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

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

Published: April 12, 2024

doi:

Rachel L Eddy², George H Xu, Jonathon A Leipsic⁴, Janice M Leung², Don D Sin², Chase S Hall, Roger C Tam⁴

¹UBC Centre for Heart Lung Innovation,St. Paul’s Hospital, ²Division of Respiratory Medicine, Department of Medicine,University of British Columbia, ³School of Biomedical Engineering,University of British Columbia, ⁴Department of Radiology,University of British Columbia, ⁵Division of Pulmonary and Critical Care Medicine,University of Kansas Medical Center

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 ¹²⁹Xe gas have been used historically; however, ¹²⁹Xe is now the primary inhaled agent because of the limited availability of ³He gas. ¹²⁹Xe also freely diffuses across the alveolar membrane and is absorbed by red blood cells in the pulmonary capillaries; in this so-called 'dissolved phase,' ¹²⁹Xe resonates at unique frequencies that allow for measurement of regional gas exchange in a single breath-hold scan⁴^,⁷^,⁸. For quantification, volume-matched anatomical ¹H MR images are typically contemporaneously acquired for co-registration with ¹²⁹Xe to delineate boundaries of the thoracic cavity. Conventional ¹H MRI, though, does not provide further lung structural information. The impetus for clinical translation of hyperpolarized ¹²⁹Xe MRI grew in recent years with UK NHS approval in 2015 and US FDA approval in late 2022⁵^,⁹, yet advanced structural characterization is still mostly missing from the pulmonary MRI arsenal.

Chest computed tomography (CT) remains the mainstay of clinical imaging assessment of the lungs, providing three-dimensional high-resolution images of lung structure using conventional imaging protocols. Quantitative approaches have enabled rapid and repeatable measurement of parenchymal integrity, such as emphysema and interstitial lung abnormalities, large airway morphology and pulmonary vasculature, and regional anatomic characterization by identification and segmentation of lung lobes¹⁰^,¹¹. In the research space, quantitative CT has been widely used to better understand structural alterations and their relationships with patient outcomes in asthma and COPD in large observational studies such as the Severe Asthma Research Program (SARP)¹², Genetic Epidemiology of COPD (COPDGene)¹³, Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS)¹⁴, Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE)¹⁵, and Canadian Cohort of Obstructive Lung Disease (CanCOLD)¹⁶. Alternative CT methods such as expiratory imaging¹⁷^,¹⁸ or computational models¹⁹ may derive functional information, but these methods are indirect, and conventional CT does not otherwise provide much for functional characterization of the lungs.

Taken together, CT and ¹²⁹Xe MRI provide complementary lung structure-function information that can be exploited for regional analysis using image registration. Lung lobes identified on CT have allowed for lobar characterization of MRI ventilation patterns in asthma²⁰^,²¹^,²², COPD²³^,²⁴, bronchiectasis²⁵, and lung cancer²⁶^,²⁷. MRI ventilation abnormalities in asthma have also been directly spatially matched to abnormally remodeled large airways²⁸^,²⁹^,³⁰^,³¹ and air trapping indicative of small airways dysfunction²⁰^,³² measured on CT, and to probe regional treatment responses following whole-lung bronchial thermoplasty³³. In COPD, MRI ventilation abnormalities have been linked to small airway dysfunction in milder diseases and emphysema in more severe diseases³⁴^,³⁵^,³⁶. Beyond ventilation imaging in obstructive lung disease, heterogeneous spatial relationships between CT interstitial lung abnormalities and ¹²⁹Xe MRI gas exchange patterns have also been demonstrated in idiopathic pulmonary fibrosis³⁷. Such studies have provided a deeper understanding of regional lung structure-function in a range of lung diseases that can be used to inform future image-guided interventions.

Direct registration of anatomic CT and functional hyperpolarized gas MRI is challenging, however, due to fundamentally different imaging contrast between the two methods, the absence of hyperpolarized gas signal in regions of ventilation abnormalities, and potentially different lung volumes. Figure 1 shows four examples of ¹²⁹Xe and paired anatomical ¹H MRI and CT in a healthy volunteer (Figure 1A) and three participants with chronic obstructive pulmonary disease (COPD; Figure 1B–D), highlighting heterogeneous ¹²⁹Xe ventilation patterns and varying missing lung boundaries in the COPD cases. The key to overcoming these challenges has been using the anatomical ¹H MRI acquired contemporaneously with hyperpolarized gas MRI as an intermediate step to register hyperpolarized gas MRI to CT indirectly³⁴^,³⁸. Early work employed side-by-side visual comparison and manual segmentation of CT structures, such as lung lobes, onto MRI space²⁰. Advancements in computational resources and open-source image processing tools have enabled three-dimensional registration of CT and hyperpolarized gas MRI, for example, using modality independent neighborhood descriptor (MIND)²³^,³⁰^,³⁴^,³⁹^,⁴⁰^,⁴¹ or Advanced Normalization Toolkit (ANTs) registration²¹^,²²^,²⁷^,³¹^,³²^,³⁷^,³⁸^,⁴²^,⁴³, both of which were top performers in a pulmonary image registration challenge⁴⁴. One novel method coupled the two registrations rather than treating them independently⁴⁵, which has been implemented in a full pulmonary image analysis pipeline designed for phenotyping lung disease⁴⁶. Overall, hyperpolarized gas MRI to CT registration accuracy was improved using the intermediate ¹H step³⁸ and using deformable approaches over affine-only approaches³⁸^,⁴⁵.

The goal here is to build from the existing literature and provide a protocol for ¹²⁹Xe MR to CT image registration using open-source platforms⁴⁷^,⁴⁸^,⁴⁹. The protocol is implemented using ANTsPy, and, in line with previous work³⁸, registers a single-label lung mask from ¹H MRI to the single-label lung mask from CT; the resulting transformation is subsequently applied to the ¹²⁹Xe image to map it to the CT image space. The protocol outlined is intended to be appropriate for research or clinical settings, where applicable, and hyperpolarized ¹²⁹Xe MRI is available.

For context, image acquisition and analysis for the examples provided herein were performed as follows. Chest CT was acquired at full inspiration (total lung capacity, TLC) according to an established low-dose research protocol⁵⁰ with parameters: 64 x 0.625 collimation, 120 peak kilovoltage, tube current 100 mA, 0.5 s revolution time, spiral pitch 1.0, 1.25 mm slice thickness, 0.80 mm slice spacing, standard reconstruction kernel, display field-of-view limited to the most lateral extents of the lungs (to maximize spatial resolution). CT segmentation and analysis were performed using commercial software (see Table of Materials).

¹²⁹Xe and volume-matched ¹H MRI were performed according to published guidelines⁹. For full MRI acquisition details and protocol, readers are directed to another article in this collection⁵¹. MRI segmentation and registration were performed using a semi-automated custom pipeline using k-means clustering for ¹²⁹Xe segmentation, seeded-region growing for ¹H segmentation, and landmark-based affine registration to map the ¹H image to the ¹²⁹Xe image⁵². Affine registration is typically sufficient for ¹H-¹²⁹Xe MR registration to account for most lung inflation or patient position differences between acquisitions; deformable registration is typically not necessary. The ¹H-¹²⁹Xe registration step can be eliminated with simultaneously acquired ¹²⁹Xe and ¹H MRI in the same breath-hold⁵³^,⁵⁴.

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, im…

Representative 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</su…

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…

Divulgaciones

The authors have nothing to disclose.

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.

Materials

3D Slicer	Brigham and Women's Hospital (BWH)	https://www.slicer.org/	Image analysis/visualization software; open source
ANTsPy	NA	https://github.com/ANTsX/ANTsPy	Coding infrastructure; open source
ITK-SNAP	NA	http://www.itksnap.org/pmwiki/pmwiki.php	Image analysis/visualization software; open source
MAGNETOM Vida 3.0T MRI	Siemens Healthineers	NA	Can be any 1.5 T or 3.0 T scanner with broadband imaging capability
MATLAB	Mathworks	https://www.mathworks.com/products/matlab.html	General software, good for image analysis; available by subscription
reg.py	NA	NA	Registration script (Supplementary File 1)
Revolution HD CT scanner	GE Healthcare	NA	Can be any CT scanner with ≥64 detectors
VIDA Insights	VIDA Diagnostics Inc.	NA	CT analysis software; can be any to generate masks

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