Automated MR-based lung volume segmentation in population-based whole-body MR imaging: correlation with clinical characteristics, pulmonary function testing and obstructive lung disease.

Autor: Mueller J; Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany., Karrasch S; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.; Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research, Munich, Germany.; Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität, Munich, Germany., Lorbeer R; Department of Radiology, University Hospital, LMU Munich, Munich, Germany., Ivanovska T; Department of Computational Neuroscience, Computer Vision, Georg-August-University, Gottingen, Germany., Pomschar A; Department of Radiology, University Hospital, LMU Munich, Munich, Germany., Kunz WG; Department of Radiology, University Hospital, LMU Munich, Munich, Germany., von Krüchten R; Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.; Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany., Peters A; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.; Institute for Cardiovascular Prevention, Ludwig-Maximilian-University-Hospital, Munich, Germany.; German Center for Cardiovascular Disease Research (DZHK e.V.), Partnersite Munich, Munich, Germany., Bamberg F; Department of Diagnostic and Interventional Radiology, University of Tuebingen, Tuebingen, Germany., Schulz H; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.; Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research, Munich, Germany., Schlett CL; Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany. Christopher.Schlett@post.harvard.edu.; Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany. Christopher.Schlett@post.harvard.edu.
Jazyk: angličtina
Zdroj: European radiology [Eur Radiol] 2019 Mar; Vol. 29 (3), pp. 1595-1606. Date of Electronic Publication: 2018 Aug 27.
DOI: 10.1007/s00330-018-5659-9
Abstrakt: Objectives: Whole-body MR imaging is increasingly utilised; although for lung dedicated sequences are often not included, the chest is typically imaged. Our objective was to determine the clinical utility of lung volumes derived from non-dedicated MRI sequences in the population-based KORA-FF4 cohort study.
Methods: 400 subjects (56.4 ± 9.2 years, 57.6% males) underwent whole-body MRI including a coronal T1-DIXON-VIBE sequence in inspiration breath-hold, originally acquired for fat quantification. Based on MRI, lung volumes were derived using an automated framework and related to common predictors, pulmonary function tests (PFT; spirometry and pulmonary gas exchange, n = 214) and obstructive lung disease.
Results: MRI-based lung volume was 4.0 ± 1.1 L, which was 64.8 ± 14.9% of predicted total lung capacity (TLC) and 124.4 ± 27.9% of functional residual capacity. In multivariate analysis, it was positively associated with age, male, current smoking and height. Among PFT indices, MRI-based lung volume correlated best with TLC, alveolar volume and residual volume (RV; r = 0.57 each), while it was negatively correlated to FEV 1 /FVC (r = 0.36) and transfer factor for carbon monoxide (r = 0.16). Combining the strongest PFT parameters, RV and FEV 1 /FVC remained independently and incrementally associated with MRI-based lung volume (β = 0.50, p = 0.04 and β = - 0.02, p = 0.02, respectively) explaining 32% of the variability. For the identification of subjects with obstructive lung disease, height-indexed MRI-based lung volume yielded an AUC of 0.673-0.654.
Conclusion: Lung volume derived from non-dedicated whole-body MRI is independently associated with RV and FEV 1 /FVC. Furthermore, its moderate accuracy for obstructive lung disease indicates that it may be a promising tool to assess pulmonary health in whole-body imaging when PFT is not available.
Key Points: • Although whole-body MRI often does not include dedicated lung sequences, lung volume can be automatically derived using dedicated segmentation algorithms • Lung volume derived from whole-body MRI correlates with typical predictors and risk factors of respiratory function including smoking and represents about 65% of total lung capacity and 125% of the functional residual capacity • Lung volume derived from whole-body MRI is independently associated with residual volume and the ratio of forced expiratory volume in 1 s to forced vital capacity and may allow detection of obstructive lung disease.
Databáze: MEDLINE
Externí odkaz: