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Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model

Dynamic inhaled gas ((3)He/(129)Xe/(19)F) MRI permits the acquisition of regional fractional-ventilation which is useful for detecting gas-trapping in lung-diseases such as lung fibrosis and COPD. Deninger’s approach used for analyzing the wash-out data can be substituted with the stretched-exponent...

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Autores principales: Sembhi, Ramanpreet, Ranota, Tuneesh, Fox, Matthew, Couch, Marcus, Li, Tao, Ball, Iain, Ouriadov, Alexei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914115/
https://www.ncbi.nlm.nih.gov/pubmed/36766611
http://dx.doi.org/10.3390/diagnostics13030506
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author Sembhi, Ramanpreet
Ranota, Tuneesh
Fox, Matthew
Couch, Marcus
Li, Tao
Ball, Iain
Ouriadov, Alexei
author_facet Sembhi, Ramanpreet
Ranota, Tuneesh
Fox, Matthew
Couch, Marcus
Li, Tao
Ball, Iain
Ouriadov, Alexei
author_sort Sembhi, Ramanpreet
collection PubMed
description Dynamic inhaled gas ((3)He/(129)Xe/(19)F) MRI permits the acquisition of regional fractional-ventilation which is useful for detecting gas-trapping in lung-diseases such as lung fibrosis and COPD. Deninger’s approach used for analyzing the wash-out data can be substituted with the stretched-exponential-model (SEM) because signal-intensity is attenuated as a function of wash-out-breath in (19)F lung imaging. Thirteen normal-rats were studied using (3)He/(129)Xe and (19)F MRI and the ventilation measurements were performed using two 3T clinical-scanners. Two Cartesian-sampling-schemes (Fast-Gradient-Recalled-Echo/X-Centric) were used to test the proposed method. The fully sampled dynamic wash-out images were retrospectively under-sampled (acceleration-factors (AF) of 10/14) using a varying-sampling-pattern in the wash-out direction. Mean fractional-ventilation maps using Deninger’s and SEM-based approaches were generated. The mean fractional-ventilation-values generated for the fully sampled k-space case using the Deninger method were not significantly different from other fractional-ventilation-values generated for the non-accelerated/accelerated data using both Deninger and SEM methods (p > 0.05 for all cases/gases). We demonstrated the feasibility of the SEM-based approach using retrospective under-sampling, mimicking AF = 10/14 in a small-animal-cohort from the previously reported dynamic-lung studies. A pixel-by-pixel comparison of the Deninger-derived and SEM-derived fractional-ventilation-estimates obtained for AF = 10/14 (≤16% difference) has confirmed that even at AF = 14, the accuracy of the estimates is high enough to consider this method for prospective measurements.
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spelling pubmed-99141152023-02-11 Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model Sembhi, Ramanpreet Ranota, Tuneesh Fox, Matthew Couch, Marcus Li, Tao Ball, Iain Ouriadov, Alexei Diagnostics (Basel) Article Dynamic inhaled gas ((3)He/(129)Xe/(19)F) MRI permits the acquisition of regional fractional-ventilation which is useful for detecting gas-trapping in lung-diseases such as lung fibrosis and COPD. Deninger’s approach used for analyzing the wash-out data can be substituted with the stretched-exponential-model (SEM) because signal-intensity is attenuated as a function of wash-out-breath in (19)F lung imaging. Thirteen normal-rats were studied using (3)He/(129)Xe and (19)F MRI and the ventilation measurements were performed using two 3T clinical-scanners. Two Cartesian-sampling-schemes (Fast-Gradient-Recalled-Echo/X-Centric) were used to test the proposed method. The fully sampled dynamic wash-out images were retrospectively under-sampled (acceleration-factors (AF) of 10/14) using a varying-sampling-pattern in the wash-out direction. Mean fractional-ventilation maps using Deninger’s and SEM-based approaches were generated. The mean fractional-ventilation-values generated for the fully sampled k-space case using the Deninger method were not significantly different from other fractional-ventilation-values generated for the non-accelerated/accelerated data using both Deninger and SEM methods (p > 0.05 for all cases/gases). We demonstrated the feasibility of the SEM-based approach using retrospective under-sampling, mimicking AF = 10/14 in a small-animal-cohort from the previously reported dynamic-lung studies. A pixel-by-pixel comparison of the Deninger-derived and SEM-derived fractional-ventilation-estimates obtained for AF = 10/14 (≤16% difference) has confirmed that even at AF = 14, the accuracy of the estimates is high enough to consider this method for prospective measurements. MDPI 2023-01-30 /pmc/articles/PMC9914115/ /pubmed/36766611 http://dx.doi.org/10.3390/diagnostics13030506 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sembhi, Ramanpreet
Ranota, Tuneesh
Fox, Matthew
Couch, Marcus
Li, Tao
Ball, Iain
Ouriadov, Alexei
Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model
title Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model
title_full Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model
title_fullStr Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model
title_full_unstemmed Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model
title_short Feasibility of Dynamic Inhaled Gas MRI-Based Measurements Using Acceleration Combined with the Stretched Exponential Model
title_sort feasibility of dynamic inhaled gas mri-based measurements using acceleration combined with the stretched exponential model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914115/
https://www.ncbi.nlm.nih.gov/pubmed/36766611
http://dx.doi.org/10.3390/diagnostics13030506
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