Optical-Flow-Based B-Mode Elastography: Application in the Hypertensive Rat Carotid
Bibliographic record
Abstract
Background-Ultrasound elastography is now used worldwide in tissue characterization. The primary premises of elastography are that speckle kinematics reproduces underlying tissue kinematics and that tissue motion can be inferred from speckle tracking. This implicitly assumes that speckle pattern is a material property that can be tracked with respect to time and space. It is then convenient to express the motion of such a material property in terms of total derivative, also known as optical flow (OF) equations. Aims-The present paper introduces a new iterative OF-based elastography (OFBE) method devoted to B-mode data. The first OFBE iteration computes axial and lateral displacement fields. Such displacement fields are used for data rigid registration, prior to the second OFBE iteration which computes the 2-D strain tensor. Methods-The OFBE method was validated in the common carotid artery of rat hypertension models. The effect of aging on carotid stiffness was investigated in female recombinant inbred rats (RI-17, (n=2)) in the first experiment. The outcomes of low/high-salt diets were examined in young male Dahl salt-sensitive rats (SS, n=6; SM12, n=6; SM9, n=6) in the second experiment. Results-Good concordance was observed between left and right carotid axial strain measurements with 11.4% relative error, whereas 4.6% relative error occurred between diastolic and systolic axial strain measurements. Old (80 and 85 weeks) RI-17 carotids were determined to be twice as stiff with 5.70 +/- 0.97% (strain+/-std) as young carotids (30 and 34 weeks) with 13.26 +/- 2.73%, p < 0.001. Carotid axial strain measurement also indicated that salt diets had a significant impact on SS (p=0.008) and SM12 (p < 0.001) but not on SM9 (p=0.881) rats.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".