129 Xe Image Processing Pipeline: An open-source, graphical user interface application for the analysis of hyperpolarized 129 Xe MRI

• Published in: Magnetic resonance in medicine
• Main Authors: Bdaiwi, Abdullah S, Willmering, Matthew M, Plummer, Joseph W, Hussain, Riaz, Roach, David J, Parra-Robles, Juan, Niedbalski, Peter J, Woods, Jason C, Walkup, Laura L, Cleveland, Zackary I
• Format: Journal Article
• Language: English
• Published: United States 31.10.2024
• Subjects: diffusion analysis; gas exchange analysis; hyperpolarized 129Xe; ventilation analysis
• DOI: 10.1002/mrm.30347
• ISSN: 0740-3194

Hyperpolarized Xe MRI presents opportunities to assess regional pulmonary microstructure and function. Ongoing advancements in hardware, sequences, and image processing have helped it become increasingly adopted for both research and clinical use. As the number of applications and users increase, standardization becomes crucial. To that end, this study developed an executable, open-source Xe image processing pipeline (XIPline) to provide a user-friendly, graphical user interface-based analysis pipeline to analyze and visualize Xe MR data, including scanner calibration, ventilation, diffusion-weighted, and gas exchange images. The customizable XIPline is designed in MATLAB to analyze data from all three major scanner platforms. Calibration data is processed to calculate optimal flip angle and determine Xe frequency offset. Data processing includes loading, reconstructing, registering, segmenting, and post-processing images. Ventilation analysis incorporates three common algorithms to calculate ventilation defect percentage and novel techniques to assess defect distribution and ventilation texture. Diffusion analysis features ADC mapping, modified linear binning to account for ADC age-dependence, and common diffusion morphometry methods. Gas exchange processing uses a generalized linear binning for data acquired using 1-point Dixon imaging. The XIPline workflow is demonstrated using analysis from representative calibration, ventilation, diffusion, and gas exchange data. The application will reduce redundant effort when implementing new techniques across research sites by providing an open-source framework for developers. In its current form, it offers a robust and adaptable platform for Xe MRI analysis to ensure methodological consistency, transparency, and support for collaborative research across multiple sites and MRI manufacturers.