Pulmonary Ultrashort Echo Time<sup>19</sup>F MR Imaging with Inhaled Fluorinated Gas Mixtures in Healthy Volunteers: Feasibility
Bibliographic record
Abstract
PURPOSE: To perform static breath-hold fluorine 19 ((19)F) three-dimensional (3D) ultrashort echo time (UTE) magnetic resonance (MR) imaging of the lungs in healthy volunteers by using a mixture of 79% perfluoropropane (PFP) and 21% O2. MATERIALS AND METHODS: This study protocol was approved by the local research ethics board and by Health Canada. All volunteers provided written informed consent. Ten healthy volunteers underwent MR imaging at 3.0 T. Fluorine 19 3D UTE MR images were acquired during a 15-second breath hold according to one of two breathing protocols: protocol A, a 1-L inhalation of a mixture of 79% PFP and 21% O2, and protocol B, continuous breathing from a 5-L bag of a mixture of 79% PFP and 21% O2 followed by a 1-L inhalation of the same PFP-O2 mixture from a separate bag and a subsequent breath hold. The signal-to-noise ratio (SNR) was measured in the three most central image sections and was compared between breathing protocols by using an unpaired t test. RESULTS: Overall, the SNR was significantly greater for breathing protocol B (continuous breathing) than for breathing protocol A (single breath) (P = .018). The mean SNRs were 18 ± 6 (standard deviation) and 32 ± 6 for images acquired by using breathing protocols A and B, respectively. Breathing protocol B improves SNR by "washing out" the air from the lungs and increasing the PFP concentration prior to (19)F imaging. CONCLUSION: This study demonstrates the feasibility of (19)F 3D UTE static breath-hold MR imaging of human lungs with inert fluorinated gases.
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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 | 0.002 |
| 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 | 0.001 |
| 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".