LAUSR

Précis: Two novel, quantitative metrics, and 1 traditional metric were able to distinguish between many, but not all healthy and glaucomatous eyes in the bottom 5th percentile of global circumpapillary retinal nerve fiber layer (cpRNFL) thickness. Purpose: To test the hypothesis that objective optical coherence tomography measures can distinguish between a healthy control with global cpRNFL thickness within the lower 5% of normal and a glaucoma patient with an equivalent cpRNFL thickness. Patients and Methods: A total of 37 healthy eyes from over 700 normative eyes fell within the bottom 5th percentile in global cpRNFL thickness. The global cpRNFL thickness of 35 glaucomatous eyes from 188 patients fell within the same range. For the traditional methods, the global cpRNFL thickness percentile and the global ganglion cell layer (GCL) thickness percentile for the central ±8 degrees, were calculated for all 72 eyes. For the novel cpRNFL method, the normalized root mean square (RMS) difference between the cpRNFL thickness profile and the global thickness–matched normative thickness profile was calculated. For the superior-inferior (SI) GCL method, the normalized mean difference in superior and inferior GCL thickness was calculated for the central ±8 degrees. Results: The best quantitative metric, the RMS cpRNFL method, had an accuracy of 90% compared with 81% for the SI GCL and 81% for the global GCL methods. As expected, the global cpRNFL had the worst accuracy, 72%. Similarly, the RMS cpRNFL method had an area under the curve of 0.93 compared with 0.83 and 0.84 for the SI GCL and global GCL methods, respectively. The global cpRNFL method had the worst area under the curve, 0.75. Conclusion: Quantitative metrics can distinguish between most of the healthy and glaucomatous eyes with low global cpRNFL thickness. However, even the most successful metric, RMS cpRNFL, missed some glaucomatous eyes.