Corvis ST Helpful in Glaucoma Assessment

AI model shows high accuracy in predicting glaucoma progression.

DERMOT MCGRATH REPORTS

Visual field progression in open-angle glaucoma (OAG) can be predicted with relatively high accuracy using an artificial intelligence (AI) prediction model applied to measurements obtained using an ultra-high-speed tonometry device (Corvis ST, Oculus), according to a study presented at the 27th ESCRS Winter Meeting.

“Visual field progression can be predicted with relatively high accuracy using Corvis ST measurements registered one month after prostaglandin analogues treatment,” said Dr Marta I Martínez-Sánchez. “The moment of maximum concavity of the cornea seems crucial for estimating the risk of progression.”

The early identification of potential fast progressors could have an evident clinical benefit, she noted.

“Identifying fast progressors would allow better optimization of resources by focusing more on these at-risk eyes,” she explained. “In addition, the prognosis of our patients could be improved because we can be more aggressive in the treatment and follow-up in those eyes with predicted high risk of progression.”

Explaining the background to the study, Dr Martínez-Sánchez said she and her co-workers set out to create an AI algorithm to predict the risk of visual field progression in 65 eyes of newly diagnosed and treatment-naive patients with early open-angle glaucoma or ocular hypertension using measurements derived from several different sources: Goldmann applanation tonometry, Ocular Response Analyzer

(ORA, Reichert), and Corvis ST Dynamic Corneal Response (DCR) parameters. The measurements were taken at baseline and one, three, and six months after initiating therapy with prostaglandin analogues.

The team tested different AI models to achieve the best predictions evaluated by their accuracy and area under the curve (AUC). The predictive variables were then analysed to assess which were more relevant for the final prediction of the visual field progression as determined by Humphrey VF analyser (Carl Zeiss Meditec).

“Defining visual progression is not easy, so we took into account different ways of evaluating progression,” she said. “We included the Advanced Glaucoma Intervention Study (AGIS) defect score as well as trend analysis, expert analysis, and event-based analysis. In the artificial intelligence algorithm, we included all forms of defining VF progression, although we gave more importance to event-based analysis as a marker of progression.”

The most accurate data predictors were those registered at the one-month follow-up using the Corvis ST parameters, predicting glaucomatous progression with an accuracy of 86.2%. The main variables involved in the prediction were the arc length at the moment of maximum concavity, the time from deformation onset to maximum concavity, and the corneal deflection length at the time of maximum concavity.

“This was consistent across different algorithms, and we also found the results did not improve by including baseline variables or additional variables such as corneal hysteresis or IOP values,” she said.