Abstract 94: Predicting Aortic Aneurysm Rupture: A Computational Fluid Dynamics Analysis
Bibliographic record
Abstract
Aortic size is the primary factor used to predict abdominal aortic aneurysm (AAA) rupture potential; however, this method fails to account for AAA that rupture at smaller sizes, or for those that reach extreme sizes without rupture. Currently there is no truly reliable way to evaluate the susceptibility of a particular AAA to rupture. Although computational fluid dynamic (CFD)methods have been used previously to evaluate AAA flow dynamics, these studies have yet to predict the rupture potential for specific AAA anatomy. We hypothesize that the site of maximal pressure and wall shear stress (WSS) within individual AAA will lead to biomechanical wall failure and will predict the site of aortic rupture. In order to test this hypothesis we used commercially-available CFD software (ANSYS CFX v. 12.1) to solve the governing equations for mass and momentum for CTA-derived 3D images of ruptured AAA (RAAA) (n=5; 4 male, 1 female). Blood flow was considered to be laminar, Newtonian, and steady-state. The simulations were performed on a UNIX platform with 8 platform processors. The solution was considered to be converged when the maximum residuals for all governing equations were below 1.0 x 10 -5 . ANSYS software was used to generate a fully hexahedral mesh. Predicted intra-aortic pressure and WSS profiles were obtained. The average AAA size at rupture was 8.3 +/- 1.52 cm. Three of the five RAAA ruptured at or near the site of maximal diameter. The maximal predicted intra-aortic pressure was 14.25 +/- 6.29 Pa and generally was localized on the anterior aortic wall. In most cases the site of actual rupture was the lateral wall of the AAA where the pressure was not significantly different from that at the site of maximal pressure (12.12 +/- 6.27 Pa, p >0.05, ns). In the normal aorta, velocity profiles are laminar to the aortic bifurcation, whereas in AAA there is significant vortex flow pattern within the aneurysm. In these RAAA the highest predicted WSS was on the anterior aortic wall and measured 0.184 +/- 0.02 Pa. At the actual site of rupture, WSS was significantly lower at 0.044 +/- 0.0006 Pa (p<0.0001). In all cases the rupture occurred in a low WSS region and was always associated with eddy formation or flow recirculation. This CFD study was the first to model blood flow in the geometry of actual RAAA. Interestingly, the site of rupture was not in the region of maximal pressure or WSS as predicted. Rupture occurred in all cases in flow recirculation zones where low WSS predominated. This work will provide the basis for future research on a more precise prediction of rupture risk.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".