2D vs 3D echocardiography: are we underestimating the end diastolic volume in mice following myocardial infarction?
Bibliographic record
Abstract
Purpose: The accurate assessment of the left ventricular (LV) volume and function is of paramount importance in basic cardiovascular research. For practical reasons two dimensional (2D) echocardiography has been used frequently in this research area. Recently, three dimensional (3D) echocardiography has become available for small animals studies too. The purpose of this study was to compare the volume estimates obtained by 2D and 3D determination of End Diastolic Volume (EDV) in mice before myocardial infarction (MI) and 3 weeks after MI. Methods: EDV was measured in male Swiss mice (n=15) using 2D and 3D-echocardiography, three days before the induction of MI by occlusion of the left anterior descending (LAD) artery. Three weeks after MI - when dilatation of the infarct has been established - mice were subjected to 2D and 3D-echo again. All echocardiographic data were obtained by using a Vevo 2100 imaging device (VisualSonics, Toronto, Canada). For 2D estimates, high resolution long-axis pictures of the LV were taken in B-mode at frame rates > 80Hz. For 3D estimates ECG t-triggered short-axis pictures of the LV were taken at 500 um distance from apex to base. All 2D/3D measurements and processing of data were completed by the same observer (JJD). Results: Before MI, EDV measurements were higher using 3D versus the 2D method in 12 out of 15 mice (3D EDV: 105.3±6.0 mm3 vs 2D EDV: 84.1±3.4 mm3; p<0.01). At day 21 post-MI, this difference was even more pronounced (3D EDV: 229.3±16.0 mm3 vs 2D EDV: 184.8±9.8 mm3; p<0.001). Moreover, the differences between the two methods were analyzed with the Bland and Altman plot, which showed a difference in both time points: before the MI induction (Regression p<0.05) and 3 weeks after the MI (Regression p<0.001). Conclusion: Following MI, the morphology of the heart and in particular the LV shape is disturbed, becoming irregular as adverse remodeling develops. The 3D-echo determination of EDV yields higher readings compared to the 2D-echo before MI but this difference becomes greater after MI. The explanation for this observation could be that 2D-echocardiography determination assumes normal geometry and hence it could be underestimating the changes in shape and volume of the LV.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".