Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
April 12th, 2024
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.
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.
Overview
This article presents a protocol for registering 129 Xe MRI with CT images to enhance lung structure-function analysis. The method utilizes open-source platforms for image registration, facilitating regional analysis.
Key Study Components
Area of Science
- Neuroscience
- Medical Imaging
- Radiology
Background
- CT and 129 Xe MRI provide complementary information about lung structure and function.
- Image registration is essential for accurate regional analysis.
- Existing literature on 129 Xe MR techniques informs this protocol.
- Open-source platforms enhance accessibility for researchers.
Purpose of Study
- To develop a robust protocol for CT and 129 Xe MRI image registration.
- To improve the analysis of lung function through enhanced imaging techniques.
- To provide a reproducible method for researchers in the field.
Methods Used
- Open images and masks in image visualization software.
- Verify orientation of CT, Proton, and Xenon files.
- Save images and masks as NIfTI files.
- Utilize a Python computing environment for registration.
Main Results
- The protocol allows for effective registration of CT and 129 Xe MRI images.
- Facilitates detailed regional analysis of lung structure and function.
- Demonstrates the utility of open-source tools in medical imaging.
- Provides a foundation for future research in lung imaging.
Conclusions
- The developed protocol enhances the accuracy of lung imaging analysis.
- Combining CT and 129 Xe MRI offers comprehensive insights into lung function.
- Open-source platforms promote collaboration and innovation in research.
Frequently Asked Questions
Executive Industry Relevance
Integrating hyperpolarized 129Xe MRI with CT imaging enables comprehensive evaluation of lung structure and function, supporting advanced target validation and mechanistic de-risking in respiratory drug discovery. This multi-modal approach enhances predictive confidence at key inflection points in pulmonary R&D pipelines, facilitating risk-adjusted portfolio decisions for novel therapeutics targeting lung disease. The method's quantitative and regional outputs position it as a strategic asset for translational research and preclinical model development.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables interrogation of regional lung structure-function relationships for mechanistic de-risking.
- Supports functional target validation by correlating imaging biomarkers with disease-relevant phenotypes.
- Facilitates predictive confidence in early-stage respiratory asset triage.
Screening & Assay Development
- Prepares validated imaging-based assays for quantitative evaluation of pulmonary interventions.
- Standardizes regional lung function measurements for reproducibility across studies.
- Enables scalable, platform-ready workflows for compound screening in disease-relevant systems.
Translational & Preclinical Research
- Aligns imaging biomarkers with translational endpoints for preclinical model validation.
- Provides continuity from discovery through preclinical assessment of lung-targeted therapies.
- Supports risk-adjusted advancement by quantifying structure-function changes in disease models.
Pipeline & Workflow Integration
This multi-modal imaging protocol bridges early discovery, lead identification, and preclinical validation in respiratory R&D workflows.
- Discovery Biology: Quantitative structure-function mapping informs hypothesis testing and pathway clarification.
- Screening: Imaging-based assays deliver reproducible, regional readouts for compound evaluation.
- Analytics: Registration outputs enable direct comparison of structural and functional lung metrics.
- Translational Research: Imaging endpoints support biomarker alignment and preclinical model continuity.
- Enterprise Reuse: The protocol is adaptable across respiratory models and supports cross-program standardization.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in lung disease research.
- Operational Value: Delivers standardized, reproducible imaging workflows for multi-site studies.
- Strategic Value: Improves go/no-go decisions and capital efficiency by enabling robust target validation.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of respiratory assets.
Implementation Considerations
- Requires expertise in advanced imaging modalities and image registration techniques.
- Demands access to CT and hyperpolarized 129Xe MRI instrumentation and computational infrastructure.
- Necessitates cross-team standardization of imaging protocols and data formats.
- Adaptation may be needed for different lung disease models or imaging platforms.
- Technical challenges in image registration and alignment must be addressed for consistent outputs.
