Experimental determination of human peripheral nerve stimulation thresholds in a 3‐axis planar gradient system
Bibliographic record
Abstract
In MRI, strong, rapidly switched gradient fields are desirable because they can be used to reduce imaging time, obtain images with better resolution, or improve image signal-to-noise ratios. Improvements in gradient strength can be made by either increasing the gradient amplifier strength or by enhancing gradient efficiency. Unfortunately, many MRI pulse sequences, in combination with high-performance amplifiers and existing gradient hardware, can cause peripheral nerve stimulation (PNS). This makes improvements in gradient amplifiers ineffective at increasing safely usable gradient strength. Customized gradient coils are one way to achieve significant improvements in gradient performance. One specific gradient configuration, a planar gradient system, promises improved gradient strength and switching time for cardiac imaging. The PNS thresholds for planar gradients were characterized through human stimulation experiments on all three gradient axes. The specialized gradient was shown to have significantly higher stimulation thresholds than traditional cylindrical designs (y-axis SR(min) = 210 +/- 18 mT/m/ms and DeltaG(min) = 133 +/- 13 mT/m; x-axis SR(min) = 222 +/- 24 mT/m/ms and DeltaG(min) = 147 +/- 17 mT/m; z-axis SR(min) = 252 +/- 26 mT/m/ms and DeltaG(min) = 218 +/- 26 mT/m). This system could be operated at gradient strengths 2 to 3 times higher than cylindrical configurations without causing stimulation.
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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) | 0.000 | 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) | 0.000 | 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".