirometry parameters. In asthma patients, using the AC ≤137° as a surrogate criterion for the diagnosis of ACOS, the sensitivity and specificity were 62.5% and 89.1%, respectively.ConclusionThe AC on the MEFV curve quantified by computer models correlates with the extent of emphysema. The AC may become a surrogate marker for the diagnosis of emphysema and help to diagnose ACOS.

Impact of COPD on prognosis of lung cancer: from a perspective on disease heterogeneity

“…In addition, computer quantification of AC on MEFV curve has been proved to be an alternative method for predicting the presence of emphysema, which consequently facilitates the emphysema-predominant COPD phenotype determination. 26 – 28 In this study, we categorized COPD into emphysema-predominant phenotype and nonemphysema-predominant phenotype according to the computer quantification of AC. Our results were obtained on disease heterogeneity perspective, which showed that COPD, especially the emphysema-predominant phenotype was significantly associated with worsened OS of squamous carcinoma.…”

“… 26 , 27 We referred to the Topalovic’s method to make a quantitative measurement of AC. 27 According to our previous research, 28 the raw PFT data points of the MEFV curve were reestablished and analyzed by a computer model. The ACs were measured with standard procedures using the computer model based on Matlab software 8.5 (The MathWorks, Natick, MA, USA).…”

The link between chronic obstructive pulmonary disease phenotypes and histological subtypes of lung cancer: a case&ndash;control study

“…In the present study, computer quantification of AC on the MEFV curve was used to categorize phenotypes: emphysema-predominant and non-emphysema-predominant. 35 – 37 The results obtained showed that compared to non-COPD, both phenotypes independently increased the risk of overall lung cancer and most lung cancer subtypes (including adenocarcinoma, SCC, SCLC, and large-cell carcinoma). A previous cross-sectional study reported that the risk odds of SCC were significantly increased among lung cancer patients with emphysema.…”

“…The procedure was performed according to previous work. 37 A few COPD patients whose raw PFT data were not available were excluded from further analysis. Studies have demonstrated that sharp AC in the MEFV curve is an indicator of emphysema.…”

“…Computer quantification of airway collapse (AC) on maximum expiratory flow volume (MEFV) curve is an alternative and reproducible method to predict the presence of emphysema that facilitates the identification of the emphysema-predominant phenotype of COPD. 35 – 37 …”