A Pseudo Non-Cartesian Pulse Sequence For Hyperpolarized Xenon-129 Gas MRI of Rodent Lungs At Low Magnetic Field Strength
Bibliographic record
Abstract
Background: Early diagnosis of radiation-induced lung injury (RILI) following radiation therapy is critical for prevention of permanent lung damage. Pulmonary imaging using magnetic resonance imaging (MRI) of the apparent diffusion coefficient (ADC) of hyperpolarized xenon (129Xe) gas shows promise for early measurement of RILI.\nMethods: An ultra-short echo time imaging sequence based on a pseudo-Cartesian k-space trajectory, known as Sectoral, is implemented at low magnetic field (0.07 T) for efficient use of the non-renewable magnetization of hyperpolarized 129Xe gas. A pilot study was performed to demonstrate the feasibility of ADC mapping using the Sectoral sequence on healthy and 2-weeks post irradiated rats.\nResults: A significant (p < 0.05) correlation between mean ADC values from Sectoral ADC maps and the mean linear intercept (Lm), as a measure of interalveolar wall distance, from histological sections of the lungs was observed (p = 0.0061) and a significant (p < 0.05) separation between healthy and irradiated lungs was observed with full width at half maximum ADC (p = 0.0317).\nConclusion: Sectoral MRI with 129Xe is feasible in rats. Decreases in ADC were measured following lung irradiations which correlate with Lm.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".