Comparison of Two Different Speckle Tracking Software Systems: Does the Method Matter?
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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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 | 0.166 | 0.259 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".