Why the study?
Patients with Alzheimer's disease have cerebral hemodynamic disorders, but quantitative measurement of intracranial hemodynamics and their role in disease progression required further exploration using novel computational fluid dynamics modeling.
Does a computational fluid dynamics (CFD) model identify differences in cerebral blood flow and cerebrovascular resistance in patients with Alzheimer's disease compared to healthy controls?
Does a computational fluid dynamics (CFD) model identify differences in cerebral blood flow and cerebrovascular resistance in patients with Alzheimer's disease compared to healthy controls?
Computational fluid dynamics reveals that patients with Alzheimer's disease have significantly lower cerebral blood flow and higher cerebrovascular resistance, suggesting hemodynamic dysfunction is involved in AD progression.
Exploratory CFD modeling of AD hemodynamics is hypothesis-generating; leaves open validation for progression monitoring or risk stratification.
Background: It has gradually recognized that the patients with Alzheimer’s disease (AD) have cerebral hemodynamic disorders. The purpose of the present study was to exploit a novel computational fluid dynamics (CFD) model, which could be used to measure intracranial hemodynamics quantitively in AD patients and to further explore how the hemodynamic changes are involved in progression of AD.Methods: A novel CFD model was constructed by personal magnetic resonance angiography (MRA), vessel ultrasound and blood pressure value of all subjects, of whom included AD patients, vascular dementia (VaD) patients and well-matched healthy controls (HCs). Demographic, clinical and imaging data of all subjects were recorded and analyzed. Quantitative total cerebral blood flow (CBF) and cerebrovascular resistance (CVR) were compared among three groups, in order to ascertain the potential hemodynamic disorders in AD patients.Results: Total CBF and CVR of AD patients were significantly different from those of HCs (both P<0.01), but not different from patients with VaD (both P>0.5), despite the cerebral arteries in AD patients were anatomically intact. Total CBF was negatively correlated with total CVR (rs=-0.822, P<0.001) in AD patients. Comparing with HCs, Elevated CVR (OR=2.25, P=0.004) and age ( OR=2.06, P=0.021) were independent risk factor of AD.Conclusions: CFD can be applied to non-invasively and conveniently quantify and visualize biomechanical changes of cerebral blood flow. Patients with AD have dysfunction of cerebral hemodynamic, including lower CBF and higher CVR, and the CVR was an independent risk factor of AD. These findings provide quantitative evidence to support that increase of cerebrovascular resistance may involve in development of AD.
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Xie et al. (2020) studied this question.
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