Multiscale modeling of blood circulation with cerebral autoregulation and network pathway analysis for hemodynamic redistribution in the vascular network with anatomical variations and stenosis conditions

TL;DR

This study develops a multiscale, image-informed model of cerebral blood flow regulation that simulates flow redistribution in the Circle of Willis under various anatomical and stenotic conditions, revealing key collateral activation patterns.

Contribution

The paper introduces a coupled systemic and cerebral arterial network model with autoregulation, enabling detailed simulation of collateral flow dynamics in response to structural variations and stenosis.

Findings

Baseline simulations match clinical flow distributions with minimal cross-flow.

Anatomical variations activate specific collateral pathways, notably the ACoA.

Progressive stenosis leads to flow reversal and network reconfiguration consistent with experimental data.

Abstract

Cerebral hemodynamics is fundamentally regulated by the Circle of Willis (CoW), which redistributes flow through communicating arteries to stabilize perfusion under anatomical variations and vascular stenosis. In this study, we develop a multiscale circulation model by coupling a systemic hemodynamic framework with a cerebral arterial network reconstructed from medical imaging. The model incorporates a cerebral autoregulation mechanism (CAM) and enables quantitative simulation of flow redistribution within the CoW under normal, anatomically varied, and stenotic conditions. Baseline simulations reproduce physiological flow distributions in which communicating arteries remain nearly inactive, showing negligible cross-flow and agreement with clinical measurements. In contrast, anatomical variations reveal distinct collateral activation patterns: the anterior communicating artery (ACoA) emerges as the earliest and most sensitive functional collateral, whereas the posterior communicating arteries (PCoAs) exhibit structure-dependent engagement. Progressive stenosis simulations further demonstrate a transition from a complete CoW to a fetal-type posterior cerebral artery (PCA) configuration, characterized by early ACoA flow reversal followed by ipsilateral PCoA activation, consistent with experimental and transcranial Doppler observations. Finally, a path-based quantitative analysis is introduced to illustrate how the cerebral vascular network dynamically reconfigures collateral pathways in response to structural changes. Overall, the proposed framework provides a physiologically interpretable, image-informed tool for investigating cerebral flow regulation through functional collaterals within the CoW, with potential applications in the diagnosis and treatment planning of cerebrovascular diseases.