Retinal vessel multifractals predict pial collateral status in patients with acute ischemic stroke

Area of Science:

• Neuroscience
• Ophthalmology
• Medical Imaging

Background:

• Pial collateral blood flow significantly influences outcomes in acute ischemic stroke.
• Assessing pial collateral status is crucial for stroke management and prognosis.

Purpose of the Study:

• To investigate if retinal vessel metrics can predict pial collateral status in acute ischemic stroke patients.
• To explore the relationship between retinal vessel characteristics and stroke severity.

Main Methods:

• Computed tomography angiography (CTA) was used to grade pial collateral status in 35 acute ischemic stroke patients.
• Retinal fundus images were analyzed for multifractal dimensions and standard retinal metrics.
• Support vector machine learning was employed to develop a classifier for pial collateral status.

Main Results:

• Patients with poor pial collaterals had higher NIHSS and mRS scores.
• Elevated multifractal dimensions (D0, D1, f(α)max) of retinal vessels were observed in patients with poor pial collaterals.
• A support vector machine classifier demonstrated fair sensitivity (0.743) and specificity (0.707) in differentiating poor from good collateral status.

Conclusions:

• This study is the first to demonstrate increased retinal vessel multifractal dimensions in acute ischemic stroke patients with poor pial collaterals.
• A novel retinal vessel classifier can potentially identify patients with poor collateral status non-invasively.
• These findings may lead to improved stroke outcome prediction and management strategies.