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

Imaging Disease Progression in COPD (MR-COPDII)

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

Study Overview

• Status: Completed
• Conditions: Chronic Obstructive Pulmonary Disease

Detailed Description

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.

• Study Type: Observational
• Enrollment (Actual): 252

Contacts and Locations

Study Locations

• Germany
  • Giessen, Germany, 35392
    • Universitätsklinikum Gießen und Marburg GmbH,Klinik für Diagnostische und Interventionelle Radiologie
  • Greifswald, Germany, 17475
    • Universitätsmedizin Greifswald, Institut für Diagnostische Radiologie u. Neuroradiologie
  • Grosshansdorf, Germany, 22927
    • LungenClinic Grosshansdorf, Pneumologisches Forschungsinstitut
  • Hamburg, Germany, 20354
    • Hamburger Institut für Therapieforschung (HIT) GmbH
  • Hannover, Germany, 30625
    • Medizinische Hochschule Hannover, Zentrum Radiologie, Institut für Diagnostische und Interventionelle Radiologie
  • Heidelberg, Germany, 69126
    • Thoraxklinik Heidelberg, Diagnostische und Interventionelle Radiologie
  • Kiel, Germany, 24105
    • Universitätsklinikum Schleswig Holstein, Klinik für Diagnostische Radiologie, Campus Kiel
  • Marburg, Germany, 35043
    • Universitätsklinikum, Zentrum für Radiologie, Klinik für Diagnostische und Interventionelle Radiologie
  • Muenchen, Germany, 81377
    • Klinikum der Universität Muenchen, Klinik und Poliklinik für Radiologie
  • Nuernberg, Germany, 90419
    • Klinikum Nord-Nuernberg, Radiologie

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 40 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The trial is fully embedded in the COSYCONET cohort and will only comprise participants of the precursor trial performed between 2013 and 2016:Image-Based Structural and Functional Phenotyping of the COSYCONET Cohort Using MRI and CT (MR-COPD), NCT 02629432.

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
COSYCONET COPD Subcohort; 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?

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

Collaborators and Investigators

• Sponsor: University Hospital Heidelberg
• Collaborators: Hannover Medical School; Philipps University Marburg Medical Center; German Center for Lung Research
• Investigators: Principal Investigator: Juergen Biederer, Prof, University Hosital Heidelberg; Principal Investigator: Bertram J. Jobst, MD, University Hospital Heidelberg

Publications and helpful links

General Publications

• Biederer J, Mirsadraee S, Beer M, Molinari F, Hintze C, Bauman G, Both M, Van Beek EJ, Wild J, Puderbach M. MRI of the lung (3/3)-current applications and future perspectives. Insights Imaging. 2012 Aug;3(4):373-86. doi: 10.1007/s13244-011-0142-z. Epub 2012 Jan 15.
• Biederer J, Beer M, Hirsch W, Wild J, Fabel M, Puderbach M, Van Beek EJ. MRI of the lung (2/3). Why ... when ... how? Insights Imaging. 2012 Aug;3(4):355-71. doi: 10.1007/s13244-011-0146-8. Epub 2012 Feb 13.
• Wild JM, Marshall H, Bock M, Schad LR, Jakob PM, Puderbach M, Molinari F, Van Beek EJ, Biederer J. MRI of the lung (1/3): methods. Insights Imaging. 2012 Aug;3(4):345-53. doi: 10.1007/s13244-012-0176-x. Epub 2012 Jun 13.
• COPDGene CT Workshop Group; Barr RG, Berkowitz EA, Bigazzi F, Bode F, Bon J, Bowler RP, Chiles C, Crapo JD, Criner GJ, Curtis JL, Dass C, Dirksen A, Dransfield MT, Edula G, Erikkson L, Friedlander A, Galperin-Aizenberg M, Gefter WB, Gierada DS, Grenier PA, Goldin J, Han MK, Hanania NA, Hansel NN, Jacobson FL, Kauczor HU, Kinnula VL, Lipson DA, Lynch DA, MacNee W, Make BJ, Mamary AJ, Mann H, Marchetti N, Mascalchi M, McLennan G, Murphy JR, Naidich D, Nath H, Newell JD Jr, Pistolesi M, Regan EA, Reilly JJ, Sandhaus R, Schroeder JD, Sciurba F, Shaker S, Sharafkhaneh A, Silverman EK, Steiner RM, Strange C, Sverzellati N, Tashjian JH, van Beek EJ, Washington L, Washko GR, Westney G, Wood SA, Woodruff PG. A combined pulmonary-radiology workshop for visual evaluation of COPD: study design, chest CT findings and concordance with quantitative evaluation. COPD. 2012 Apr;9(2):151-9. doi: 10.3109/15412555.2012.654923. Epub 2012 Mar 19.
• Gietema HA, Muller NL, Fauerbach PV, Sharma S, Edwards LD, Camp PG, Coxson HO; Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) investigators. Quantifying the extent of emphysema: factors associated with radiologists' estimations and quantitative indices of emphysema severity using the ECLIPSE cohort. Acad Radiol. 2011 Jun;18(6):661-71. doi: 10.1016/j.acra.2011.01.011. Epub 2011 Mar 9.
• Jorres RA, Welte T, Bals R, Koch A, Schnoor M, Vogelmeier C. [Systemic manifestations and comorbidities in patients with chronic obstructive pulmonary disease (COPD) and their effect on clinical state and course of the disease--an overview of the cohort study COSYCONET]. Dtsch Med Wochenschr. 2010 Mar;135(10):446-9. doi: 10.1055/s-0030-1249185. Epub 2010 Mar 2. German.
• Karch A, Vogelmeier C, Welte T, Bals R, Kauczor HU, Biederer J, Heinrich J, Schulz H, Glaser S, Holle R, Watz H, Korn S, Adaskina N, Biertz F, Vogel C, Vestbo J, Wouters EF, Rabe KF, Sohler S, Koch A, Jorres RA; COSYCONET Study Group. The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline. Respir Med. 2016 May;114:27-37. doi: 10.1016/j.rmed.2016.03.008. Epub 2016 Mar 11.

Study record dates

Study Major Dates

• Study Start (Actual): November 10, 2017
• Primary Completion (Actual): December 31, 2019
• Study Completion (Actual): April 30, 2024

Study Registration Dates

• First Submitted: February 17, 2018
• First Submitted That Met QC Criteria: July 7, 2018
• First Posted (Actual): July 19, 2018

Study Record Updates

• Last Update Posted (Actual): May 24, 2024
• Last Update Submitted That Met QC Criteria: May 23, 2024
• Last Verified: May 1, 2024

More Information

Terms related to this study

• Keywords: MRI; COPD; Disease Progression
• Additional Relevant MeSH Terms: Pathologic Processes; Respiratory Tract Diseases; Disease Attributes; Chronic Disease; Disease Progression; Lung Diseases; Lung Diseases, Obstructive; Pulmonary Disease, Chronic Obstructive
• Other Study ID Numbers: 82DZLS24A1

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Pseudonymized Data from structured image reads will be transferred to the central COSYCONET data base at Hannover Medical School.
• IPD Sharing Time Frame: 12 months after data completion
• IPD Sharing Access Criteria: Data access requests by scientists, members or non-members of the COSYCONET consortium, will be reviewed by the COSYCONET Executive Board.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No