Date of Award
Master of Science
Richard N. Nzokwe
Purpose: To evaluate functional and structural deficits in a canine model of compressive optic neuropathy (CON).
Methods: CON was induced in healthy beagles by implanting a silicone implant into the orbit and inducing optic nerve compression for 24 hours. Retinal nerve fiber layer (RNFL) thickness was evaluated using optical coherence tomography (OCT). Pattern electroretinography (pERG) was performed to evaluate retinal ganglion cell (RGC) function 10 minutes and 30, 90 and 180 days after CON induction.
Results: Optic nerve compression resulted in significant immediate pERG deficits (P50-N95=0.4+0.1yV; mean+SEM) when compared to control (6.2+0.4 yV; p<0.0001). Analysis of OCT scans in the area centralis immediately after compression showed significant increase in RNFL thickness in CON dogs (39.5+1.8 ym) when compared to control values (26.4+1.5 ym, p<0.0001). Increased area centralis RNFL thickness correlated significantly with pERG deficits (r2= 0.43, p=0.03). Analysis of peripapillary RNFL showed significantly decreased thickness (p=0.0098), which did not correlate with pERG deficits. Analysis of area centralis showed progressive loss of RNFL thickness at 90 and 180 days post compression. PERG amplitudes showed significant recovery at 90 days post compression (p<0.05), but this effect was gone by 180 days. Full-field ERG recordings did not reveal deficits at any time.
Conclusions: CON resulted in initial thickening of area centralis RNFL, followed by progressive RNFL loss. Pattern ERG analysis showed significant temporary improvement in RGC function. Inclusion of large retinal blood vessel profile in peripapillary RNFL analysis seems to decrease detection sensitivity and specificity for RNFL changes in early stages of compressive injury.
Richard Nzoyem Nzokwe
Nzokwe, Richard Nzoyem, "Characterization of functional and structural deficits in a canine model of compressive optic neuropathy using optical coherence tomography and pattern electroretinography" (2011). Graduate Theses and Dissertations. 10232.