Automated evaluation of diaphragm configuration based on chest CT in COPD patients.

BACKGROUND: Severe chronic obstructive pulmonary disease (COPD) often results in hyperinflation and flattening of the diaphragm. An automated computed tomography (CT)-based tool for quantifying diaphragm configuration, a biomarker for COPD, was developed in-house and tested in a large cohort of COPD patients. METHODS: We used the LungQ platform to extract the lung-diaphragm intersection, as direct diaphragm segmentation is challenging. The tool computed the diaphragm index (surface area/projected surface area) as a measure of diaphragm configuration on inspiratory scans in a COPDGene subcohort. Visual inspection of 250 randomly selected segmentations served as a quality check. Associations between the diaphragm index, Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages, forced expiratory volume in 1 s (FEV1) % predicted, and CT-derived emphysema scores were explored using analysis of variance and Pearson correlation. RESULTS: The tool yielded incomplete segmentation in 9.2% (2.4% major defect, 6.8% minor defect) of 250 randomly selected cases. In 8431 COPDGene subjects (4240 healthy; 4191 COPD), the diaphragm index was increasingly lower with higher GOLD stages (never-smoked 1.83 ± 0.16; GOLD-0 1.79 ± 0.18; GOLD-1 1.71 ± 0.15; GOLD-2: 1.67 ± 0.16; GOLD-3 1.58 ± 0.14; GOLD-4 1.54 ± 0.11) (p < 0.001). Associations were found between the diaphragm index and both FEV1% predicted (r = 0.44, p < 0.001) and emphysema score (r = -0.36, p < 0.001). CONCLUSION: We developed an automated tool to quantify the diaphragm configuration in chest CT. The diaphragm index was associated with COPD severity, FEV1%predicted, and emphysema score. RELEVANCE STATEMENT: Due to the hypothesized relationship between diaphragm dysfunction and diaphragm configuration in COPD patients, automatic quantification of diaphragm configuration may prove useful in evaluating treatment efficacy in terms of lung volume reduction. KEY POINTS: Severe COPD changes diaphragm configuration to a flattened state, impeding function. An automated tool quantified diaphragm configuration on chest-CT providing a diaphragm index. The diaphragm index was correlated to COPD severity and may aid treatment assessment.

Effect of Chest Computed Tomography Kernel Use on Emphysema Score in Severe Chronic Obstructive Pulmonary Disease Patients Evaluated for Lung Volume Reduction.

BACKGROUND: Chest computed tomography (CT) emphysema quantification is a vital diagnostic tool in patient evaluation for bronchoscopic lung volume reduction (BLVR). Smooth kernels for CT image reconstruction are generally recommended for quantitative analyses. This recommendation is not always followed, which may affect quantification of emphysema extent and eventually, treatment decisions. OBJECTIVE: The main goal is to demonstrate the influence of CT reconstruction kernels on emphysema quantification in patients with severe COPD, considered for BLVR. METHODS: Chest CT scans were acquired with one multi-detector CT system and reconstructed using three different kernels: smooth, medium smooth, and sharp. Other parameters were kept constant. Emphysema scores (ESs), meaning the percentage of voxels below -950 Hounsfield units, were calculated and compared to the smooth reference kernel using paired t tests. Bland-Altman plots were made to assess the biases and limits of agreement between kernels. RESULTS: Ninety-eight COPD patient CT scans were analyzed. The sharp kernel had a systematic bias of 6.2% and limits of agreement of 16.6% to -4.2% compared to the smooth kernel. The medium smooth kernel had a systematic bias of 5.7% and limits of agreement of 9.2% and 2.2% compared to the smooth kernel. The ES differed, for a single patient, up to 18% for different kernels. CONCLUSIONS: Chest CT kernel reconstruction can lead to a significant difference in emphysema severity quantification. This may cause invalid treatment selection in COPD patients evaluated for BLVR. Standardization of a smooth CT kernel setting and/or normalization to a standard kernel is strongly recommended.

Evaluation of spirometry-gated computed tomography to measure lung volumes in emphysema patients.

INTRODUCTION: In emphysema patient 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. The aim of this study was to compare lung volumes derived from spirometry-gated CT and "breath-hold-coached" CT to the reference standard: body plethysmography. METHODS: In this single-centre retrospective cohort study, emphysema patients being 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. RESULTS: 200 patients were included in the study (mean±sd age 62±8 years, forced expiratory flow in 1 s 29.2±8.7%, TLC 7.50±1.46 L, RV 4.54±1.07 L). The mean±sd 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±sd 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). CONCLUSION: In 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.

Measuring pulmonary function in COPD using quantitative chest computed tomography analysis.

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.

Digital arterial pressure pulse wave analysis and cardiovascular events in the general population: the Prevention of Renal and Vascular End-stage Disease study.

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 ±â€Š11.8 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 = 0.43). After adjustment for heart rate, highlogDPPI 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.