A variable field strength system for hyperpolarized noble gas MR imaging of rodent lungs
Bibliographic record
Abstract
Abstract Hyperpolarized Noble Gas (HNG), 3He (helium) or 129Xe (xenon), MR imaging has become a promising approach for visualizing lung anatomy and function. It has been theoretically predicted that low field strengths (0.05–0.2 T) may provide optimal signal‐to‐noise ratio (SNR) and spatial resolution for clinical HNG MR imaging. These optimum field strengths correspond to frequencies between 1.62–6.5 MHz and 0.59–2.35 MHz for 3He and 129Xe respectively. The optimum field strength depends on the size and geometry of the sample and radiofrequency (RF) coil as well as the field dependence of the HNG MR properties in the lung (e.g., relaxation times, susceptibility effects). In particular, little is known about the field dependence of the apparent transverse relaxation time, T , which is expected to strongly influence HNG signal. In this paper, a broadband (0.1–100 MHz) variable field strength MR imaging system for rodents is described. A custom‐built resistive magnet was constructed and shimmed to provide the necessary homogeneity for imaging. RF coils and transmit/receive switches for different frequencies were also developed. Preliminary proton (1H) and hyperpolarized 129Xe images of test objects are presented, including a desiccated lung phantom. In vivo 129Xe signals from rat lungs were acquired at 73.5 mT and T was estimated to be approximately 80 ± 8 ms, in good agreement with previously reported values. The MR system developed should be useful for imaging rodent lungs at different field strengths to verify the expected SNR and spatial resolution possible using HNG imaging and to investigate long range diffusion and oxygen‐induced transverse relaxation. © 2008 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 33B: 124–137, 2008
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".