Newell, John D.

Introduction: Heart failure (HF) affects interstitial lung structure and function. AI-assisted quantitative computed tomography (qCT) offers possibility of objective assesment of lung structure, allowing to detect the presence and the severity of HF. Hypothesis: Can automated qCT analysis discriminate HF from controls and identify tissue structures most linked to degree of congestion ? Methods: Subjects underwent right heart catheterization (RHC), native CT chest imaging (full inspiration/expiration) by Naeotom-α photon-counting CT scanner (Siemens), lab testing, echocardiography. Automated AI-based analysis (VIDA Diagnostics) was employed to evaluate lung volumes, densities and tissue texture. Image series were used in mediastinal and lung window reconstruction with slice thickness 0,8 mm and increments 0,5 mm. Results: 186 HF patients (85% HFrEF, NYHA 2.8±0.5, 58 y, 80% males, NTproBNP 4491 pg/ml, LVEF 26%) and 43 controls of similar sex and BMI were analyzed; both groups free of primary lung disease. In HF, 85 % had PH (mPAP>20mmHg). HF patients had comparable inspiratory lung volume, reduced air volume and increased lung tissue volume, compared to controls. Mean lung density (-782±50 vs -832±25 HU, p<0.0001), density variability and estimated lung fluid content (21.3 vs 16.7%, p<0.0001) were all higher in HF compared to controls. Across various density cut-offs, the most notable difference was at lung tissue density < -856 HU at inspiration. Lung tissue density corelated with mean PA pressure (r=0.49, p<0.0001), and less with pulmonary vascular resistance (r=0.21, p=0.006). Insp/exp scan analysis showed no difference in air trapping, but reduced lung tissue compliance (Jacobian strain: 1.8±0.4 vs 1.6±0.3, p=0.0005) in HF. Lung texture analysis showed increased ground-glass opacity (GGO) mass (48.8 g vs 9.1 g; p < 0.001), reticulation (42.2 g vs. 8.4 g; p < 0.001) and consolidation (0.5 g vs 0.2 g; p=0.0011) in HF compared to controls, with no difference in honeycombing. GGO mass correlated strongly with pulmonary capillary wedge pressure (PCWP) (r=0.48, p<0.001) and mitral regurgitation grade (r=0.28,<0.0001), but not with inflammation (hsCRP, IL6, WBC), smoking exposure or oncotic pressure. Conclusions: qCT distinguished HF patients from controls by increased lung tissue mass, reduced air volume, increased lung density and increased mass of GGO and reticulation. GGO mass in HF strongly reflects increased hydrostatic pressure, but not inflammation.

Abstract Emphysema’s significant morbidity and mortality underscore the need for reliable outcome metrics in clinical trials. However, commonly accepted chronic obstructive pulmonary disease outcome measures do not adequately capture emphysema severity or progression. Computed tomography (CT) metrics have been validated as accurate indicators of pathological emphysema and predictors of chronic obstructive pulmonary disease progression, exacerbations, and mortality. This position paper reviews the evidence supporting CT densitometry as a biomarker for emphysema, establishes implementation standards, and highlights areas for future research. A systematic literature review addressed three key questions: whether CT densitometry can be used as a diagnostic biomarker of emphysema, whether CT densitometry can be used as a prognostic biomarker, and whether longitudinal change in densitometry can be used as a disease progression monitoring biomarker. Emphysema metrics, such as the percentage of low attenuation areas below −950 Hounsfield units, are validated, highly reproducible diagnostic and prognostic biomarkers. Volume-adjusted lung density is recommended for disease monitoring. Both metrics demonstrate a scan–rescan intraclass correlation coefficient of 0.99 with proper technique. The paper also discusses relevant CT physics, techniques, and sources of variation, including technical factors, physiological changes, and software analysis. Key recommendations for clinical trials include using standardized CT techniques, proper subject selection, and longitudinal evaluation with volume-adjusted lung density.

Abstract Rationale Ground-glass opacities (GGOs) in the absence of interstitial lung disease are understudied. Objectives To assess the association of GGOs with white blood cells (WBCs) and progression of quantified chest computed tomography emphysema. Methods We analyzed data of participants in the SPIROMICS study (Subpopulations and Intermediate Outcome Measures in COPD Study). Chest radiologists and pulmonologists labeled regions of the lung as GGOs, and the adaptive multiple feature method (AMFM) trained the computer to assign those labels to image voxels and quantify the volume of the lung with GGOs (%GGOAMFM). We used multivariable linear regression, zero-inflated negative binomial, and proportional hazards regression models to assess the association of %GGOAMFM with WBCs, changes in percentage emphysema, and clinical outcomes. Measurements and Main Results Among 2,714 participants, 1,680 had chronic obstructive pulmonary disease (COPD) and 1,034 had normal spirometry. Among participants with COPD, on the basis of multivariable analysis, current smoking and chronic productive cough were associated with higher %GGOAMFM. Higher %GGOAMFM was cross-sectionally associated with higher WBC and neutrophil concentrations. Higher %GGOAMFM per interquartile range at visit 1 (baseline) was associated with an increase in emphysema at 1-year follow-up visit by 11.7% (relative increase; 95% confidence interval, 7.5–16.1%; P &lt; 0.001). We found no association between %GGOAMFM and 1-year FEV1 decline, but %GGOAMFM was associated with exacerbations and all-cause mortality during a median follow-up of 1,544 days (interquartile interval, 1,118–2,059). Among normal spirometry participants, we found similar results, except that %GGOAMFM was associated with progression to COPD at 1-year follow-up. Conclusions Our findings suggest that GGOAMFM is associated with increased systemic inflammation and emphysema progression.

Abstract Rationale It is unknown whether air pollution is associated with radiographic features of interstitial lung disease in individuals with chronic obstructive pulmonary disease (COPD). Objectives To determine whether air pollution increases the prevalence of interstitial lung abnormalities (ILA) or percent high-attenuation areas (HAA) on computed tomography (CT) in individuals with a heavy smoking history and COPD. Methods We performed a cross-sectional study of SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), focused on current or former smokers with COPD. Ten-year exposure to particulate matter ⩽2.5 μm in aerodynamic diameter (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2), and ozone before enrollment CT (completed between 2010 and 2015) were estimated with validated spatiotemporal models at residential addresses. We applied adjusted multivariable modified Poisson regression and linear regression to investigate associations between pollution exposure and relative risk (RR) of ILA or increased percent HAA (between −600 and −250 Hounsfield units), respectively. We assessed for effect modification by MUC5B-promoter polymorphism (variant allele carriers GT or TT vs. GG at rs3705950), smoking status, sex, and percent emphysema. Results Among 1,272 participants with COPD assessed for HAA, 424 were current smokers, and 249 were carriers of the variant MUC5B allele. A total of 519 participants were assessed for ILA. We found no association between pollution exposure and ILA or HAA. Associations between pollutant exposures and risk of ILA were modified by the presence of MUC5B polymorphism (P value interaction term for NOx = 0.04 and PM2.5 = 0.05) and smoking status (P value interaction term for NOx = 0.05; NO2 = 0.01; and ozone = 0.05). With higher exposure to NOx and PM2.5, MUC5B variant carriers had an increased risk of ILA (RR per 26 ppb NOx, 2.41; 95% confidence interval [CI], 0.97–6.0; and RR per 4 μg ⋅ m−3 PM2.5, 1.43; 95% CI, 0.93–2.2, respectively). With higher exposure to NO2, former smokers had an increased risk of ILA (RR per 10 ppb, 1.64; 95% CI, 1.0–2.7). Conclusions Exposure to ambient air pollution was not associated with interstitial features on CT in this population of heavy smokers with COPD. MUC5B modified the association between pollution and ILA, suggesting that gene–environment interactions may influence prevalence of interstitial lung features in COPD.