Normal left atrial strain and strain rate using cardiac magnetic resonance feature tracking in healthy volunteers
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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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".