Unsupervised AI can help identify central visual field loss patterns
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Using artificial intelligence to identify central visual field loss patterns better predicted quality of life impairment in patients with glaucoma compared with using central visual field mean deviation alone, according to findings from a retrospective study.
“The preservation of central visual function is essential to the care of glaucoma patients,” Mengyu Wang, PhD, of the Schepens Eye Research Institute, Harvard Medical School, and colleagues wrote.
Wang and colleagues used visual field data from the Glaucoma Research Network consortium for their analysis. The study comprised 8,712 patients with 13,951 Humphrey 10-2 (Carl Zeiss Meditec) test results from 13,951 eyes for cross-sectional analyses and 824 patients with a minimum of five reliable 10-2 test results at 6-month intervals or more from 1,191 eyes for longitudinal analyses.
Researchers used total deviation values to determine central visual field patterns using patients' most recent 10-2 test results. They also used a 24-2 VF within a 3-month window of the 10-2 tests to stage eyes into mild, moderate or severe functional loss. To determine central visual field patterns, they applied an unsupervised AI (archetypal analysis).
The AI identified 17 central visual field patterns for eyes with all severities of functional loss. Further, 11 central visual field patterns were determined for mild glaucoma, 11 for moderate glaucoma and 16 for severe glaucoma. Several arcuate defect patterns were found among the 17 central visual field patterns, and most of the diffuse loss patterns preserved the less vulnerable zone. Similar central visual field defects across different glaucoma stages and unique central visual field defects specific to a certain glaucoma stage were observed. Researchers wrote that this could represent different subtypes of central visual field loss with different “underlying pathophysiologic features and biomarkers.
“The quantification of central visual field loss by spatial pattern analyses with archetypal analysis independently confirmed the observational findings of frequent arcuate defects and relative preservation of the inferotemporal less vulnerable zone,” they said.
“Our model could be used by clinicians to decide which patients or eyes need to be treated more aggressively to slow down visual field worsening,” they concluded. “More work is needed to demonstrate the correlation between central visual field patterns and the structural damage, perhaps using macular ganglion cell thickness maps.”
Perspective
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Lisa M. Young, OD, FAAO
Central 10-2 visual field testing used to be reserved for managing advanced cases of glaucoma, but its recently discovered significance has changed the way we approach our testing strategy.
What’s the benefit of testing 10-2? This test pattern gives us the ability to test the macula with a greater sensitivity, potentially revealing damage and subsequent vision impairments that would not be evident from 24-2 testing.
Does 10-2 replace 24-2 testing? Definitely not. It is used in conjunction with 24-2 testing to better assess central defects.
Does 10-2 have progression analysis? No, but in a retrospective analysis of 10-2 data, Wang and colleagues were able to use AI to identify central visual field loss patterns that were better at predicting quality of life impairment in patients with glaucoma compared with using central visual field mean deviation alone.
Is the 10-2 part of my practice? Absolutely. I am a believer in performing 10-2 testing earlier in the disease process. As clinicians, this test can potentially help us diagnose glaucoma sooner, detect progression earlier and help us better understand our patient’s visual difficulties.
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