Protocols for multi‐site trials using hyperpolarized <sup>129</sup>Xe MRI for imaging of ventilation, alveolar‐airspace size, and gas exchange: A position paper from the <sup>129</sup>Xe MRI clinical trials consortium
Bibliographic record
Abstract
Hyperpolarized (HP) 129 Xe MRI uniquely images pulmonary ventilation, gas exchange, and terminal airway morphology rapidly and safely, providing novel information not possible using conventional imaging modalities or pulmonary function tests. As such, there is mounting interest in expanding the use of biomarkers derived from HP 129 Xe MRI as outcome measures in multi‐site clinical trials across a range of pulmonary disorders. Until recently, HP 129 Xe MRI techniques have been developed largely independently at a limited number of academic centers, without harmonizing acquisition strategies. To promote uniformity and adoption of HP 129 Xe MRI more widely in translational research, multi‐site trials, and ultimately clinical practice, this position paper from the 129 Xe MRI Clinical Trials Consortium ( https://cpir.cchmc.org/XeMRICTC ) recommends standard protocols to harmonize methods for image acquisition in HP 129 Xe MRI. Recommendations are described for the most common HP gas MRI techniques—calibration, ventilation, alveolar‐airspace size, and gas exchange—across MRI scanner manufacturers most used for this application. Moreover, recommendations are described for 129 Xe dose volumes and breath‐hold standardization to further foster consistency of imaging studies. The intention is that sites with HP 129 Xe MRI capabilities can readily implement these methods to obtain consistent high‐quality images that provide regional insight into lung structure and function. While this document represents consensus at a snapshot in time, a roadmap for technical developments is provided that will further increase image quality and efficiency. These standardized dosing and imaging protocols will facilitate the wider adoption of HP 129 Xe MRI for multi‐site pulmonary research.
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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 | 0.261 | 0.185 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.038 | 0.031 |
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".