Oscillometry and pulmonary magnetic resonance imaging in asthma and COPD
Bibliographic record
Abstract
Developed over six decades ago, pulmonary oscillometry has re-emerged as a noninvasive and effort-independent method for evaluating respiratory-system impedance in patients with obstructive lung disease. Here, we evaluated the relationships between hyperpolarized 3He ventilation-defect-percent (VDP) and respiratory-system resistance, reactance and reactance area (AX) measurements in 175 participants including 42 never-smokers without respiratory disease, 56 ex-smokers with chronic-obstructive-pulmonary-disease (COPD), 28 ex-smokers without COPD and 49 asthmatic never-smokers. COPD participants were dichotomized based on x-ray computed-tomography (CT) evidence of emphysema (relative-area CT-density-histogram ≤ 950HU (RA950) ≥ 6.8%). In asthma and COPD subgroups, MRI VDP was significantly related to the frequency-dependence of resistance (R5-19; asthma: ρ = 0.48, P = 0.0005; COPD: ρ = 0.45, P = 0.0004), reactance at 5 Hz (X5: asthma, ρ = −0.41, P = 0.004; COPD: ρ = −0.38, P = 0.004) and AX (asthma: ρ = 0.47, P = 0.0007; COPD: ρ = 0.43, P = 0.0009). MRI VDP was also significantly related to R5-19 in COPD participants without emphysema (ρ = 0.54, P = 0.008), and to X5 in COPD participants with emphysema (ρ = −0.36, P = 0.04). AX was weakly related to VDP in asthma (ρ = 0.47, P = 0.0007) and COPD participants with (ρ = 0.39, P = 0.02) and without (ρ = 0.43, P = 0.04) emphysema. AX is sensitive to obstruction but not specific to the type of obstruction, whereas the different relationships for MRI VDP with R5-19 and X5 may reflect the different airway and parenchymal disease-specific biomechanical abnormalities that lead to ventilation defects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".