Transmit‐only/receive‐only radiofrequency coil configuration for hyperpolarized <sup>129</sup>Xe <scp>MRI</scp> of rat lungs
Bibliographic record
Abstract
Abstract We report a novel radiofrequency (RF) transmit‐only/receive‐only (TO/RO) coil configuration providing excellent transmit B1+ field uniformity as well as high sensitivity for hyperpolarized 129Xe MR lung imaging of rats at 3T (35.34 MHz). The TO/RO coil configuration consisted of two separate components: (i) a high‐pass birdcage transmit coil which produces a homogeneous B1+ magnetic field, (ii) a saddle‐shaped single‐turn receive‐only surface coil that couples closely to the rat lung. On transmit, the receive‐only coil is decoupled from the transmit coil using a detuning circuit. On receive, the bird‐cage coil is deactivated through the use of PIN diodes. The sensitivity and uniformity of the saddle‐shaped receive coil were optimized solving the Biot‐Savart equation using 3D finite element modeling. The electrical performance of the new TO/RO configuration in transmit/receive (T/R) mode was compared with a commercial T/R birdcage coil of similar diameter, which was considering to be the gold standard for conventional T/R mode imaging. Experimental results in phantoms confirm that our novel TO/RO coil configuration provides a factor of three increase in SNR without compromising B1 transmit uniformity compared with the commercial T/R birdcage coil configuration. The novel TO/RO coil was successfully tested for in vivo rat lung imaging. © 2015 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 45B: 115–124, 2015
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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 | 0.000 |
| 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".