Design of carotid bifurcation phantoms for integrative imaging investigations of arterial wall and flow dynamics
Bibliographic record
Abstract
Vascular phantoms are well regarded as essential experimental tools in the development of new ultrasound techniques for assessing wall mechanics and blood flow. However, existing phantoms are ill-suited for evaluation of integrative imaging methods that seek to concurrently assess biomechanics and hemodynamics. Here, we present a novel design protocol for acoustically-compatible anthropomorphic walled phantoms with artery-like vessel elasticity of carotid bifurcation with stenotic-narrowing. Our protocol involved a set of three-dimensional printed mold parts (consisted of a vessel core and an outer mold) for investment casting of polyvinyl alcohol solution to construct the elastic vessel tube. Agar-gelatin slab was formed around the vessel tube mimicking surrounding tissue. For demonstration, a set of healthy and stenosed (25%, 50%, and 75%) carotid bifurcation phantoms were developed. Imaging experiments were performed on these phantoms to visualize complex blood flow (recirculation and flow jet formation observed) and pulse wave dynamics (derived pulse wave velocity = 4.67 ± 0.71 m/s). Integrative imaging of wall motion and blood flow in our phantoms also revealed fluid-structure interaction differences between healthy and diseased models. These findings show that phantoms developed with our new protocol are useful in vascular imaging studies that individually or jointly assess wall motion and flow dynamics.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".