Establishing a Standardized Healthy Reference Distribution for Multi-Site 129Xe Gas Exchange MRI Across Major Scanner Platforms

Motivation: Quantitative 129Xe gas exchange MRI, conducted across different imaging centers and scanner platforms, requires consistent healthy reference distributions. Goal(s): To establish standardized reference values from an 18-30yr old multicenter healthy cohort for 129Xe gas exchange MRI. Approach: Participants from three research centers underwent pulmonary function tests and a standardized 129Xe MRI/MRS protocol. Data were processed centrally and corrected for T2*. Results: A balanced multicenter dataset revealed minimal variability between combined and site-specific reference distributions, validating the combined values for cross-center use. The distribution for 208-ppm excitation could be reliably transformed for 218-ppm excitation. Impact: This study provides robust cross-platform reference distributions for 129Xe gas exchange MRI, facilitating comparison of quantitative imaging in multi-center respiratory research.

Authors

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
2024-11-26
DOI
https://doi.org/10.58530/2024/3196
Citations
1
Primary Topic
Medical Imaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Establishing a Standardized Healthy Reference Distribution for Multi-Site 129Xe Gas Exchange MRI Across Major Scanner Platforms

Juan Parra‐Robles, Junlan Lu, Andrew D. Hahn, Sean B. Fain et al.
1 citations
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
Medical Imaging Techniques and Applications
0.40
article

Establishing a Standardized Healthy Reference Distribution for Multi-Site 129Xe Gas Exchange MRI Across Major Scanner Platforms

Juan Parra‐Robles, Junlan Lu, Andrew D. Hahn, Sean B. Fain, Zackary I. Cleveland, David Mummy, Aryil Bechtel, Suphachart Leewiwatwong, Bastiaan Driehuys, Matthew M. Willmering, Shuo Zhang
article en
1 citations

Abstract

Motivation: Quantitative 129Xe gas exchange MRI, conducted across different imaging centers and scanner platforms, requires consistent healthy reference distributions. Goal(s): To establish standardized reference values from an 18-30yr old multicenter healthy cohort for 129Xe gas exchange MRI. Approach: Participants from three research centers underwent pulmonary function tests and a standardized 129Xe MRI/MRS protocol. Data were processed centrally and corrected for T2*. Results: A balanced multicenter dataset revealed minimal variability between combined and site-specific reference distributions, validating the combined values for cross-center use. The distribution for 208-ppm excitation could be reliably transformed for 218-ppm excitation. Impact: This study provides robust cross-platform reference distributions for 129Xe gas exchange MRI, facilitating comparison of quantitative imaging in multi-center respiratory research.

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 32%
Medical Imaging Techniques and Applications
0.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.