RETINAL VASCULAR BED AREA IN EYES WITH RETINAL VEIN OCCLUSION ON ULTRA-WIDEFIELD FLUORESCEIN ANGIOGRAPHY: WAVE Study.

PURPOSE: To compute retinal vascular bed area (RVBA) in square millimeters on distortion corrected ultra-widefield fluorescein angiography images in eyes with retinal vein occlusion (RVO). METHODS: Prospective observational study. The peripheral distortion of baseline ultra-widefield fluorescein angiography (Optos 200Tx) images of 30 patients with RVO from the WAVE study (NCT01710839) and 13 control eyes of normal subjects was corrected using the stereographic projection method to compute RVBA in square millimeters. RESULTS: In comparison with age- and sex-matched normal control eyes, eyes with RVO had a decreased global RVBA for the entire retina (50.5 ± 20.4 mm 2 vs. 62.6 ± 12.2 mm 2 , P = 0.023). Eyes with RVO and the unaffected fellow eye had a similar RVBA globally (50.5 ± 20.4 mm 2 vs. 46.2 ± 18.9 mm 2 , P = 0.523). The RVBA was observed to negatively correlate with nonperfusion area (R = -0.47, P = 0.009). However, RVBA was not related to the severity of macular edema ( P > 0.05). CONCLUSION: Eyes with RVO have a similar RVBA to the unaffected fellow eyes but with a reduction when compared with normal control eyes. Retinal vascular bed area appears to be a surrogate biomarker of retinal ischemia on ultra-widefield fluorescein angiography but not the extent of macular edema.

NEW BIOMARKER QUANTIFYING THE EFFECT OF ANTI-VEGF THERAPY IN EYES WITH PROLIFERATIVE DIABETIC RETINOPATHY ON ULTRAWIDE FIELD FLUORESCEIN ANGIOGRAPHY: RECOVERY Study.

PURPOSE: To quantify changes of the retinal vascular bed area (RVBA) in mm2 on stereographically projected ultrawide field fluorescein angiography images in eyes with proliferative diabetic retinopathy after antivascular endothelial growth factor injection. METHODS: This is a prospective, observational study. The early-phase ultrawide field fluorescein angiography images (Optos 200Tx) of 40 eyes with proliferative diabetic retinopathy and significant nonperfusion obtained at baseline and after six months (NCT02863354) were stereographically projected by correcting peripheral distortion. The global retinal vasculature on ultrawide field fluorescein angiography was extracted for calculating RVBA by summing the real size (mm2) of all the pixels automatically. RESULTS: For the entire cohort, the global RVBA for the entire retina decreased from 67.1 ± 15.5 to 43.6 ± 18.8 mm2 after anti-VEGF treatment at six months (P < 0.001). In the subgroup receiving monthly anti-VEGF injections, the global RVBA decreased from 68.7 ± 16.2 to 33.9 ± 13.3 mm2 (P < 0.001). In the subgroup receiving anti-VEGF every three months, the global RVBA decreased from 65.6 ± 15.1 to 50.8 ± 19.3 mm2 (P = 0.004). CONCLUSION: RVBA seems to be a new biomarker to indicate efficiency of retinal vascular changes after anti-VEGF injection. Eyes with proliferative diabetic retinopathy and significant nonperfusion demonstrate reduced RVBA after anti-VEGF treatment.

Effect of phase-plate adjustment on retinal image sharpness and visible retinal area on ultrawide field imaging.

BACKGROUND: To evaluate changes in image sharpness across ultrawide field (UWF) images and the effect of phase-plate adjustment on image contrast and extent of visible retinal area (VRA). METHODS: This was a single site evaluation of 200° UWF images acquired with phase-plate adjustment (California, Optos, plc) and without (200TX, Optos, plc). Images were acquired using standardized protocol. VRA was manually outlined on each image and quantified using customized software. Mean image sharpness was evaluated using an automated method within the full VRA of each image and within the peripheral region of the VRA. The VRA and image sharpness were evaluated and compared between the two devices. RESULTS: Twenty eyes of 10 healthy volunteers were evaluated. Devices with and without phase-plate adjustment produced a similar extent of VRA. Eye steering increased VRA in devices with and without phase-plate adjustment by 39.3% and 34.3%, respectively. Regardless of gaze direction, mean sharpness of the full VRA was reduced in peripheral area with or without phase-plate adjustment. Compared to images without phase-plate adjustment, use of phase-plate adjustment reduced the loss of peripheral image sharpness in all fields (-4.2 to -26.0%; p < 0.001 all fields). The sharpness of the peripheral area for on-axis images was 61.5% higher with phase-plate adjustment. CONCLUSIONS: The use of phase-plate adjustment does not alter the extent of VRA. However, for on-axis images the loss of sharpness in the periphery is 4.5-fold less with phase-plate adjustment, potentially reducing the need to steer images and improving lesion detection in these areas.

A Novel Adaptive Deformable Model for Automated Optic Disc and Cup Segmentation to Aid Glaucoma Diagnosis.

This paper proposes a novel Adaptive Region-based Edge Smoothing Model (ARESM) for automatic boundary detection of optic disc and cup to aid automatic glaucoma diagnosis. The novelty of our approach consists of two aspects: 1) automatic detection of initial optimum object boundary based on a Region Classification Model (RCM) in a pixel-level multidimensional feature space; 2) an Adaptive Edge Smoothing Update model (AESU) of contour points (e.g. misclassified or irregular points) based on iterative force field calculations with contours obtained from the RCM by minimising energy function (an approach that does not require predefined geometric templates to guide auto-segmentation). Such an approach provides robustness in capturing a range of variations and shapes. We have conducted a comprehensive comparison between our approach and the state-of-the-art existing deformable models and validated it with publicly available datasets. The experimental evaluation shows that the proposed approach significantly outperforms existing methods. The generality of the proposed approach will enable segmentation and detection of other object boundaries and provide added value in the field of medical image processing and analysis.

Regional Image Features Model for Automatic Classification between Normal and Glaucoma in Fundus and Scanning Laser Ophthalmoscopy (SLO) Images.

Glaucoma is one of the leading causes of blindness worldwide. There is no cure for glaucoma but detection at its earliest stage and subsequent treatment can aid patients to prevent blindness. Currently, optic disc and retinal imaging facilitates glaucoma detection but this method requires manual post-imaging modifications that are time-consuming and subjective to image assessment by human observers. Therefore, it is necessary to automate this process. In this work, we have first proposed a novel computer aided approach for automatic glaucoma detection based on Regional Image Features Model (RIFM) which can automatically perform classification between normal and glaucoma images on the basis of regional information. Different from all the existing methods, our approach can extract both geometric (e.g. morphometric properties) and non-geometric based properties (e.g. pixel appearance/intensity values, texture) from images and significantly increase the classification performance. Our proposed approach consists of three new major contributions including automatic localisation of optic disc, automatic segmentation of disc, and classification between normal and glaucoma based on geometric and non-geometric properties of different regions of an image. We have compared our method with existing approaches and tested it on both fundus and Scanning laser ophthalmoscopy (SLO) images. The experimental results show that our proposed approach outperforms the state-of-the-art approaches using either geometric or non-geometric properties. The overall glaucoma classification accuracy for fundus images is 94.4% and accuracy of detection of suspicion of glaucoma in SLO images is 93.9 %.