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Record W4409474327 · doi:10.1002/nbm.70033

Three‐Dimensional Free‐Breathing Ultrashort Echo Time (UTE) <sup>1</sup>H MRI Regional Ventilation: Comparison With Hyperpolarized <sup>129</sup>Xe MRI and Pulmonary Function Testing in Healthy Volunteers and People With Cystic Fibrosis

2025· article· en· W4409474327 on OpenAlexaff
Fei Tan, Rachel L. Eddy, V. Diamond, Jonathan H. Rayment, Peder E. Z. Larson

Bibliographic record

VenueNMR in Biomedicine · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Institutes of Health
KeywordsNuclear medicineVentilation (architecture)Correlation coefficientMedicineMagnetic resonance imagingNuclear magnetic resonancePulmonary function testingPhysicsRadiologyMathematicsStatistics

Abstract

fetched live from OpenAlex

ABSTRACT MRI can provide localized assessment of lung function for monitoring people with lung disease. Hyperpolarized 129Xe MRI directly images pulmonary gas distribution but requires specialized hardware. Conventional 1H MRI acquisitions can also provide functional maps using free‐breathing approaches. The purpose of this study is to evaluate regional ventilation derived from 3D ultrashort echo‐time (UTE) 1H MRI using Motion‐Compensated Low‐Rank constrained reconstruction (MoCoLoR), by comparing against 129Xe MRI and pulmonary function testing as reference‐standard. The study is retrospective in design. The study included 57 participants (25.4 ± 15.8 years, 35 males and 22 females): 12 healthy volunteers, 20 pediatric, and 25 adult people with cystic fibrosis (CF) scanned between January 2022 and February 2023. Field strength/sequence: 3T; 129Xe: 2D multislice spoiled gradient‐recalled sequence; UTE 1H: variable‐density 3D radial sequence. K‐means‐based 129Xe ventilation defect percent (VDP), forced expiratory volume in 1 s (FEV1), and lung clearance index (LCI) were evaluated against UTE 1H VDP from a modified k‐means method. The correspondence of ventilation defect maps from 129Xe and UTE 1H was also evaluated. Statistical tests included the Pearson correlation coefficient (r) and t tests, with p < 0.05 considered significant. 129Xe and UTE 1H VDP were significantly correlated (r = 0.64, p = ). Bland–Altman analysis showed a bias of −0.05 (p = ) and limits of agreement of (0.07, −0.17). The Dice spatial accuracy of the UTE‐based ventilation defect regions using 129Xe as reference was 0.64 ± 0.05. UTE 1H VDP was significantly correlated with FEV1 (r = −0.54, p = ) and LCI (r = 0.48, p = ) and was significantly different between healthy and CF participants (p = 0.017), although the correlations and differences were stronger for 129Xe VDP. UTE 1H VDP correlated with 129Xe VDP, FEV1, and LCI, and demonstrated high, consistent Dice spatial accuracy against 129Xe VDP. UTE 1H VDP captured variations in lung ventilation and has the advantage that it can be widely implemented on any MR system for evaluation and monitoring of patients with lung disease.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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