Multicolor Scanning Laser Ophthalmoscopy Strengthens Surgeons' Preoperative Decision-Making and Intraoperative Performance on Epiretinal Membrane

Progress of Imaging in Diabetic Retinopathy-From the Past to the Present

Advancement of imaging technology in retinal diseases provides us more precise understanding and new insights into the diseases' pathologies. Diabetic retinopathy (DR) is one of the leading causes of sight-threatening retinal diseases worldwide. Colour fundus photography and fluorescein angiography have long been golden standard methods in detecting retinal vascular pathology in this disease. One of the major advancements is macular observation given by optical coherence tomography (OCT). OCT dramatically improves the diagnostic quality in macular edema in DR. The technology of OCT is also applied to angiography (OCT angiograph: OCTA), which enables retinal vascular imaging without venous dye injection. Similar to OCTA, in terms of their low invasiveness, single blue color SLO image could be an alternative method in detecting non-perfused areas. Conventional optical photography has been gradually replaced to scanning laser ophthalmoscopy (SLO), which also make it possible to produce spectacular ultra-widefield (UWF) images. Since retinal vascular changes of DR are found in the whole retina up to periphery, it would be one of the best targets in UWF imaging. Additionally, evolvement of artificial intelligence (AI) has been applied to automated diagnosis of DR, and AI-based DR management is one of the major topics in this field. This review is trying to look back on the progress of imaging of DR comprehensively from the past to the present.

Evaluation of macular vascular density and foveal avascular zone changes by optical coherence tomography angiography (OCT-A) after intravitreal dexamethasone implant in diabetic macular edema resistant to Anti-VEGF treatment

PURPOSE

Analysis of foveal avascular zone (FAZ) width and vascular density (VD) changes before and after intravitreal dexamethasone implant (IDI) treatment in diabetic macular edema (DME) patients resistant to anti-VEGF treatment.

METHODS

In this retrospective study, patients who were regularly treated with at least 5 doses of intravitreal Anti-VEGF (bevacizumab, ranibizumab or aflibercept) for DME and whose DME continued were considered resistant to Anti-VEGF and were treated with IDI for the first time. Thirty-four eyes of 34 patients were included in the study. FAZ and VD values of optical coherence tomography angiography (OCT-A) scans at 0, 1 and 3 months were examined.

RESULTS

In OCT-A measurements, the pre-IDI superficial plexus FAZ (SFAZ) area (0.350 ± 0.120 mm²) was decreased at 1 (0.292 ± 0.132 mm², p < 0.001) and at 3 months (0.311 ± 0.153 mm², p = 0.017). Pre-IDI deep plexus FAZ (DFAZ) area (0.651 ± 0.313 mm²) was decreased at 1-month post-IDI (0.481 ± 0.247 mm², p < 0.001) while no significant change was observed at 3 months (0.575 ± 0.259 mm², p = 0.197). There was no significant change in the mean post-IDI total VD rate in both superficial (pre 39.2% ± 2.4; 1st month 39.2% ± 2.6%; 3rd month 39.5% ± 3.4%) and deep retinal plexus (pre 43.3% ± 2.6%; 1st month 43.5 ± 2.8%; 3rd month 43.6% ± 4.6%) (p = 0.408 and p = 0.607, respectively).

CONCLUSION

The study showed that IDI caused a significant decrease in the FAZ area without any change in VD in patients with DME resistant to the anti-VEGF agents. IDI might be related to a decrease in the macular ischemia secondary to diabetic retinopathy.

Multicolor image classification using the multimodal information bottleneck network (MMIB-Net) for detecting diabetic retinopathy

Multicolor (MC) imaging is an imaging modality that records confocal scanning laser ophthalmoscope (cSLO) fundus images, which can be used for the diabetic retinopathy (DR) detection. By utilizing this imaging technique, multiple modal images can be obtained in a single case. Additional symptomatic features can be obtained if these images are considered during the diagnosis of DR. However, few studies have been carried out to classify MC Images using deep learning methods, let alone using multi modal features for analysis. In this work, we propose a novel model which uses the multimodal information bottleneck network (MMIB-Net) to classify the MC Images for the detection of DR. Our model can extract the features of multiple modalities simultaneously while finding concise feature representations of each modality using the information bottleneck theory. MC Images classification can be achieved by picking up the combined representations and features of all modalities. In our experiments, it is shown that the proposed method can achieve an accurate classification of MC Images. Comparative experiments also demonstrate that the use of multimodality and information bottleneck improves the performance of MC Images classification. To the best of our knowledge, this is the first report of DR identification utilizing the multimodal information bottleneck convolutional neural network in MC Images.

Recent Advances and Clinical Application of Color Scanning Laser Ophthalmoscope

Scanning laser ophthalmoscopes (SLOs) have been available since the early 1990s, but they were not commonly used because their advantages were not enough to replace conventional color fundus photography. In recent years, color SLOs have improved significantly, and the colored SLO images are obtained by combining multiple SLO images taken by lasers of different wavelengths. A combination of these images of different lasers can create an image that is close to that of the real ocular fundus. One advantage of the advanced SLOs is that they can obtain images with a wider view of the ocular fundus while maintaining a high resolution even through non-dilated eyes. The current SLOs are superior to the conventional fundus photography in their ability to image abnormal alterations of the retina and choroid. Thus, the purpose of this review was to present the characteristics of the current color SLOs and to show how that can help in the diagnosis and the following of changes after treatments. To accomplish these goals, we will present our findings in patients with different types of retinochoroidal disorders.