129Xe MRI Ventilation Defects in Asthma: What is the Upper Limit of Normal and Minimal Clinically Important Difference?
Bibliographic record
Abstract
The minimal clinically important difference (MCID) and upper limit of normal (ULN) for MRI ventilation defect percent (VDP) were previously reported for hyperpolarized 3He gas MRI. Hyperpolarized 129Xe VDP is more sensitive to airway dysfunction than 3He, therefore the objective of this study was to determine the ULN and MCID for 129Xe MRI VDP in healthy and asthma participants. We retrospectively evaluated healthy and asthma participants who underwent spirometry and 129XeMRI on a single visit; participants with asthma completed the asthma control questionnaire (ACQ-7). The MCID was estimated using distribution- (smallest detectable difference [SDD]) and anchor-based (ACQ-7) methods. Two observers measured VDP (semiautomated k-means-cluster segmentation algorithm) in 10 participants with asthma, five-times each in random order, to determine SDD. The ULN was estimated based on the 95% confidence interval of the relationships between VDP and age. Mean VDP was 1.6 ± 1.2% for healthy (n = 27) and 13.7 ± 12.9% for asthma participants (n = 55). ACQ-7 and VDP were correlated (r = .37, p = .006; VDP = 3.5·ACQ + 4.9). The anchor-based MCID was 1.75% while the mean SDD and distribution-based MCID was 2.25%. VDP was correlated with age for healthy participants (p = .56, p =.003; VDP = .04·Age-.01). The ULN for all healthy participants was 2.0%. By age tertiles, the ULN was 1.3% ages 18–39 years, 2.5% for 40–59 years and 3.8% for 60–79 years. The 129Xe MRI VDP MCID was estimated in participants with asthma; the ULN was estimated in healthy participants across a range of ages, both of which provide a way to interpret VDP measurements in clinical investigations.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".