Impact of three B1 mapping techniques on variable flip angle T1 measurements
Bibliographic record
Abstract
Introduction: Variable flip angle (VFA) T1 mapping has become a popular tool to estimate T1 times in vivo due to its time-efficient high-resolution 3D coverage. For accurate T1 estimates at 3 Tesla, the acquisition of a B1 map is essential to correct the nominal flip angles. B1 maps are typically acquired at a low resolution (~4 mm) since the B1 field is slowly varying. For accurate T1 measures of cortical grey matter (GM), the B1 mapping method must also be accurate for long T1 and T2 relaxation times due to partial volume effects of GM and CSF. This work evaluates the impact of 3 published B1 mapping techniques (the double angle method (DAM), actual flip angle imaging (AFI) and Bloch-Siegert shift (BS)) to correct VFA T1 measurements in phantoms that mimic GM and CSF. VFA measurements were performed with standard and optimized spoiling. Gold standard inversion recovery (GS IR) T1 measurements (not requiring B1 measurement) are included for reference.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".