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Method Article

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

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DOI:

10.3791/66257

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April 12th, 2024

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In This Article

Summary

CT and 129Xe MRI provide complementary lung structure-function information that can be exploited for regional analysis using image registration. Here, we provide a protocol that builds from the existing literature for 129Xe MR to CT image registration using open-source platforms.

Abstract

Hyperpolarized 129Xe gas MRI is an emerging technique to evaluate and measure regional lung function including pulmonary gas distribution and gas exchange. Chest computed tomography (CT) still remains the clinical gold standard for imaging of the lungs, though, in part due to the rapid CT protocols that acquire high-resolution images in seconds and the widespread availability of CT scanners. Quantitative approaches have enabled the extraction of structural lung parenchymal, airway and vascular measurements from chest CT that have been evaluated in many clinical research studies. Together, CT and 129Xe MRI provide complementary information that can be used to evaluate regional lung structure and function, resulting in new insights into lung health and disease. 129Xe MR-CT image registration can be performed to measure regional lung structure-function to better understand lung disease pathophysiology, and to perform image-guided pulmonary interventions. Here, a method for 129Xe MRI-CT registration is outlined to support implementation in research or clinical settings. Registration methods and applications that have been employed to date in the literature are also summarized, and suggestions are provided for future directions that may further overcome technical challenges related to 129Xe MR-CT image registration and facilitate broader implementation of regional lung structure-function evaluation.

Introduction

Hyperpolarized gas magnetic resonance imaging (MRI) first emerged as a novel functional pulmonary imaging modality to evaluate pulmonary ventilation distribution nearly three decades ago1. Since then, research studies using hyperpolarized gas MRI have revealed numerous insights into the nature of lung function in patients with chronic lung diseases such as asthma, chronic obstructive pulmonary disease (COPD), and cystic fibrosis2,3,4,5,6. Both hyperpolarized 3He and 1....

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Protocol

The imaging cases shown here were approved by the University of British Columbia Providence Health Care Research Ethics Board (REB# H21-01237, H21-02149, H22-01264). Participants provided written informed consent prior to completing imaging. The overall pipeline from image acquisition to registration is outlined in Figure 2, and the protocol details here focus on the MR-CT image registration only. Image acquisition and segmentation are dependent on available or preferred imaging hardware, imaging protocols, and image analysis software tools and, therefore, are left to readers' preference. The protocol is designed to be agnostic to tho....

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Results

This study prospectively acquired paired CT and 129Xe MRI in a research setting for regional lung structure-function characterization and image-guided bronchoscopy across a range of lung diseases and conditions. Figure 3 shows registered 129Xe MRI ventilation and CT in coronal and sagittal planes for four representative participants with a range of MRI ventilation patterns (for the same participants of Figure 1). The registered 129

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Discussion

CT and 129Xe MRI provide complementary information to evaluate regional lung structure and function that is best facilitated using image registration. Multi-modal image registration can be non-trivial to implement, and so the protocol provided here is intended to provide the tools for readers to register 129Xe MRI to CT. The provided protocol uses ANTsPy for easier implementation for users with a broad range of image processing experience using Python rather than C++, as in conventional ANTs. Overal.......

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Disclosures

RLE receives personal consulting fees from VIDA Diagnostics Inc. outside the submitted work. JAL has received an institutional grant from GE Healthcare and honoraria for lectures from Philips and GE Healthcare outside the submitted work.

Acknowledgements

This research was supported in part through computational resources and services provided by Advanced Research Computing at the University of British Columbia, and by a University of British Columbia Department of Radiology AI Grant. RLE was supported by a Michael Smith Health Research BC Trainee Award.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
3D SlicerBrigham and Women's Hospital (BWH)https://www.slicer.org/Image analysis/visualization software; open source
ANTsPyNAhttps://github.com/ANTsX/ANTsPyCoding infrastructure; open source
ITK-SNAPNAhttp://www.itksnap.org/pmwiki/pmwiki.phpImage analysis/visualization software; open source
MAGNETOM Vida 3.0T MRISiemens HealthineersNACan be any 1.5 T or 3.0 T scanner with broadband imaging capability
MATLABMathworkshttps://www.mathworks.com/products/matlab.htmlGeneral software, good for image analysis; available by subscription
reg.pyNANARegistration script (Supplementary File 1)
Revolution HD CT scannerGE HealthcareNACan be any CT scanner with ≥64 detectors
VIDA InsightsVIDA Diagnostics Inc.NACT analysis software; can be any to generate masks

References

  1. Albert, M. S., et al. Biological magnetic resonance imaging using laser-polarized 129Xe. Nature. 370 (6486), 199-201 (1994).
  2. Sheikh, K., Coxson, H. O., Parraga, G. This is what COPD looks like. Respirology. 21 (2), 224-236 (2016).
  3. Ebner, L., et al.

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