Imaging Progression of Chronic Obstructive Pulmonary Disease Using MRI and CT (MR-COPDII)

Study Overview
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Brief Summary
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In this follow-up trial, MRI and CT images of the lung will be acquired prospectively in a subcohort of 370 patients, three years after they successfully participated in the first COSYCONET subtrial with CT and MRI (MR-COPD I, NCT (clinical.Trials.gov identifier) 02629432). The objective is to obtain longitudinal data from a well-characterized collective of COPD patients in order to identify suitable image-based biomarkers to improve the prognosis of disease progression of COPD in comparison to clinical tests

Detailed Description
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There is evidence that both computed tomography (CT) and proton magnetic resonance imaging (1H-MRI) have the potential to detect changes in lung structure and function earlier and with higher sensitivity than currently available clinical tests. We state the hypothesis that the progression of regional lung alterations as detected with MRI and CT precedes the worsening of airflow limitation and clinical symptoms. Before the method can be recommended for patient stratification or for monitoring disease progression, final proof is needed that any changes over time correlate with clinical symptoms and that the quantitative parameters and biomarkers obtained with imaging are predictive for the further course of the disease. Therefore, a dedicated prospective longitudinal trial is required. The primary end point of the study is to use changes in lung perfusion MRI (e.g. pulmonary blood volume, pulmonary blood flow) and CT (e.g. airway wall thickness, extent of emphysema, extent of air trapping) within a 3-year interval for the prediction of long-term disease progression as monitored by clinical tests (within the following 3 years; BODE index (BODE= body-mass index, airflow obstruction, dyspnea and exercise capacity index in chronic obstructive pulmonary disease). A progression of the disease is defined as an increase of the multidimensional 10-point BODE index by at least one point. This is an exploratory study. The local two-sided type-I error rate is set to 5%. Statistical analysis will be primarily conducted as a complete case analysis. Logistic regression models with dependent variable COPD progression will be used. Imaging biomarkers are used as independent variables. All models are adjusted for the prognostic factors age, sex, GOLD (GOLD= Global Initiative For Chronic Obstructive Lung Disease) stage and smoking status as well as the factor study center.

Official Title
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Imaging Disease Progression in COPD (MR-COPDII)

Conditions
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Chronic Obstructive Pulmonary Disease

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients enrolled into the COSYCONET main cohort (Impact of Systemic Manifestations/Comorbidities on Clinical State, Prognosis, Utilisation of Health care resources in Patients with COPD (COSYCONET), NCT01245933), having already successfully participated in the COSYCONET subtrial with CT and MRI performed between December 2013 and July 2016 (Image-Based Structural and Functional Phenotyping of the COSYCONET Cohort Using MRI and CT (MR-COPD), NCT 02629432) Exclusion Criteria: Insufficient quality of MRI and CT obtained at baseline (MR-COPD I) Having undergone lung surgery (e.g. lung volume reduction, lung transplantation) Moderate or severe exacerbation requiring antibiotic treatment within prior to appointment Absence of consent Inability to understand the intention of the project Contraindications to MRI and/or CT

Ages Eligible for Study
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Minimum Age: 40 Years
Maximum Age: 100 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| COSYCONET COPD Subcohort<br>MRI and CT of the lung will be performed in a multi-centre subcohort of 370 patients having already participated in the precursor trial  Image-Based Structural and Functional Phenotyping of the COSYCONET Cohort Using MRI and CT (MR-COPD), NCT 02629432. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity and specificity of pulmonary blood flow calculated from first pass perfusion MRI to predict disease progression in COPD | Changes from baseline in MRI-based lung perfusion: pulmonary blood flow (PBF) | Baseline: December 2013-July 2016 Follow-Up: November 2017-June 2020 | 
| Sensitivity and specificity of pulmonary blood volume calculated from first pass perfusion MRI to predict disease progression in COPD | Changes from baseline in MRI-based lung perfusion: pulmonary blood volume (PBV) | Baseline: December 2013-July 2016 Follow-Up: November 2017-June 2020 | 
| Sensitivity and specificity of visual perfusion deficit on first pass perfusion MRI to predict disease progression in COPD | Changes from baseline in MRI-based lobar perfusion deficit score (visual 4-point rating scale: 0=normal perfusion, 1= mild heterogeneities, 2= perfusion defects affecting up to 50% of a lobe, 3= perfusion defects affecting more than 50% of the lobe). Lobar scores are summed up to a total perfusion deficit score for each patient. A completely healthy subject with unimpared lung perfusion would be scored as 0 (best possible result), while the result for more than 50% involvement of all lung lobes would be scored as 18 (worst possible result). | December 2013-July 2016 Follow-Up: November 2017-June 2020 | 
| Sensitivity and specificity of airway wall metrics on CT to predict disease progression in COPD | Changes from baseline in CT-based metrics for the extent of airway wall thickening (standardized airway wall thickness: PI10) | Baseline: December 2013-July 2016 Follow-Up: November 2017-June 2020 | 
| Sensitivity and specificity of emphysema quantification with CT to predict disease progression in COPD | Changes from baseline in CT-based metrics for the extent of emphysema (low attenuation areas in percent of total lung volume: LAA%) | Baseline: December 2013-July 2016 Follow-Up: November 2017-June 2020 | 
| Sensitivity and specificity of air trapping on expiratory CT to predict disease progression in COPD | Changes from baseline in CT-based metrics for the extent air trapping (expiratory to inspiratory ratio of mean lung density (E/I-MLD) | Baseline: December 2013-July 2016 Follow-Up: November 2017-June 2020 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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MRI, COPD, Disease Progression