Predicting cerebrovascular age and its clinical relevance: Modeling using 3D morphological features of brain vessels.

Aging manifests as many phenotypes, among which age-related changes in brain vessels are important, but underexplored. Thus, in the present study, we constructed a model to predict age using cerebrovascular morphological features, further assessing their clinical relevance using a novel pipeline. Age prediction models were first developed using data from a normal cohort (n = 1181), after which their relevance was tested in two stroke cohorts (n = 564 and n = 455).

Global intracranial arterial tortuosity is associated with intracranial atherosclerotic burden.

The effect of arterial tortuosity on intracranial atherosclerosis (ICAS) is not well understood. This study aimed to evaluate the effect of global intracranial arterial tortuosity on intracranial atherosclerotic burden in patients with ischemic stroke. We included patients with acute ischemic stroke who underwent magnetic resonance angiography (MRA) and classified them into three groups according to the ICAS burden.

The effect of intensive statin therapy in non-symptomatic intracranial arteries: The STAMINA-MRI sub-study.

Background And Aims: Pleiotropic effects of statins result in the stabilization of symptomatic intracranial arterial plaque. However, little is known about the effect of statins in non-symptomatic cerebral arteries. We hypothesized that intensive statin therapy could produce a change in the non-symptomatic cerebral arteries.

Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity and inter-individual differences involved in this process have not been thoroughly studied. We used machine learning to examine the anatomical profile of the cerebral arterial tree.