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Multi-site Analysis of Functional Gas Exchange Measures on 129Xe MRI Among Healthy Volunteers

2025· article· en· W4410277295 on OpenAlexaff
Andrew McHorse, H. Qin, Peter Niedbalski, Adam Schmidt, Jackie Liggins, Joseph Leung, Don D. Sin, Rachel L. Eddy, Aparna Swaminathan, Bastiaan Driehuys, David Mummy

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineIsotopes of xenonNuclear medicineNuclear magnetic resonanceNuclear physicsXenonPhysics

Abstract

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Abstract RATIONALE: Hyperpolarized 129Xe gas exchange MRI has shown promise as a diagnostic and prognostic tool for diverse cardiopulmonary conditions, including asthma, COPD, and interstitial lung diseases. The increasing clinical use of 129Xe MRI requires a thorough characterization of the normal variation in gas exchange metrics observed in healthy individuals to differentiate expected variation from true disease processes. This study expands upon earlier models to evaluate associations between patient demographics and 129Xe gas exchange metrics in a large cohort of healthy volunteers aged 19 to 87 across three institutions. METHODS: Participants (N=134, 71F/63M, age 54±16 yrs) with no history of pulmonary disease, less than 5 pack-years smoking history, and no smoking history within the last 5 years underwent hyperpolarized 129Xe MRI. For each participant, 3D isotropic images of gas phase (airspaces) and dissolved phase (interstitial membrane tissue uptake and red blood cell transfer [RBC]) were acquired using the 1-point Dixon method at 3 Tesla during a single breath-hold. The imaging-derived metrics, membrane-to-gas ratio (M:Gas) and RBC-to-gas ratio (RBC:Gas), as well as the spectroscopy-based measure, RBC-to-membrane ratio (RBC:M), were analyzed using a multivariate linear regression model with age, sex, and BMI as covariates. Participants were included from three sites: University of Kansas Medical Center (N=27), University of British Columbia (N=58), and Duke University (N=49). Variability between the three participating institutions was assessed using ANOVA and the Tukey range test. RESULTS: Example 129Xe MRI images across a range of ages are shown in Figure 1. Multivariate regression analysis revealed that BMI and male sex were positively correlated in the M:Gas model (p=0.0001 and p=0.03 respectively). RBC:Gas signal increased in males (p=0.0002) and decreased with age (p<0.0001). Age and sex were both significant covariates in the RBC:M model (p<0.0001 and p<0.0001). Each additional 10 years of age was associated with a decrease of 0.04, and males were associated with a 0.12 higher RBC:M than females. CONCLUSION: This large cohort study demonstrates that 129Xe MRI gas exchange metrics vary as a function of patient age, sex, and BMI in healthy individuals, with sex and age playing a larger role in RBC signal whereas BMI plays the greatest role in membrane signal. The consistency of these findings across three institutions validates previous single-site models and establishes the robustness of these demographic associations. Appropriate correction factors may need to be developed to enable meaningful inter-subject comparisons and better delineate the range of expected healthy values.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.366
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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