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Association of coronary artery calcification with clinical and physiological characteristics in patients with COPD: Results from COSYCONET

  • Kathrin Kahnert
    Correspondence
    Corresponding author. Department of Medicine V, University Hospital (LMU Munich), Ziemssenstr. 1, 80336, Munich, Germany.
    Affiliations
    Department of Medicine V, University Hospital, LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
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  • Rudolf A. Jörres
    Affiliations
    Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), University Hospital of Munich (LMU), Munich, Germany
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  • Bertram Jobst
    Affiliations
    Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany

    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany

    Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Germany
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  • Mark O. Wielpütz
    Affiliations
    Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany

    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany

    Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Germany
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  • Axinja Seefelder
    Affiliations
    Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany

    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany

    Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Germany
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  • Caroline M. Hackl
    Affiliations
    Department of Medicine V, University Hospital, LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
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  • Franziska C. Trudzinski
    Affiliations
    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany

    Department of Pneumology and Critical Care Medicine, Thoraxklinik Heidelberg, Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
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  • Henrik Watz
    Affiliations
    Pulmonary Research Institute at LungenClinic Grosshansdorf, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Grosshansdorf, Germany
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  • Robert Bals
    Affiliations
    Department of Internal Medicine V - Pulmonology, Allergology, Respiratory Intensive Care Medicine, Saarland University Hospital, Homburg, Germany
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  • Jürgen Behr
    Affiliations
    Department of Medicine V, University Hospital, LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
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  • Klaus F. Rabe
    Affiliations
    Lung Clinic Grosshansdorf, Airway Research Center (ARCN), Grosshansdorf, Germany
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  • Claus F. Vogelmeier
    Affiliations
    Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL), University Medical Center Giessen and Marburg, Philipps-University Marburg (UMR), Marburg, Germany
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  • Peter Alter
    Affiliations
    Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL), University Medical Center Giessen and Marburg, Philipps-University Marburg (UMR), Marburg, Germany
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  • Tobias Welte
    Affiliations
    Department of Pneumology, Hannover Medical School, Hannover, Germany
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  • FelixJ.F. Herth
    Affiliations
    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany

    Department of Pneumology and Critical Care Medicine, Thoraxklinik Heidelberg, Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
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  • H.U. Kauczor
    Affiliations
    Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany

    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany
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  • Jürgen Biederer
    Affiliations
    Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Germany

    Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), Im Neuenheimer Feld 156, 69120, Heidelberg, Germany

    Germany University of Latvia, Faculty of Medicine, Raina bulvaris 19, Riga, 1586 Latvia

    Christian-Albrechts-Universität zu Kiel, Faculty of Medicine, 24098, Kiel, Germany
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Open AccessPublished:October 18, 2022DOI:https://doi.org/10.1016/j.rmed.2022.107014

      Highlights

      • CT thorax examinations are frequently used for phenotyping of COPD.
      • Coronary vessel wall calcification can be quantified from non-ECG gated CT scans.
      • The Agatston score can automatically be derived from non-ECG gated CT scans.
      • A higher Agatston-score cut-off value of 1500 AU should be used in this setting.

      Abstract

      Chronic obstructive pulmonary disease (COPD) is frequently associated with coronary artery disease (CAD). When considering computed tomography (CT) for COPD phenotyping, coronary vessel wall calcification would be a potential marker of cardiac disease. However, non-ECG gated scans as used in COPD monitoring do not comply with established quantitative approaches using ECG-triggered CT and the Agatston score. We studied the diagnostic potential of Agatston scores from non-triggered scans for cardiac disease.
      The study population was a sub-group of the COPD cohort COSYCONET that underwent CT scanning in addition to comprehensive clinical assessments, echocardiographic data and physician-based diagnoses of comorbidities. Agatston scores from non-contrast enhanced, non-triggered CT were used to identify a cut-off value for CAD via ROC analysis.
      399 patients were included (152 female, mean age 66.0 ± 8.2 y). In terms of CAD, an Agatston score ≥1500 AU performed best (AUC 0.765; 95% CI: 0.700, 0.831) and was superior to the conventional cut-off value (400 AU). Using this value for defining groups, there were differences (p < 0.05) in lung function, left atrial diameter and left ventricular end-systolic diameter as well as CT-determined central airway wall thickness pointing towards a bronchitis phenotype. In multivariate analysis, BMI, hyperlipidemia, arterial hypertension, GOLD D (p < 0.05) but particularly Agatston score ≥1500 AU (Odds ratio 10.5; 95% CI: 4.8; 22.6)) were predictors of CAD.
      We conclude that in COPD patients, Agatston scores derived from non-ECG gated CT showed a much higher cut-off value (1500 AU) for actionable coronary artery disease than the score derived from ECG-triggered CT in cardiology patients.

      Abbreviations:

      COPD (chronic obstruktive pulmonary disease), CAD (Coronary artery disease), CT (computed tomography), ECG (electrocardiogramm), FEV1 (Forced expiratory volume in 1 second), FVC (Forced vital capacity), RV (Residual volume), FRC (Functional residual capacity), TLC (total lung capacity), TLCO (transfer factor for carbon monoxide), KCO (transfer coefficient for carbon monoxide), GLI (Global Lung Initiative), CAT (COPD assessment test), SGRQ (St. Georges Respiratory Questionnaire), AU (Agatston score Units), ROC (Receiver operating statistics), CI (Confidence Interval)

      1. Background

      Chronic obstructive pulmonary disease (COPD), in particular when related to tobacco smoke exposure, is frequently associated with cardiovascular comorbidities, among which coronary artery disease (CAD) is most prevalent [
      • Waschki B.
      • Alter P.
      • Zeller T.
      • Magnussen C.
      • Neumann J.T.
      • Twerenbold R.
      • et al.
      High-sensitivity troponin I and all-cause mortality in patients with stable COPD: an analysis of the COSYCONET study.
      ]. Since computed tomography (CT) is increasingly used to assess and monitor COPD and its complications, coronary vessel wall calcifications as a marker of coronary artery disease are frequently detected. Under the assumption that such coronary vessel wall calcifications are an independent risk factor for mortality in patients with and without COPD [
      • Raggi P.
      • Gongora M.C.
      • Gopal A.
      • Callister T.Q.
      • Budoff M.
      • Shaw L.J.
      Coronary artery calcium to predict all-cause mortality in elderly men and women.
      ,
      • Williams M.C.
      • Murchison J.T.
      • Edwards L.D.
      • Agustí A.
      • Bakke P.
      • Calverley P.M.
      • et al.
      Coronary artery calcification is increased in patients with COPD and associated with increased morbidity and mortality.
      ], it is considered to be clinically valuable to quantify this finding and to estimate the individual risk for cardiac ischemia in COPD patients presenting with calcification on CT [
      • Agatston A.S.
      • Janowitz W.R.
      • Hildner F.J.
      • Zusmer N.R.
      • Viamonte Jr., M.
      • Detrano R.
      Quantification of coronary artery calcium using ultrafast computed tomography.
      ].
      The established measurement of coronary artery calcification uses thin slice non-contrast enhanced CT to quantify the volume affected by increased density due to calcium-deposition measured by the Agatston score. Clinically predictive ranges of this score have been described for patients without COPD [
      • Agarwal S.
      • Cox A.J.
      • Herrington D.M.
      • Jorgensen N.W.
      • Xu J.
      • Freedman B.I.
      • et al.
      Coronary calcium score predicts cardiovascular mortality in diabetes: diabetes heart study.
      ,
      • Dzaye O.
      • Berning P.
      • Dardari Z.A.
      • Berman D.S.
      • Budoff M.J.
      • Miedema M.D.
      • et al.
      Coronary artery calcium is associated with long-term mortality from lung cancer: results from the Coronary Artery Calcium Consortium.
      ] well as for patients with COPD [
      • Williams M.C.
      • Murchison J.T.
      • Edwards L.D.
      • Agustí A.
      • Bakke P.
      • Calverley P.M.A.
      • et al.
      Coronary artery calcification is increased in patients with COPD and associated with increased morbidity and mortality.
      ]. The Agatston score is determined from CT with electrocardiogram (ECG) triggering [
      • Agatston A.S.
      • Janowitz W.R.
      • Hildner F.J.
      • Zusmer N.R.
      • Viamonte Jr., M.
      • Detrano R.
      Quantification of coronary artery calcium using ultrafast computed tomography.
      ]. This is considered necessary to reduce false positive increases of calcifications due to motion artifacts.
      However, modern, fast CT scanning reduces motion artifacts even without ECG triggering, therefore it has been attempted to use the same scoring method in routine CT scans obtained without specific ECG-triggering [
      • Xia C.
      • Rook M.
      • Pelgrim G.J.
      • Sidorenkov G.
      • Wisselink H.J.
      • van Bolhuis J.N.
      • et al.
      Early imaging biomarkers of lung cancer, COPD and coronary artery disease in the general population: rationale and design of the ImaLife (Imaging in Lifelines) Study.
      ]. This is considered useful, as non-triggered, non-contrast enhanced CT scans of the chest are a standard procedure used in COPD patients, mostly for phenotyping and lung cancer screening, and may also be useful for the determination of the Agatston scores. In fact, calcium scoring from non-triggered CT scans has already been shown to correlate with the presence of cardiac disease [
      • Xie X.
      • Zhao Y.
      • de Bock G.H.
      • de Jong P.A.
      • Mali W.P.
      • Oudkerk M.
      • et al.
      Validation and prognosis of coronary artery calcium scoring in nontriggered thoracic computed tomography: systematic review and meta-analysis.
      ,
      • Bhatt S.P.
      • Kazerooni E.A.
      • Newell Jr., J.D.
      • Hokanson J.E.
      • Budoff M.J.
      • Dass C.A.
      • et al.
      Visual estimate of coronary artery calcium predicts cardiovascular disease in COPD.
      ]. There are also studies in which the score has been compared with COPD phenotypes, but this was restricted to lung function, without a comprehensive analysis of COPD characteristics [
      • Williams M.C.
      • Murchison J.T.
      • Edwards L.D.
      • Agustí A.
      • Bakke P.
      • Calverley P.M.
      • et al.
      Coronary artery calcification is increased in patients with COPD and associated with increased morbidity and mortality.
      ]. These characteristics comprise the pattern of comorbidities, symptoms and functional alteration. This raises two questions. First, regarding the heterogeneity of COPD patients, which characteristics and phenotypes are linked to the Agatston score, second, whether the conventional cut-off value used for the Agatston score (400 AU) is still appropriate in non-triggered CT scans in non-cardiology patients. Using data from a large COPD cohort, we addressed these questions. The COPD characteristics comprised anthropometric data, symptoms, exacerbations, COPD categories, comorbidities, lung function, echocardiographic assessments, as well as parenchymal and airway parameters from CT scans. If the Agatston score from routine CT scans in COPD patients should turn out as a useful biomarker for coronary artery disease, its computation would be an easy way to obtain additional diagnostic information from these scans.

      2. Methods

      2.1 Study population

      The German COPD cohort study COSYCONET (“COPD and SYstemic consequences-COmor bidities NETwork”) investigates the interaction of lung disease, comorbidities and systemic inflammation. The recruitment started in 2010 in 31 German study centers. After the baseline visit, follow-up visits were scheduled at 6, 18, 36, 54, 72 and 90 months after baseline. Broad inclusion criteria were applied i.e. patients were enrolled, if the following inclusion criteria were fulfilled aged 40 years and older, diagnosis of COPD (according to GOLD criteria) or chronic bronchitis, availability for repeated study visits over at least 18 months; and if none of the following exclusion criteria were fulfilled having undergone major lung surgery, moderate or severe exacerbation within the last 4 weeks, having a lung tumor, physical or cognitive impairment resulting in an inability to walk or to understand the intention of the project [
      • Karch A.
      • Vogelmeier C.
      • Welte T.
      • Bals R.
      • Kauczor H.U.
      • Biederer J.
      • et al.
      The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline.
      ]. Data obtained in the third follow-up visit of the COSYCONET cohort (visit 4) was used, corresponding to n = 1427 patients [
      • Karch A.
      • Vogelmeier C.
      • Welte T.
      • Bals R.
      • Kauczor H.U.
      • Biederer J.
      • et al.
      The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline.
      ]. Of these, 1176 patients were of GOLD grades 1–4 [
      • Vogelmeier C.F.
      • Criner G.J.
      • Martinez F.J.
      • Anzueto A.
      • Barnes P.J.
      • Bourbeau J.
      • et al.
      Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary.
      ]. Low-dose CT scans of the thorax in inspiration and expiration were performed in 602 patients and 16 study centers, of whom 547 patients had assessments of the Agatston score in non-ECG gated CT scans, among them 399 patients of GOLD grades 1–4 (see Figure S1) [
      • Vogelmeier C.F.
      • Criner G.J.
      • Martinez F.J.
      • Anzueto A.
      • Barnes P.J.
      • Bourbeau J.
      • et al.
      Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary.
      ]. These patients were included into the analysis. The COSYCONET study was conducted in accordance with the amended Declaration of Helsinki. All participants had given their written informed consent, and the study was approved by the Ethics Committee of the University of Marburg as coordinating study center and the ethics committees of all participating study centers; it is registered on ClinicalTrials.gov (NCT01245933) [
      • Karch A.
      • Vogelmeier C.
      • Welte T.
      • Bals R.
      • Kauczor H.U.
      • Biederer J.
      • et al.
      The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline.
      ]. CT scans were obtained according to the approval of the Ethics committee of the University of Heidelberg as the coordinating ethics committee for the radiologic examinations obtained throughout the study.

      3. Assessments

      3.1 Symptomology and lung function testing

      Detailed information on the recruitment process, inclusion and exclusion criteria, as well as assessments has been published previously [
      • Karch A.
      • Vogelmeier C.
      • Welte T.
      • Bals R.
      • Kauczor H.U.
      • Biederer J.
      • et al.
      The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline.
      ]. The presence of comorbidities was recorded on the basis of patients’ reports of a physician-based diagnosis. Spirometric and body plethysmographic lung function data included forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), residual volume (RV), functional residual capacity (FRC), total lung capacity (TLC), all in percent predicted, and the ratios FEV1/FVC as well as RV/TLC. The data given are post-bronchodilator values. Moreover, values of single-breath transfer factor for carbon monoxide (TLCO) and transfer coefficient of carbon monoxide (KCO) were analyzed. Predicted values of spirometric measures and of KCO and TLCO were taken from the Global Lung Initiative (GLI) [
      • Stanojevic S.
      • Graham B.L.
      • Cooper B.G.
      • Thompson B.R.
      • Carter K.W.
      • Francis R.W.
      • et al.
      Official ERS technical standards: global Lung Function Initiative reference values for the carbon monoxide transfer factor for Caucasians.
      ,
      • Quanjer P.H.
      • Stanojevic S.
      • Cole T.J.
      • Baur X.
      • Hall G.L.
      • Culver B.H.
      • et al.
      Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations.
      ,
      • Hall G.L.
      • Filipow N.
      • Ruppel G.
      • Okitika T.
      • Thompson B.
      • Kirkby J.
      • et al.
      Official ERS technical standard: global Lung Function Initiative reference values for static lung volumes in individuals of European ancestry.
      ].
      GOLD grades 1–4 were defined as follows post-bronchodilator FEV1/FVC< 0.7 and GOLD grade 1(mild) FEV1 ≥80% predicted, GOLD grade 2 (moderate) 50% ≤ FEV1 <80% predicted, GOLD grade 3 (severe) 30% ≤ FEV1 <50% predicted and GOLD grade 4 (very severe) FEV1 <30% predicted [
      • Vogelmeier C.F.
      • Criner G.J.
      • Martinez F.J.
      • Anzueto A.
      • Barnes P.J.
      • Bourbeau J.
      • et al.
      Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary.
      ]. GOLD groups A-D were based on the modified Medical Research Council dypnea scale (mMRC) [
      Global Initiative for Chronic Obstructive Lung Disease
      Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease.
      ], in combination with the exacerbation risk based on the 12-month history of exacerbations of all severities as well as hospitalization [
      Global Initiative for Chronic Obstructive Lung Disease
      Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease.
      ]. Therefore, the groups were defined as follows: GOLD group A (mMRC score ≤1 and exacerbation history <1), GOLD group B (mMRC score ≥2 and exacerbation history <1), GOLD group C (mMRC score ≤1 and exacerbation history >1 or 1 exacerbation leading to hospital admission) and GOLD group D (mMRC score ≥2 and exacerbation history >1 or 1 exacerbation leading to hospital admission) [
      • Vogelmeier C.F.
      • Criner G.J.
      • Martinez F.J.
      • Anzueto A.
      • Barnes P.J.
      • Bourbeau J.
      • et al.
      Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary.
      ].The COPD specific symptom burden as well as disease-specific quality of life were assessed on the basis of the COPD assessment test (CAT) and the St. George's Respiratory Questionnaire (SGRQ). Smoking status describes active smokers compared to non-smokers or ex-smokers.

      3.2 Computed tomography

      Clinical CT scanners with at least 40-row detector arrays were standardized to a non-enhanced low-dose chest CT protocol incl. End-inspiratory and end-expiratory acquisitions of the entire lung. A thin slice collimation of 0.6 mm, a pitch of 0.6–1.0, a tube potential of 120 kVp and a tube current of 35 effective mAs for most scanner types were used as previously described [
      • Biederer JWJ B.H.F.C.
      • Tuengerthal S.
      • Rehbock B.
      Protocol recommendations for computed tomography of the lung: consensus of the chest imaging workshop of the German radiologic society.
      ]. The protocol was adjusted to the respective scanner specifications if necessary (supplemental table 1). The total maximum effective dose of both inspiratory and expiratory CT scans was kept below 3.5 mSv. Apart from daily calibration for air and every three months for water during routine maintenance), repeat phantom scans were performed only by investigators from the coordinating study center (Catphan®, The Phantom Laboratory, Salem, NY, USA). CT image reconstructions comprised three-dimensional datasets with thin slice thickness and smooth as well as edge-enhancing algorithms (supplemental Table 1). The COSYCONET image repository was coordinated by the study center in Heidelberg, where the examinations were reviewed using a multimodal, OsiriX-based viewer (OsiriX 64-bit, Pixmeo SARL, Geneva, Switzerland). CT images were evaluated separately and blinded to clinical data by two experienced thoracic radiologists. The semi-quantitative, visual analysis of CT data was performed on the basis of modified guidelines of the COPD Gene CT Workshop Group [
      • Barr R.G.
      • Berkowitz E.A.
      • Bigazzi F.
      • Bode F.
      • Bon J.
      • Bowler R.P.
      • et al.
      A combined pulmonary-radiology workshop for visual evaluation of COPD: study design, chest CT findings and concordance with quantitative evaluation.
      ].
      Automated coronary artery calcification (CAC) was determined via the Agatston score, which in brief quantifies calcification based on its extent and density [
      • Agatston A.S.
      • Janowitz W.R.
      • Hildner F.J.
      • Zusmer N.R.
      • Viamonte Jr., M.
      • Detrano R.
      Quantification of coronary artery calcium using ultrafast computed tomography.
      ]. For this purpose, the standard images obtained for analysis of the lungs were used (see above) and no additional reconstructions were performed. Agatston et al. proposed the following interpretation of the Agatston score for coronary artery calcification: low risk (<100 Agatston score units (AU)), intermediate risk (101–400 AU) and high risk (≥401AU) [
      • Williams M.C.
      • Murchison J.T.
      • Edwards L.D.
      • Agustí A.
      • Bakke P.
      • Calverley P.M.A.
      • et al.
      Coronary artery calcification is increased in patients with COPD and associated with increased morbidity and mortality.
      ]. As a reference, we used the cut-off value of 400 AU established for ECG-triggered CT scans as a marker for the presence of coronary artery disease. With the use of Youden index and ROC curves we then determined optimal alternative cut-off values for the prediction of coronary heart disease based on the data comprising non-ECG gated CT scans. The Youden index is the sum of sensitivity and specificity (minus 1) and commonly used to identify an optimal cut-off value.

      3.3 Quantitative CT post-processing

      CT data were analyzed following an established in-house scientific software (YACTA, programmer O. W.) for densitometry and airway analysis in a fully automatic mode [
      • Jobst B.J.
      • Weinheimer O.
      • Buschulte T.
      • Trauth M.
      • Tremper J.
      • Delorme S.
      • et al.
      Longitudinal airway remodeling in active and past smokers in a lung cancer screening population.
      ,
      • Konietzke P.
      • Wielpütz M.O.
      • Wagner W.L.
      • Wuennemann F.
      • Kauczor H.U.
      • Heussel C.P.
      • et al.
      Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval.
      ,
      • Jobst B.J.
      • Weinheimer O.
      • Trauth M.
      • Becker N.
      • Motsch E.
      • Groß M.L.
      • et al.
      Effect of smoking cessation on quantitative computed tomography in smokers at risk in a lung cancer screening population.
      ,
      • Konietzke P.
      • Weinheimer O.
      • Wielpütz M.O.
      • Wagner W.L.
      • Kaukel P.
      • Eberhardt R.
      • et al.
      Quantitative CT detects changes in airway dimensions and air-trapping after bronchial thermoplasty for severe asthma.
      ,
      • Leutz-Schmidt P.
      • Weinheimer O.
      • Jobst B.J.
      • Dinkel J.
      • Biederer J.
      • Kauczor H.U.
      • et al.
      Influence of exposure parameters and iterative reconstruction on automatic airway segmentation and analysis on MDCT-An ex vivo phantom study.
      ,
      • Lim H.J.
      • Weinheimer O.
      • Wielpütz M.O.
      • Dinkel J.
      • Hielscher T.
      • Gompelmann D.
      • et al.
      Fully automated pulmonary lobar segmentation: influence of different prototype software programs onto quantitative evaluation of chronic obstructive lung disease.
      ,
      • Wielpütz M.O.
      • Eichinger M.
      • Weinheimer O.
      • Ley S.
      • Mall M.A.
      • Wiebel M.
      • et al.
      Automatic airway analysis on multidetector computed tomography in cystic fibrosis: correlation with pulmonary function testing.
      ]. Densitometry comprised the following variables: total lung volume in inspiration (LV), total volume of lung areas with a density below −950 HU (emphysema volume, EV), the fraction of emphysema volume in relation to the total lung volume in inspiration in percent (emphysema index, EI). Furthermore, mean lung density (MLD) in Hounsfield Units averaging CT-based density values from all voxels of the entire lung was assessed. In addition, the respective percentiles of lung density were determined. For quantification of airway dimensions, the tracheobronchial tree was segmented down to the 8th airway generation. Using the parameter-free integral-based method, the following metrics of airway geometry were computed for each generation: total diameter (TD), luminal area (LA), wall area (WA), as well as the ratio of wall area to the sum of wall and lumen area (wall percentage, WP) [
      • Jobst B.J.
      • Weinheimer O.
      • Buschulte T.
      • Trauth M.
      • Tremper J.
      • Delorme S.
      • et al.
      Longitudinal airway remodeling in active and past smokers in a lung cancer screening population.
      ,
      • Konietzke P.
      • Wielpütz M.O.
      • Wagner W.L.
      • Wuennemann F.
      • Kauczor H.U.
      • Heussel C.P.
      • et al.
      Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval.
      ,
      • Jobst B.J.
      • Weinheimer O.
      • Trauth M.
      • Becker N.
      • Motsch E.
      • Groß M.L.
      • et al.
      Effect of smoking cessation on quantitative computed tomography in smokers at risk in a lung cancer screening population.
      ,
      • Konietzke P.
      • Weinheimer O.
      • Wielpütz M.O.
      • Wagner W.L.
      • Kaukel P.
      • Eberhardt R.
      • et al.
      Quantitative CT detects changes in airway dimensions and air-trapping after bronchial thermoplasty for severe asthma.
      ,
      • Leutz-Schmidt P.
      • Weinheimer O.
      • Jobst B.J.
      • Dinkel J.
      • Biederer J.
      • Kauczor H.U.
      • et al.
      Influence of exposure parameters and iterative reconstruction on automatic airway segmentation and analysis on MDCT-An ex vivo phantom study.
      ,
      • Lim H.J.
      • Weinheimer O.
      • Wielpütz M.O.
      • Dinkel J.
      • Hielscher T.
      • Gompelmann D.
      • et al.
      Fully automated pulmonary lobar segmentation: influence of different prototype software programs onto quantitative evaluation of chronic obstructive lung disease.
      ,
      • Wielpütz M.O.
      • Eichinger M.
      • Weinheimer O.
      • Ley S.
      • Mall M.A.
      • Wiebel M.
      • et al.
      Automatic airway analysis on multidetector computed tomography in cystic fibrosis: correlation with pulmonary function testing.
      ].

      3.4 Statistical analyses

      Data are given as numbers and percentages, or mean values and standard deviations (SD). To define optimal cut-off values for the Agatston score, ROC (receiver operating characteristic) analyses with the Youden criterion were used. Comparisons between groups (patients with vs. without Agatston score values ≥ 1500 AU) were performed by the Mann-Whitney-U test, or by chi-square-tests in case of categorical variables. The associations between variables were assessed by linear and logistic regression analyses including one dependent and multiple independent variables. In these analyses, age, gender and BMI were always included as predictors. Other predictors were included according to the specific study question (see results). P values < 0.05 were considered significant. All analyses were performed with the software SPSS Version 26 (IBM Corp., Armonk, NY, USA).

      4. Results

      4.1 Study population

      The study population comprised 247 male and 152 female patients of GOLD grades 1–4. Baseline characteristics are given in Table 1, while Table 2 shows the pattern of comorbidities. The distribution of the Agatston score, mean lung density, the 15th percentile of lung density, emphysema index and airway wall thickness from generations 1–6 is shown in Table S1. Please note that the distribution of the Agatston score was very broad and exceeded the conventional scores obtained with ECG-gated scans. Regarding the excluded patients (n = 777), there was a significant (p < 0.001) difference in age (66.0 y study population vs 68.0 y excluded patients) and no difference in pack-years (47.4 vs 46.4). There were no significant differences in sex, coronary artery disease and cardiac disease but a small difference in heart failure (6.8% vs 10.4%, p = 0.043).
      Table 1Patient characteristics.
      VariablesMean ± SD
      Sex (m/f) (numbers)247/152
      Age (years)66.0 ± 8.2
      BMI (kg/m2)26.6 ± 4.8
      Pack-years47.4 ± 35.3
      FEV1 (%predicted)55.5 ± 18.9
      FEV1/FVC (Z-Score)−2.97 ± 1.08
      RV (%predicted)166.5 ± 47.2
      TLC (%predicted)116.5 ± 16.4
      RV/TLC (%predicted)153.7 ± 33.3
      FRC (%predicted)143.4 ± 34.0
      FRC/TLC (%predicted)122.1 ± 18.3
      KCO (%predicted)64.5 ± 21.5
      TLCO (%predicted)58.8 ± 21.5
      GOLD grades 1/2/3/4 (numbers)47/189/129/34
      GOLD groups A/B/C/D (numbers)154/82/72/90
      Active smoking (number/percent)80/20%
      Characteristics of the total study population (n = 399). Numbers are given for categorical variables, and mean values and standard deviations for continuous variables. FEV1 = forced expiratory volume in 1 s, FVC = forced vital capacity, RV = residual volume, FRC = functional residual capacity, TLC = total lung capacity, ITGV = intrathoracic gas volume and the ratios FEV1/FVC, RV/TLC as well as FRC/TLC. TLCO = transfer factor for carbon monoxide, KCO = transfer coefficient of carbon monoxide.
      Table 2Distribution of comorbidities.
      ComorbiditiesNumbers (%)
      Bronchiectasis12 (3%)
      Sleep apnea53 (13.3%)
      Arterial hypertension215 (53.9%)
      Coronary artery disease68 (17.0%)
      Myocardial infarction37 (9.3%)
      Heart failure27 (6.8%)
      Cardiac disease*88 (22.1%)
      Chronic bronchitis264 (66.2%)
      Gastrointestinal disorder102 (25.6%)
      Gastroesophageal reflux disease133 (33.3%)
      Diabetes50 (12.5%)
      Osteoporosis71 (17.8%)
      Mental disorder104 (26.1%)
      Hyperlipidemia190 (47.6%)
      Hyperuricemia84 (21.1%)
      Asthma92 (23.1%)
      Pattern of comorbidities across the study population (n = 399). Absolute numbers and percentages are given. * Coronary artery disease or myocardial infarction or heart failure (at least one of these).

      4.2 Agatston score in relation to cardiac disease

      We determined the relationship between the Agatston Score and the presence of coronary artery disease, myocardial infarction and heart failure in order to derive optimal cut-off values for the association with these disorders in a binary score. Using ROC analysis, we identified a significant relationship to coronary artery disease (AUC 0.765; 95% CI: 0.700, 0.831), the best cut-off value in terms of the Youden index being ≥1500 AU (see Fig. 1), corresponding to a sensitivity of 66% and a specificity of 82%. This cut-off was also the best for the history of myocardial infarction (AUC 0.757; 95% CI: 0.682, 0.833) and heart failure (AUC 0.599; 95% CI: 0.476, 0.721), as well as the combined variable called cardiac disease (AUC 0.740; 95% CI: 0.678, 0.803) (see Table S2), in which we kept heart failure despite being not significant as a single entity. In order to compare its potential diagnostic value with that of other cut-off values, particularly that of ≥400 AU, which has been repeatedly proposed [
      • Bergström G.
      • Persson M.
      • Adiels M.
      • Björnson E.
      • Bonander C.
      • Ahlström H.
      • et al.
      Prevalence of subclinical coronary artery atherosclerosis in the general population.
      ,
      • Neves P.O.
      • Andrade J.
      • Monção H.
      Coronary artery calcium score: current status.
      ], as well as an intermediate cut-off value of 1100 AU, we determined the percentages of coronary artery disease, heart failure and cardiac disease in general when using the different cut-off values. The results are shown in Fig. 2A–C. For cut-off values of 1100 and 400 AU, values of AUC as well as sensitivity, specificity and accuracy are shown in Table S2. It can be seen that accuracy increased when raising the cut-off value to 1500 AU.
      Fig. 1
      Fig. 1Receiver operating curve (ROC) for the relationship between the Agatston Score and the presence of coronary artery disease. The black bar indicates the highest Youden index which was achieved for Agatston scores of at least 1500 AU derived from non-ECG gated CT scans (AUC 0.765; 95% CI: 0.700; 0.831).
      Fig. 2
      Fig. 2A- C. Percentages of coronary artery disease, heart failure and cardiac disease stratified according to different Agaston-Score cut-off values derived from non-ECG gated CT scans. A–C illustrate the percentages of the coronary artery disease, heart failure and cardiac disease stratified according to different Agatston cut-off values of 400 AU, 1100 AU and 1500 AU. The value of 400 AU is the conventional for ECG gated scans, while that of 1500 AU was identified in the present study for non-ECG gated scans. The intermediate value of 1100 AU was chosen to illustrate the fact that the optimal cut-off for these conditions is far larger than 400 AU.

      4.3 Agatston Score, clinical and functional characteristics

      Patients with Agatston score ≥1500 AU were older, had slightly higher BMI and higher number of pack-years (p < 0.05 each), but without significant differences in smoking status (active versus non-active). An elevated score was more frequent in men (p < 0.001). Patients with higher score also showed higher FEV1, FVC, FEV1/FVC, and lower TLC, FRC, FRC/TLC, RV and RV/TLC, each as %predicted (p < 0.05), while there were no significant differences regarding CO diffusing capacity in terms of DLCO and KCO, again each as %predicted (Table 3).
      Table 3Comparisons of baseline characteristics and functional data according to Agatston Score cut-off value of 1500 AU.
      VariablesAgatston-Score <1500 AUAgatston-Score ≥1500 AUp-value
      Mean ± SD/absolute numbersMean ± SD/absolute numbers
      Sex (m/f)162/13385/19<0.001*
      Age (years)64.4 ± 8.170.7 ± 6.7<0.001*
      BMI (kg/m2)26.3 ± 4.927.5 ± 4.60.016*
      Pack-years44.1 ± 34.156.6 ± 37.10.001*
      FEV1 (%predicted)54.3 ± 18.759.0 ± 19.30.041*
      FEV1/FVC (Z-Score)−3.06 ± 1.07−2.71 ± 1.090.005*
      TLC (%predicted)117.7 ± 16.3113.2 ± 16.60.016*
      RV (%predicted)185.4 ± 53.5163.6 ± 48.8<0.001*
      RV/TLC (%predicted)157.4 ± 33.9157.4 ± 33.9<0.001*
      FRC (%predicted)146.5 ± 33.4134.9 ± 34.50.003*
      FRC/TLC (%predicted)123.7 ± 18.2117.9 ± 18.10.007*
      KCO (%predicted)64.5 ± 21.264.6 ± 22.30.892
      TLCO (%predicted)58.8 ± 21.658.8 ± 23.20.956
      GOLD grades 1/2/3/4 (numbers)31/137/97/3016/52/32/40.140
      GOLD groups A/B/C/D (numbers)114/56/57/6840/26/15/220.269
      Characteristics of the total study population stratified according to Agaston Score cut-off value of 1500 at visit 4. Numbers are given for categorical variables, and mean values and standard deviations for continuous variables. Comparisons between groups were performed by chi-square tests and Mann-Whitney-U test as appropriate. FEV1 = forced expiratory volume in 1 s, FVC = forced vital capacity, RV = residual volume, FRC = functional residual capacity, TLC = total lung capacity, ITGV = intrathoracic gas volume and the ratios FEV1/FVC, RV/TLC as well as FRC/TLC. TLCO = transfer factor for carbon monoxide, KCO = transfer coefficient of carbon monoxide.
      Values of the Agatston score ≥1500 AU were not associated with single CAT items (p > 0.05 each, Mann- Whitney-U test), and the same was true for the SGRQ impact score, activity score, symptom score and total score. There were also no significant differences regarding the distribution over GOLD grades 1–4 and groups ABCD, or regarding patients with high symptom burden (GOLD BD versus AC) and high exacerbation rate (CD versus AB).
      The prevalence of sleep apnea, arterial hypertension, heart failure, coronary artery disease, the history of myocardial infarction, diabetes and hyperuricemia was significantly higher in patients with Agatston values ≥ 1500 AU (p < 0.05 each), and there was a tendency towards lower prevalence of mental disorders (p = 0.070) (Table 4).
      Table 4Comorbidities stratified according to Agatston score ≥1500 AU.
      ComorbiditiesAgatston-Score <1500Agatston-Score ≥1500p-value
      Numbers (%)Numbers (%)
      Bronchiectasis11 (3.7%)1 (1.0%)0.198
      Sleep apnea33 (11.2%)20 (19.2%)0.044*
      Arterial hypertension149 (50.5%)66 (63.5%)0.029
      Coronary artery disease23 (7.8%)45 (43.3%)<0.001*
      Myocardial infarction11 (3.7%)26 (25%)<0.001*
      Heart failure13 (4.4%)14 (13.5%)0.003*
      Cardiac disease*34 (11.5%)54 (51.9%)<0.001*
      Chronic bronchitis197 (66.8%)67 (64.4%)0.718
      Gastrointestinal disorder76 (25.8%)26 (25.0%)1.000
      Gastroesophageal reflux disease105 (35.6%)28 (26.9%)0.117
      Diabetes28 (9.5%)22 (21.2%)0.003*
      Osteoporosis54 (18.3%)17 (16.3%)0.766
      Mental disorder84 (28.5%)20 (19.2%)0.070
      Hyperlipidemia138 (46.8%)52 (50.0%)0.648
      Hyperuricemia54 (18.3%)30 (28.8%)0.026*
      Asthma74 (25.1%)18 (17.3%)0.136
      The table shows absolute numbers and percentages. Comparisons between groups were performed by chi-square tests.

      4.4 Relationship of Agatston score to quantitative CT

      In the CT scans, patients with Agatston scores ≥1500 AU showed higher values of mean lung density (p = 0.004), while there were no differences between groups for emphysema index and 15th percentile of mean lung density (p > 0.05, each) (Table 5, Mann-Whitney U test). Moreover, there were significant differences (p < 0.05, each) between the two Agatston groups regarding the wall thickness of airways of generations 1–8, in parallel with differences in the percentage of walls relative to the total area of the airways as well as airway diameter up to generation 6 (p < 0.05 each).
      Table 5CT parameters stratified according to Agatston score ≥1500 AU.
      VariablesAgatston-Score <1500Agatston-Score ≥1500p-value
      Mean ± SDMean ± SD
      Mean lung density (HU)−849.4 ± 29.4−841.1 ± 32.00.004*
      Emphysema Index (%)17.8 ± 13.715.3 ± 12.60.131
      15th percentile of mean lung density−944.9 ± 25.0−941.5 ± 25.50.153
      Airway wall thickness (G1) mm2.4 ± 0.32.6 ± 0.3<0.001*
      Airway wall thickness (G2) mm2.2 ± 0.32.3 ± 0.2<0.001*
      Airway wall thickness (G3) mm2.1 ± 0.42.3 ± 0.3<0.001*
      Airway wall thickness (G4) mm1.8 ± 0.42.0 ± 0.3<0.001*
      Airway wall thickness (G5) mm1.4 ± 0.31.5 ± 0.30.001*
      Airway wall thickness (G6) mm1.2 ± 0.31.2 ± 0.30.002*
      Airway wall thickness (G7) mm1.0 ± 0.31.1 ± 0.30.016*
      Airway wall thickness (G8) mm0.9 ± 0.40.9 ± 0.40.034*
      CT characteristics of the total study population stratified according to Agaston Score cut-off value of 1500 at visit 4. Mean values and standard deviations for continuous variables. Comparisons between groups were performed by Mann-Whitney-U test.

      4.5 Multivariate analysis of the diagnostic role of the Agatston score

      In order to account for the interplay between covariates and to identify the independent predictive power of the Agatston score for cardiac disease, we performed logistic regression analysis with coronary artery disease as dependent variable. The predictors were sex, age, BMI, pack-years, the categories GOLD ABCD, moreover FEV1, FRC/TLC and TLCO, all of them in % predicted as well as obstructive sleep apnea, peripheral artery disease, diabetes, arterial hypertension, hyperlipidemia, and the binary Agatston score ≥1500 AU. BMI, hyperlipidemia, hypertension and GOLD group D were risk factors (p < 0.05 each). Additionally and independent from these, an Agatston score ≥1500 AU was associated with an Odds ratio of 8.8 (95% CI: 4.3; 18.4) for coronary artery disease (p < 0.001). The result is shown in Fig. 3, in which for simplicity a dichotomous variable GOLD D vs ABC has been chosen, without changing the major result. When the analysis was repeated with cut-off values of 400, 1100, 1500, 2500 AU and step-wise selection, always the cut-off value of 1500 AU was identified as the best predictor.
      Fig. 3
      Fig. 3Odds ratios and 95% confidence intervals of different risk factors, comorbidities, lung function and the Agaston Score cut-off value of 1500 AU for the presence of coronary artery disease. The figure shows the odds ratios for the outcome variable coronary artery disease for of the depicted predictors, as derived from binary logistic regression analysis. The bars show the odds ratios for changes by the amounts indicated for each of the predictors, and the Whiskers indicate their 95% confidence intervals. It can be seen that an Agatston score of at least 1500 AU was associated with an odds ration above 8 despite the presence of multiple other predictors of cardiac disease.

      4.6 Sensitivity analysis

      There were two study sites in which different slice thickness of CT was used. When excluding these sites, the same cut-off value of ≥1500 AU for the Agatston score with regard to cardiac diseases was obtained. When excluding the two study sites with lower slice thickness, the prevalence of heart failure, coronary artery disease, the history of myocardial infarction and diabetes was significantly higher in patients with Agatston values ≥ 1500 AU (p < 0.05 each).

      5. Discussion

      In the present work, we propose to use 1500 AU of the Agatston score as the cut-off value for routine CT scans performed in the diagnosis and monitoring of COPD scans, which is much higher than the usually applied maximum value of 400 AU. As today many COPD patients undergo CT scans for phenotyping and monitoring of their lung disease, we analyzed their clinical usefulness for the quantification of coronary calcification by means of the Agatston score.The major difference to cardiac scans is that COPD scans are normally neither ECG-gated nor contrast-enhanced. Although the Agatston score is not directly related to symptoms and exacerbations, we also found higher values to be associated with a bronchitis phenotype as indicated by larger airway diameter and thickness in CT and lower hyperinflation/air trapping in lung function. These findings underline that lung CT scans indicating coronary calcification as incidental finding via a proper cut-off value are an indication for coronary artery disease.
      The majority of COPD patients show cardiac comorbidities, which are a major cause of death [
      • Lozano R.
      • Naghavi M.
      • Foreman K.
      • Lim S.
      • Shibuya K.
      • Aboyans V.
      • et al.
      Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.
      ] but these comorbidities are still under-diagnosed [
      • Alter P.
      • Mayerhofer B.A.
      • Kahnert K.
      • Watz H.
      • Waschki B.
      • Andreas S.
      • et al.
      Prevalence of cardiac comorbidities, and their underdetection and contribution to exertional symptoms in COPD: results from the COSYCONET cohort.
      ]. Thus, any diagnostic indication regarding their presence is of value. While such indications could be derived from symptoms and lung function, potentially, in a different manner in men and women approach is hampered by the overlap with COPD symptoms. Echocardiography requires specific expertise and subject to high variability if not performed by specialists. A number of studies have demonstrated the diagnostic value of routine chest CT scans for phenotyping of the lung disease [
      • Bhatt S.P.
      • Washko G.R.
      • Hoffman E.A.
      • Newell Jr., J.D.
      • Bodduluri S.
      • Diaz A.A.
      • et al.
      Imaging advances in chronic obstructive pulmonary disease. Insights from the genetic epidemiology of chronic obstructive pulmonary disease (COPDGene) study.
      ] and lung cancer screening [
      • Venkatesan P.
      GOLD report: 2022 update.
      ]. As they are increasingly part of clinical routine in COPD, it begs the question whether they are also informative for cardiac diseases, even though not obtained under the specific technical conditions.
      The COSYCONET cohort study comprised chest CT scans in a prospective sub-study including analysis of parenchymal and airway characteristics and provided detailed information on patients’ clinical and functional state. Scans were standardized to the extent possible. Due to scanner geometry, two study centers used a slightly different slice thickness, which, however, had no impact on the results regarding the proposed cut-off value of the Agatston score. This suggests that the proposed cut-off value can be applied in the heterogeneous settings of clinical routine.
      Our finding of high Agatston score values is in line with previous findings of the COPDGene cohort based on sub-population of 50 patients and showing that ungated scans lead to systematically higher estimates of calcification than gated scans [
      • Budoff M.J.
      • Nasir K.
      • Kinney G.L.
      • Hokanson J.E.
      • Barr R.G.
      • Steiner R.
      • et al.
      Coronary artery and thoracic calcium on noncontrast thoracic CT scans: comparison of ungated and gated examinations in patients from the COPD Gene cohort.
      ]. The reason for the differences is the difference in CT slice thickness. Standard reconstruction for coronary artery calcium scoring is based on 3 mm non-overlapping slices [
      • McCollough C.H.
      • Ulzheimer S.
      • Halliburton S.S.
      • Shanneik K.
      • White R.D.
      • Kalender W.A.
      Coronary artery calcium: a multi-institutional, multimanufacturer international standard for quantification at cardiac CT.
      ], while for COPD monitoring smaller slice thickness such as 1 mm is common. Nevertheless, studies have shown good correlations between coronary calcium scores derived from standard calcium scoring reconstructions and those from non-gated CTs [
      • Budoff M.J.
      • Nasir K.
      • Kinney G.L.
      • Hokanson J.E.
      • Barr R.G.
      • Steiner R.
      • et al.
      Coronary artery and thoracic calcium on noncontrast thoracic CT scans: comparison of ungated and gated examinations in patients from the COPD Gene cohort.
      ,
      • Kirsch J.
      • Buitrago I.
      • Mohammed T.L.
      • Gao T.
      • Asher C.R.
      • Novaro G.M.
      Detection of coronary calcium during standard chest computed tomography correlates with multi-detector computed tomography coronary artery calcium score.
      ]. The Agatston score is well suited for automated quantification although it might be inferior to visual inspection. For example, the Weston score was associated with time to first coronary artery event, whereas Agatston score was not, at least when using the cut-off value of ≥400 AU [
      • Bhatt S.P.
      • Kazerooni E.A.
      • Newell Jr., J.D.
      • Hokanson J.E.
      • Budoff M.J.
      • Dass C.A.
      • et al.
      Visual estimate of coronary artery calcium predicts cardiovascular disease in COPD.
      ]. The authors did not provide information whether a different cut-off value would have yielded a different result.
      In our study population there were no or only weak associations of the Agatston score with COPD symptoms or exacerbation history; this was also reflected in a similar distribution over GOLD groups A-D. These findings are in accordance with previous investigations [
      • Williams M.C.
      • Murchison J.T.
      • Edwards L.D.
      • Agustí A.
      • Bakke P.
      • Calverley P.M.A.
      • et al.
      Coronary artery calcification is increased in patients with COPD and associated with increased morbidity and mortality.
      ]. Regarding lung function, patients with elevated Agatston score showed less lung hyperinflation but no differences in CO diffusing capacity. In the univariate analysis there were also no differences regarding GOLD grades, however the multivariable analysis revealed GOLD group D as additional factor linked to an elevated Agatston score. These observations indicate a correlation between high Agatston score and a COPD phenotype linked to bronchitis and recurrent exacerbations. It appeared that the existence of this phenotype was more important than smoking history in terms of pack-years which might be stronger associated with emphysema than bronchitis.
      This was confirmed by our observation that central airway wall thickness was greater in patients with high Agatston score, while the quantitative emphysema score did not differ. This is consistent with a previous study where there was no association with the quantitative emphysema score but at the same time an association with bronchial wall thickening. However, the latter disappeared, after adjustment for confounders [
      • Bhatt S.P.
      • Nath H.P.
      • Kim Y.I.
      • Ramachandran R.
      • Watts J.R.
      • Terry N.L.J.
      • et al.
      Centrilobular emphysema and coronary artery calcification: mediation analysis in the SPIROMICS cohort.
      ]. When we adjusted airway wall thickness for age, BMI, gender and FEV1 %predicted, the differences regarding the Agatston score of ≥1500 AU remained statistically significant for airway generations 1–4. It may be speculated that the measurement error in the higher generation was too high to observe an association with the Agatston score. From a pathophysiological perspective, the link between elevated Agatston score, corresponding to more prevalent cardiac disease, and airway wall thickness might be due to inflammation, either local or systemic. Associations between systemic inflammation and cardiovascular events have also been suggested by the ETHOS study regarding eosinophil counts [
      • Martinez F.J.
      • Rabe K.F.
      • Ferguson G.T.
      • Wedzicha J.A.
      • Singh D.
      • Wang C.
      • et al.
      Reduced all-cause mortality in the ETHOS trial of budesonide/glycopyrrolate/formoterol for chronic obstructive pulmonary disease. A randomized, double-blind, multicenter, parallel-group study.
      ].
      The data of this study underline that routine CTs obtained in COPD phenotyping are useful for additional diagnosis of cardiac diseases. We propose to use an Agatston score of ≥1500 AU in case of chest CT scans performed for phenotyping and monitoring of COPD patients. The score can be automatically computed by commercially available CT software, albeit the proportion of inconclusive results will be higher in ungated scans. This was reflected by the fact that in our analysis only 399 of 547 scans allowed for a meaningful estimation of Agatston score. Still, given the minimal additional effort, the quantification of coronary vessel wall calcium load could be part of the CT report, thus extracting the maximum information possible from scans used for COPD phenotyping. Thus, for clinical practice, the determination of coronary calcium from non-ECG gated CT scans by means of automated evaluation is feasible and a valuable. Once available, it will help the treating physicians to detect asymptomatic patients if the score is 1500 AU or above; these patients might benefit from further, specific cardiologic assessment. From Fig. 3 it can be inferred that in addition to anamnestic risk factors an elevated Agatston score was linked to a nearly 10-fold increase in the likelihood of coronary artery disease. This underlines that with minor additional effort a significant diagnostic gain can be obtained from available CT information.

      6. Limitations

      We did not have ECG-gated CT scans specifically designed for the Agatston score for comparison and therefore could not assess whether the cut-off value of 400 AU was also suitable in our population with ECG-gated scans. In addition, the Agatston score was available in only about 72% of our total study population. Although this limits the usefulness of routine CT scans regarding the Agatston score, this might be compensated by the fact that this score can be computed automatically. Moreover, a mortality analysis was not feasible, as only 15 patients of the study population died. Furthermore, the coronary artery calcium load is subject to changes with age and gender [
      • Hoff J.A.
      • Chomka E.V.
      • Krainik A.J.
      • Daviglus M.
      • Rich S.
      • Kondos G.T.
      Age and gender distributions of coronary artery calcium detected by electron beam tomography in 35,246 adults.
      ]. Due to the relatively narrow age distribution in our study population, with a median age of 68 years, age did not appear to be relevant for the Agatston cut-off value as shown in the sensitivity analysis. The same was true for gender. It should be kept in mind that our results refer to a COPD population and not necessarily the general population. Even within the COPD patients we had to exclude a great number of patients due to missing data but their basic characteristics, especially the history of coronary artery disease, were very similar to the patients included. The diagnosis of cardiac disease was based on physician-based diagnoses and could not be verified by independent, invasive procedures, however, in previous analyses regarding cardiovascular diseases these diagnoses turned out to be useful and plausible [
      • Alter P.
      • Jorres R.A.
      • Watz H.
      • Welte T.
      • Glaser S.
      • Schulz H.
      • et al.
      Left ventricular volume and wall stress are linked to lung function impairment in COPD.
      ,
      • Alter P.
      • Watz H.
      • Kahnert K.
      • Rabe K.F.
      • Biertz F.
      • Fischer R.
      • et al.
      Effects of airway obstruction and hyperinflation on electrocardiographic axes in COPD.
      ,
      • Alter P.
      • Mayerhofer B.A.
      • Kahnert K.
      • Watz H.
      • Waschki B.
      • Andreas S.
      • et al.
      Prevalence of cardiac comorbidities, and their underdetection and contribution to exertional symptoms in COPD: results from the COSYCONET cohort.
      ].

      7. Conclusion

      Automated quantification of coronary vessel wall calcification from non-ECG gated CT scans, as commonly obtained in COPD monitoring, turned out to be a useful risk predictor for cardiac disease. Furthermore, calcification correlated with the airway-phenotype of COPD in terms of lung function impairment and increased central airway wall thickness. I nstead of the usual Agatston score of 400 AU recommended for ECG-gated CT, we found a cut-off value of 1500 AU adequate for non-triggered routine CT scans in COPD, being linked to a 10-fold increase in coronary artery disease. Our proposal could be easily implemented into clinical practice.

      COSYCONET Study-Group

      Andreas, Stefan (Lungenfachklinik, Immenhausen); Bals, Robert (Universitätsklinikum des Saarlandes); Behr, Jürgen and Kahnert, Kathrin (Klinikum der Ludwig-Maximilians-Universität München); Bewig, Burkhard and Thomas Bahmer (Universitätsklinikum Schleswig Holstein); Buhl, Roland (Universitätsmedizin der Johannes-Gutenberg-Universität Mainz); Ewert, Ralf and Stubbe, Beate (Universitätsmedizin Greifswald); Ficker, Joachim H. (Klinikum Nürnberg, Paracelsus Medizinische Privatuniversität Nürnberg); Gogol, Manfred (Institut für Gerontologie, Universität Heidelberg); Grohé, Christian (Ev. Lungenklinik Berlin); Hauck, Rainer (Kliniken Südostbayern AG, Kreisklinik Bad Reichenhall); Held, Matthias and Jany, Berthold (Klinikum Würzburg Mitte gGmbH, Standort Missioklinik); Henke, Markus (Asklepios Fachkliniken München-Gauting); Herth, Felix (Thoraxklinik Heidelberg gGmbH); Höffken, Gerd (Fachkrankenhaus Coswig GmbH); Katus, Hugo A. (Universitätsklinikum Heidelberg); Kirsten, Anne-Marie and Watz, Henrik (Pneumologisches Forschungsinstitut an der Lungenclinic Grosshansdorf GmbH); Koczulla, Rembert and Kenn, Klaus (Schön Klinik Berchtesgadener Land); Kronsbein, Juliane (Berufsgenossenschaftliches Universitätsklinikum Bergmannsheil, Bochum); Kropf-Sanchen, Cornelia (Universitätsklinikum Ulm); Lange, Christoph and Zabel, Peter (Forschungszentrum Borstel); Pfeifer, Michael (Klinik Donaustauf); Randerath, Winfried J. (Wissenschaftliches Institut Bethanien e. V., Solingen); Seeger, Werner (Justus-Liebig-Universität Gieβen); Studnicka, Michael (Uniklinikum Salzburg); Taube, Christian and Teschler, Helmut (Ruhrlandklinik gGmbH Essen); Timmermann, Hartmut (Hamburger Institut für Therapieforschung GmbH); Virchow, J. Christian (Universitätsklinikum Rostock); Vogelmeier, Claus (Universitätsklinikum Gieβen und Marburg GmbH, Standort Marburg); Wagner, Ulrich (Klinik Löwenstein gGmbH); Welte, Tobias (Medizinische Hochschule Hannover); Wirtz, Hubert (Universitätsklinikum Leipzig).

      Names of participating study nurses

      Doris Lehnert, Evangelische Lungenklinik Berlin; Birte Struck, Bergmannsheil Berufsgenossenschaftliches Universitätsklinikum Bochum; Lenka Krabbe, Medizinische-Klinik Borstel; Barbara Arikan, Julia Tobias, Klinik Donaustauf; Gina Spangel, Julia Teng, Ruhrlandklinik gGmbH Essen, Kornelia Speth, Universitätsklinikum Gieβen; Jeanette Pieper, Universitätsmedizin Greifswald; Margret Gleiniger, Britta Markworth, Zaklina Hinz, Petra Hundack-Winter, Pneumologisches Forschungsinstitut Groβhansdorf; Ellen Burmann, Hamburger Institut für Therapieforschung Hamburg; Katrin Wons, Sylvia Wagner Medizinische Hochschule Hannover; Ulrike Rieber, Beate Schaufler, Thoraxklinik am Universitätsklinikum Heidelberg; Martina Seibert, Universitätsklinikum des Saarlandes, Homburg/Saar; Katrin Schwedler, Lungenfachklinik Immenhausen; Sabine Michalewski, Sonja Rohweder, Universitätsklinikum Schleswig-Holstein, Campus Kiel; Patricia Berger, Universitätsklinikum Leipzig; Diana Schottel, Krankenhaus Lindenbrunn, Coppenbrügge; Manuel Klöser, Universitätsmedizin der Johannes Gutenberg-Universität Mainz; Vivien Janke, Universitätsklinikum Marburg; Rosalie Untsch, Asklepios Fachkliniken, München-Gauting; Jana Graf, Klinikum der Universität München; Anita Reichel, Klinikum Nürnberg; Gertraud Weiβ, Erich Traugott, Barbara Ziss, Schön Klinik Berchtesgadener Land; Ilona Kietzmann, Wissenschaftliches Institut Bethanien für Pneumologie e. V, Solingen; Michaela Schrade-Illmann, Beate Polte, Universitätsklinikum-Ulm; Cornelia Böckmann, Gudrun Hübner, Lena Sterk, Anne Wirz, Klinikum Würzburg Mitte gGmbH, Standort Missioklinik, Würzburg.

      Authors’ contributions

      Kathrin Kahnert was involved in the conception of the study, analyzing and interpreting the data, statistical analysis, conceptualizing and drafting of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Rudolf Jörres was involved in the conception of the study, analyzing and interpreting the data, statistical analysis, conceptualizing and drafting of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Bertram Jobst was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Mark Wielpütz was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Axinja Seefelder was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Caroline Hackl was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Franziska Trudzinski was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Henrik Watz was involved in the interpretation of the data from this analysis and drafting of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Robert Bals was involved in the interpretation of the data from this analysis and drafting of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Jürgen Behr was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Klaus Rabe was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Claus Vogelmeier contributed to the overall design of COSYCONET, to the interpretation of the data from this analysis, to the development and critical revision of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Mark Wielpütz was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Tobias Welte contributed to the overall design of COSYCONET, to the interpretation of the data from this analysis, to the development and critical revision of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Felix Herth was involved in the interpretation of the data from this analysis, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Hans-Ulrich Kauczor was involved in the interpretation of the data from this analysis and in interpretation of the CT scans, took part in the discussion and critical revision of this manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work. Jürgen Biederer was involved in the conception of the study, statistical analysis and interpretation of the data, conceptualizing and drafting of the manuscript, approved the final submitted version, and agreed to be accountable for all aspects of the work.

      Funding

      This work is supported by the German Center for Lung Research (DZL) , grant number 82DZLI05A2 (COSYCONET), the BMBF , grant number 01GI0881 and is furthermore supported by unrestricted grants from AstraZeneca GmbH , Boehringer Ingelheim Pharma GmbH & Co. KG , GlaxoSmithKline GmbH&Co. KG , Grifols Deutschland GmbH , Novartis Deutschland GmbH .
      The funding body had no involvement in the design of the study, or the collection, analysis or interpretation of the data.

      Availability of data and materials

      The basic data are part of the German COPD cohort COSYCONET (www.asconet.net/) and available upon request. There is a detailed procedure for this on the website of this network. Specifically, the data can be obtained by submission of a proposal that is evaluated by the steering committee. All results to which the manuscript refers, are documented appropriately in the text, figures or tables.

      Ethics approval and consent to participate

      All assessments were approved by the central (Marburg (Ethikkommission FB Medizin Marburg) and local (Bad Reichenhall (Ethikkommission bayerische Landesärztekammer); Berlin (Ethikkommission Ärztekammer Berlin); Bochum (Ethikkommission Medizinische Fakultät der RUB); Borstel (Ethikkommission Universität Lübeck); Coswig (Ethikkommission TU Dresden); Donaustauf (Ethikkommission Universitätsklinikum Regensburg); Essen (Ethikkommission Medizinische Fakultät Duisburg-Essen); Gieβen (Ethikkommission Fachbereich Medizin); Greifswald (Ethikkommission Universitätsmedizin Greifswald); Groβhansdorf (Ethikkommission Ärztekammer Schleswig-Holstein); Hamburg (Ethikkommission Ärztekammer Hamburg); MHH Hannover/Coppenbrügge (MHH Ethikkommission); Heidelberg Thorax/Uniklinik (Ethikkommission Universität Heidelberg); Homburg (Ethikkommission Saarbrücken); Immenhausen (Ethikkommission Landesärztekammer Hessen); Kiel (Ethikkommission Christian-Albrechts-Universität zu Kiel); Leipzig (Ethikkommission Universität Leipzig); Löwenstein (Ethikkommission Landesärztekammer Baden-Württemberg); Mainz (Ethikkommission Landesärztekammer Rheinland-Pfalz); München LMU/Gauting (Ethikkommission Klinikum Universität München); Nürnberg (Ethikkommission Friedrich-Alexander-Universität Erlangen Nürnberg); Rostock (Ethikkommission Universität Rostock); Berchtesgadener Land (Ethikkommission Land Salzburg); Schmallenberg (Ethikkommission Ärztekammer Westfalen-Lippe); Solingen (Ethikkommission Universität Witten-Herdecke); Ulm (Ethikkommission Universität Ulm); Würzburg (Ethikkommission Universität Würzburg)) Ethical Committees, and written informed consent was obtained from all patients.
      The study was based on 2741 patients recruited within the COSYCONET framework (ClinicalTrials.gov, Identifier: NCT01245933).
      For further information see:
      Karch A, Vogelmeier C, Welte T, Bals R, Kauczor HU, Biederer J, Heinrich J, Schulz H, Glaser S, Holle R et al.: The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline. Respir Med 2016, 114:27–37.

      Consent for publication

      Within the ethical approval, the participants of the study gave their consent to publish the data collected during the study period.

      Declaration of competing interest

      The authors declare that they have no competing interests. Financial support provided to individuals is disclosed on the conflict of interest declaration provided from each single author.

      Acknowledgements

      We would like to thank all patients for their kind participation as well as the COSYCONET Study-Group and the participating study nurses for their efforts.

      Appendix A. Supplementary data

      The following are the Supplementary data to this article:

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