A semi-automated technique for labeling and counting of apoptosing retinal cells.

BACKGROUND: Retinal ganglion cell (RGC) loss is one of the earliest and most important cellular changes in glaucoma. The DARC (Detection of Apoptosing Retinal Cells) technology enables in vivo real-time non-invasive imaging of single apoptosing retinal cells in animal models of glaucoma and Alzheimer's disease. To date, apoptosing RGCs imaged using DARC have been counted manually. This is time-consuming, labour-intensive, vulnerable to bias, and has considerable inter- and intra-operator variability. RESULTS: A semi-automated algorithm was developed which enabled automated identification of apoptosing RGCs labeled with fluorescent Annexin-5 on DARC images. Automated analysis included a pre-processing stage involving local-luminance and local-contrast "gain control", a "blob analysis" step to differentiate between cells, vessels and noise, and a method to exclude non-cell structures using specific combined 'size' and 'aspect' ratio criteria. Apoptosing retinal cells were counted by 3 masked operators, generating 'Gold-standard' mean manual cell counts, and were also counted using the newly developed automated algorithm. Comparison between automated cell counts and the mean manual cell counts on 66 DARC images showed significant correlation between the two methods (Pearson's correlation coefficient 0.978 (p < 0.001), R Squared = 0.956. The Intraclass correlation coefficient was 0.986 (95% CI 0.977-0.991, p < 0.001), and Cronbach's alpha measure of consistency = 0.986, confirming excellent correlation and consistency. No significant difference (p = 0.922, 95% CI: -5.53 to 6.10) was detected between the cell counts of the two methods. CONCLUSIONS: The novel automated algorithm enabled accurate quantification of apoptosing RGCs that is highly comparable to manual counting, and appears to minimise operator-bias, whilst being both fast and reproducible. This may prove to be a valuable method of quantifying apoptosing retinal cells, with particular relevance to translation in the clinic, where a Phase I clinical trial of DARC in glaucoma patients is due to start shortly.

The clinical translation of a measure of gain control: the contrast-contrast effect task.

The goal of the current project was to further develop a measure of gain control--the Contrast-Contrast Effect (CCE)--for use in clinical studies of schizophrenia. The CCE is based on an illusion in which presenting a medium contrast patch surrounded by a high-contrast patch induces individuals to perceive that center patch as having lower contrast than when the patch is presented in isolation. Thus, in the CCE, impaired gain control should lead to more accurate perceptions of the center patch. We tested 132 individuals with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, schizophrenia or schizoaffective disorder and 130 demographically similar healthy controls. The results indicated that the CCE effect can be obtained with standard equipment, simplified scoring, and a short interstimulus interval (100 ms), revealing a robust suppression of perceived contrast of the center patch when surrounded by a high-contrast annulus. Furthermore, we found a significant reduction in the effect of the high-contrast surround among individuals with schizophrenia, though the effect size was smaller than original reported by Dakin. However, when we eliminated subjects who performed poorly on "catch" trials that controlled for off-task performance, the reduced surround effect among patients was no longer significant in the main analyses. Importantly, this suggests that at least part of the reduced surround effect (if not all) in schizophrenia could be attributable to impaired attentional mechanisms that contribute to off-task performance. Additional analyses suggested that the length of the task could be shortened without losing power to detect surround effects in healthy individuals.