Effects of diffusion time on short‐range hyperpolarized <sup>3</sup>He diffusivity measurements in emphysema
Bibliographic record
Abstract
PURPOSE: To characterize the effect of diffusion time on short-range hyperpolarized (3)He magnetic resonance imaging (MRI) diffusion measurements across a wide range of emphysema severity. MATERIALS AND METHODS: (3)He diffusion MRI was performed on 19 lungs or lobes resected from 18 subjects with varying degrees of emphysema using three diffusion times (1.6 msec, 5 msec, and 10 msec) at constant b value. Emphysema severity was quantified as the mean apparent diffusion coefficient (ADC) and as the percentage of pixels with ADC higher than multiple thresholds from 0.30-0.55 cm(2)/sec (ADC index). Quantitative histology (mean linear intercept) was obtained in 10 of the lung specimens from 10 of the subjects. RESULTS: The mean ADCs with diffusion times of 1.6, 5.0, and 10.0 msec were 0.46, 0.40, and 0.37 cm(2)/sec, respectively (P < 0.0001, analysis of variance [ANOVA]). There was no relationship between the ADC magnitude and the effect of diffusion time on ADC values. The mean linear intercept correlated with ADC (r = 0.91-0.94, P < 0.001) and ADC index (r = 0.78-0.92, P < 0.01) at all diffusion times. CONCLUSION: Decreases in ADC with longer diffusion time were unrelated to emphysema severity. The strong correlations between the ADC at all diffusion times tested and quantitative histology demonstrate that ADC is a robust measure of emphysema.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".