Ventilation defect percentage from PREFUL MRI in pediatric primary ciliary dyskinesia
Bibliographic record
Abstract
Background: Primary ciliary dyskinesia (PCD) is a genetic disease with significant lung morbidity. We previously showed that ventilation defect percentage (VDP; the ratio of non-ventilating lung to thoracic volume) from hyperpolarized 129-Xe MRI (Xe-MRI) is a sensitive and repeatable lung function measure in PCD. Contrast-free, free-breathing imaging techniques like phase resolved functional lung MRI (PREFUL) have not been investigated in PCD, and offer the advantage of increased clinical translatability, especially in pediatrics. Objective: Determine the feasibility, validity, and repeatability of PREFUL VDP in pediatric PCD. Methods: Participants were recruited from SickKids, if they had a confirmed PCD diagnosis, >6 years, could breath-hold for 10 seconds, medically stable and not needing supplemental oxygen. Participants underwent same day repeat Xe-MRI and PREFUL scans. Results: 8 participants completed the study. The VDP from PREFUL had a significant and good agreement with Xe-MRI (R2=0.82, p<0.001). PREFUL had excellent repeatability based on the intraclass correlation of 0.94 and the Bland and Altman plot. Same day repeat scans show the ventilation defects, and corresponding VDP, from Xe-MRI and PREFUL (Figure). Conclusions: In PCD, PREFUL VDP demonstrated feasibility, validity, and repeatability. This suggests that PREFUL may be an alternative technique to Xe-MRI, the latter of which is not widely available. erj;64/suppl_68/PA3944/F1 F1 F1
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".