HRCT characteristics of severe emphysema patients: Interobserver variability among expert readers and comparison with quantitative software.

PURPOSE: For a successful bronchoscopic lung volume reduction coil treatment it is important to place the coils in the most emphysematous lobes. Therefore assessment of the lobe with greatest destruction is essential. Our aims were to investigate the level of agreement among expert reviewers of HRCT-scans in emphysema patients and the comparison with QCT (quantitative computed tomography) software. METHOD: Five experienced CT-assessors, conducted a visual assessment of the baseline HRCT-scans of emphysema patients who participated in the RENEW bronchoscopic lung volume reduction coil study. On the same HRCT-scans, a QCT analysis was performed. RESULTS: In total 134 HRCT-scans were rated by all 5 experts. All 5 CT-assessors agreed on which was the most destructed lobe in 61 % of the left lungs (ƙ:0.459) and 60 % of the right lungs (ƙ:0.370). The consensus of the 5 assessors matched the QCT in the left lung for 77 % of the patients (ƙ:0.425) and in the right lung for 82 % (ƙ:0.524). CONCLUSIONS: Our results show that the interobserver agreement between five expert CT-assessors was only fair to moderate when evaluating the most destructed lobe. CT-assessor consensus improved matching with QCT determination of lobar destruction compared to individual assessor determinations. Because some CT-features are associated with treatment outcomes and important for optimal patient selection of bronchoscopic lung volume reduction treatment, we recommend including more than one CT-reviewer and supported by QCT measurements.

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.

Progression of Emphysema and Small Airways Disease in Cigarette Smokers.

BACKGROUND: Little is known about factors associated with emphysema progression in cigarette smokers. We evaluated factors associated with change in emphysema and forced expiratory volume in 1 second (FEV1) in participants with and without chronic obstructive pulmonary disease (COPD). METHODS: This retrospective study included individuals participating in the COPD Genetic Epidemiology study who completed the 5-year follow-up, including inspiratory and expiratory computed tomography (CT) and spirometry. All paired CT scans were analyzed using micro-mapping, which classifies individual voxels as emphysema or functional small airway disease (fSAD). Presence and progression of emphysema and FEV1 were determined based on comparison to nonsmoker values. Logistic regression analyses were used to identify clinical parameters associated with disease progression. RESULTS: A total of 3088 participants were included with a mean ± SD age of 60.7±8.9 years, including 72 nonsmokers. In all Global initiative for chronic Obstructive Lung Disease (GOLD) stages, the presence of emphysema at baseline was associated with emphysema progression (odds ratio [OR]: GOLD 0: 4.32; preserved ratio-impaired spirometry [PRISm]; 5.73; GOLD 1: 5.16; GOLD 2: 5.69; GOLD 3/4: 5.55; all p ≤0.01). If there was no emphysema at baseline, the amount of fSAD at baseline was associated with emphysema progression (OR for 1% increase: GOLD 0: 1.06; PRISm: 1.20; GOLD 1: 1.7; GOLD 3/4: 1.08; all p ≤ 0.03).In 1735 participants without spirometric COPD, progression in emphysema occurred in 105 (6.1%) participants and only 21 (1.2%) had progression in both emphysema and FEV1. CONCLUSIONS: The presence of emphysema is an important predictor of emphysema progression. In patients without emphysema, fSAD is associated with the development of emphysema. In participants without spirometric COPD, emphysema progression occurred independently of FEV1 decline.

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.

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.

Endobronchial valves for severe emphysema.

The results of the randomised controlled trials investigating the bronchoscopic lung volume reduction treatment using endobronchial valves (EBV) are promising, and have led to their inclusion in treatment guidelines, US Food and Drug Administration approval and inclusion in routine care in an increasing number of countries. The one-way valve treatment has advanced and is now a regular treatment option. However, this new phase will lead to new challenges in terms of implementation. We believe that key issues in future research concern advanced patient selection, improved methods for target lobe selection, increased knowledge on the predictive risk of a pneumothorax, positioning of pulmonary rehabilitation in conjunction with the EBV treatment, the positioning of lung volume reduction surgery versus EBV treatment, and the long-term efficacy, adverse events, impact on exacerbations and hospitalisations, costs and survival. Hopefully, the increasing number of patients treated, the setup of (inter)national registries and future research efforts will further optimise all aspects of this treatment.

Airway wall thickening on CT: Relation to smoking status and severity of COPD.

Airway wall thickening in cigarette smokers is thought to be a result of inflammatory changes and airway remodeling. This study investigates if CT-derived airway wall thickening associates to disease severity in smokers with and without COPD and if airway wall thickening is reversible by smoking cessation. We examined 2000 smokers and 46 never-smokers who returned for a 5-year follow-up visit in the COPDGene-study. Multivariable regression analyses were performed at visit 1 to associate airway wall thickness (expressed as Pi10) with percent predicted forced expiratory volume in 1 s (FEV1%-predicted), 6-min walking distance (6MWD), and St. George Respiratory Questionnaire (SGRQ). Longitudinal analyses were performed to assess the effect of smoking cessation on Pi10 using linear mixed models. A higher Pi10 was significantly associated with worse FEV1%-predicted, 6MWD, and SGRQ in all GOLD-stages. Longitudinal analyses showed that subjects that quit smoking significantly decreased in Pi10 (ΔPi10 = -0.18 mm, p < 0.001). Subjects that started smoking had a significant increase in Pi10 (ΔPi10 = 0.14 mm, p < 0.001). Pi10 is a clinically relevant biomarker of smoking-related airway injury in smokers with and without COPD. The change in Pi10 with change in smoking status suggests that it can quantify a reversible component of smoking-related airway inflammation.

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.

Automatic segmentation of the solid core and enclosed vessels in subsolid pulmonary nodules.

Subsolid pulmonary nodules are commonly encountered in lung cancer screening and clinical routine. Compared to other nodule types, subsolid nodules are associated with a higher malignancy probability for which the size and mass of the nodule and solid core are important indicators. However, reliably measuring these characteristics on computed tomography (CT) can be hampered by the presence of vessels encompassed by the nodule, since vessels have similar CT attenuation as solid cores. This can affect treatment decisions and patient management. We present a method based on voxel classification to automatically identify vessels and solid cores in given subsolid nodules on CT. Three experts validated our method on 170 screen-detected subsolid nodules from the Multicentric Italian Lung Disease trial. The agreement between the proposed method and the observers was substantial for vessel detection and moderate for solid core detection, which was similar to the inter-observer agreement. We found a relatively high variability in the inter-observer agreement and low method-observer agreements for delineating the borders of vessels and solid cores, illustrating the difficulty of this task. However, 92.4% of the proposed vessel and 80.6% of the proposed solid core segmentations were labeled as usable in clinical practice by the majority of experts.

Minimal important difference of target lobar volume reduction after endobronchial valve treatment for emphysema.

BACKGROUND AND OBJECTIVE: Target lobar volume reduction (TLVR) is an important efficacy outcome measure for bronchoscopic lung volume reduction (BLVR) treatment using one-way endobronchial valves (EBV) in patients with severe emphysema. The commonly used cut-off value for TLVR that expresses a perceivable clinical benefit is -350 mL. However, a scientifically determined minimal important difference (MID) for TLVR never has been published. The objective of the present study was to determine the MID for TLVR on HRCT in patients who were treated with EBV. METHODS: A total of 318 patients with severe emphysema from two BLVR trials were analysed. Anchor-based methods were used to define the TLVR MID at 6 months follow-up. Forced expiratory volume in 1 s (FEV1 ), residual volume (RV) and St. George's Respiratory Questionnaire (SGRQ) were used as anchors. RESULTS: The calculated TLVR MID with each anchor was: FEV1 -587 mL, RV -534 mL and SGRQ -560 mL. The combined MID (average of the three anchor-based MIDs) was -563 mL. CONCLUSION: Using the anchor-based method, we established a TLVR MID of -563 mL in patients with severe emphysema at 6 months follow-up after EBV treatment. This value can be useful for both interpreting the results from trials and clinical practice, as well as for designing future studies on lung volume reduction.

Disease Severity Dependence of the Longitudinal Association Between CT Lung Density and Lung Function in Smokers.

BACKGROUND: In smokers, the lung parenchyma is characterized by inflammation and emphysema, processes that can result in local gain and loss of lung tissue. CT measures of lung density might reflect lung tissue changes; however, longitudinal data regarding the effects of CT lung tissue on FEV1 in smokers with and without COPD are scarce. METHODS: The 15th percentile of CT lung density was obtained from the scans of 3,390 smokers who completed baseline and 5-year follow-up of the Genetic Epidemiology of COPD (COPDGene) study visits. The longitudinal relationship between total lung capacity-adjusted lung density (TLC-PD15) and FEV1 was assessed by using multivariable mixed models. Separate models were performed in smokers at risk, smokers with preserved ratio and impaired spirometry (PRISm), and smokers with COPD according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging system. RESULTS: The direction of the relationship between lung density and lung function was GOLD stage dependent. In smokers with PRISm, a 1-g/L decrease in TLC-PD15 was associated with an increase of 2.8 mL FEV1 (P = .02). In contrast, among smokers with GOLD III to IV COPD, a 1-g/L decrease in TLC-PD15 was associated with a decrease of 4.1 mL FEV1 (P = .002). CONCLUSIONS: A decline in TLC-PD15 was associated with an increase or decrease in FEV1 depending on disease severity. The associations are GOLD stage specific, and their presence might influence the interpretation of future studies that use CT lung density as an intermediate study end point for a decline in lung function. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.

Normalized emphysema scores on low dose CT: Validation as an imaging biomarker for mortality.

The purpose of this study is to develop a computed tomography (CT) biomarker of emphysema that is robust across reconstruction settings, and evaluate its ability to predict mortality in patients at high risk for lung cancer. Data included baseline CT scans acquired between August 2002 and April 2004 from 1737 deceased subjects and 5740 surviving controls taken from the National Lung Screening Trial. Emphysema scores were computed in the original scans (origES) and after applying resampling, normalization and bullae analysis (normES). We compared the prognostic value of normES versus origES for lung cancer and all-cause mortality by computing the area under the receiver operator characteristic curve (AUC) and the net reclassification improvement (NRI) for follow-up times of 1-7 years. normES was a better predictor of mortality than origES. The 95% confidence intervals for the differences in AUC values indicated a significant difference for all-cause mortality for 2 through 6 years of follow-up, and for lung cancer mortality for 1 through 7 years of follow-up. 95% confidence intervals in NRI values showed a statistically significant improvement in classification for all-cause mortality for 2 through 7 years of follow-up, and for lung cancer mortality for 3 through 7 years of follow-up. Contrary to conventional emphysema score, our normalized emphysema score is a good predictor of all-cause and lung cancer mortality in settings where multiple CT scanners and protocols are used.

Follow-up of CT-derived airway wall thickness: Correcting for changes in inspiration level improves reliability.

OBJECTIVES: Airway wall thickness (AWT) is affected by changes in lung volume. This study evaluated whether correcting AWT on computed tomography (CT) for differences in inspiration level improves measurement agreement, reliability, and power to detect changes over time. METHODS: Participants of the Dutch-Belgian lung cancer screening trial who underwent 3-month repeat CT for an indeterminate pulmonary nodule were included. AWT on CT was calculated by the square root of the wall area at a theoretical airway with an internal perimeter of 10mm (Pi10). The scan with the highest lung volume was labelled as the reference scan and the scan with the lowest lung volume was labelled as the comparison scan. Pi10 derived from the comparison scan was corrected by multiplying it with the ratio of CT lung volume of the comparison scan to CT lung volume on the reference scan. Agreement of uncorrected and corrected Pi10 was studied with the Bland-Altman method, reliability with intra-class correlation coefficients (ICC), and power to detect changes over time was calculated. RESULTS: 315 male participants were included. Limit of agreement and reliability for Pi10 was -0.61 to 0.57mm (ICC=0.87), which improved to -0.38 to 0.37mm (ICC=0.94) after correction for inspiration level. To detect a 15% change over 3 months, 71 subjects are needed for Pi10 and 26 subjects for Pi10 adjusted for inspiration level. CONCLUSIONS: Correcting Pi10 for differences in inspiration level improves reliability, agreement, and power to detect changes over time.

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.

Smokers with emphysema and small airway disease on computed tomography have lower bone density.

Osteoporosis is more common in patients with COPD and in smokers. The aim of this study was to assess whether measures of emphysema and airway disease on computed tomography (CT) were associated with lower bone density or vertebral fractures in smokers with and without COPD. For this purpose, we included participants from the NELSON lung cancer screening trial. Bone density was measured as Hounsfield Units in the first lumbar vertebra, and vertebral fractures were assessed semiquantitatively. The 15th percentile method (Perc15) was used to assess emphysema, and the airway lumen perimeter (Pi10) was used for airway wall thickness. Expiratory/inspiratory-ratiomean lung density (E/I-ratioMLD) was used as a measure for air trapping and tracheal index to assess tracheal deformity. Linear regression models and logistic regression models were used to assess associations between CT biomarkers, bone density, and presence of fractures. Exactly 1,093 male participants were eligible for analysis. Lower Perc15 and higher E/I-ratioMLD were significantly associated with lower bone density (b=-1.27, P=0.02 and b=-0.37, P=0.02, respectively). Pi10 and tracheal index were not associated with bone density changes. CT-derived biomarkers were not associated with fracture prevalence. Bone density is lower with increasing extent of emphysema and small airway disease but is not associated with large airway disease and tracheal deformity. This may indicate the necessity to measure bone density early in smokers with emphysema and air trapping to prevent vertebral fractures.

Automatic Pulmonary Artery-Vein Separation and Classification in Computed Tomography Using Tree Partitioning and Peripheral Vessel Matching.

We present a method for automatic separation and classification of pulmonary arteries and veins in computed tomography. Our method takes advantage of local information to separate segmented vessels, and global information to perform the artery-vein classification. Given a vessel segmentation, a geometric graph is constructed that represents both the topology and the spatial distribution of the vessels. All nodes in the geometric graph where arteries and veins are potentially merged are identified based on graph pruning and individual branching patterns. At the identified nodes, the graph is split into subgraphs that each contain only arteries or veins. Based on the anatomical information that arteries and veins approach a common alveolar sag, an arterial subgraph is expected to be intertwined with a venous subgraph in the periphery of the lung. This relationship is quantified using periphery matching and is used to group subgraphs of the same artery-vein class. Artery-vein classification is performed on these grouped subgraphs based on the volumetric difference between arteries and veins. A quantitative evaluation was performed on 55 publicly available non-contrast CT scans. In all scans, two observers manually annotated randomly selected vessels as artery or vein. Our method was able to separate and classify arteries and veins with a median accuracy of 89%, closely approximating the inter-observer agreement. All CT scans used in this study, including all results of our system and all manual annotations, are publicly available at "http://www.w3.org/1999/xlink">http://arteryvein.grand-challenge.org".

Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database.

OBJECTIVES: To benchmark the performance of state-of-the-art computer-aided detection (CAD) of pulmonary nodules using the largest publicly available annotated CT database (LIDC/IDRI), and to show that CAD finds lesions not identified by the LIDC's four-fold double reading process. METHODS: The LIDC/IDRI database contains 888 thoracic CT scans with a section thickness of 2.5 mm or lower. We report performance of two commercial and one academic CAD system. The influence of presence of contrast, section thickness, and reconstruction kernel on CAD performance was assessed. Four radiologists independently analyzed the false positive CAD marks of the best CAD system. RESULTS: The updated commercial CAD system showed the best performance with a sensitivity of 82 % at an average of 3.1 false positive detections per scan. Forty-five false positive CAD marks were scored as nodules by all four radiologists in our study. CONCLUSIONS: On the largest publicly available reference database for lung nodule detection in chest CT, the updated commercial CAD system locates the vast majority of pulmonary nodules at a low false positive rate. Potential for CAD is substantiated by the fact that it identifies pulmonary nodules that were not marked during the extensive four-fold LIDC annotation process. KEY POINTS: • CAD systems should be validated on public, heterogeneous databases. • The LIDC/IDRI database is an excellent database for benchmarking nodule CAD. • CAD can identify the majority of pulmonary nodules at a low false positive rate. • CAD can identify nodules missed by an extensive two-stage annotation process.

Normalizing computed tomography data reconstructed with different filter kernels: effect on emphysema quantification.

OBJECTIVES: To propose and evaluate a method to reduce variability in emphysema quantification among different computed tomography (CT) reconstructions by normalizing CT data reconstructed with varying kernels. METHODS: We included 369 subjects from the COPDGene study. For each subject, spirometry and a chest CT reconstructed with two kernels were obtained using two different scanners. Normalization was performed by frequency band decomposition with hierarchical unsharp masking to standardize the energy in each band to a reference value. Emphysema scores (ES), the percentage of lung voxels below -950 HU, were computed before and after normalization. Bland-Altman analysis and correlation between ES and spirometry before and after normalization were compared. Two mixed cohorts, containing data from all scanners and kernels, were created to simulate heterogeneous acquisition parameters. RESULTS: The average difference in ES between kernels decreased for the scans obtained with both scanners after normalization (7.7 ± 2.7 to 0.3 ± 0.7; 7.2 ± 3.8 to -0.1 ± 0.5). Correlation coefficients between ES and FEV1, and FEV1/FVC increased significantly for the mixed cohorts. CONCLUSIONS: Normalization of chest CT data reduces variation in emphysema quantification due to reconstruction filters and improves correlation between ES and spirometry. KEY POINTS: • Emphysema quantification is sensitive to the reconstruction kernel used. • Normalization allows comparison of emphysema quantification from images reconstructed with varying kernels. • Normalization allows comparison of emphysema quantification obtained with scanners from different manufacturers. • Normalization improves correlation of emphysema quantification with spirometry. • Normalization can be used to compare data from different studies and centers.