Anatomical, functional and metabolic imaging of radiation‐induced lung injury using hyperpolarized MRI
Bibliographic record
Abstract
MRI of hyperpolarized (129)Xe gas and (13)C-enriched substrates (e.g. pyruvate) presents an unprecedented opportunity to map anatomical, functional and metabolic changes associated with lung injury. In particular, inhaled hyperpolarized (129)Xe gas is exquisitely sensitive to changes in alveolar microanatomy and function accompanying lung inflammation through decreases in the apparent diffusion coefficient (ADC) of alveolar gas and increases in the transfer time (T(tr)) of xenon exchange from the gas and into the dissolved phase in the lung. Furthermore, metabolic changes associated with hypoxia arising from lung injury may be reflected by increases in lactate-to-pyruvate signal ratio obtained by magnetic resonance spectroscopic imaging following injection of hyperpolarized [1-(13)C]pyruvate. In this work, the application of hyperpolarized (129)Xe and (13)C MRI to radiation-induced lung injury (RILI) is reviewed and results of ADC, T(tr) and lactate-to-pyruvate signal ratio changes in a rat model of RILI are summarized. These results are consistent with conventional functional (i.e. blood gases) and histological (i.e. tissue density) changes, and correlate significantly with inflammatory cell counts (i.e. macrophages). Hyperpolarized MRI may provide an earlier indication of lung injury associated with radiotherapy of thoracic tumors, potentially allowing adjustment of treatment before the onset of severe complications and irreversible fibrosis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".