Normal left atrial strain and strain rate using cardiac magnetic resonance feature tracking in healthy volunteers
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Bibliographic record
Abstract
AIMS: The aim of our study was to establish normal ranges for left atrial (LA) strain and strain rate using cardiac magnetic resonance feature tracking (CMR-FT), LA sphericity index, and to compare LA strain using CMR-FT with 2D-speckle tracking echocardiography (STE) in a healthy population. METHODS AND RESULTS: A total of 112 volunteers (45 male, 67 female) had adequate tracking for analysis on CMR-FT (Circle Cardiovascular Imaging, Calgary, Canada). The median age was 42 years (range 19-79 years, interquartile range 30-53 years). LA reservoir, conduit, booster strain, strain rate using CMR-FT, and sphericity index were evaluated. Of the 112 volunteers, 91 patients had adequate tracking on 2D-STE using three commonly applied zero-baseline time reference methods: R-R gating, P-P gating, and volume gating (defining end-systole at the LA maximum and end-diastole at the LA minimum). The LA strain, strain rate using CMR-FT, and sphericity index were reported and comparable between both genders (P > 0.05 for all). The LA booster function including strain and strain rate increased significantly with age (P < 0.001 for all), while the LA conduit function gradually decreased. In comparison with STE, the LA reservoir strain was comparable between CMR and volume-gating methods (38.48 ± 9.31 vs. 36.77 ± 6.46; P = 0.13) but not with R-R and P-P gating methods (P < 0.001 for all). LA strain, strain rate, and sphericity index using CMR-FT had good intraobserver and interobserver reproducibility. CONCLUSION: LA strain, strain rate using CMR-FT, and sphericity index can be quickly assessed with good intraobserver and interobserver reproducibility.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 | 0.002 |
| 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 it