Application of ImageJ in Optical Coherence Tomography Angiography (OCT-A): A Literature Review

Background. This study aimed to review the literature on the application of ImageJ in optical coherence tomography angiography (OCT-A) images. Methods. A general search was performed in PubMed, Google Scholar, and Scopus databases. The authors evaluated each of the selected articles in order to assess the implementation of ImageJ in OCT-A images. Results. ImageJ can aid in reducing artifacts, enhancing image quality to increase the accuracy of the process and analysis, processing and analyzing images, generating comparable parameters such as the parameters that assess perfusion of the layers (vessel density (VD), skeletonized density (SD), and vessel length density (VLD)) and the parameters that evaluate the structure of the layers (fractal dimension (FD), vessel density index (VDI), and lacunarity (LAC)), and the foveal avascular zone (FAZ) that are used widely in the retinal and choroidal studies), and establishing diagnostic criteria. It can help to save time when the dataset is huge with numerous plugins and options for image processing and analysis with reliable results. Diverse studies implemented distinct binarization and thresholding techniques, resulting in disparate outcomes and incomparable parameters. Uniformity in methodology is required to acquire comparable data from studies employing diverse processing and analysis techniques that yield varied outcomes. Conclusion. Researchers and professionals might benefit from using ImageJ because of how quickly and correctly it processes and analyzes images. It is highly adaptable and potent software, allowing users to evaluate images in a variety of ways. There exists a diverse range of methodologies for analyzing OCTA images through the utilization of ImageJ. However, it is imperative to establish a standardized strategy to ensure the reliability and consistency of the method for research purposes

Central retinal vein and artery occlusion associated with sildenafil: a case report and review of the literature

Abstract Background Sildenafil is a selective phosphodiesterase type 5 inhibitor used for the treatment of erectile dysfunction and pulmonary hypertension. It is available over the counter in many countries. While there have been a few reports of retinal vascular occlusion following sildenafil consumption, most cases have other comorbidities as risk factors for the disease, and the exact causal role of this drug in these conditions remains unclear. Case presentation We present the case of a healthy 32-year-old Iranian man who developed combined central retinal vein occlusion and retinal artery occlusion following sildenafil exposure. The patient underwent a hypercoagulative state workup for possible underlying risk factors. Additionally, we conducted a literature search on PubMed using the keywords: retinal vein occlusion AND Sildenafil OR Viagra, retinal artery occlusion AND Sildenafil OR Viagra, retinal vascular occlusion AND Sildenafil OR Viagra. To obtain more objective results in the reviews, we employed an adverse drug reaction possibility algorithm. The patient was found to be otherwise healthy, and ancillary tests were unremarkable. A literature review identified seven reports of retinal vascular occlusion following sildenafil use. In most of these cases, the role of sildenafil was not clearly established. To the best of our knowledge, our case achieved the highest score based on the algorithm compared with previous reports. Conclusion Sildenafil may be associated with severe retinal vascular accidents in otherwise healthy young individuals

Assessment of area and structural irregularity of retinal layers in diabetic retinopathy using machine learning and image processing techniques

Abstract Diabetes retinopathy prevention necessitates early detection, monitoring, and treatment. Non-invasive optical coherence tomography (OCT) shows structural changes in the retinal layer. OCT image evaluation necessitates retinal layer segmentation. The ability of our automated retinal layer segmentation to distinguish between normal, non-proliferative (NPDR), and proliferative diabetic retinopathy (PDR) was investigated in this study using quantifiable biomarkers such as retina layer smoothness index (SI) and area (S) in horizontal and vertical OCT images for each zone (fovea, superior, inferior, nasal, and temporal). This research includes 84 eyes from 57 individuals. The study shows a significant difference in the Area (S) of inner nuclear layer (INL) and outer nuclear layer (ONL) in the horizontal foveal zone across the three groups (p < 0.001). In the horizontal scan, there is a significant difference in the smoothness index (SI) of the inner plexiform layer (IPL) and the upper border of the outer plexiform layer (OPL) among three groups (p < 0.05). There is also a significant difference in the area (S) of the OPL in the foveal zone among the three groups (p = 0.003). The area (S) of the INL in the foveal region of horizontal slabs performed best for distinguishing diabetic patients (NPDR and PDR) from normal individuals, with an accuracy of 87.6%. The smoothness index (SI) of IPL in the nasal zone of horizontal foveal slabs was the most accurate at 97.2% in distinguishing PDR from NPDR. The smoothness index of the top border of the OPL in the nasal zone of horizontal slabs was 84.1% accurate in distinguishing NPDR from PDR. Smoothness index of IPL in the temporal zone of horizontal slabs was 89.8% accurate in identifying NPDR from PDR patients. In conclusion, optical coherence tomography can assess the smoothness index and irregularity of the inner and outer plexiform layers, particularly in the nasal and temporal regions of horizontal foveal slabs, to distinguish non-proliferative from proliferative diabetic retinopathy. The evolution of diabetic retinopathy throughout severity levels and its effects on retinal layer irregularity need more study