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PURPOSE: To correlate the dimension of the visual field (VF) tested by Goldman kinetic perimetry with the extent of visibility of the highly reflective layer between inner and outer segments of photoreceptors (IOS) seen in optical coherence tomography (OCT) images in patients with retinitis pigmentosa (RP). METHODS: In a retrospectively designed cross-sectional study, 18 eyes of 18 patients with RP were examined with OCT and Goldmann perimetry using test target I4e and compared with 18 eyes of 18 control subjects. A-scans of raw scan data of Stratus OCT images (Carl Zeiss Meditec, AG, Oberkochen, Germany) were quantitatively analyzed for the presence of the signal generated by the highly reflective layer between the IOS in OCT images. Starting in the fovea, the distance to which this signal was detectable was measured. Visual fields were analyzed by measuring the distance from the center point to isopter I4e. OCT and visual field data were analyzed in a clockwise fashion every 30 degrees , and corresponding measures were correlated. RESULTS: In corresponding alignments, the distance from the center point to isopter I4e and the distance to which the highly reflective signal from the IOS can be detected correlate significantly (r = 0.75, P < 0.0001). The greater the distance in VF, the greater the distance measured in OCT. CONCLUSIONS: The authors hypothesize that the retinal structure from which the highly reflective layer between the IOS emanates is of critical importance for visual and photoreceptor function. Further research is warranted to determine whether this may be useful as an objective marker of progression of retinal degeneration in patients with RP.

Original publication




Journal article


Invest Ophthalmol Vis Sci

Publication Date





3617 - 3621


Cross-Sectional Studies, Diagnostic Techniques, Ophthalmological, Electroretinography, Humans, Photoreceptor Cells, Vertebrate, Prospective Studies, Retinitis Pigmentosa, Retrospective Studies, Tomography, Optical Coherence, Vision Disorders, Visual Field Tests, Visual Fields