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  • Title: Glaucoma Diagnostic Ability of the New Circumpapillary Retinal Nerve Fiber Layer Thickness Analysis Based on Bruch's Membrane Opening.
    Author: Lee EJ, Lee KM, Kim H, Kim TW.
    Journal: Invest Ophthalmol Vis Sci; 2016 Aug 01; 57(10):4194-204. PubMed ID: 27548890.
    Abstract:
    PURPOSE: To compare the diagnostic ability of the new spectral-domain optical coherence tomography (SD-OCT) algorithm for measuring circumpapillary retinal nerve fiber layer (RNFL) thickness centered on Bruch's membrane opening (BMO), with the conventional circumpapillary RNFL thickness measurement centered on the optic disc. METHODS: In 75 eyes with primary open-angle glaucoma (POAG) and 71 healthy control eyes, circumpapillary RNFL thickness was measured with SD-OCT, first by centering the scan circle on the optic disc (RNFLDi), and then on the BMO (RNFLBMO). Difference between the topographic profiles of RNFLDi and RNFLBMO was compared and factors influencing any discrepancies between methods were investigated. Glaucoma diagnostic abilities of each method were assessed using the areas under receiver operating characteristic curve (AUCs). RESULTS: Axial length did not differ between POAG and healthy eyes. A longer axial length and larger width of externally oblique border tissue (BT) associated with tilted optic disc were the two major factors influencing discrepancies between RNFLBMO and RNFLDi (both P < 0.001). Compared with RNFLBMO, RNFLDi tended to result in a thinner nasal RNFL in eyes with externally oblique BT, while RNFLBMO and RNFLDi were comparable in eyes without externally oblique BT. The glaucoma diagnostic capabilities were generally comparable, but RNFLBMO was superior to RNFLDi in eyes having a larger width (>250 μm) of externally oblique BT (AUC = 0.933 vs. 0.843, respectively, P = 0.027). CONCLUSIONS: The new circumpapillary RNFL scanning algorithm centered on BMO may provide a more reliable RNFL profile in eyes with tilted optic discs, with a largely comparable glaucoma diagnostic ability to the conventional algorithm.
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