Numerical Study of Cerebroarterial Hemodynamic Changes Following Carotid Artery Operation: A Comparison Between Multiscale Modeling and Stand-Alone Three-Dimensional Modeling
Bibliographic record
Abstract
Free outflow boundary conditions have been widely adopted in hemodynamic model studies, they, however, intrinsically lack the ability to account for the regulatory mechanisms of systemic hemodynamics and hence carry a risk of producing incorrect results when applied to vascular segments with multiple outlets. In the present study, we developed a multiscale model capable of incorporating global cardiovascular properties into the simulation of blood flows in local vascular segments. The multiscale model was constructed by coupling a three-dimensional (3D) model of local arterial segments with a zero-one-dimensional (0-1-D) model of the cardiovascular system. Numerical validation based on an idealized model demonstrated the ability of the multiscale model to preserve reasonable pressure/flow wave transmission among different models. The multiscale model was further calibrated with clinical data to simulate cerebroarterial hemodynamics in a patient undergoing carotid artery operation. The results showed pronounced hemodynamic changes in the cerebral circulation following the operation. Additional numerical experiments revealed that a stand-alone 3D model with free outflow conditions failed to reproduce the results obtained by the multiscale model. These results demonstrated the potential advantage of multiscale modeling over single-scale modeling in patient-specific hemodynamic studies. Due to the fact that the present study was limited to a single patient, studies on more patients would be required to further confirm the findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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 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".