Rapid and efficient mapping of regional ventilation in the rat lung using hyperpolarized <sup>3</sup>He with Flip angle variation for offset of RF and relaxation (FAVOR)
Bibliographic record
Abstract
A novel imaging method is presented, Flip Angle Variation for Offset of RF and Relaxation (FAVOR), for rapid and efficient measurement of rat lung ventilation using hyperpolarized helium-3 (3He) gas. The FAVOR technique utilizes variable flip angles to remove the cumulative effect of RF pulses and T1 relaxation on the hyperpolarized gas signal and thereby eliminates the need for intervening air wash-out breaths and multiple cycles of 3He wash-in breaths before each image. The former allows an improvement in speed (by a factor of approximately 30) while the latter reduces the cost of each measurement (by a factor of approximately 5). The FAVOR and conventional ventilation methods were performed on six healthy male Brown Norway rats (190-270 g). Lobar measurements of ventilation, r, obtained with the FAVOR method were not significantly different from those obtained with the conventional method for the right middle and caudal and left lobes (P>0.05 by a Wilcoxon matched pairs test). A methacholine challenge test was also administered to an animal and reduction and recovery of r was detected by the FAVOR method. The reduced 3He consumption and the improvement in speed provided by FAVOR suggest that it may allow measurement of ventilation in human subjects not previously possible.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".