Multi‐center benchmarking of cervical spinal cord <scp>RF</scp> coils for 7 T <scp>MRI</scp> : A traveling spines study
Bibliographic record
Abstract
PURPOSE: The depth within the body, small diameter, long length, and varying tissue surrounding the spinal cord impose specific considerations when designing RF coils. The optimal coil configuration for 7 T cervical spinal cord MRI is unknown and currently there are very few coil options. The purpose of this work was (1) to establish a quality control protocol for evaluating 7 T cervical spinal cord coils, and (2) to use that protocol to evaluate the performance of four different coil designs. METHODS: Three healthy volunteers and a custom anthropomorphic phantom (the traveling spines cohort) were scanned at seven 7 T imaging centers using a common protocol and each center's specific cervical spinal cord coil. Four different coil designs were tested (two in-house, one Rapid Biomedical, and one MRI.TOOLS design). RESULTS: profile along the cervical spinal cord; however, it was limited in its ability to provide the requested flip angles (especially for larger individuals). The latter was also the case for the second in-house coil (MSSM). CONCLUSION: The results of this study serve as a guide for the spinal cord MRI community in selecting the most suitable coil based on specific requirements and offer a standardized protocol for assessing future coils.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".