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PurposeThree‐dimensional hyperpolarized 129Xe gas exchange imaging suffers from low SNR and long breath‐holds, which could be improved using compressed sensing (CS). The purpose of this work was to assess whether gas exchange ratio maps are quantitatively preserved in CS‐accelerated dissolved‐phase 129Xe imaging and to investigate the feasibility of CS‐dissolved 129Xe imaging with reduced‐cost natural abundance (NA) xenon.Methods129Xe gas exchange imaging was performed at 1.5 T with a multi‐echo spectroscopic imaging sequence. A CS reconstruction with an acceleration factor of 2 was compared retrospectively with conventional gridding reconstruction in a cohort of 16 healthy volunteers, 5 chronic obstructive pulmonary disease patients, and 23 patients who were hospitalized following COVID‐19 infection. Metrics of comparison included normalized mean absolute error, mean gas exchange ratio, and red blood cell (RBC) image SNR. Dissolved 129Xe CS imaging with NA xenon was assessed in 4 healthy volunteers.ResultsCS reconstruction enabled acquisition time to be halved, and it reduced background noise. Median RBC SNR increased from 6 (2–18) to 11 (2–100) with CS, and there was strong agreement between CS and gridding mean ratio map values (R2 = 0.99). Image fidelity was maintained for gridding RBC SNR > 5, but below this, normalized mean absolute error increased nonlinearly with decreasing SNR. CS increased the mean SNR of NA 129Xe images 3‐fold.ConclusionCS reconstruction of dissolved 129Xe imaging improved image quality with decreased scan time, while preserving key gas exchange metrics. This will benefit patients with breathlessness and/or low gas transfer and shows promise for NA‐dissolved 129Xe imaging.
PurposeThree‐dimensional hyperpolarized 129Xe gas exchange imaging suffers from low SNR and long breath‐holds, which could be improved using compressed sensing (CS). The purpose of this work was to assess whether gas exchange ratio maps are quantitatively preserved in CS‐accelerated dissolved‐phase 129Xe imaging and to investigate the feasibility of CS‐dissolved 129Xe imaging with reduced‐cost natural abundance (NA) xenon.Methods129Xe gas exchange imaging was performed at 1.5 T with a multi‐echo spectroscopic imaging sequence. A CS reconstruction with an acceleration factor of 2 was compared retrospectively with conventional gridding reconstruction in a cohort of 16 healthy volunteers, 5 chronic obstructive pulmonary disease patients, and 23 patients who were hospitalized following COVID‐19 infection. Metrics of comparison included normalized mean absolute error, mean gas exchange ratio, and red blood cell (RBC) image SNR. Dissolved 129Xe CS imaging with NA xenon was assessed in 4 healthy volunteers.ResultsCS reconstruction enabled acquisition time to be halved, and it reduced background noise. Median RBC SNR increased from 6 (2–18) to 11 (2–100) with CS, and there was strong agreement between CS and gridding mean ratio map values (R2 = 0.99). Image fidelity was maintained for gridding RBC SNR > 5, but below this, normalized mean absolute error increased nonlinearly with decreasing SNR. CS increased the mean SNR of NA 129Xe images 3‐fold.ConclusionCS reconstruction of dissolved 129Xe imaging improved image quality with decreased scan time, while preserving key gas exchange metrics. This will benefit patients with breathlessness and/or low gas transfer and shows promise for NA‐dissolved 129Xe imaging.
PurposeHyperpolarized 129Xe 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 129Xe image processing pipeline (XIPline) to provide a user‐friendly, graphical user interface‐based analysis pipeline to analyze and visualize 129Xe MR data, including scanner calibration, ventilation, diffusion‐weighted, and gas exchange images.MethodsThe 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 determine129Xe 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.ResultsThe XIPline workflow is demonstrated using analysis from representative calibration, ventilation, diffusion, and gas exchange data.ConclusionThe 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 129Xe MRI analysis to ensure methodological consistency, transparency, and support for collaborative research across multiple sites and MRI manufacturers.
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