Name: multi-modal pulmonary imaging: using complementary information from ct and hyperpolarized 129xe mri to evaluate lung structure-function
Uploaded: 2024-04-12T13:20:00
Description: Read this Scientific Article Protocol about Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function at JoVE.com

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.

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...

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...

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 &#39;dissolved phase,&#39; 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,&#160;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&#160;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.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3D Slicer</td>
			<td>Brigham and Women&#39;s Hospital (BWH)</td>
			<td>https://www.slicer.org/</td>
			<td>Image analysis/visualization software; open source</td>
		</tr>
		<tr>
			<td>ANTsPy</td>
			<td>NA</td>
			<td>https://github.com/ANTsX/ANTsPy</td>
			<td>Coding infrastructure; open source</td>
		</tr>
		<tr>
			<td>ITK-SNAP</td>
			<td>NA</td>
			<td>http://www.itksnap.org/pmwiki/pmwiki.php</td>
			<td>Image analysis/visualization software; open source</td>
		</tr>
		<tr>
			<td>MAGNETOM Vida 3.0T MRI</td>
			<td>Siemens Healthineers</td>
			<td>NA</td>
			<td>Can be any 1.5 T or 3.0 T scanner with broadband imaging capability</td>
		</tr>
		<tr>
			<td>MATLAB</td>
			<td>Mathworks</td>
			<td>https://www.mathworks.com/products/matlab.html</td>
			<td>General software, good for image analysis; available by subscription</td>
		</tr>
		<tr>
			<td>reg.py</td>
			<td>NA</td>
			<td>NA</td>
			<td>Registration script (Supplementary File 1)</td>
		</tr>
		<tr>
			<td>Revolution HD CT scanner</td>
			<td>GE Healthcare</td>
			<td>NA</td>
			<td>Can be any CT scanner with &#8805;64 detectors</td>
		</tr>
		<tr>
			<td>VIDA Insights</td>
			<td>VIDA Diagnostics Inc.</td>
			<td>NA</td>
			<td>CT analysis software; can be any to generate masks</td>
		</tr>
	</tbody>
</table>

multi-modal pulmonary imaging: using complementary information from ct and hyperpolarized 129xe mri to evaluate lung structure-function

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.

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...

Read this Scientific Article Protocol about Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function at JoVE.com

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

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.

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

Hyperpolarized 129Xe gas MRI is an emerging technique to evaluate and measure regional lung function including pulmonary gas distribution and gas ...

To begin, open images followed by masks in the desired image visualization software to verify that the image and mask orientation match for all CT, Proton, and Xenon files. Then, save the image DICOMS and single label masks as NIfTI files in the same folder as the reg. py file.For CT Xenon MRI registration, open the reg. py file in the desired Python computing environment setup. If using a virtual environment, set the number of central processing units, number of threads, and RAM as desired or as available in the computing environment.Next, set the desired transformation and interpolation, followed by the fixed and moving image. Run reg. py in the Python computing environment.Once the registration is complete, proceed for evaluation. Keeping the ct. nii image as the base image, open ventilation warp.nii.gz as another image and overlay it on the CT image with the desired color map. Review the overlap of the xenon MR image with the CT image in all image planes to evaluate the visual alignment of landmarks such as the carina and lung boundaries. Registration results showed good alignment of all lung boundaries for the healthy participant.In the three participants with chronic obstructive pulmonary disease, there was good alignment of lung boundaries were available ranging from diffuse ventilation abnormalities, upper lobe ventilation abnormalities with absent apical lung boundaries and lower lobe ventilation abnormalities with absent diaphragmatic lung boundaries.

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