Automatic analysis of bronchus-artery dimensions to diagnose and monitor airways disease in cystic fibrosis.

BACKGROUND: Cystic fibrosis (CF) lung disease is characterised by progressive airway wall thickening and widening. We aimed to validate an artificial intelligence-based algorithm to assess dimensions of all visible bronchus-artery (BA) pairs on chest CT scans from patients with CF. METHODS: The algorithm fully automatically segments the bronchial tree; identifies bronchial generations; matches bronchi with the adjacent arteries; measures for each BA-pair bronchial outer diameter (Bout), bronchial lumen diameter (Bin), bronchial wall thickness (Bwt) and adjacent artery diameter (A); and computes Bout/A, Bin/A and Bwt/A for each BA pair from the segmental bronchi to the last visible generation. Three datasets were used to validate the automatic BA analysis. First BA analysis was executed on 23 manually annotated CT scans (11 CF, 12 control subjects) to compare automatic with manual BA-analysis outcomes. Furthermore, the BA analysis was executed on two longitudinal datasets (Copenhagen 111 CTs, ataluren 347 CTs) to assess longitudinal BA changes and compare them with manual scoring results. RESULTS: The automatic and manual BA analysis showed no significant differences in quantifying bronchi. For the longitudinal datasets the automatic BA analysis detected 247 and 347 BA pairs/CT in the Copenhagen and ataluren dataset, respectively. A significant increase of 0.02 of Bout/A and Bin/A was detected for Copenhagen dataset over an interval of 2 years, and 0.03 of Bout/A and 0.02 of Bin/A for ataluren dataset over an interval of 48 weeks (all p<0.001). The progression of 0.01 of Bwt/A was detected only in the ataluren dataset (p<0.001). BA-analysis outcomes showed weak to strong correlations (correlation coefficient from 0.29 to 0.84) with manual scoring results for airway disease. CONCLUSION: The BA analysis can fully automatically analyse a large number of BA pairs on chest CTs to detect and monitor progression of bronchial wall thickening and bronchial widening in patients with CF.

Quantitative CT Evaluation of Emphysema Progression over 10 Years in the COPDGene Study.

Background Long-term studies of chronic obstructive pulmonary disease (COPD) can evaluate emphysema progression. Adjustment for differences in equipment and scanning protocols of individual CT examinations have not been studied extensively. Purpose To evaluate emphysema progression in current and former smokers in the COPDGene cohort over three imaging points obtained at 5-year intervals accounting for individual CT parameters. Materials and Methods Current and former cigarette smokers enrolled between 2008 and 2011 from the COPDGene study were prospectively followed for 10 years between 2008 and 2020. Extent of emphysema as adjusted lung density (ALD) from quantitative CT was measured at baseline and at 5- and 10-year follow-up. Linear mixed models adjusted for CT technical characteristics were constructed to evaluate emphysema progression. Mean annual changes in ALD over consecutive 5-year study periods were estimated by smoking status and baseline emphysema. Results Of 8431 participants at baseline (mean age, 60 years ± 9 [SD]; 3905 female participants), 4913 were at 5-year follow-up and 1544 participants were at 10-year follow-up. There were 4134 (49%) participants who were current smokers, and 4449 (53%) participants had more than trace emphysema at baseline. Current smokers with more than trace emphysema showed the largest decline in ALD, with mean annual decreases of 1.4 g/L (95% CI: 1.2, 1.5) in the first 5 years and 0.9 g/L (95% CI: 0.7, 1.2) in the second 5 years. Accounting for CT noise, field of view, and scanner model improved model fit for estimation of emphysema progression (P < .001 by likelihood ratio test). Conclusion Evaluation at CT of emphysema progression in the COPDGene study showed that, during the span of 10 years, participants with pre-existing emphysema who continued smoking had the largest decline in ALD. Adjusting for CT equipment and protocol factors improved these longitudinal estimates. Clinical trial registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See the editorial by Parraga and Kirby in this issue.

Bronchiectasis is associated with lower lung function in lung cancer screening participants.

BACKGROUND AND OBJECTIVE: Bronchiectasis is a frequent incidental finding on chest computed tomography (CT), but its relevance in lung cancer screening is not fully understood. We investigated the association between bronchiectasis and respiratory symptoms, pulmonary function, and emphysema in lung cancer screening participants with and without chronic obstructive pulmonary disease (COPD). METHODS: We included 3260 (ex-)smokers from the Dutch-Belgian lung cancer screening trial (NELSON). Bronchiectasis was scored by chest radiologists. The relationship with pulmonary function (FEV1%predicted, FEV1/FVC), respiratory complaints (cough, dyspnea, wheezing, mucus hypersecretion), and CT-quantified emphysema (15th percentile) was examined with independent t-tests and multivariate regression. RESULTS: Bronchiectasis was present in 5.4% (n = 175/3260). There was no difference in prevalence between subjects with and without COPD (68/1121 [5.9%] vs. 109/2139 [5.1%]; p = .368). COPD subjects with bronchiectasis had a lower FEV1%predicted (76.2% vs. 85.0%; p < .001), lower FEV1/FVC (0.58 vs. 0.62; p < .001), and more emphysema (- 938 HU vs. - 930 HU; p = .001) than COPD subjects without bronchiectasis. In COPD subjects, bronchiectasis was independently associated with a lower FEV1%predicted (B = - 7.7; CI [- 12.3, - 3.3]), lower FEV1/FVC (B = - 2.5; CI [- 4.3, - 0.8]), more cough (OR 2.4; CI [1.3, 4.3]), more mucus hypersecretion (OR 1.8; CI [1.0, 3.1]) and more dyspnea (OR 2.3; CI [1.3, 3.9]). In those without COPD (n = 2139), bronchiectasis was associated with more cough, mucus hypersecretion, and wheezing, but not with deteriorating lung function. CONCLUSION: Bronchiectasis was present in 5.4% of our lung cancer screening participants and was associated with more respiratory symptoms and, in those with COPD, with lower lung function and more emphysema. CLINICAL RELEVANCE STATEMENT: In a lung cancer screening population, bronchiectasis has a prevalence of 5.4% with a mainly mild severity. This finding is of little clinical relevance unless mild COPD is also present. In those subjects, bronchiectasis was associated with a lower lung function, more respiratory symptoms, and more emphysema. KEY POINTS: • Bronchiectasis was found in 5.4% of lung cancer screening participants, consisting of (ex-)smokers with and without mild COPD. • In those with mild COPD, bronchiectasis was associated with a lower lung function, more respiratory symptoms, and more emphysema. • Incidental findings of mild bronchiectasis are not very relevant in a lung cancer screening population, unless COPD is also present.

Plasma sRAGE levels strongly associate with centrilobular emphysema assessed by HRCT scans.

BACKGROUND: There is a strong need for biomarkers to better characterize individuals with COPD and to take into account the heterogeneity of COPD. The blood protein sRAGE has been put forward as promising biomarker for COPD in general and emphysema in particular. Here, we measured plasma sRAGE levels using quantitative LC-MS and assessed whether the plasma sRAGE levels associate with (changes in) lung function, radiological emphysema parameters, and radiological subtypes of emphysema. METHODS: Three hundred and twenty-four COPD patients (mean FEV1: 63%predicted) and 185 healthy controls from the COPDGene study were selected. Plasma sRAGE was measured by immunoprecipitation in 96-well plate methodology to enrich sRAGE, followed by targeted quantitative liquid chromatography-mass spectrometry. Spirometry and HRCT scans (inspiration and expiration) with a 5-year follow-up were used; both subjected to high quality control standards. RESULTS: Lower sRAGE values significantly associated with the presence of COPD, the severity of airflow obstruction, the severity of emphysema on HRCT, the heterogeneous distribution of emphysema, centrilobular emphysema, and 5-year progression of emphysema. However, sRAGE values did not associate with airway wall thickness or paraseptal emphysema. CONCLUSIONS: Rather than being a general COPD biomarker, sRAGE is especially a promising biomarker for centrilobular emphysema. Follow-up studies should elucidate whether sRAGE can be used as a biomarker for other COPD phenotypes as well.

Computed Tomography-based Airway Surface Area-to-Volume Ratio for Phenotyping Airway Remodeling in Chronic Obstructive Pulmonary Disease.

Rationale: Airway remodeling in chronic obstructive pulmonary disease (COPD) is due to luminal narrowing and/or loss of airways. Existing computed tomographic metrics of airway disease reflect only components of these processes. With progressive airway narrowing, the ratio of the airway luminal surface area to volume (SA/V) should increase, and with predominant airway loss, SA/V should decrease.Objectives: To phenotype airway remodeling in COPD.Methods: We analyzed the airway trees of 4,325 subjects with COPD Global Initiative for Chronic Obstructive Lung Disease stages 0 to 4 and 73 nonsmokers enrolled in the multicenter COPDGene (Genetic Epidemiology of COPD) cohort. Surface area and volume measurements were estimated for the subtracheal airway tree to derive SA/V. We performed multivariable regression analyses to test associations between SA/V and lung function, 6-minute-walk distance, St. George's Respiratory Questionnaire, change in FEV1, and mortality, adjusting for demographics, total airway count, airway wall thickness, and emphysema. On the basis of the change in SA/V over 5 years, we categorized subjects into predominant airway narrowing [positive ∆(SA/V) more than 0] and predominant airway loss [negative ∆(SA/V) less than 0] and compared survival between the two groups.Measurements and Main Results: Airway SA/V was independently associated with FEV1/FVC (ß = 0.12; 95% confidence interval [CI], 0.09-0.14; P < 0.001) and FEV1% predicted (ß = 20.10; 95% CI, 15.13-25.08; P < 0.001). Airway SA/V was also independently associated with 6-minute-walk distance, respiratory quality of life, and lung function decline. Compared with subjects with predominant airway narrowing (n = 2,914; 66.3%), those with predominant airway loss (n = 1,484; 33.7%) had worse survival (adjusted hazard ratio for all-cause mortality = 1.58; 95% CI, 1.18-2.13; P = 0.002).Conclusions: Computed tomography-based airway SA/V is an imaging biomarker of airway remodeling and provides differential information on predominant airway narrowing and loss in COPD. SA/V is associated with respiratory morbidity, lung function decline, and survival.

Determinants of Lung Fissure Completeness.

Rationale: New advanced bronchoscopic treatment options for patients with severe chronic obstructive pulmonary disease (COPD) have led to increased interest for COPD phenotyping, including fissure completeness. Objectives: We investigated clinical, environmental, and genetic factors contributing to fissure completeness in patients with and without COPD. Methods: We used data from 9,926 participants of the COPDGene study who underwent chest computed tomographic (CT) scans. Fissure completeness was calculated from CT scans after quantitative CT analysis at baseline and 5-year follow-up. Clinical and environmental factors, including sex, race, smoking, COPD, emphysema, maternal smoking during pregnancy and maternal COPD, were tested for impact on fissure completeness. Genome-wide association analyses were performed separately in non-Hispanic White subjects and African American subjects. Measurements and Main Results: African American subjects had significantly higher fissure completeness than non-Hispanic White subjects for all three fissures (P < 0.001). There was no change in fissure completeness between baseline and 5-year follow-up. For all fissures, no clinically relevant differences in fissure completeness were found for other clinical or environmental factors, including COPD severity. Rs2173623, rs264866, rs2407284, rs7310342, rs4904145, rs6504172, and rs7209556 showed genome-wide significant associations with fissure completeness in non-Hispanic White subjects. In African American subjects, rs264866, rs4904145 and rs6504172 were identified as significant associations. Rs2173623, rs6504172, and rs7209556 lead to WNT5A and HOXB antisense RNA expression, which play an important role during embryogenesis. Conclusions: Fissure completeness is genetically determined and not dependent on age, sex, smoking status, the presence and severity of COPD (including exacerbation frequency), maternal smoking during pregnancy, or maternal COPD.

Quantitative imaging analysis detects subtle airway abnormalities in symptomatic military deployers.

BACKGROUND: Exposure to inhalational hazards during post-9/11 deployment to Southwest Asia and Afghanistan puts military personnel at risk for respiratory symptoms and disease. Pulmonary function and qualitative chest high resolution computed tomography (HRCT) are often normal in "deployers" with persistent respiratory symptoms. We explored the utility of quantitative HRCT imaging markers of large and small airways abnormalities, including airway wall thickness, emphysema, and air trapping, in symptomatic deployers with clinically-confirmed lung disease compared to controls. METHODS: Chest HRCT images from 45 healthy controls and 82 symptomatic deployers with asthma, distal lung disease or both were analyzed using Thirona Lung quantification software to calculate airway wall thickness (by Pi10), emphysema (by percentage of lung volume with attenuation < -950 Hounsfield units [LAA%-950]), and three parameters of air trapping (expiratory/inspiratory total lung volume and mean lung density ratios, and LAA%-856). SAS v.9.4 was used to compare demographic and clinical characteristics between deployers and controls using Chi-Square, Fisher Exact or t-tests. Linear regression was used to assess relationships between pulmonary function and quantitative imaging findings. RESULTS: Gender and smoking status were not statistically significantly different between groups, but deployers were significantly younger than controls (42 vs 58 years, p < 0.0001), had higher body mass index (31 vs 28 kg/m2, p = 0.01), and had fewer total smoking pack-years (8 vs. 26, p = 0.007). Spirometric measures were not statistically significantly different between groups. Pi10 and LAA%-950 were significantly elevated in deployers compared to controls in unadjusted analyses, with the emphysema measure remaining significantly higher in deployers after adjustment for age, sex, smoking, BMI, and expiratory total lung volume. Air trapping parameters were more common in control images, likely due to differences in age and smoking between groups. Among deployers, LAA%-950 and Pi10 were significantly correlated with spirometric markers of obstruction based on ratio of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) and/or percent predicted FEV1. CONCLUSIONS: Quantitative chest HRCT imaging analysis identifies emphysema in deployers with asthma and distal lung disease, and may be useful in detecting and monitoring deployment-related lung disease in a population where spirometry is typically normal.

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research.

Fleischner Society Visual Emphysema CT Patterns Help Predict Progression of Emphysema in Current and Former Smokers: Results from the COPDGene Study.

Background The correlation between visual emphysema patterns and subsequent progression of disease may provide a way to enrich a study population for treatment trials of emphysema. Purpose To evaluate the potential relationship between emphysema visual subtypes and progression of emphysema and gas trapping. Materials and Methods Current and former smokers with and without chronic obstructive pulmonary disease (COPD) enrolled in the prospective Genetic Epidemiology of COPD (COPDGene) study (ClinicalTrials.gov identifier: NCT02445183) between 2008 and 2011 had their Fleischner Society visual CT scores assessed at baseline, quantitative inspiratory, and expiratory CT and at 5 years. They also underwent pulmonary function testing at baseline CT and at 5 years. The dependent variables were inspiratory lung density at 15th percentile (adjusted for lung volume) as a measure of emphysema and percentage of lung volume with attenuation less than -856 HU at expiratory CT as a measure of air trapping. Statistical analysis used a linear mixed model, adjusted for age, height, sex, race, smoking status, and scanner make. Results A total of 4166 participants (mean age, 60 years ± 9 [standard deviation]; 2091 [50%] men) were evaluated. In participants with COPD (1655 participants, 40%), those with visual presence of mild, moderate, and confluent emphysema at baseline CT showed a mean decline in lung density of 4.6 g/L ± 1.1 (P < .001), 6.7 g/L ± 1.1 (P < .001), and 6.4 g/L ± 1.2 (P < .001), respectively, compared with 2.4 g/L ± 1.3 (P < .001) for those with trace emphysema. For participants without COPD, those with visual presence of mild and moderate emphysema at baseline CT showed a mean decline in lung density of 3.6 g/L ± 1.0 (P < .001) and 3.1 g/L ± 1.6 (P < .001), respectively, compared with 1.8 g/L ± 1.0 (P < .001) for those with trace emphysema. Conclusion The pattern of parenchymal emphysema at baseline CT was an independent predictor of subsequent progression of emphysema in participants who are current or former cigarette smokers with and without chronic obstructive pulmonary disease. © RSNA, 2020 Online supplemental material is available for this article.

Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence.

Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assistance when results from definitive viral testing are delayed. Purpose To develop and validate an artificial intelligence (AI) system to score the likelihood and extent of pulmonary COVID-19 on chest CT scans using the COVID-19 Reporting and Data System (CO-RADS) and CT severity scoring systems. Materials and Methods The CO-RADS AI system consists of three deep-learning algorithms that automatically segment the five pulmonary lobes, assign a CO-RADS score for the suspicion of COVID-19, and assign a CT severity score for the degree of parenchymal involvement per lobe. This study retrospectively included patients who underwent a nonenhanced chest CT examination because of clinical suspicion of COVID-19 at two medical centers. The system was trained, validated, and tested with data from one of the centers. Data from the second center served as an external test set. Diagnostic performance and agreement with scores assigned by eight independent observers were measured using receiver operating characteristic analysis, linearly weighted κ values, and classification accuracy. Results A total of 105 patients (mean age, 62 years ± 16 [standard deviation]; 61 men) and 262 patients (mean age, 64 years ± 16; 154 men) were evaluated in the internal and external test sets, respectively. The system discriminated between patients with COVID-19 and those without COVID-19, with areas under the receiver operating characteristic curve of 0.95 (95% CI: 0.91, 0.98) and 0.88 (95% CI: 0.84, 0.93), for the internal and external test sets, respectively. Agreement with the eight human observers was moderate to substantial, with mean linearly weighted κ values of 0.60 ± 0.01 for CO-RADS scores and 0.54 ± 0.01 for CT severity scores. Conclusion With high diagnostic performance, the CO-RADS AI system correctly identified patients with COVID-19 using chest CT scans and assigned standardized CO-RADS and CT severity scores that demonstrated good agreement with findings from eight independent observers and generalized well to external data. © RSNA, 2020 Supplemental material is available for this article.

Soluble receptor for advanced glycation end products (sRAGE) as a biomarker of COPD.

BACKGROUND: Soluble receptor for advanced glycation end products (sRAGE) is a proposed emphysema and airflow obstruction biomarker; however, previous publications have shown inconsistent associations and only one study has investigate the association between sRAGE and emphysema. No cohorts have examined the association between sRAGE and progressive decline of lung function. There have also been no evaluation of assay compatibility, receiver operating characteristics, and little examination of the effect of genetic variability in non-white population. This manuscript addresses these deficiencies and introduces novel data from Pittsburgh COPD SCCOR and as well as novel work on airflow obstruction. A meta-analysis is used to quantify sRAGE associations with clinical phenotypes. METHODS: sRAGE was measured in four independent longitudinal cohorts on different analytic assays: COPDGene (n = 1443); SPIROMICS (n = 1623); ECLIPSE (n = 2349); Pittsburgh COPD SCCOR (n = 399). We constructed adjusted linear mixed models to determine associations of sRAGE with baseline and follow up forced expiratory volume at one second (FEV1) and emphysema by quantitative high-resolution CT lung density at the 15th percentile (adjusted for total lung capacity). RESULTS: Lower plasma or serum sRAGE values were associated with a COPD diagnosis (P < 0.001), reduced FEV1 (P < 0.001), and emphysema severity (P < 0.001). In an inverse-variance weighted meta-analysis, one SD lower log10-transformed sRAGE was associated with 105 ± 22 mL lower FEV1 and 4.14 ± 0.55 g/L lower adjusted lung density. After adjusting for covariates, lower sRAGE at baseline was associated with greater FEV1 decline and emphysema progression only in the ECLIPSE cohort. Non-Hispanic white subjects carrying the rs2070600 minor allele (A) and non-Hispanic African Americans carrying the rs2071288 minor allele (A) had lower sRAGE measurements compare to those with the major allele, but their emphysema-sRAGE regression slopes were similar. CONCLUSIONS: Lower blood sRAGE is associated with more severe airflow obstruction and emphysema, but associations with progression are inconsistent in the cohorts analyzed. In these cohorts, genotype influenced sRAGE measurements and strengthened variance modelling. Thus, genotype should be included in sRAGE evaluations.

Five-year Progression of Emphysema and Air Trapping at CT in Smokers with and Those without Chronic Obstructive Pulmonary Disease: Results from the COPDGene Study.

Background CT is used to quantify abnormal changes in the lung parenchyma of smokers that might overlap chronic obstructive pulmonary disease (COPD), but studies on the progression of expiratory air trapping in smokers are scarce. Purpose To evaluate the relationship between longitudinal changes in forced expiratory volume in 1 second (FEV1) and CT-quantified emphysema and air trapping in smokers. Materials and Methods Cigarette smokers with and those without COPD participating in the multicenter observational COPDGene study were evaluated. Subjects underwent inspiratory and expiratory chest CT and spirometry at baseline and 5-year follow-up. Emphysema was quantified by using adjusted lung density (ALD). Air trapping was quantified by using mean lung density at expiratory CT and CT-measured functional residual capacity-to-total lung volume ratio. Linear models were used to regress quantitative CT measurements taken 5 years apart, and models were fit with and without adding FEV1 as a predictor. Analyses were stratified by Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage (GOLD 0, no COPD; GOLD 1, mild COPD; GOLD 2, moderate COPD; GOLD 3, severe COPD; GOLD 4, very severe COPD). Subjects with preserved FEV1-to-forced vital capacity ratio and reduced FEV1 percentage predicted were categorized as having preserved ratio impaired spirometry (PRISm). Results A total of 4211 subjects (503 with PRISm; 2034 with GOLD 0, 388 with GOLD 1, 816 with GOLD 2, 381 with GOLD 3, 89 with GOLD 4) were evaluated. ALD decreased by 1.7 g/L (95% confidence interval [CI]: -2.5, -0.9) in subjects with GOLD 0 at baseline and by 5.3 g/L (95% CI: -6.2, -4.4) in those with GOLD 1-4 (P < .001 for both). When adjusted for changes in FEV1, corresponding numbers were -2.2 (95% CI: -3.0, -1.3) and -4.6 g/L (95% CI: -5.6, -3.4) (P < .001 for both). Progression in air trapping was identified only in GOLD stage 2-4. Approximately 33%-50% of changes in air trapping in GOLD stages 2-4 were accounted for by changes in FEV1. Conclusion CT measures of emphysema and air trapping increased over 5 years in smokers. Forced expiratory volume in one second accounted for less than 10% of emphysema progression and less than 50% of air trapping progression detected at CT. © RSNA, 2020 Online supplemental material is available for this article.

A New Oxygen Uptake Measurement Supporting Target Selection for Endobronchial Valve Treatment.

BACKGROUND: Adequate target lobe selection for endobronchial valve (EBV) treatment in patients with severe emphysema is essential for treatment success and can be based on emphysema destruction, lobar perfusion, lobar volume, and collateral ventilation. As some patients have >1 target lobe for EBV treatment, we were interested whether we could identify the least functional lobe. OBJECTIVES: The objective of this study was to investigate the relationship between endoscopic lobar measurement of oxygen uptake, lobar destruction, and vascular volume, and whether this could help in identifying the least functional lobe and thus optimal target for EBV treatment. METHOD: We prospectively included patients who were scheduled for EBV treatment in our hospital. A customized gas analysis setup was used to measure lobar O2 uptake after lobar balloon occlusion. Quantitative CT analysis was performed to assess the degree of emphysematous destruction and lobar arterial and venous volumes. RESULTS: Twenty-one (5 male/16 female) patients with emphysema (median age 63 years, FEV1 25% of predicted, residual volume 234% of predicted) were included, and 49 endoscopic lobar measurements were performed. A lower O2 uptake significantly correlated with a higher degree of emphysematous lobar destruction (Spearman's ρ: 0.39, p < 0.01), and lower arterial and venous vascular volumes of the lobes (-0.46 and -0.47, respectively; both p < 0.001). CONCLUSIONS: Endoscopic measurement of lobar O2 uptake is feasible in patients with emphysema. Measurement of lobar O2 uptake helped to identify the least functional lobe and can be used as additional tool for EBV target lobe selection.

Chartis Measurement of Collateral Ventilation: Conscious Sedation versus General Anesthesia - A Retrospective Comparison.

BACKGROUND: Absence of interlobar collateral ventilation using the Chartis measurement is the key predictor for successful endobronchial valve treatment in severe emphysema. Chartis was originally validated in spontaneous breathing patients under conscious sedation (CS); however, this can be challenging due to cough, mucus secretion, mucosal swelling, and bronchoconstriction. Performing Chartis under general anesthesia (GA) avoids these problems and may result in an easier procedure with a higher success rate. However, using Chartis under GA with positive pressure ventilation has not been validated. OBJECTIVES: In this study we investigated the impact of anesthesia technique, CS versus GA, on the feasibility and outcomes of Chartis measurement. METHODS: We retrospectively analyzed all Chartis measurements performed at our hospital from October 2010 until December 2017. RESULTS: We analyzed 250 emphysema patients (median forced expiratory volume in 1 s 26%, range 12-52% predicted). In 121 patients (48%) the measurement was performed using CS, in 124 (50%) using GA, and in 5 (2%) both anesthesia techniques were used. In total, 746 Chartis readings were analyzed (432 CS, 277 GA, and 37 combination). Testing under CS took significantly longer than GA (median 19 min [range 5-65] vs. 11 min [3-35], p < 0.001) and required more measurements (3 [1-13] vs. 2 [1-6], p < 0.001). There was no significant difference in target lobe volume reduction after treatment (-1,123 mL [-3,604 to 332] in CS vs. -1,251 mL [-3,333 to -1] in GA, p = 0.35). CONCLUSIONS: In conclusion, Chartis measurement under CS took significantly longer and required more measurements than under GA, without a difference in treatment outcome. We recommend a prospective trial comparing both techniques within the same patients to validate this approach.

Predicting Lung Volume Reduction after Endobronchial Valve Therapy Is Maximized Using a Combination of Diagnostic Tools.

BACKGROUND: Bronchoscopic lung volume reduction using one-way endobronchial valves (EBVs) has been proven to be effective in patients with severe emphysema. However, the selection of patients without collateral ventilation prior to treatment is critical for procedural success. Collateral ventilation can be assessed directly with the Chartis system or indirectly using computed tomography (CT) fissure analysis. OBJECTIVES: We retrospectively evaluated the diagnostic value of a combination of the quantitative CT interlobar fissure completeness score (FCS) and Chartis in predicting responders to EBV therapy. METHODS: CT data from four prospective studies were pooled and analyzed using semiautomated software to quantify the completeness of interlobar fissures. These FCSs were compared to a reference standard of achieving ≥350 ml of target lobe volume reduction after EBV treatment. Using a receiver operating characteristic curve, optimal thresholds predictive of complete fissures (responders) and incomplete fissures (non-responders) were determined. A subgroup of patients with partially complete fissures was identified, where software had lower accuracy. The complementary value of Chartis was investigated in this group. RESULTS: A fissure was defined as complete (FCS >95%), incomplete (FCS <80%), or partially complete (80% < FCS < 95%). The positive predictive value (PPV) of complete fissures is 88.1%, and the negative predictive value (NPV) is 92.9%, with an overall accuracy of 89.2%. Chartis was utilized in patients with partially complete fissures, with a PPV of 82.3%, an NPV of 84.6%, and an accuracy of 83.3%. CONCLUSION: Combining diagnostic tools could reduce the burden on patients and the healthcare system while providing clinicians with a better means for patient selection for EBV therapy.

Azithromycin reduces bronchial wall thickening in infants with cystic fibrosis.

BACKGROUND: COMBAT-CF showed that children aged 0-3 years treated with azithromycin did clinically better than placebo but there was no effect on CT-scores. We reanalysed CTs using an automatic bronchus-artery (BA) analysis. METHOD: Inspiratory and expiratory CTs at 12 and 36 months were analysed. BA-analysis measures BA-diameters: bronchial outer wall (Bout), bronchial inner wall (Bin), artery (A), and bronchial wall thickness (Bwt) and computes BA-ratios: Bout/A and Bin/A for bronchial widening, Bwt/A and Bwa/Boa (bronchial wall area/bronchial outer area) for bronchial wall thickening. Low attenuation regions (LAR) were analysed using an automatic method. Mixed-effect model was used to compare BA-outcomes at 36 months between treatment groups. RESULTS: 228 CTs (59 placebo; 66 azithromycin) were analysed. The azithromycin group had lower Bwa/Boa (p = 0.0034) and higher Bin/A (p = 0.001) relative to placebo. Bout/A (p = 0.0088) was higher because of a reduction in artery diameters which correlated to a reduction in LAR. CONCLUSION: Azithromycin-treated infants with CF show a reduction in bronchial wall thickness and possibly a positive effect on lung perfusion.

Estimating lung function from computed tomography at the patient and lobe level using machine learning.

BACKGROUND: Automated estimation of Pulmonary function test (PFT) results from Computed Tomography (CT) could advance the use of CT in screening, diagnosis, and staging of restrictive pulmonary diseases. Estimating lung function per lobe, which cannot be done with PFTs, would be helpful for risk assessment for pulmonary resection surgery and bronchoscopic lung volume reduction. PURPOSE: To automatically estimate PFT results from CT and furthermore disentangle the individual contribution of pulmonary lobes to a patient's lung function. METHODS: We propose I3Dr, a deep learning architecture for estimating global measures from an image that can also estimate the contributions of individual parts of the image to this global measure. We apply it to estimate the separate contributions of each pulmonary lobe to a patient's total lung function from CT, while requiring only CT scans and patient level lung function measurements for training. I3Dr consists of a lobe-level and a patient-level model. The lobe-level model extracts all anatomical pulmonary lobes from a CT scan and processes them in parallel to produce lobe level lung function estimates that sum up to a patient level estimate. The patient-level model directly estimates patient level lung function from a CT scan and is used to re-scale the output of the lobe-level model to increase performance. After demonstrating the viability of the proposed approach, the I3Dr model is trained and evaluated for PFT result estimation using a large data set of 8 433 CT volumes for training, 1 775 CT volumes for validation, and 1 873 CT volumes for testing. RESULTS: First, we demonstrate the viability of our approach by showing that a model trained with a collection of digit images to estimate their sum implicitly learns to assign correct values to individual digits. Next, we show that our models can estimate lobe-level quantities, such as COVID-19 severity scores, pulmonary volume (PV), and functional pulmonary volume (FPV) from CT while only provided with patient-level quantities during training. Lastly, we train and evaluate models for producing spirometry and diffusion capacity of carbon mono-oxide (DLCO) estimates at the patient and lobe level. For producing Forced Expiratory Volume in one second (FEV1), Forced Vital Capacity (FVC), and DLCO estimates, I3Dr obtains mean absolute errors (MAE) of 0.377 L, 0.297 L, and 2.800 mL/min/mm Hg respectively. We release the resulting algorithms for lung function estimation to the research community at https://grand-challenge.org/algorithms/lobe-wise-lung-function-estimation/ CONCLUSIONS: I3Dr can estimate global measures from an image, as well as the contributions of individual parts of the image to this global measure. It offers a promising approach for estimating PFT results from CT scans and disentangling the individual contribution of pulmonary lobes to a patient's lung function. The findings presented in this work may advance the use of CT in screening, diagnosis, and staging of restrictive pulmonary diseases as well as in risk assessment for pulmonary resection surgery and bronchoscopic lung volume reduction.

The relationship of fat and muscle measurements with emphysema and bronchial wall thickening in smokers.

Introduction: Differences in body composition in patients with COPD may have important prognostic value and may provide opportunities for patient-specific management. We investigated the relation of thoracic fat and muscle with computed tomography (CT)-measured emphysema and bronchial wall thickening. Methods: Low-dose baseline chest CT scans from 1031 male lung cancer screening participants from one site were quantified for emphysema, bronchial wall thickening, subcutaneous fat, visceral fat and skeletal muscle. Body composition measurements were performed by segmenting the first slice above the aortic arch using Hounsfield unit thresholds with region growing and manual corrections. COPD presence and severity were evaluated with pre-bronchodilator spirometry testing. Results: Participants had a median age of 61.5 years (58.6-65.6, 25th-75th percentile) and median number of 38.0 pack-years (28.0-49.5); 549 (53.2%) were current smokers. Overall, 396 (38.4%) had COPD (256 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1, 140 GOLD 2-3). Participants with COPD had less subcutaneous fat, visceral fat and skeletal muscle (p<0.001 for all). With increasing GOLD stages, subcutaneous (p=0.005) and visceral fat values (p=0.004) were higher, and skeletal muscle was lower (p=0.004). With increasing severity of CT-derived emphysema, subcutaneous fat, visceral fat and skeletal muscle values were lower (p<0.001 for all). With increasing CT-derived bronchial wall thickness, subcutaneous and visceral fat values were higher (p<0.001 for both), without difference in skeletal muscle. All statistical relationships remained when adjusted for age, pack-years and smoking status. Conclusion: COPD presence and emphysema severity are associated with smaller amounts of thoracic fat and muscle, whereas bronchial wall thickening is associated with fat accumulation.