Median-anchored Generalized Linear Binning vs Conventional Methods to Quantify 129Xe Lung Ventilation MRI

Motivation: Hyperpolarized (HP) 129Xe MRI is an accepted method to assess lung ventilation, but there is no robust, standardized method to quantify impaired ventilation, and existing analysis methods have not been compared comprehensively. Goal(s): To define impaired ventilation via HP-129Xe ventilation defect percentage (VDP) using median-anchored generalized linear binning (Median) and benchmark performance against established methods. Approach: HP-129Xe VDP was calculated from 10 healthy controls and 18 people with cystic fibrosis using the proposed and 5 established methods, including reader defect-scoring. Results: Median-anchoring improved robustness and agreed better with reader-scoring, indicating the potential to consistently and reliably quantify VDP. Impact: Median-anchored generalized linear binning analysis of HP-129Xe ventilation images enabled improved detection of subtle ventilation impairments in people with cystic fibrosis. This method shows promise for broader applications across obstructive diseases, advancing early diagnosis and disease monitoring.

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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0293
Primary Topic
Atomic and Subatomic Physics Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Median-anchored Generalized Linear Binning vs Conventional Methods to Quantify 129Xe Lung Ventilation MRI

Laura L. Walkup, Zackary I. Cleveland, Abdullah Bdaiwi, Riaz Hussain et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Atomic and Subatomic Physics Research
article

Median-anchored Generalized Linear Binning vs Conventional Methods to Quantify 129Xe Lung Ventilation MRI

Laura L. Walkup, Zackary I. Cleveland, Abdullah Bdaiwi, Riaz Hussain, Matthew M. Willmering, Joseph Plummer
article en

Abstract

Motivation: Hyperpolarized (HP) 129Xe MRI is an accepted method to assess lung ventilation, but there is no robust, standardized method to quantify impaired ventilation, and existing analysis methods have not been compared comprehensively. Goal(s): To define impaired ventilation via HP-129Xe ventilation defect percentage (VDP) using median-anchored generalized linear binning (Median) and benchmark performance against established methods. Approach: HP-129Xe VDP was calculated from 10 healthy controls and 18 people with cystic fibrosis using the proposed and 5 established methods, including reader defect-scoring. Results: Median-anchoring improved robustness and agreed better with reader-scoring, indicating the potential to consistently and reliably quantify VDP. Impact: Median-anchored generalized linear binning analysis of HP-129Xe ventilation images enabled improved detection of subtle ventilation impairments in people with cystic fibrosis. This method shows promise for broader applications across obstructive diseases, advancing early diagnosis and disease monitoring.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 81%
Atomic and Subatomic Physics Research
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Median-anchored Generalized Linear Binning vs Conventional Methods to Quantify 129Xe Lung Ventilation MRI — Laura L. Walkup, Zackary I. Cleveland, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS