Ultrashort Echo Time Magnetic Resonance Imaging of the Lung Using a High-Relaxivity T <sub>1</sub> Blood-Pool Contrast Agent
Bibliographic record
Abstract
The lung remains one of the most challenging organs to image using magnetic resonance imaging (MRI) due to intrinsic rapid signal decay. However, unlike conventional modalities such as computed tomography, MRI does not involve radiation and can provide functional and morphologic information on a regional basis. Here we demonstrate proof of concept for a new MRI approach to achieve substantial gains in a signal to noise ratio (SNR) in the lung parenchyma: contrast-enhanced ultrashort echo time (UTE) imaging following intravenous injection of a high-relaxivity blood-pool manganese porphyrin T1 contrast agent. The new contrast agent increased relative enhancement of the lung parenchyma by over 10-fold compared to gadolinium diethylene triamine pentaacetic acid (Gd-DTPA), and the use of UTE boosted the SNR by a factor of 4 over conventional T1-weighted gradient echo acquisitions. The new agent also maintains steady enhancement over at least 60 minutes, thus providing a long time window for obtaining high-resolution, high-quality images and the ability to measure a number of physiologic parameters.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".