Left Ventricular Strain Mapping Utilizing Novel Strain Tracking Techniques
Bibliographic record
Abstract
The objective of this study was to evaluate the effectiveness and usability of Vevo Strain 2.0 (VS2), a FUJIFILM VisualSonics Inc. software package to assess left ventricular functional parameters from ultrasound images. We hypothesized that VS2 would achieve left ventricle strain values within 20% of Vevo Strain 1.0 (VS1) while providing more physiological information and a better user experience. To achieve this, we evaluated the left ventricular strain of C57Bl/6N adult male mice (n=4) at three surgical timepoints: healthy baseline (prior to surgery), 3 weeks after induction of transverse aortic constriction via microsurgery, and 1 week after releasing the transverse aortic constriction. Strain was evaluated using VS1 and VS2 left ventricular wall motion tracking software of brightness mode ultrasound images in both the short- and long-axis planes. In the short-axis plane, global circumferential strain values were within the 20% threshold between VS1 and VS2 for all animals at all experimental timepoints. In the long-axis plane, approximately ¾ of all the global longitudinal strain values were within the 20% threshold. Further, in both planes, as strain magnitude increased, the differences in strain between VS1 and VS2 decreased, especially in strains greater than 15%. This is likely due to the fact that at small strains, noise and image quality can have a bigger impact on the overall results. From these comparisons, we can conclude that VS2 can accurately track the wall motion of the left ventricle from a short- or long-axis ultrasound image. Additionally, VS2 provided additional information regarding regional strain differences, the capacity to evaluate 4-dimensional strain using multiple views of the same left ventricle, and a more user-friendly interface with which to analyze data. This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".