Regional pulmonary response to a methacholine challenge using hyperpolarized <sup>3</sup>He magnetic resonance imaging
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Spirometry is insensitive to small airway abnormalities in asthma. Our objective was to evaluate regional lung structure and function using hyperpolarized (3)He magnetic resonance imaging (MRI) before, during and after a methacholine challenge (MCh). METHODS: Twenty-five asthmatics (mean age = 34 ± 11 years) and eight healthy volunteers (HV) (mean age = 33 ± 11 years) underwent spirometry, plethysmography and hyperpolarized (3)He MRI prior to a MCh. MRI was repeated following the MCh and again 25 min after salbutamol administration. (3)He MRI gas distribution was quantified using semiautomated segmentation of the ventilation defect percent (VDP). Tissue microstructure was measured using the (3)He apparent diffusion coefficient (ADC). Analysis of variance with repeated measures was used to evaluate changes at each time point as well as to determine interactions between regions of interest (ROI) and subject group. Pearson's correlations were performed to evaluate associations between (3)He MRI measurements and established clinical measures. RESULTS: In asthmatics, but not HV, whole-lung ADC was increased post-MCh (P < 0.01). In asthmatics only, ADC was increased post-MCh in posterior ROI (P < 0.01) and all ROI in the superior-inferior direction (P < 0.01). VDP was increased in posterior and inferior ROI (P < 0.001). There was a correlation between VDP and specific airway resistance (r = 0.74, P < 0.0001), dyspnoea score (r = 0.66, P < 0.01) and fractional exhaled nitric oxide (r = 0.45, P < 0.05). CONCLUSIONS: We evaluated the regional pulmonary response to methacholine and salbutamol using (3)He MRI and showed heterogeneous VDP and ADC consistent with bronchoconstriction and gas trapping, respectively, post-MCh. These regional alterations resolved post-salbutamol.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".