Comparison of global and segmental left ventricular myocardial deformation in patients with hypertrophic cardiomyopathy: a prospective two-dimensional VS. Threedimensional CMR feature tracking study (conference session winner)
Bibliographic record
Abstract
INTRODUCTION Recent studies demonstrated that reduced left ventricular (LV) global longitudinal strain in patients with hypertrophic cardiomyopathy (HCM) and preserved LV systolic function is an independent risk factor of adverse cardiovascular events. Two-dimensional (2D) strain assessment using cardiac magnetic resonance (CMR) cine images is well recognized as robust and highly reproducible technique. AIM The aim of our study was to investigate recently introduced three-dimensional (3D) strain analysis approach in patients with obstructive (HOCM) and non-obstructive HCM. METHODS Thirty-eight individuals (19 HCM patients without LV outflow tract (LVOT) obstruction and 19 patients with LVOT obstruction) underwent CMR imaging using 1.5 T MRI scanner (Siemens Magnetom Aera, Siemens Medical Systems, Erlangen, Germany). The cine images were used to calculate 2D and 3D left ventricular longitudinal (EllLV), circumferential (EccLV) and radial (ErrLV) strain using feature tracking (FT) technique. Global and regional (septal and lateral wall) EllLV was derived from three long-axis (two-, three- and four-chamber) cine images, while global and regional (septal and lateral wall) EccLV and ErrLV were calculated from three short-axis (basal, mid-ventricular and apical) cine images using dedicated software (CMR42, Circle Cardiovascular Imaging, Calgary, Canada). Data analysis was performed using IBM SPSS Statistics version 21.0 software (SPSS Inc., Chicago, IL, USA). Continuous variables of two groups were compared by the paired samples t test if the data were normally distributed, whereas Wilcoxon signed ranks test was used to compare nonparametric data. A P value of <0.05 was considered significant.[...].
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".