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, imaging protocols, and image analysis software tools and, therefore, are left to readers&#39; preference. The protocol is designed to be agnostic to those prior steps using single-label masks of the lungs following image segmentation.
1. Software setup
<ol>
	<li>Download and install ANTsPy (see Table of Materials), the Python wrapper for the Advanced Normalization Tools image processing library47,48,49. Tutorials are available at the link under the &#39;tutorials&#39; tab. ANTsPy is also available for Docker installation if desired. 
	NOTE: ANTsPy requires a Linux-based operating system or environment. For the examples here, ANTsPy was installed and used in a virtual high-performance computing environment on a local workstation. The protocol has tended to work better using a virtual computing environment in the authors&#39; experience.</li>
	<li>Download and install segmentation and/or visualization software of choice. 
	NOTE: For the present study, ITK-SNAP was used for visualization (see Table of Materials).</li>
	<li>Download and save the reg.py script (Supplementary File 1).</li>
</ol>
2. Image pre-processing
<ol>
	<li>Click to open images and masks in the desired image visualization software to verify image and mask orientation matches for all CT, 1H, and 129Xe files. Depending on the segmentation method and/or software used, the orientation of some images or masks may need to be adjusted. As needed, we recommend adjusting 1H and 129Xe images and mask orientation to match that of the native CT image.</li>
	<li>Save the image DICOMs and single-label masks (adjusted as in step 2.1 as needed) as Neuroimaging Informatics Technology Initiative files (NIfTI, *.nii; six files total) using the preferred software tool, in the same folder as reg.py that is accessible to the location where ANTsPy is installed and will be run. Follow the naming conventions as mentioned below.
	<ol>
		<li>1H MRI: Proton.nii; 1H MRI mask: Proton_mask.nii. 
		NOTE: Use the 1H image and mask after registration to 129Xe.</li>
		<li>129Xe MRI: Ventilation.nii; 129Xe MRI mask: Ventilation_mask.nii</li>
		<li>CT: CT.nii; CT mask: CT_mask.nii. 
		NOTE: The file names are hard-coded into the registration script and, therefore, must follow the mentioned format, or be revised in the script to match the desired naming convention. These steps can be completed together using any of the recommended software tools listed in step 1.2. With respect to those software tools, some will write the required header information automatically when saving .nii files, whereas others require additional steps to copy and write the header information.</li>
	</ol>
	</li>
</ol>
3. CT-XeMRI registration
<ol>
	<li>Open the reg.py file in the desired Python computing environment setup in step 1.1. 
	NOTE: Script reg.py is based on the built-in ANTs registration tools; additional documentation is available55.</li>
	<li>If using a virtual environment, set the number of central processing units (CPU), number threads, and RAM as desired or available in the computing environment. A virtual computing environment with 16 CPU, 1 thread per CPU, and 186 GB of available RAM was used for the examples herein.</li>
	<li>Set desired transformation and interpolation. The SyNAggro transformation with linear interpolation for images and generic label interpolation for single-label masks, which are default in the provided reg.py script, were&#160;used here. 
	NOTE: SyNAggro is a symmetric normalization transformation, which includes affine + deformable transformation plus more aggressive registration using fine-scale matching and more deformation (compared with plain SyN). Alternative transformation and interpolation algorithms are listed in the ANTs registration documentation link in step 3.155.</li>
	<li>Set the fixed and the moving image. Here, the&#160;CT (single-label mask) was set as the fixed image, and the&#160;1H MRI (single-label mask) was set as the moving image.</li>
	<li>Run reg.py in the Python computing environment. Full registration may take 5-10 min (using our parameters) or longer, depending on computing resources used or available. When complete, warped files will be automatically saved in the same directory as the original image files with the file names as follows: Proton_warped.nii.gz; Ventilation_warped.nii.gz; Ventilation_label_warped.nii.gz. 
	NOTE: NIfTI *.nii.gz files are just zipped versions of *.nii files and can be unzipped or opened as desired. Script reg.py can be modified as desired, for example, using different transformation or interpolation methods or mapping to or creating file directories.</li>
</ol>
4. Evaluation of registration results
<ol>
	<li>Open the CT.nii image as the base image in the desired visualization software.</li>
	<li>Open Ventilation_warped.nii.gz or Ventilation_label_warped.nii.gz as another image and overlay on the CT image with the desired color map.</li>
	<li>Review the overlap of the 129Xe image or mask with the CT image in all image planes (coronal, axial, sagittal), evaluating the visual alignment of landmarks such as the carina and lung boundaries (where available in the 129Xe image).</li>
	<li>Check the results. If satisfied with the results, registration is complete. 
	NOTE: The registered 129Xe image/mask can be multiplied by the CT mask to remove the trachea and main airways (if not removed prior to MRI segmentation) and remove any signal that falls outside of the CT lung boundaries after registration. Further quantification for regional structure-function measurements can be performed as desired.</li>
	<li>If not satisfied with the results, evaluate and optimize alternative types of transformation and associated parameters as needed.</li>
</ol>

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.

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. Overall, ANTs provide an open-source image registration framework that reduces the need for tuning for different metrics and/or image pairs and supports reproducible research practices49. A set of three successive algorithms are typically used in ANTs to achieve optimal registration: (1) rigid registration using only rotation and translation, (2) affine registration using rotation and translation plus scaling and shearing, and (3) deformable, non-linear registration. At a deeper level, the three steps of the default protocol provided here for CT-MR registration are: (1) Initial similarity (rigid) transformation to capture gross similarities between the CT and MR images, preparing the images for subsequent, more refined transformations. This step uses Mattes mutual information similarity metric49 with 32 histogram bins, regular sampling with 0.2% pixels sampled, gradient descent optimization with step size 0.25, multi-resolution Gaussian pyramid with four levels of down-sampling factors 6 x 4 x 2 x 1 (iterations 2100 1200 1200 10) and corresponding smoothing Gaussian sigmas 3 mm x 2 mm x 1 mm x 0 mm. (2) Affine transformation using the output from the similarity stage as the initial transformation. This step uses Mattes mutual information similarity metric with 16 histogram bins, regular sampling with 0.2% pixels sampled, gradient descent optimization with step size 0.25, multi-resolution Gaussian pyramid with four levels of down-sampling factors 4 x 2 x 2 x 1 (iterations 2100 1200 1200 100) and corresponding smoothing Gaussian sigmas 3 mm x 2 mm x 1 mm x 0 mm. (3) SyNAggro transformation as the final step to further refine the transformation using non-linear, deformable registration. This step uses Mattes mutual information similarity metric with 16 histogram bins, full sampling, gradient descent optimization with step size 0.2, multi-resolution Gaussian pyramid with three levels of down-sampling factors 4 x 2 x 1 (iterations 40 20 0), and corresponding smoothing Gaussian sigmas 2 mm x 1 mm x 0 mm, Gaussian regularization kernel width of 3 voxels for smoothing of the update transform field. These are the default settings for the SyNAggro transformation algorithm.
As previously described and used for image registration between CT and hyperpolarized gas MRI38, a variation of the symmetric normalization (SyN) transformation was used here because it was shown to be a top-performing algorithm in a pulmonary image registration challenge44. The mutual information similarity metric was used because it tends to perform best for multi-modality imaging56. To further overcome the multi-modal image contrast differences, the protocol uses the volume-matched 1H MRI to indirectly register 129Xe MRI to CT as first described by Tahir et al.38, and actually registers the single-label 1H mask to the CT mask instead of the images the resulting transformation is subsequently applied to the 129Xe image and mask. Multi-label masks, for example, lobar or segmental CT masks21,22,23,45, or MRI intensity bins57, may also be used. Registration is performed by mapping 1H MRI to the CT space to maintain CT resolution for quantitation of CT structural features, although the registration direction can be reversed as desired. As input to the registration pipeline, the protocol handles images and single-label masks in NIfTI format, because, in this way, all cross-sectional slices in a 3D image are contained in a single file. We have evaluated this protocol on paired CT-129Xe MRI data from two centers independently (University of British Columbia and University of Kansas Medical Center) with good performance, and therefore anticipate the protocol will apply well in other datasets. Nevertheless, the transformation parameters may be optimized to improve performance in local datasets as needed.
The protocol is intentionally designed to be mostly agnostic to image acquisition and segmentation since these steps are dependent on available or preferred imaging hardware, imaging protocols, and image analysis software tools. The CT protocol should ideally be thin-slice, non-contrast enhanced, with standard-equivalent reconstruction kernel to enable measurement of validated quantitative parenchymal, airway and/or vascular metrics10,11,50. CT may be acquired at full inspiration, which is best validated for quantitative measurements10, or volume-matched to MRI to better facilitate CT-MRI registration and pair structure-function measurements at the same lung inflation volume24,30. Expiratory CT could also be performed and registered to inspiratory CT for quantification of air trapping17,18,34. For segmentation and quantitative analysis, various CT software tools are available commercially58 or open-source59. On the other hand, 129Xe MRI acquisition protocols have been published9, which currently recommend separate breath-hold acquisitions for 129Xe and 1H MRI. Novel protocols have been developed that acquire 129Xe and 1H MRI in the same breath-hold53,54, and therefore, can obviate the 1H-129Xe registration pre-processing step. Moreover, this protocol focuses on 129Xe MR ventilation imaging, but is similarly applicable for 129Xe gas exchange imaging. As an emerging method, 129Xe/1H MRI segmentation and quantification are not yet standardized; many methods have been reported in the literature that could be used here and have been nicely summarized in a recent review60. Regardless of how CT and 1H-129Xe MR images are acquired and their single-label masks obtained, this registration protocol is intended to be broadly applicable.
We acknowledge the limitations of the current protocol, primarily that it is somewhat manual, especially for pre-processing to prepare for registration and for evaluation of registration performance. Automated methods have been proposed previously45, and improvements in the existing protocol towards automation will be important for seamless clinical translation. The current registration is also CPU-based; while CPU processing is likely more widely available and the registration runs within approximately 10 min, implementation with graphics processing units (GPU) and/or deep learning could further shorten the run time and potentially improve registration accuracy. Finally, recommendations or methodology for CT and 1H/129Xe MR image segmentation are not provided. There are a wide range of methods available for both, so this is left to readers&#39; choice; however, there is immense opportunity for a pipeline that encompasses automatic segmentation and registration to further accelerate clinical translation.
This registration protocol may be applied for research or clinical settings where hyperpolarized 129Xe MRI is available. In the research landscape, complementary CT and 129Xe MRI have largely supported the discovery of novel insights into regional lung structure-function, for example, in asthma20,21,22,28,29,30,31,32,COPD24,25,34,35, and IPF37,61. The bridge to clinical translation, though, comes in image-guided pulmonary interventions. Image-guided bronchial thermoplasty using CT and 129Xe MRI in patients with severe asthma afforded fewer bronchoscopic procedures, fewer peri-procedure adverse events, and non-inferior patient-reported outcomes compared to conventional whole-lung therapy62,63. In COPD, quantitative CT structure and 129Xe MRI function may suggest different bronchoscopic lung volume reduction targets based on the greatest lobar burden of CT emphysema and MRI ventilation abnormalities, highlighting the importance of considering structure and function together23. Moreover, functional lung avoidance radiotherapy schemes have been proposed40,64 to spare regions with preserved ventilatory and gas exchange function on MRI from undue radiation exposure. Additional image-guided opportunities in pulmonary interventions include surgical lung cancer resection65, airway stent and valve placement in COPD, and other novel bronchoscopic therapies for COPD or chronic bronchitis such as thermal vapor ablation, cryotherapy or rheoplasty66,67. Figure 4 illustrates lobar CT emphysema and MRI ventilation abnormalities for a patient with COPD that could be considered in treatment planning. The lungs remain one of the human body&#39;s last frontiers for image-guided interventions; together, CT and 129Xe MRI provide complementary information that has improved our understanding of lung structure-function, which can now be implemented for image-guided pulmonary interventions. The CT-129Xe MRI registration protocol provided here can enable further discovery of lung structure-function as well as image-guided interventions towards improved care, treatment, and outcomes for patients with respiratory disease.

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 129Xe MR label mask shows 129Xe signal intensity clusters from ventilation defect or signal void to hyperintense, and was multiplied by the CT label mask to remove the trachea and main airways. Visual inspection shows good alignment of all lung boundaries for the healthy participant (Figure 3A) with homogenous ventilation, with the exception of the costophrenic angle in the right lung. This discrepancy could be due to resolution differences between the two modalities or geometric distortion in the 129Xe/1H MRI; however, it is a small fraction of the overall lung volume. In the three participants with COPD, there was also good alignment of lung boundaries, where available.&#160;The COPD examples herein range from diffuse ventilation abnormalities (Figure 3B), upper lobe ventilation abnormalities with absent apical lung boundaries (Figure 3C), and lower lobe ventilation abnormalities with absent diaphragmatic lung boundaries (Figure 3D).
The authors typically opt for visual inspection of the registered images and do not prospectively quantitatively evaluate registration performance because of the nature of the multi-modal contrast differences between CT and 129Xe MRI. Common quantitative metrics of registration performance are the Dice coefficient or target registration error (TRE). Dice coefficients could be evaluated between the registered 1H (moving) and CT (fixed) images; however, this would be indirect since 1H images are used as an intermediate bridge to register 129Xe images, and the measurements of interest come from 129Xe MRI. TRE may be quantified by placing fiducial landmarks on the fixed and moving images; however placing fiducials is a time-consuming manual process, and the nature of 129Xe MRI ventilation abnormalities means there may be limited anatomical landmarks available. Although the tracheal carina and costophrenic angles typically serve as easy landmarks, the participants in Figure 3C,D highlight severe examples where there are limited obvious landmarks available. Using a similar registration framework in ANTs, Tahir et al. achieved TRE of 8.8 mm to 19.7 mm38, which is small relative to the size of the lungs (typical field-of-view 350-400 mm) and therefore acceptable; the authors anticipate TRE might be similar using the current framework.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66257/66257fig01.jpg" /> 
Figure 1: Pulmonary 129Xe and 1H and CT. Examples of 129Xe and volume-matched anatomical 1H MRI with paired CT for a healthy participant (A) and three participants with chronic obstructive pulmonary disease (COPD; B, C, D) showing a range of 129Xe ventilation patterns. <a href="https://www.jove.com/files/ftp_upload/66257/66257fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66257/66257fig02v2.jpg" /> 
Figure 2: Overall image analysis and registration pipeline. Input CT, 129Xe MR, and 1H MR images are first segmented to generate single-label masks. The 1H MR image/mask is first transformed to the 129Xe image/mask. All CT, 129Xe, and 1H images and masks are converted to NIfTI files, which are then used for 129Xe-CT registration. The 1H mask is transformed to the CT image space, and the transformation is subsequently applied to the 129Xe image/mask. <a href="https://www.jove.com/files/ftp_upload/66257/66257fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/66257/66257fig03.jpg" /> 
Figure 3: 129Xe MRI-CT registration results. Registration results for the four representative participants shown in Figure 1, where 129Xe is shown in cyan overlaid on the CT in greyscale. There was good alignment of all lung boundaries for the healthy participant (A) with homogenous ventilation, with the exception of the costophrenic angle in the right lung. There was also good alignment of lung boundaries in the three participants with COPD, where available, ranging from diffuse ventilation abnormalities (B), upper lobe ventilation abnormalities with absent apical lung boundaries (C), and lower lobe ventilation abnormalities with absent diaphragmatic lung boundaries (D). <a href="https://www.jove.com/files/ftp_upload/66257/66257fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66257/66257fig04v2.jpg" /> 
Figure 4: Lobar structure-function measurements in a participant with COPD. Lobar CT emphysema measured by the low-attenuating areas less than -950 Hounsfield Units (LAA950, yellow) and 129Xe MRI ventilation defect percent (VDP, cyan) generated after 129Xe MR-CT registration, as an example regional evaluation for an image-guided treatment plan. The schematic of lobar outlines is shown in sagittal planes. RUL = right upper lobe; RML = right middle lobe; RLL = right lower lobe; LUL = left upper lobe; LLL = left lower lobe. <a href="https://www.jove.com/files/ftp_upload/66257/66257fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary File 1: The reg.py script. <a href="https://www.jove.com/files/ftp_upload/66257/reg.zip" target="_blank">Please click here to download this File.</a>

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 ...

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472 Views.  St. Paul’s Hospital. 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.

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

Bronchial Thermoplasty:  A Novel Therapeutic Approach to Severe Asthma

Bronchial thermoplasty is a non-drug procedure for severe persistent asthma that delivers thermal energy to the airway wall in a precisely controlled manner to reduce excessive airway smooth muscle. Reducing airway smooth muscle decreases the ability of the airways to constrict, thereby reducing the frequency of asthma attacks. Bronchial thermoplasty is delivered by the Alair System and is performed in three outpatient procedure visits, each scheduled approximately three weeks apart. The first procedure treats the airways of the right lower lobe, the second treats the airways of the left lower lobe and the third and final procedure treats the airways in both upper lobes. After all three procedures are performed the bronchial thermoplasty treatment is complete.
Bronchial thermoplasty is performed during bronchoscopy with the patient under moderate sedation. All accessible airways distal to the mainstem bronchi between 3 and 10 mm in diameter, with the exception of the right middle lobe, are treated under bronchoscopic visualization. Contiguous and non-overlapping activations of the device are used, moving from distal to proximal along the length of the airway, and systematically from airway to airway as described previously. Although conceptually straightforward, the actual execution of bronchial thermoplasty is quite intricate and procedural duration for the treatment of a single lobe is often substantially longer than encountered during routine bronchoscopy. As such, bronchial thermoplasty should be considered a complex interventional bronchoscopy and is intended for the experienced bronchoscopist. Optimal patient management is critical in any such complex and longer duration bronchoscopic procedure. This article discusses the importance of careful patient selection, patient preparation, patient management, procedure duration, postoperative care and follow-up to ensure that bronchial thermoplasty is performed safely.
Bronchial thermoplasty is expected to complement asthma maintenance medications by providing long-lasting asthma control and improving asthma-related quality of life of patients with severe asthma. In addition, bronchial thermoplasty has been demonstrated to reduce severe exacerbations (asthma attacks) emergency rooms visits for respiratory symptoms, and time lost from work, school and other daily activities due to asthma.

Bronchial thermoplasty is a non-drug procedure for severe persistent asthma that delivers thermal energy to the airway wall in a precisely controlled manner to reduce excessive airway smooth muscle. Reducing airway smooth muscle decreases the ability of the airways to constrict, thereby reducing the frequency of asthma attacks.

Bronchial thermoplasty is a non-drug procedure for severe persistent asthma that delivers thermal energy to the airway wall in a precisely controlled ...

Combining Volumetric Capnography And Barometric Plethysmography To Measure The Lung Structure-function Relationship

Tools to measure lung and airways volume are critical for pulmonary researchers interested in evaluating the impact of disease or novel therapies on the lung. Barometric plethysmography is a classic technique to evaluate the lung volume with a long history of clinical use. Volumetric capnography utilizes the profile of exhaled carbon dioxide to determine the volume of the conducting airways, or dead space, and provides an index of airways homogeneity. These techniques may be used independently, or in combination to evaluate the dependence of airways volume and homogeneity on lung volume. This paper provides detailed technical instructions to replicate these techniques and our representative data demonstrates that the airways volume and homogeneity are highly correlated to lung volume. We also provide a macro for the analysis of capnographic data, which can be modified or adapted to fit different experimental designs. The advantage of these measures is that their advantages and limitations are supported by decades of experimental data, and they can be made repeatedly in the same subject without expensive imaging equipment or technically advanced analysis algorithms. These methods may be particularly useful for investigators interested in perturbations that change both the functional residual capacity of the lung and airways volume.

Here, we describe two measures of pulmonary function &#8211; barometric plethysmography, which allows the measurement of lung volume, and volumetric capnography, a tool to measure the anatomic dead space and airways uniformity. These techniques may be used independently or combined to assess airways function at different lung volumes.

Tools to measure lung and airways volume are critical for pulmonary researchers interested in evaluating the impact of disease or novel therapies on the ...

Quantitative Mapping of Specific Ventilation in the Human Lung using Proton Magnetic Resonance Imaging and Oxygen as a Contrast Agent

Specific ventilation imaging (SVI) is a functional magnetic resonance imaging technique capable of quantifying specific ventilation &#8213; the ratio of the fresh gas entering a lung region divided by the region&#8217;s end-expiratory volume &#8213; in the human lung, using only inhaled oxygen as a contrast agent. Regional quantification of specific ventilation has the potential to help identify areas of pathologic lung function. Oxygen in solution in tissue shortens the tissue&#8217;s longitudinal relaxation time (T1), and thus a change in tissue oxygenation can be detected as a change in T1-weighted signal with an inversion recovery acquired image. Following an abrupt change between two concentrations of inspired oxygen, the rate at which lung tissue within a voxel equilibrates to a new steady-state reflects the rate at which resident gas is being replaced by inhaled gas. This rate is determined by specific ventilation. To elicit this sudden change in oxygenation, subjects alternately breathe 20-breath blocks of air (21% oxygen) and 100% oxygen while in the MRI scanner. A stepwise change in inspired oxygen fraction is achieved through use of a custom three-dimensional (3D)-printed flow bypass system with a manual switch during a short end-expiratory breath hold. To detect the corresponding change in T1, a global inversion pulse followed by a single shot fast spin echo sequence was used to acquire two-dimensional T1-weighted images in a 1.5&#160;T MRI scanner, using an eight-element torso coil. Both single slice and multi-slice imaging are possible, with slightly different imaging parameters. Quantification of specific ventilation is achieved by correlating the time-course of signal intensity for each lung voxel with a library of simulated responses to the air/oxygen stimulus. SVI estimations of specific ventilation heterogeneity have been validated against multiple breath washout and proved to accurately determine the heterogeneity of the specific ventilation distribution.

Specific ventilation imaging is a functional magnetic resonance imaging technique that allows for quantification of regional specific ventilation in the human lung, using inhaled oxygen as a contrast agent. Here, we present a protocol to collect and analyze specific ventilation imaging data.

Specific ventilation imaging (SVI) is a functional magnetic resonance imaging technique capable of quantifying specific ventilation &#8213; the ratio of ...

Assessing Lung Function with Hyperpolarized Xenon-129 MRI

Quantitative Measure of Lung Structure and Function Obtained from Hyperpolarized Xenon Spectroscopy

Hyperpolarized Xenon-129 (HXe) magnetic resonance imaging (MRI) provides tools for obtaining 2- or 3-dimensional maps of lung ventilation patterns, gas diffusion, Xenon uptake by lung parenchyma, and other lung function metrics. However, by trading spatial for temporal resolution, it also enables tracing of pulmonary Xenon gas exchange on a ms timescale. This article describes one such technique, chemical shift saturation recovery (CSSR) MR spectroscopy. It illustrates how it can be used to assess capillary blood volume, septal wall thickness, and the surface-to-volume ratio in the alveoli. The flip angle of the applied radiofrequency pulses (RF) was carefully calibrated. Single-dose breath-hold and multi-dose free-breathing protocols were employed for administering the gas to the subject. Once the inhaled Xenon gas reached the alveoli, a series of 90&#176; RF pulses was applied to ensure maximum saturation of the accumulated Xenon magnetization in the lung parenchyma. Following a variable delay time, spectra were acquired to quantify the regrowth of the Xenon signal due to gas exchange between the alveolar gas volume and the tissue compartments of the lung. These spectra were then analyzed by fitting complex pseudo-Voigt functions to the three dominant peaks. Finally, the delay time-dependent peak amplitudes were fitted to a one-dimensional analytical gas-exchange model to extract physiological parameters.

Author Spotlight: Advancing Lung Disease Research with Free-Breathing Hyperpolarized Xenon-129 MRI

The manuscript presents a detailed protocol for using hyperpolarized Xenon-129 chemical shift saturation recovery (CSSR) to trace pulmonary gas exchange, assess the apparent alveolar septal wall thickness, and measure the surface-to-volume ratio. The method has the potential to diagnose and monitor lung diseases.

Hyperpolarized Xenon-129 (HXe) magnetic resonance imaging (MRI) provides tools for obtaining 2- or 3-dimensional maps of lung ventilation patterns, gas ...

A Standardized Workflow for Hyperpolarized 129Xe MRI to Study Pulmonary Function

Acquiring Hyperpolarized 129Xe Magnetic Resonance Images of Lung Ventilation

Hyperpolarized 129Xe MRI comprises a unique array of structural and functional lung imaging techniques. Technique standardization across sites is increasingly important given the recent FDA approval of 129Xe as an MR contrast agent and as interest in 129Xe MRI increases among research and clinical institutions. Members of the 129Xe MRI Clinical Trials Consortium (Xe MRI CTC) have agreed upon best practices for each of the key aspects of the 129Xe MRI workflow, and these recommendations are summarized in a recent publication. This work provides practical information to develop an end-to-end workflow for collecting 129Xe MR images of lung ventilation according to the Xe MRI CTC recommendations. Preparation and administration of 129Xe for MR studies will be discussed and demonstrated, with specific topics including choice of appropriate gas volumes for entire studies and for individual MR scans, preparation&#160;and delivery of individual 129Xe doses, and best practices for monitoring subject safety and 129Xe tolerability during studies. Key MR technical considerations will also be covered, including pulse sequence types and optimized parameters, calibration of 129Xe flip angle and center frequency, and 129Xe MRI ventilation image analysis.

Author Spotlight: Standardization and Best Practices for Advancing Lung Imaging Using 129Xe MRI

Hyperpolarized 129Xe magnetic resonance imaging (MRI) is a method for studying regionally resolved aspects of pulmonary function. This work presents an end-to-end standardized workflow for hyperpolarized 129Xe MRI of lung ventilation, with specific attention to pulse sequence design, 129Xe dose preparation, scan workflow, and best practices for subject safety monitoring.

Hyperpolarized 129Xe MRI comprises a unique array of structural and functional lung imaging techniques. Technique standardization across sites is ...

Advanced Lung Imaging for Disease Detection and Monitoring

Phase-Resolved Functional Lung MRI for Pulmonary Ventilation and Perfusion (V/Q) Assessment

Fourier decomposition is a contrast agent-free 1H MRI method for lung perfusion (Q) and ventilation (V) assessment. After image registration, the time series of each voxel is analyzed with regard to the cardiac and breathing frequency components.
Using a standard 2D spoiled gradient-echo sequence with a temporal resolution of ~300 ms, an image-sorting algorithm was developed to produce phase-resolved functional lung imaging (PREFUL) with an increased temporal resolution. Thus, it is feasible to evaluate regional flow volume loops (FVL) during tidal volume breathing and depict the propagation of the pulse wave during the cardiac cycle. This method can be applied at 1.5T or 3T with standard MR hardware without the necessity for sequence programming, as the described protocol can be implemented with the default SPGRE sequence on most systems.
PREFUL ventilation MRI has been validated using 129Xe and 19F gas imaging with good regional agreement. Perfusion-weighted PREFUL MRI has been validated using SPECT as well as dynamic contrast enhanced (DCE) MRI. PREFUL has been tested in a dual center dual vendor setting and is currently applied in several ongoing multicenter trials. Furthermore, it is feasible across a range of field strengths (0.55T-3T) and different age groups, including newborns.
Quantitative V/Q PREFUL MRI has been used in patients with cystic fibrosis, chronic obstructive pulmonary disease, chronic thromboembolic pulmonary hypertension, and corona virus disease-2019 to quantify disease and monitor treatment change after therapy. Furthermore, PREFUL V/Q imaging has been shown to predict transplant loss due to chronic lung allograft dysfunction in patients after lung transplantation. In summary, PREFUL MRI is a validated technique for quantitative ventilation and pulmonary pulse wave/perfusion imaging for regional pulmonary disease detection, quantification, and treatment monitoring with potential added value to the current clinical routine.

Author Spotlight: Enhancing Diagnostic Strategies and Biomarker Development for Comprehensive Lung Function Analysis

Here, we describe the implementation of phase-resolved functional lung MRI as a contrast-agent-free proton MR technique for the assessment of pulmonary ventilation and perfusion dynamics. Validated and applicable across different field strengths and age groups, it could enhance clinical decision-making in the future by aiding in disease quantification and therapy monitoring.

Fourier decomposition is a contrast agent-free 1H MRI method for lung perfusion (Q) and ventilation (V) assessment. After image registration, the time ...

Protocol for High-Resolution Lung Imaging Using 3T UTE MRI with Self-Gating

Pulmonary Structural MRI using Free-Breathing, Self-Gated Ultra-short Echo Time Imaging 

High quality MRI of the lungs is challenged by low tissue density, fast MRI signal relaxation, and respiratory and cardiac motion. For these reasons, structural imaging of the lungs is performed almost exclusively using Computed Tomography (CT). However, CT imaging delivers ionizing radiation, and thus is less well suited for certain vulnerable populations (e.g., pediatrics) or for research applications. As an alternative, MRI using ultra-short echo times (UTE) is attracting interest. This technique can be performed during free-breathing over the course of a ~5-10 min scan. Respiratory motion information is encoded alongside images; this information can be used to "self-gate" images. Self-gating thus removes the requirement of advanced MRI pulse sequence programming or the use of respiratory bellows, which simplifies image acquisition. In this protocol, simple, robust, and computationally efficient acquisition and reconstruction methods for acquiring high quality UTE MRI of the lungs are presented. This protocol was developed for use on a 3T MRI scanner, but the same principles can be implemented at lower magnetic field strength. The protocol includes recommended parameter settings for 3D radial UTE image acquisition as well as directions for self-gated image reconstruction to generate images at distinct respiratory phases. Through the implementation of this protocol, users can generate high-resolution UTE images of the lungs with minimal to minimal-to-no motion artifacts. These images can be used to evaluate pulmonary structure, which can be implemented for research use in a variety of pulmonary conditions.

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

A protocol is described for generating high-resolution structural images of the lungs using ultra-short-echo time (UTE) Magnetic Resonance Imaging (MRI). This protocol allows for images to be acquired using a simple MRI pulse sequence during free-breathing.

High quality MRI of the lungs is challenged by low tissue density, fast MRI signal relaxation, and respiratory and cardiac motion. For these reasons, ...

Fractal-Based CT Analysis for Lung Cancer Diagnosis and Staging

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Non-invasive assessment of pulmonary nodule malignancy remains a critical challenge in lung cancer diagnosis. Traditional methods often lack precision in differentiating benign from malignant nodules, particularly in the early stages. This study introduces an approach using multifractal spectrum analysis to quantitatively evaluate pulmonary nodule characteristics.
A fractal-based protocol was developed to process computed tomography (CT)-digital imaging and communications in medicine (DICOM) data, enabling three-dimensional (3D) visualization and analysis of pulmonary nodule's multifractal spectrum. The method involves 3D volume reconstruction, precise ROI delineation, and calculation of fractal dimensions across multiple scales. Multifractal spectra were computed for both early-stage and late-stage lung adenocarcinoma nodules, with comparative analysis performed using data tip tool quantification.
Analysis revealed that the fractal dimension of a pulmonary nodule's 3D digital matrix varies continuously with different voxel scales, forming a distinctive multifractal spectrum. Significant differences were observed between early-stage and late-stage nodules. Late-stage nodules demonstrated a wider scale range (longer X-axis) and higher extreme points in their multifractal spectra. These distinctions were quantitatively confirmed, indicating the method's potential for precise staging.
The multifractal spectrum analysis provides a highly significant and precise quantitative method for staging pulmonary nodules, effectively differentiating between benign and malignant cases. This non-invasive technique shows promise for improving early diagnosis and accurate staging of lung cancer, potentially enhancing clinical decision-making in pulmonary oncology.

This study introduces multifractal spectrum analysis for assessing pulmonary nodule malignancy. Using CT-DICOM data, the method calculates fractal dimensions across multiple voxel scales, revealing significant differences between early-stage and late-stage pulmonary nodules.

Non-invasive assessment of pulmonary nodule malignancy remains a critical challenge in lung cancer diagnosis. Traditional methods often lack precision in ...