Detection of structural pulmonary changes with real-time and high-fidelity analysis of expiratory CO2

Abstract

Abstract Background There is an unmet need for easily available sensitive markers of structural lung disease. Assessment of lung diffusion capacity with foreign gases is currently state-of-the-art, however, results are unspecific and the methods are technically demanding. We developed a fully-automatic algorithm to analyze high-fidelity expiratory CO2 flows from resting ventilation and compared the derived readouts with the diffusing capacity for carbon monoxide (DLCO) regarding their diagnostic accuracy. Methods This pilot study enrolled clinically well characterized patients with chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), pulmonary arterial hypertension (PAH) and controls without lung disease from a pulmonary hypertension clinic and investigated them by means of our newly developed algorithm. We evaluated dead-, mixed- and alveolar space volumes (DSV, MSV, ASV, respectively), their respective ventilatory equivalents for CO2 (EqCO2) and the fraction of expiratory CO2 (FECO2) over expired volume (VE) as primary readouts for diagnosis of structural lung disease and pulmonary hypertension. Results We enrolled 52 subjects, 11 COPD (7 men; median (IQR) age 64 (63–69) years), 10 ILD (7 men; 61 (54–77) years), 10 PAH patients (1 man; 64 (61–73) years) and 21 healthy controls (9 men; 56 (52–61) years; 11 non-smokers). Patients, compared to controls, showed higher MSV (221 (164–270) mL vs. 144 (131–167) mL, p < 0.001) and higher EqCO2 of the whole exhalation (38 (34–42) vs. 30 (29–35), p < 0.001), respectively. While EqCO2 was elevated in all diseased groups, MSV was only increased in COPD and ILD but not in PAH. MSV and maximum FECO2/VE slope were significantly correlated with DLCO (ρ=-0.69 and ρ = 0.72, respectively; both p < 0.001). According to receiver operating characteristic (ROC) analysis, MSV distinguished diseased from healthy subjects with an area under the curve (AUC) of 0.81 (95% CI: 0.69–0.93) with an optimal cut-off at 191 mL (sensitivity 68%, specificity 90%), and the parenchymal diseases COPD and ILD from PAH with AUC 0.74 (95% CI: 0.55–0.92), optimal cut-off at 210 mL; sensitivity 71%, specificity 80%). Conclusions Fully-automatic high-fidelity expiratory CO2 flow analysis is technically feasible, easy and safe to perform, and may represent a novel approach to detect structural changes of the lung parenchyma and/or pulmonary hypertension without need for foreign gas.