Comparison of Two Different Speckle Tracking Software Systems: Does the Method Matter?
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Bibliographic record
Abstract
BACKGROUND: Echocardiographic speckle tracking strain has gained clinical importance. However, the comparability of measurements between different software systems is not well defined. METHODS: In 47 healthy subjects left ventricular (LV) two-dimensional (2D) peak strain and time to peak strain (TTP) generated by EchoPAC (2DS) and velocity vector imaging (VVI) were compared. For each type of strain (longitudinal [LS], circumferential [CS], and radial strain [RS]) we compared global, anatomical level and segmental values. RESULTS: When comparing 2DS to VVI, Pearson correlation coefficients (r) of global LS, CS, and RS were 0.68, 0.44, and 0.59, respectively (all P < 0.05). Correlation of global TTP was higher: 0.81(LS), 0.80 (CS), and 0.68 (RS), all P < 0.01. Segmental peak strain differed significantly between 2DS and VVI in 8/18 (LS), 17/18 (CS), and 15/18 (RS) LV segments (P < 0.05). However, segmental TTP significantly differed only in 5/18 (LS), 7/18 (CS), and 4/18 (RS) of LV segments. Similar strain gradients were found for both systems: apical strain was higher than basal and midventricular strain in LS and CS, with a reversed pattern for RS (P < 0.05). CONCLUSION: TTP strain as well as strain gradients were comparable between VVI and 2DS, but most peak strain values were not. The software-dependency of peak strain values must be considered in clinical application. Further studies comparing the diagnostic and prognostic accuracy of strain values generated by different software systems are mandatory.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.000 | 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