Sci-Fri AM: Imaging - 02: Regional Ventilation Mapping of the Rat Lung Using Hyperpolarized <sup>3</sup>He Magnetic Resonance Imaging
Bibliographic record
Abstract
With the addition of inhaled contrast agents, namely hyperpolarized 3He and 129Xe, Magnetic Resonance (MR) imaging has the ability to measure anatomical and functional changes associated with disease progression in the rodent lung. Hyperpolarized 3He MR imaging has been used to measure regional ventilation in the normal rat lung using the dynamic gas signal from inside the lungs. This method employs a variable flip angle approach (FAVOR) to mitigate the effects of RF pulses and relaxation both in the ventilator system and in the rat lung. Theoretical models are used to fit signal enhancement curves to generate two-dimensional maps of the ventilation parameter, r, which is defined as the percent refreshment of gas per unit volume per breath. Healthy Sprague-Dawley rats (∼525 g) were anesthetized and ventilated with hyperpolarized 3He using a custom ventilator system. Imaging experiments were performed at 3.0 T and 2D projection images were acquired. The average r value obtained for the whole lung (r = 0.30 ± 0.02) agreed with expected values based on geometrical calculations. The ventilation gradient calculated in the anterior/posterior direction agreed with previously published xenon-enhanced CT results; however, there is no significant precedent for known ventilation gradients in the superior/inferior direction. In the future, these imaging techniques will be extended to measure ventilation gradients in all three dimensions using hyperpolarized 129Xe. The development of imaging tools to regionally quantify ventilation is expected to improve our understanding of breathing physiology in both normal rat lungs as well as rat models of asthma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".