Characterization of Flow Structure and Wall Shear Stress in Patient-Specific Abdominal Aortic Aneurysm Phantom Using Particle Image Velocimetry
Bibliographic record
Abstract
Abdominal aortic aneurysm (AAA) is an irreversible dilation of the abdominal aorta that carries a significant risk of rupture if not adequately screened and treated. This condition poses a severe threat, with a mortality rate exceeding 80% in certain age groups. The enlargement of the abdominal aorta leads to notable hemodynamic alterations in AAAs, characterized by flow separation and vortical structures. Current understanding acknowledges a correlation between the growth and rupture mechanisms of AAA and the disturbed hemodynamics, emphasizing metrics such as time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), endothelial cell activation potential (ECAP), and relative residence time (RRT). In this study, we utilized a quantitative velocity measurement technique, particle image velocimetry (PIV), to characterize the flow structure and wall shear stress in a patient-specific aneurysmal abdominal aorta phantom. AAA phantoms generated from patient computed tomography (CT) images were used. Phase-averaged flow fields for 12 phases of physiological flow were investigated, and velocity contours, streamline patterns, and swirling strength contours were constructed in the AAA at three different PIV planes. A method previously developed and validated to extract wall shear stress from PIV measurements is applied to obtain shear stress indexes, including TAWSS, OSI, ECAP, and RRT. In addition, to link our findings with the clinical rupture risk, actual rupture location in the CT images of the aneurysm sac for the studied case was compared with the flow structure and shear stress distributions obtained from PIV measurements. The progression of vortex structures in the bulge along with the flow separation and reattachment zones in relation to the shear stress indexes are presented and discussed in detail. When flow dynamics in actual rupture location is analyzed, there is a high level of flow disturbance characterized by flow circulation, low TAWSS, and high OSI, ECAP, and RRT, consistent with previous studies. Here, we present a PIV-based flow examination through patient-specific phantom, which will contribute to experimental investigations for understanding the influence of disturbed hemodynamics on AAA biomechanics.
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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".