In vivo regional ventilation mapping using fluorinated gas MRI with an x‐centric FGRE method
Bibliographic record
Abstract
PURPOSE: Inert fluorinated gas lung MRI is a new and promising alternative to hyperpolarized gas lung MRI; it is less expensive and does not require expensive isotopes/polarizers. The thermally polarized nature of signal obtained from fluorinated gases makes it relatively easy to use for dynamic lung imaging and for obtaining lung ventilation maps. In this study, we propose that the sensitivity and resolution of fluorine-19 (19F) in vivo images can be improved using the x-centric pulse sequence, thereby achieving a short echo time/pulse repetition time. This study is a transitional step for converting to more sustainable gases for lung imaging. METHODS: A 19F-resolution phantom was used to validate the efficiency of performing the x-centric pulse sequence on a clinical scanner. Ventilation maps were obtained in the lungs of five normal rats with a washout approach (adapted from Xe-enhanced computed tomography [Xe-CT] regional ventilation mapping), using mixtures of either sulfur hexafluoride/oxygen or perfluoropropane/oxygen and a two-breath x-centric method. RESULTS: Fractional ventilation (r) values obtained in this study (0.35-0.46 interval) were in good agreement with previously published values for 3He/129Xe. Calculated r gradients agreed well with published gradients obtained in rats with Xe-CT measurements. CONCLUSIONS: These results suggest that fluorinated gases can be reliably used in vivo in dynamic lung studies as an alternative to 3He/129Xe.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".