Bronchial thermoplasty guided by hyperpolarised gas magnetic resonance imaging in adults with severe asthma: a 1-year pilot randomised trial
Bibliographic record
Abstract
Patient-specific localisation of ventilation defects using hyperpolarised gas magnetic resonance imaging (MRI) introduces the possibility of regionally targeted bronchial thermoplasty (BT) for the treatment of severe asthma. We aimed to demonstrate that BT guided by MRI to ventilation defects reduces the number of radiofrequency activations while resulting in improved asthma quality-of-life and control scores that are non-inferior to standard BT. In a 1-year pilot randomised controlled trial, 14 patients with severe asthma who were clinically eligible to receive BT underwent hyperpolarised gas MRI to characterise ventilation defects and were randomised to MRI-guided or standard BT. End-points were improved Asthma Quality of Life Questionnaire (AQLQ) and Asthma Control Questionnaire (ACQ) scores, the proportion of AQLQ and ACQ responders and the number of radiofrequency activations and bronchoscopy sessions. Participants who underwent MRI-guided BT received 53% fewer radiofrequency activations than those who had standard BT (p=0.003). At 12 months, the mean improvement from baseline was similar between the MRI-guided group (n=5) and the standard group (n=7) for AQLQ score (MRI-guided: 1.8, 95% CI 0.1-3.5, p=0.04; standard: 0.7, 95% CI -0.9-2.3, p=0.30) (p=0.25) and ACQ-5 score (MRI-guided: -1.4, 95% CI -2.6- -0.2, p=0.03; standard: -0.7, 95% CI -1.3-0.0, p=0.04) (p=0.17). A similar proportion of participants in both groups achieved a clinically relevant improvement in AQLQ score (MRI-guided: 80%; standard: 71%) and ACQ-5 score (MRI-guided: 80%; standard: 57%). Hyperpolarised gas MRI-guided BT reduced the number of radiofrequency activations, and resulted in asthma quality of life and control improvements at 12 months that were non-inferior to standard BT.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".