Pulmonary Ultrashort Echo Time<sup>19</sup>F MR Imaging with Inhaled Fluorinated Gas Mixtures in Healthy Volunteers: Feasibility
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it