Accelerated interleaved spiral‐IDEAL imaging of hyperpolarized <sup>129</sup>Xe for parametric gas exchange mapping in humans
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Bibliographic record
Abstract
Purpose To demonstrate the feasibility of mapping gas exchange with single breath‐hold hyperpolarized (HP) 129 Xe in humans, acquiring parametric maps of lung physiology. The potential benefit of acceleration using parallel imaging for this application is also explored. Methods Six healthy volunteers were scanned with a modified spiral‐IDEAL sequence to acquire gas exchange‐weighted images using a single dose of 129 Xe. These images were fit with the model of xenon exchange (MOXE) on a voxel‐wise basis calculating parametric maps of lung physiology, specifically: air–capillary barrier thickness (δ), alveolar septal thickness ( d ), capillary transit time ( t x ), pulmonary hematocrit (HCT), and alveolar surface area‐to‐volume ratio (SVR). An accelerated version of the sequence was also tested in subset of 4 volunteers and compared to the fully sampled (FS) results. Results Mean image‐wide values calculated from MOXE parametric maps derived from FS dissolved 129 Xe spiral‐IDEAL images were: δ = 0.89 ± 0.17 μm, d = 7.5 ± 0.5 μm, t x = 1.1 ± 0.2s, HCT = 28.8 ± 2.3%, and SVR = 140 ± 16 cm −1 , in good agreement with previously published values based on whole‐lung spectroscopy of healthy human subjects. Parallel imaging sufficiently reduces artifacting in accelerated images, but increases disagreement with MOXE parameters derived from FS data with mean voxel‐wise unsigned relative differences of: δ = 39 ± 9%, d = 22 ± 3%, t x = 117 ± 43%, HCT = 11 ± 2%, and SVR = 31 ± 12%. Conclusion Dissolved HP 129 Xe spiral‐IDEAL imaging for gas exchange mapping is feasible in humans using a single breath‐hold. Accelerated gas exchange mapping is also shown to be feasible but requires further improvements to increase quantitative accuracy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 it