Efficacy of Visual Retraining in the Hemianopic Field after Stroke: Results of a Randomized Clinical Trial

Digital therapeutics using virtual reality-based visual perceptual learning for visual field defects in stroke: A double-blind randomized trial

INTRODUCTION

Visual field defects (VFDs) represent a debilitating poststroke complication, characterized by unseen parts of the visual field. Visual perceptual learning (VPL), involving repetitive visual training in blind visual fields, may effectively restore visual field sensitivity in cortical blindness. This current multicenter, double-blind, randomized, controlled clinical trial investigated the efficacy and safety of VPL-based digital therapeutics (Nunap Vision [NV]) for treating poststroke VFDs.

METHODS

Stroke outpatients with VFDs (>6 months after stroke onset) were randomized into NV (defective field training) or Nunap Vision-Control (NV-C, central field training) groups. Both interventions provided visual perceptual training, consisting of orientation, rotation, and depth discrimination, through a virtual reality head-mounted display device 5 days a week for 12 weeks. The two groups received VFD assessments using Humphrey visual field (HVF) tests at baseline and 12-week follow-up. The final analysis included those completed the study (NV, n = 40; NV-C, n = 35). Efficacy measures included improved visual area (sensitivity ≥6 dB) and changes in the HVF scores during the 12-week period.

RESULTS

With a high compliance rate, NV and NV-C training improved the visual areas in the defective hemifield (>72 degrees2) and the whole field (>108 degrees2), which are clinically meaningful improvements despite no significant between-group differences. According to within-group analyses, mean total deviation scores in the defective hemifield improved after NV training (p = .03) but not after NV-C training (p = .12).

CONCLUSIONS

The current trial suggests that VPL-based digital therapeutics may induce clinically meaningful visual improvements in patients with poststroke VFDs. Yet, between-group differences in therapeutic efficacy were not found as NV-C training exhibited unexpected improvement comparable to NV training, possibly due to learning transfer effects.

Training in cortically-blind fields confers patient-specific benefit against retinal thinning after occipital stroke

Purpose

Damage to the adult primary visual cortex (V1) causes vision loss in the contralateral hemifield, initiating a process of trans-synaptic retrograde degeneration (TRD). Here, we examined retinal correlates of TRD using a new metric to account for global changes in inner retinal thickness, and asked if perceptual training in the intact or blind field impacts its progression.

Methods

We performed a meta-analysis of optical coherence tomography (OCT) data in 48 participants with unilateral V1 stroke and homonymous visual defects, who completed clinical trial NCT03350919. After measuring the thickness of the macular ganglion cell and inner plexiform layers (GCL-IPL), and the peripapillary retinal nerve fiber layer (RNFL), we computed individual laterality indices (LI) at baseline and after ~6 months of daily motion discrimination training in the intact- or blind-field. Increasingly positive LI denoted greater layer thinning in retinal regions affected versus unaffected by the cortical damage.

Results

Pre-training, the affected GCL-IPL and RNFL were thinner than their unaffected counterparts, generating LI values positively correlated with time since stroke. Participants trained in their intact-field exhibited increased LIGCL-IPL. Those trained in their blind-field had no significant change in LIGCL-IPL. LIRNFL did not change in either group.

Conclusions

Relative shrinkage of the affected versus unaffected macular GCL-IPL can be reliably measured at an individual level and increases with time post-V1 stroke. Relative thinning progressed during intact-field training, but appeared to be halted by training within the blind field, suggesting a potentially neuroprotective effect of this simple behavioral intervention.

Linking Multi-Modal MRI to Clinical Measures of Visual Field Loss After Stroke

Loss of vision across large parts of the visual field is a common and devastating complication of cerebral strokes. In the clinic, this loss is quantified by measuring the sensitivity threshold across the field of vision using static perimetry. These methods rely on the ability of the patient to report the presence of lights in particular locations. While perimetry provides important information about the intactness of the visual field, the approach has some shortcomings. For example, it cannot distinguish where in the visual pathway the key processing deficit is located. In contrast, brain imaging can provide important information about anatomy, connectivity, and function of the visual pathway following stroke. In particular, functional magnetic resonance imaging (fMRI) and analysis of population receptive fields (pRF) can reveal mismatches between clinical perimetry and maps of cortical areas that still respond to visual stimuli after stroke. Here, we demonstrate how information from different brain imaging modalities-visual field maps derived from fMRI, lesion definitions from anatomical scans, and white matter tracts from diffusion weighted MRI data-provides a more complete picture of vision loss. For any given location in the visual field, the combination of anatomical and functional information can help identify whether vision loss is due to absence of gray matter tissue or likely due to white matter disconnection from other cortical areas. We present a combined imaging acquisition and visual stimulus protocol, together with a description of the analysis methodology, and apply it to datasets from four stroke survivors with homonymous field loss (two with hemianopia, two with quadrantanopia). For researchers trying to understand recovery of vision after stroke and clinicians seeking to stratify patients into different treatment pathways, this approach combines multiple, convergent sources of data to characterize the extent of the stroke damage. We show that such an approach gives a more comprehensive measure of residual visual capacity-in two particular respects: which locations in the visual field should be targeted and what kind of visual attributes are most suited for rehabilitation.