Hyperpolarised<sup>129</sup>Xe magnetic resonance imaging to monitor treatment response in children with cystic fibrosis
Bibliographic record
Abstract
Xe gas (XeMRI) can quantify ventilation inhomogeneity by measuring the percentage of unventilated lung volume (ventilation defect per cent (VDP)). While previous studies have demonstrated its sensitivity for detecting early cystic fibrosis (CF) lung disease, the utility of XeMRI to monitor response to therapy in CF is unknown. The aim of this study was to assess the ability of XeMRI to capture treatment response in paediatric CF patients undergoing inpatient antibiotic treatment for a pulmonary exacerbation.15 CF patients aged 8-18 years underwent XeMRI, spirometry, plethysmography and multiple-breath nitrogen washout at the beginning and end of inpatient treatment of a pulmonary exacerbation. VDP was calculated from XeMRI images obtained during a static breath hold using semi-automated k-means clustering and linear binning approaches.XeMRI was well tolerated. VDP, lung clearance index and the forced expiratory volume in 1 s all improved with treatment; however, response was not uniform in individual patients. Of all outcome measures, VDP showed the largest relative improvement (-42.1%, 95% CI -52.1--31.9%, p<0.0001).These data support further investigation of XeMRI as a tool to capture treatment response in CF lung disease.
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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 | 0.000 | 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) | 0.000 | 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".