Sümbül U, Zlateski A, Vishwanathan A, Masland RH, Seung SH.
Automated computation of arbor densities: a step toward identifying neuronal cell types. Front Neuroanat 2014;8:139.
AbstractThe shape and position of a neuron convey information regarding its molecular and functional identity. The identification of cell types from structure, a classic method, relies on the time-consuming step of arbor tracing. However, as genetic tools and imaging methods make data-driven approaches to neuronal circuit analysis feasible, the need for automated processing increases. Here, we first establish that mouse retinal ganglion cell types can be as precise about distributing their arbor volumes across the inner plexiform layer as they are about distributing the skeletons of the arbors. Then, we describe an automated approach to computing the spatial distribution of the dendritic arbors, or arbor density, with respect to a global depth coordinate based on this observation. Our method involves three-dimensional reconstruction of neuronal arbors by a supervised machine learning algorithm, post-processing of the enhanced stacks to remove somata and isolate the neuron of interest, and registration of neurons to each other using automatically detected arbors of the starburst amacrine interneurons as fiducial markers. In principle, this method could be generalizable to other structures of the CNS, provided that they allow sparse labeling of the cells and contain a reliable axis of spatial reference.
Sun JK, Lin MM, Lammer J, Prager S, Sarangi R, Silva PS, Aiello LP.
Disorganization of the retinal inner layers as a predictor of visual acuity in eyes with center-involved diabetic macular edema. JAMA Ophthalmol 2014;132(11):1309-16.
AbstractIMPORTANCE: Biomarkers that predict future visual acuity (VA) in eyes with baseline diabetic macular edema (DME) would substantively improve risk assessment, management decisions, and selection of eyes for clinical studies targeting DME. OBJECTIVE: To determine whether baseline or early change in the novel spectral domain-optical coherence tomography (SD-OCT) parameter disorganization of the retinal inner layers (DRIL) is predictive of VA in eyes with center-involved DME. DESIGN, SETTING, AND PARTICIPANTS: At a tertiary care referral center for diabetic eye disease, a retrospective, longitudinal cohort study obtained demographics, VA, and SD-OCT images from baseline, 4-month, and 8-month visits in 96 participants (120 eyes) with diabetes mellitus and baseline center-involved DME (SD-OCT central subfield thickness, ≥ 320 µm for men and ≥ 305 µm for women). Exclusion criteria included substantial media opacity, cataract surgery within 6 months, and nondiabetic retinal pathology affecting VA. On SD-OCT, the 1-mm-wide retinal area centered on the fovea was evaluated by masked graders for DRIL extent, cysts, hyperreflective foci, microaneurysms, cone outer segment tip visibility, and external limiting membrane or photoreceptor disruption and reflectivity. MAIN OUTCOMES AND MEASURES: Visual acuity and SD-OCT-derived retinal morphology. RESULTS: Greater DRIL extent at baseline correlated with worse baseline VA (point estimate, 0.04; 95% CI, 0.02-0.05 per 100 µm; P < .001). An increase in DRIL during 4 months was associated with VA worsening at 8 months (point estimate, 0.03; 95% CI, 0.02-0.05 per 100 µm; P < .001). A multivariate model that included a 4-month change in VA, DRIL, and external limiting membrane disruption was predictive of an 8-month VA change (r = 0.80). Each approximately 300-µm DRIL increase during 4 months predicted a 1-line, 8-month VA decline. When DRIL increased at least 250 µm at 4 months, no eyes had VA improvement of at least 1 line at 8 months. When DRIL decreased at least 250 µm at 4 months, no eyes had VA decline of at least 1 line at 8 months, and 77.7% had VA improvement of at least 1 line. CONCLUSIONS AND RELEVANCE: Disorganization of the retinal inner layers in the 1-mm foveal area is associated with VA, and change in DRIL predicts future change in VA. Early change in DRIL prospectively identifies eyes with a high likelihood of subsequent VA improvement or decline. Therefore, DRIL warrants further study as a robust, readily obtained, and noninvasive biomarker of future VA response in eyes with DME.