Slice‐by‐slice <i>B</i><sub>1</sub><sup>+</sup> shimming at 7 T
Bibliographic record
Abstract
Parallel transmission has been used to reduce the inevitable inhomogeneous radiofrequency fields produced in human high-field MRI greater than 3 T. Further improvements in the transmit homogeneity and efficiency are possible by leveraging the additional degree of freedom permitted by multislice acquisitions. Compared to simple scaling of the flip angle to compensate for B1+ falloff along the radiofrequency coil, calculation of B1+ shim solutions on a slice-by-slice basis can markedly improve homogeneity and/or reduce transmitted power and global SAR. Performance measures were acquired at 7 T with a 15-channel head-only transceive array featuring elements distributed over all three logical axes, facilitating B1+ shimming over arbitrary orientations. Compared to a circularly polarized volume mode of the same coil, shimming to maximize excitation efficiency on a slice-by-slice basis yielded improvements in mean B1+ by 12.8±2.4% and a reduction in standard deviation of B1+ of 16.3±6.8%, while reducing relative SAR by 6.2±3.1%. When shimming for greater uniformity, the mean and standard deviation of B1+ were further improved by 15.9±2.6% and 26.2±10.4%, respectively, at the expense of a 135±8% increase in global SAR. Robust multislice-shim solutions are demonstrated that can be quickly calculated, applied in real time, and reliably improve on volume coil modes.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".