COPD is diagnosed and evaluated by pulmonary function testing (PFT). Chest computed tomography (CT) primarily serves a descriptive role for diagnosis and severity evaluation. CT densitometry-based emphysema quantification and lobar fissure integrity assessment are most commonly used, mainly for lung volume reduction purposes and scientific efforts.A shift towards a more quantitative role for CT to assess pulmonary function is a logical next step, since more, currently underutilised, information is present in CT images. For instance, lung volumes such as residual volume and total lung capacity can be extracted from CT; these are strongly correlated to lung volumes measured by PFT.This review assesses the current evidence for use of quantitative CT as a proxy for PFT in COPD and discusses challenges in the movement towards CT as a more quantitative modality in COPD diagnosis and evaluation. To better understand the relevance of the traditional PFT measurements and the role CT might play in the replacement of these parameters, COPD pathology and traditional PFT measurements are discussed.

IntroductionIn emphysema patients, being evaluated for bronchoscopic lung volume reduction (BLVR), accurate measurement of lung volumes is important. Total Lung Capacity (TLC) and Residual Volume (RV) are commonly measured by body-plethysmography, but can also be derived from chest computed tomography (CT). Spirometry-gated CT scanning potentially improves the agreement of CT and body-plethysmography.ObjectiveTo compare lung volumes derived from spirometry-gated CT and “breath-hold-coached” CT to the reference standard: body-plethysmography.MethodsIn this single centre retrospective cohort study, emphysema patients, evaluated for BLVR, underwent body-plethysmography, inspiration (TLC) and expiration (RV) CT-scan with spirometer guidance (“gated group”) or with breath-hold-coaching (“non-gated group”). Quantitative analysis was used to calculate lung volumes from the CT.ResultsWe included 200 patients (age 62±8 years, FEV1 29.2±8.7%, TLC 7.50±1.46 L, RV 4.54±1.07 L). The mean CT-derived TLC was 280(±340)ml lower compared to body-plethysmography in the gated group (n=100), and 590(±430)ml lower for the non-gated group (n=100) (both p<0.001). The mean CT-derived RV was 300(±470)ml higher in the gated group and 700(±720)ml higher in the non-gated group (both p<0.001). Pearson correlation factors were 0.947 for TLC gated, 0.917 for TLC non-gated, 0.823 for RV gated, 0.693 for RV non-gated, 0.539 for %RV/TLC gated and 0.204 for %RV/TLC non-gated. The differences between the gated and non-gated CT results for TLC and RV were significant for all measurements (p<0.001).ConclusionIn severe COPD patients with emphysema, CT-derived lung volumes are strongly correlated to body-plethysmography lung volumes, and especially for RV, more accurate when using spirometry-gating.

Background: Arterial stiffness influences the contour of the digital pressure pulse wave. Method: Here, we investigated whether the digital pulse propagation index (DPPI), based on the digital pressure pulse wave, DPPI is associated with cardiovascular events, heart failure, and mortality in a large population-based cohort. Between 2001 and 2003, DPPI was measured with a PortaPres noninvasive hemodynamic monitoring device (FinaPres Medical Systems, Amsterdam, The Netherlands) in participants of the Prevention of Renal and Vascular End-stage Disease study, a community-based cohort. We assessed the main determinants of the DPPI and investigated associations of DPPI with cardiovascular events and mortality. Results: The study included 5474 individuals. Mean age was 52.3 AE 11.8 years and 50.5% was male. Median baseline DPPI was 5.81 m/s (interquartile range 5.47-6.20). Higher age, mean arterial blood pressure, body height, heart rate, current smoking, and lower HDL cholesterol levels and waist circumference were independent determinants of the DPPI (r 2 ¼ 0.43). After adjustment for heart rate, high log DPPI was associated with all-cause mortality [hazard ratio: 1.67, 95% confidence interval (1.55-1.81) per SD; P < 0.001], cardiovascular mortality [hazard ratio 1.95 (1.72-2.22); P < 0.001], and incident heart failure with reduced ejection fraction [hazard ratio 1.81 (1.60-2.06); P < 0.001]. These associations remained independent upon further adjustment for confounders. Optimal cutoff values for DPPI ranged between 6.1 and 6.3 m/s for all endpoints. After multivariable adjustment, DPPI was no longer associated with coronary artery disease events or cerebrovascular events. Conclusion: The DPPI is associated with an increased risk of development of new onset heart failure with reduced ejection fraction and all-cause and cardiovascular mortality, but not with coronary artery events or cerebrovascular events.