@article {647366, title = {Facilitating Glaucoma Diagnosis With Intereye Retinal Nerve Fiber Layer Asymmetry Using Spectral-Domain Optical Coherence Tomography.}, journal = {J Glaucoma}, volume = {25}, number = {2}, year = {2016}, month = {2016 Feb}, pages = {167-76}, abstract = {PURPOSE: To test whether increased intereye retinal nerve fiber layer (RNFL) asymmetry may be indicative of glaucoma. To determine the best statistical methods and intereye RNFL cutoffs for differentiating between normal and glaucoma subjects to better alert clinicians to early glaucomatous damage. METHODS: Sixty-six primary open-angle glaucoma (OAG) and 40 age-matched normal subjects had both eyes imaged at the Massachusetts Eye and Ear Infirmary with a commercially available spectral-domain optical coherence tomography (OCT) machine. Statistical methodologies were used to find cutoffs that achieved the best sensitivities and specificities for differentiating OAG from normal subjects. RESULTS: Intereye RNFL asymmetry for global average, all quadrants, and all sectors was significantly greater in OAG than normal subjects. Intereye RNFL asymmetry for global average showed the greatest statistical difference (P\<0.001) between OAG (23.64{\textpm}14.90 μm) and normal eyes (3.58{\textpm}3.96 μm), with 6.60 times greater asymmetry in OAG eyes. The inferior quadrant showed the second greatest difference, with 3.91 times greater asymmetry in OAG eyes. Using a statistically determined cutoff of 6.0 μm as abnormal, intereye RNFL asymmetry for global average achieved a sensitivity of 74.24\% and specificity of 90\% in differentiating between normal and OAG subjects, achieving a better combination of sensitivity and specificity than intereye RNFL asymmetry of any quadrant or sector. CONCLUSIONS: Intereye RNFL asymmetry may be a useful clinical OCT measurement to provide quantitative assessment of early glaucomatous damage. Newly developed algorithms for intereye RNFL asymmetry may improve the ability to detect glaucoma.}, issn = {1536-481X}, doi = {10.1097/IJG.0000000000000080}, author = {Field, Matthew G and Alasil, Tarek and Baniasadi, Neda and Que, Christian and Simavli, Huseyin and Sobeih, Doaa and Sola-Del Valle, David and Best, Matthew J and Chen, Teresa C} }