In vivo investigation of the multi‐exponential <i>T</i><sub>2</sub> decay in human white matter at 7 T: Implications for myelin water imaging at UHF
Bibliographic record
Abstract
Introduction Multi‐component T 2 mapping using a gradient‐ and spin‐echo (GraSE) acquisition has become standard for myelin water imaging at 3 T. Higher magnetic field strengths promise signal‐to‐noise ratio benefits but face specific absorption rate limits and shortened T 2 times. This study investigates compartmental T 2 times in vivo and addresses advantages and challenges of multi‐component T 2 mapping at 7 T. Methods We acquired 3D multi‐echo GraSE data in seven healthy adults at 7 T, with three subjects also scanned at 3 T. Stimulated echoes arising from B 1 + inhomogeneities were accounted for by the extended phase graph (EPG) algorithm. We used the computed T 2 distributions to determine T 2 times that identify different water pools and assessed signal‐to‐noise and fit‐to‐noise characteristics of the signal estimation. We compared short T 2 fractions and T 2 properties of the intermediate water pool at 3 T and 7 T. Results Flip angle mapping confirmed that EPG accurately determined the larger B 1 + inhomogeneity at 7 T. Multi‐component T 2 analysis demonstrated shortened T 2 times at 7 T compared with 3 T. Fit‐to‐noise and signal‐to‐noise ratios were improved at 7 T but depended on B 1 + homogeneity. Adjusting the shortest T 2 to 8 ms and the T 2 threshold that separates different water compartments to 20 ms yielded short T 2 fractions at 7 T that conformed to 3 T data. Short T 2 fractions in myelin‐rich white matter regions were lower at 7 T than at 3 T, and higher in iron‐rich structures. Discussion Adjusting the T 2 compartment boundaries was required due to the shorter T 2 relaxation times at 7 T. Shorter echo spacing would better sample the fast decaying signal but would increase peripheral nerve stimulation. Multi‐channel transmission will improve T 2 measurements at 7 T. Conclusion We used a multi‐echo 3D GraSE sequence to characterize the multi‐exponential T 2 decay at 7 T. We adapted T 2 parameters for evaluation of the short T 2 fraction. Obtained 7 T multi‐component T 2 maps were in good agreement with 3 T data.
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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 | 0.001 |
| 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) | 0.000 | 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".