Multi-Parametric Retinal Microvascular Functional Perfusion Imaging Based on Dynamic Fundus Fluorescence Angiography.

Area of Science:

• Ophthalmology
• Medical Imaging
• Biomedical Engineering

Background:

• Retinal microvascular disease is a major cause of visual impairment worldwide.
• Current imaging techniques struggle with artifacts, hindering early diagnosis of microvascular damage and hemodynamic changes.
• Early and precise diagnosis is crucial for preventing vision loss.

Purpose of the Study:

• To develop and validate an FFA-based multi-parametric retinal microvascular functional perfusion imaging (RM-FPI) scheme.
• To precisely assess microstructural damage and quantify hemodynamic distribution in retinal microvasculature.
• To enable early and accurate diagnosis of retinal microvascular diseases.

Main Methods:

• Developed an FFA-based RM-FPI scheme using spatiotemporal filtering (singular value decomposition) and lognormal fitting to remove artifacts.
• Collected dynamic fundus fluorescein angiography (FFA) data from patients (n=7).
• Extracted retinal time-fluorescence intensity curves and estimated perfusion parameters post-filtering and fitting.

Main Results:

• RM-FPI significantly improved signal-to-clutter ratio (7.32 ± 0.43 dB), average contrast (14.34 ± 0.24 dB), and resolution (11.0 ± 2.0 µm) compared to unfiltered data.
• Successfully imaged retinal microvascular distribution and quantified spatial hemodynamic changes, revealing parabolic blood flow distribution.
• Demonstrated RM-FPI's capability to quantify, visualize, and diagnose retinal vein occlusion across severity levels.

Conclusions:

• The proposed RM-FPI scheme offers a method for artifact removal and precise hemodynamic quantification in retinal microvasculature.
• RM-FPI enables early and accurate diagnosis of retinal microvascular diseases, potentially preventing visual impairment.
• This technique could be beneficial in managing and preventing the progression of retinal microvascular conditions.