Mapping of <sup>3</sup>He apparent diffusion coefficient anisotropy at sub‐millisecond diffusion times in an elastase‐instilled rat model of emphysema
Bibliographic record
Abstract
Hyperpolarized (3) He gas can provide detailed anatomical maps of the macroscopic airways in the lungs (i.e., ventilation) as well as insight into the lung microstructure through the apparent diffusion coefficient. In particular, the apparent diffusion coefficient of (3) He in the lung exhibits anisotropic effects that depend on diffusion time (δ), and it has been shown to be extraordinarily sensitive to enlargement in terminal airways and alveoli associated with emphysema. In this study, the anisotropic nature of the (3) He apparent diffusion coefficient is studied in a rat model of emphysema, based on elastase instillation, specifically for δ values less than one millisecond. Longitudinal (D(L) ) and transverse (D(T) ) diffusion coefficients were mapped at δ = 360 μs and δ = 800 μs based on a cylinder model of lung structure and correlated with histological measurement of alveolar damage based on mean linear intercept (L(m) ). Whole-lung mean D(T) measured at δ = 360 μs in the elastase-instilled rat lungs (0.14 ± 0.09 cm(2) /s) demonstrated the most significant increase (p = 0.00195) compared to the sham-instilled cohort (0.06 ± 0.06 cm(2) /s) and had a strong linear correlation with L(m) (Pearson's correlation coefficient of 0.9). These results suggest that measurement of (3) He apparent diffusion coefficient anisotropy, specifically D(T) , can provide a sensitive indicator of emphysema, particularly at very short diffusion times (δ = 360 μs).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".