Measuring residual visual function after cerebral damage - a potential path for optimising rehabilitation approaches.

Area of Science:

• Neuroimaging
• Clinical Neuroscience
• Visual Science

Background:

• Visual field integrity is typically assessed via subjective perimetry or objective functional magnetic resonance imaging (fMRI).
• Central visual pathway lesions, such as those from strokes, can result in cortical sparing not evident from perimetry or lesion anatomy alone.
• Variability in spared cortical areas exists even with stereotypical perimetry results like hemianopia or quadrantanopia.

Purpose of the Study:

• To explore the utility of fMRI visual field mapping for identifying residual visual function in patients with central visual pathway damage.
• To highlight fMRI's potential as a guide for optimizing rehabilitation strategies in stroke survivors and individuals with cerebral visual impairment (CVI).
• To integrate neuroimaging data with other clinical assessments for a comprehensive understanding of visual function.

Main Methods:

• Review of recent neuroimaging literature focusing on residual visual function, anatomy, and structural connectivity in stroke survivors.
• Discussion of current rehabilitation approaches for visual pathway damage.
• Proposal of a brain imaging-based approach for characterizing visual function in individuals with CVI.

Main Results:

• fMRI visual field maps can objectively quantify visual function and reveal cortical areas spared by lesions, which may be missed by traditional perimetry.
• Objective mapping of residual visual function provides a richer clinical picture when combined with standardized tests, anatomical scans, and tractography.
• Neuroimaging approaches hold promise for personalized visual rehabilitation and understanding visual developmental disorders like CVI.

Conclusions:

• fMRI visual field mapping offers a valuable, objective tool for assessing visual function and guiding rehabilitation after central visual pathway damage.
• Integrating fMRI with other clinical data enhances the characterization of visual deficits and informs personalized treatment strategies.
• This approach is particularly relevant for conditions like cerebral visual impairment (CVI), where traditional assessments may be insufficient.