Effect of respiration on the B<sub>0</sub> field in the human spinal cord at 3T
Bibliographic record
Abstract
PURPOSE: Respiration affects the bulk magnetic susceptibility, causing frequency shifts as shown in the brain at 7T. Due to the close proximity of the spine to the lungs, this effect is expected to be even larger in the spinal cord, resulting in detrimental B0 offset. The goal of this study was to quantify the effect of respiration on B0 variation in the spinal cord. METHODS: Seven healthy subjects were scanned at 3T. Field maps were acquired during inspired and expired conditions. Frequency shift was quantified in the brain, brainstem, and cervico-thoracic spinal cord. A skewed Gaussian function with linear term was fitted to the frequency shift as a function of z-location along the spine. RESULTS: Large frequency shifts were measured along the cord, with a maximum of 74 Hz at C7 (P < 0.05), corresponding to 0.58 ppm. The proposed model was adequately fitted to the respiratory-induced frequency-shifts (adjusted R(2) = 0.9954). The morphology of subjects (weight and height) seemed to have an impact on the amplitude of frequency shift, although correlations were not significant. CONCLUSIONS: This study provides a deeper understanding of the contribution of respiration to B0 shift in the spinal cord. The proposed model can be useful for designing future hardware or software strategies to compensate for these B0 variations dynamically.
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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 | 0.002 |
| 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".