Effect of T<sub>1</sub> relaxation on ventilation mapping using hyperpolarized <sup>129</sup>Xe multiple breath wash‐out imaging
Bibliographic record
Abstract
Purpose To investigate the effect of incorporating T 1 as a function of wash‐out breath number (T 1 ( n )) on estimation of fractional ventilation ( r ) using hyperpolarized 129 Xe multiple breath wash‐out (MBWO) imaging in rats. Methods MBWO imaging was performed in 8 healthy mechanically ventilated rats at several inter‐image delay times (τ) and tidal volumes ( TV ). r maps were calculated from the imaging data using a model of T 1 ( n ) (assuming that the longitudinal relaxation rate of 129 Xe in the lung is directly proportional to p A O 2 ) and compared to r maps obtained by assuming a fixed T 1 measured before wash‐out breaths ( r ′). Results Fractional ventilation was overestimated by up to 19.3% when T 1 was fixed. An inverse relationship between bias (Δ r ) and ventilation was observed at all τ and TV . Additionally, Δ r significantly increased when TV was decreased ( F statistic F (2,7) = 48.97, P < 10 −4 ). Histograms from r ′ maps were significantly more skewed toward lower values as compared to r histograms at all τ and TV ( P < 0.05) except TV = V dose – 1 mL. Conclusion Analysis of hyperpolarized 129 Xe MBWO imaging using a model incorporating T 1 ( n ) corrects for an overestimating bias in the mapping of fractional ventilation in mechanically ventilated rats introduced by assuming a fixed T 1 .
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".