3D myocardial <i>T</i><sub>1</sub> mapping at 3T using variable flip angle method: Pilot study
Bibliographic record
Abstract
PURPOSE: Myocardial T1 mapping is an emerging technique that could improve cardiovascular magnetic resonance diagnostic accuracy. In this study, a variable flip angle approach with B1 correction is proposed at 3T on the myocardium, employing standard 3D spoiled fast gradient echo and echo planar imaging sequences. METHODS: The method was tested on phantoms to determine the set of standard 3D spoiled fast gradient echo angles adapted to myocardial T1 measurements and was compared to the inversion-recovery spin-echo reference T1 method. Seven volunteers underwent magnetic imaging resonance to acquire myocardial T1 maps and T1 values of the human heart. RESULTS: This original method demonstrated good reproducibility in phantoms and a significant correlation between variable flip angle T1 values and reference inversion-recovery spin-echo T1 values. It yielded myocardial T1 values consistent with expected T1 and an increasing homogenization of myocardial segments owing to B1 correction. The mean myocardial T1 value was 1341 ± 42 ms. CONCLUSION: Myocardial 3D T1 mapping using the variable flip angle approach can potentially be useful for evaluating fibrosis on the entire myocardium using a standard clinical sequence.
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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 | 0.001 | 0.001 |
| 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".