Ultra-widefield fundus fluorescein angiography in pediatric retinal vascular diseases

Purpose: To describe the utility of RetCam ultra-wide-field fundus fluorescein angiography in pediatric retinal vascular diseases. Methods: A retrospective chart review was carried out in 43 eyes of 22 pediatric patients who were diagnosed or suspected to have a retinal vascular disease. Fluorescein angiography was carried out using the 130 degree lens of RetCam 3. Fluorescein angiography guided treatment (laser/cryotherapy) was carried out wherever required. Results: Diseases studied included - coats disease, familial exudative vitreoretinopathy, retinopathy of prematurity, congenital retinal folds, double optic nerve head, persistent fetal vasculature and incontinentia pigmenti. RetCam assisted fluorescein angiography was helpful in establishing a diagnosis in 4 patients (18%), in decision making regarding treatment in 18 patients (82%), in deciding need for retreatment in 5 patients (23%), helped in staging of disease in 5 patients (23%) and in detecting clinically subtle findings in 6 patients (27%). Conclusion: RetCam assisted FFA is extremely useful to document peripheral retinal vascular pathologies in pediatric patients and helps to take crucial therapeutic and retreatment decisions.

Automatic layer segmentation of optical coherence tomography images in retinal vascular diseases / 上海交通大学学报（医学版）

Objective • To explore the layer segmentation method of optical coherence tomography (OCT) images of retinal vascular diseases using an unsupervised learning method, and compare it with the built-in layering method of OCT machine. Methods • Standardized image acquisition was performed on OCT images from 50 patients with myopic choroidal neovascularization (mCNV) and 20 patients with diabetic macular edema (DME). Standards were established by manual marking of hierarchical information by professional physicians. A retinal multi-layer segmentation method based on the minimization of interlayer energy was proposed, and the results were compared with those obtained by the built-in layering method of OCT machine. The layering accuracy was verified by the unmarked boundary position error. Results • This segmentation method divided the retina of each patient into five layers: internal limiting membrane, lower layer of nerve fiber layer, upper layer of outer nuclear layer, upper layer of ellipsoid zone and Bruch's membrane. The average segmentation error in the overall data set was (4.831±7.015) μm. The error of mCNV group and DME group were (4.839±16.819) μm and (5.048±9.986) μm, respectively, both of which were lower than the automatic measurement results of OCT machine [(13.638±58.024) μm and (14.796±45.342) μm, respectively]. The accuracy of this method at each layer was higher than that of the automatic measurement. Conclusion • This multi-layer segmentation method can be used for segmentation of different types of retinal vascular diseases, and the results are significantly better than those obtained by the built-in method in OCT machine. It can be extended for layer segmentation of other retinal vascular diseases.