Chromatic pupillometry dissects function of the three different light-sensitive retinal cell populations in RPE65 deficiency.

PURPOSE: The aim of the study was to objectively characterize the function of rods, cones, and intrinsic photosensitive retinal ganglion cells (ipRGCs) in patients with RPE65 mutations by using two published protocols for chromatic pupillometry, and to correlate the data with the clinical phenotype. METHODS: The study group comprised 11 patients with RPE65 mutations, and for control purposes, 32 healthy probands and 2 achromats. A custom-made binocular chromatic pupillometer (Bino I) connected to a ColorDome Ganzfeld stimulator was used to assess changes in pupil diameter in response to red (640 nm) and blue (462 nm) light stimuli. Light intensities, stimulus duration, and background varied depending on the protocol used. Results were compared to the clinical phenotype, that is, visual field (Goldmann perimetry), best corrected visual acuity, and full-field stimulus testing (FST). RESULTS: No significant differences in any of the pupil response parameters were observed in intraday or intervisit variability tests. Pupil responses to rod-weighted stimulation were significantly diminished in all RPE65 patients. Pupil responses to cone-weighted stimuli differed among RPE65 patients and did not always correlate with residual visual field and cone sensitivity loss in FST. Pupil responses to ipRGC-weighted answers were slightly but significantly diminished, and the postillumination pupil response was significantly increased. CONCLUSIONS: Chromatic pupillometry represents a highly sensitive and objective test to quantify the function of rods, cones, and ipRGCs in patients with RPE65 mutations.

Automated segmentation of retinal blood vessels in spectral domain optical coherence tomography scans.

The correct segmentation of blood vessels in optical coherence tomography (OCT) images may be an important requirement for the analysis of intra-retinal layer thickness in human retinal diseases. We developed a shape model based procedure for the automatic segmentation of retinal blood vessels in spectral domain (SD)-OCT scans acquired with the Spectralis OCT system. The segmentation procedure is based on a statistical shape model that has been created through manual segmentation of vessels in a training phase. The actual segmentation procedure is performed after the approximate vessel position has been defined by a shadowgraph that assigns the lateral vessel positions. The active shape model method is subsequently used to segment blood vessel contours in axial direction. The automated segmentation results were validated against the manual segmentation of the same vessels by three expert readers. Manual and automated segmentations of 168 blood vessels from 34 B-scans were analyzed with respect to the deviations in the mean Euclidean distance and surface area. The mean Euclidean distance between the automatically and manually segmented contours (on average 4.0 pixels respectively 20 µm against all three experts) was within the range of the manually marked contours among the three readers (approximately 3.8 pixels respectively 18 µm for all experts). The area deviations between the automated and manual segmentation also lie within the range of the area deviations among the 3 clinical experts. Intra reader variability for the experts was between 0.9 and 0.94. We conclude that the automated segmentation approach is able to segment blood vessels with comparable accuracy as expert readers and will provide a useful tool in vessel analysis of whole C-scans, and in particular in multicenter trials.