Hyperpolarized <sup>3</sup>He magnetic resonance imaging-derived pulmonary pressure-volume curves
Bibliographic record
Abstract
We aimed to evaluate the potential for the use of hyperpolarized helium-3 magnetic resonance imaging (MRI) apparent diffusion coefficient (ADC) surrogates of alveolar size, together with literature-based morphological parameters in a theoretical model of lung mechanics to simulate noninvasive transpulmonary pressure-volume curves. Fourteen ex-smokers with chronic obstructive pulmonary disease (COPD) (n = 8 stage II, n = 6 stage III/IV COPD) and five age-matched never-smokers, provided written, informed consent and were evaluated at baseline and 26 + or - 2 mo later (n = 15 subjects) using plethysmography, spirometry, and (3)He MRI at 3.0 T. Total lung capacity, residual volume, and literature-based morphological parameters were used with alveolar volumes derived from (3)He ADC to simulate noninvasive pressure-volume curves. The resultant anterior-posterior transpulmonary pressure gradient was significantly decreased for stage II COPD (P < 0.01) and stage III COPD subjects (P < 0.001) compared with healthy volunteers. Both COPD subgroups showed increased alveolar radius compared with healthy subjects (P < 0.01, stage II COPD; P < 0.001, stage III COPD). In addition, surface area and surface tension were significantly increased in stage III COPD compared with healthy volunteers (P < 0.01). These results suggest that (3)He MRI provides a potential noninvasive approach to evaluate lung mechanics regionally and further supports the use of ADC values as a regional noninvasive probe of pulmonary microstructure and compliance.
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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 | 0.001 | 0.002 |
| 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".