Abstract

Bilateral common carotid artery (CCA) stenosis (BCAS) is a useful model to mimic vascular cognitive impairment and dementia (VCID). However, current BCAS models have the disadvantages of high cost and incompatibility with MRI scanning due to metal implantation. We have established a new low-cost VCID model that better mimics human VCID and is compatible with live-animal MRI. The right and the left CCAs were temporarily ligated to 32 and 34 gauge needles with three ligations, respectively. After needle removal, CCA blood flow, cerebral blood flow, white matter injury (WMI) and cognitive function were measured. In male mice, needle removal led to ∼49.8% and ∼28.2% blood flow recovery in the right and left CCA, respectively. This model caused persistent and long-term cerebral hypoperfusion in both hemispheres (more severe in the left hemisphere), and WMI and cognitive dysfunction in about 90% of mice, which is more reliable compared to other models. Importantly, these pathological changes and cognitive impairments lasted for up to 24 weeks after surgery. The survival rate over 24 weeks was 81.6%. Female mice showed similar cognitive dysfunction, but a higher survival rate (91.6%) and relatively milder white matter injury. A novel, low-cost VCID model compatible with live-animal MRI with long-term outcomes was established.Significance StatementBCAS is an animal model mimicking carotid artery stenosis to study VCID. However, current BCAS models cost high cost and is incompatibility with MRI scanning due to metal implantation. We established a new asymmetric BCAS model by ligating the common carotid artery to various needle gauges followed by an immediate needle removal. Needle removal led to moderate stenosis in the right CCA and severe stenosis in the left CCA. This needle model replicates the hallmarks of VCID well in about 90% of mice, which is more reliable compared to other models, has ultra-low cost, and is compatible with MRI scanning in live animals. It will provide a new valuable tool and offer new insights for VCID research.

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