Purpose: This study aimed to calculate a predicted integrated visual field (IVF) based on predicted monocular visual fields (MVFs) derived, with a new method, from wide-scan optical coherence tomography (OCT) data. Materials and Methods: Visual field testing used the central (6 × 4) 24 points of the Humphrey Field Analyzer 24-2 program. OCT scans of a corresponding retinal area, centered on the fovea, were divided into a 6 × 4 grid. The thickness of the macular retinal nerve fiber layer (mRNFL), ganglion cell layer + inner plexiform layer (GCIPL), and mRNFL + GCIPL (GCC) was measured in each grid area. Next, a support vector machine was used to create a MVF prediction model, with training data from 101 eyes of 60 glaucoma patients. Then, the prediction model was validated with data from 108 eyes of 54 glaucoma patients, for MVF and IVF. A simulated IVF was created by merging bilateral simulated MVFs. Results: The overall average of the median 95% prediction interval length for the MVF prediction model (measured in dB) was 10.0, 18.3, and 11.3 for the mRNFL, GCIPL, and GCC, respectively. In the validation data, the overall average root mean squared error (dB) between actual and predicted sensitivity for the IVF was 9.6, 10.5, and 9.5 for the mRNFL, GCIPL, and GCC, respectively, in the 24 grid areas. The intraclass correlation coefficient between average actual and predicted IVF was 0.61, 0.44, and 0.59 in the mRNFL, GCIPL, and GCC, respectively, in the 24 grid areas. Conclusions: We calculated a predicted IVF based on predicted MVFs that were derived, with a new method, from OCT data and validated the accuracy of the calculated IVF. This technique should improve glaucoma management in cases when standard visual field testing is difficult.
ASJC Scopus subject areas
- Sensory Systems
- Cellular and Molecular Neuroscience