Effect of Common Carotid Artery Inlet Length on Normal Carotid Bifurcation Hemodynamics
Bibliographic record
Abstract
Controversy exists regarding the suitability of fully developed versus measured inlet velocity profiles for image-based computational fluid dynamics (CFD) studies of carotid bifurcation hemodynamics. Here, we attempt to resolve this by investigating the impact of the reconstructed common carotid artery (CCA) inlet length on computed metrics of "disturbed" flow. Twelve normal carotid bifurcation geometries were reconstructed from contrast-enhanced angiograms acquired as part of the Vascular Aging--The Link That Bridges Age to Atherosclerosis study (VALIDATE). The right carotid artery lumen geometry was reconstructed from its brachiocephalic origin to well above the bifurcation, and the CCA was truncated objectively at locations one, three, five, and seven diameters proximal to where it flares into the bifurcation. Relative to the simulations carried out using the full CCA, models truncated at one CCA diameter strongly overestimated the amount of disturbed flow. Substantial improvement was offered by using three CCA diameters, with only minor further improvement using five CCA diameters. With seven CCA diameters, the amounts of disturbed flow agreed unambiguously with those predicted by the corresponding full-length models. Based on these findings, we recommend that image-based CFD models of the carotid bifurcation should incorporate at least three diameters of CCA length if fully developed velocity profiles are to be imposed at the inlet. The need for imposing measured inlet velocity profiles would seem to be relevant only for those cases where the CCA is severely truncated.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".