Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging
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Published on: June 5, 2019
Christoph Kolb1, Andreas Wetscherek, Maria Teodora Buzan
1From the *Junior Group Medical Image Computing and †Division of Medical Physics in Radiology, DKFZ, Heidelberg, Germany; ‡Joint Department of Physics at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, London, United Kingdom; §Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University, Heidelberg, Germany; ∥Department of Pneumology, luliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania; ¶Department of Diagnostic and of Interventional Radiology Heidelberg University, Heidelberg; #Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg; **Department of Pneumology and Respiratory Critical Care Medicine, Thoraxklinik at Heidelberg University Hospital; ††Translational Lung Research Center Heidelberg (TLRC-H), member of the German Center for Lung Research (DZL), Heidelberg; ‡‡Institute of Clinical Radiology, Munich; §§Comprehensive Pneumology Center Munich (CPC-M), member of the German Center for Lung Research (DZL); and ∥∥Division of Radiology, DKFZ, Heidelberg, Germany.
Objective:
We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI).
Methods:
A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference).
Results:
Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior.
Conclusions:
The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.
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