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J.C. Fleischhauer, D. Barthelmes, F.K. Sutter, M. Kurz–Levin, M.M. Bosch, G. Niemeyer, H. Helbig; Quantitative OCT Imaging in Patients With Cone–Dystrophies . Invest. Ophthalmol. Vis. Sci. 2005;46(13):544.
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© ARVO (1962-2015); The Authors (2016-present)
To evaluate OCT changes in the retina in patients with cone–dystrophies compared to healthy individuals (normals).
Prospective study in patients with cone–dystrophies. Diagnosis of cone–dystrophy was established by the following: vision testing (Snellen and EDTRS), slit lamp examination, color vision testing (Panel D15), Ganzfeld–ERG recording (ISCEV standard). 3 groups were established according to clinical findings. Group 1 included patients with a best corrected vision (BCVA) <= 0.2 Snellen, group 2 patients with a BCVA between 0.4 and 0.6 and group 3 patients with a BCVA >= 0.8. Patients with any accompanying diseases (including macular edema) were excluded. OCT imaging was done with Zeiss Stratus OCT 3. OCT images were analyzed calculating density profiles from 20 scan–lines through the fovea. Profiles were averaged and analyzed quantitatively for retinal thickness and distances between different retinal reflectivity layers (4 intensity peaks).
A normal OCT profile contains 4 peaks (P1–P4) presumably representing: RPE (P1), a highly reflective layer delimiting inner and outer rod segments (P2), outer limiting membrane (P3) and inner limiting membrane (P4), (subjective correlation with retinal anatomy). With decreasing BCVA, retinal thickness (distance P1–P4) as well as relative reflection maximum of P2 and cone–driven ERG amplitudes decrease. P3 can only be found in group 3 and normals. Mean retinal thickness (distance P1 to P4) was significantly different from normals in group 1 and group 2 but not in group 3.
We show that OCT recordings can be interpreted quantitatively and might be used for diagnosing and distinguishing retinal diseases affecting the photoreceptors. OCT images in cone dystrophy show a distinctive pattern. OCT recordings in cone–dystrophies might help classifying the disease stage and might help diagnosing early forms.
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