Automated quantification of retinal arteriovenous nicking from colour fundus images

Progress in clinical research and applications of retinal vessel quantification technology based on fundus imaging

Retinal blood vessels are the only directly observed blood vessels in the body; changes in them can help effective assess the occurrence and development of ocular and systemic diseases. The specificity and efficiency of retinal vessel quantification technology has improved with the advancement of retinal imaging technologies and artificial intelligence (AI) algorithms; it has garnered attention in clinical research and applications for the diagnosis and treatment of common eye and related systemic diseases. A few articles have reviewed this topic; however, a summary of recent research progress in the field is still needed. This article aimed to provide a comprehensive review of the research and applications of retinal vessel quantification technology in ocular and systemic diseases, which could update clinicians and researchers on the recent progress in this field.

Recent trends and advances in fundus image analysis: A review

Automated retinal image analysis holds prime significance in the accurate diagnosis of various critical eye diseases that include diabetic retinopathy (DR), age-related macular degeneration (AMD), atherosclerosis, and glaucoma. Manual diagnosis of retinal diseases by ophthalmologists takes time, effort, and financial resources, and is prone to error, in comparison to computer-aided diagnosis systems. In this context, robust classification and segmentation of retinal images are primary operations that aid clinicians in the early screening of patients to ensure the prevention and/or treatment of these diseases. This paper conducts an extensive review of the state-of-the-art methods for the detection and segmentation of retinal image features. Existing notable techniques for the detection of retinal features are categorized into essential groups and compared in depth. Additionally, a summary of quantifiable performance measures for various important stages of retinal image analysis, such as image acquisition and preprocessing, is provided. Finally, the widely used in the literature datasets for analyzing retinal images are described and their significance is emphasized.

Detection of Glaucoma and Other Vision-Threatening Ocular Diseases in the Population Recruited at Specific Health Checkups in Japan

Background

The efficacy of vision screening for adults has not been well established. The present study aimed to investigate the prevalence of vision-threatening ocular diseases, including glaucoma, among subjects who participated in specific health checkups in Japan.

Methods

This cross-sectional study included 1360 individuals who underwent comprehensive ophthalmic examinations at 16 ophthalmology clinics located in three municipalities. We surveyed the study participants using a questionnaire. The participants also underwent visual acuity and refraction tests, intraocular pressure tests, slit-lamp microscopy, fundus examinations, fundus photography, optical coherence tomography, and static perimetry.

Results

The mean age of the subjects was 63.7 ± 8.7 years (range, 40–74 years). Among the 1360 participants, 168 (12.4%) were diagnosed with glaucoma and 33 (2.4%) with preperimetric glaucoma. Cataracts were seen in 741 participants (54.5%), and 77 (5.7%) were diagnosed with clinically significant cataracts. Retinal diseases included macular degeneration (1.2%), diabetic retinopathy (1.0%), chorioretinal atrophy (0.5%), macular epiretinal membrane (2.9%), branch retinal vein occlusion (0.7%), and others (2.0%). Regarding the type of glaucoma, 93.5% of participants with glaucoma were diagnosed with open-angle glaucoma in a broad sense (81.0% with normal-tension glaucoma and 12.5% with primary open-angle glaucoma). Multivariate analysis showed that male sex, age, systemic comorbidities, and myopia were significant risk factors for open-angle glaucoma.

Conclusion

Many adults with ocular diseases were screened by ophthalmic checkups. The addition of simultaneous ophthalmic checkups to specific health checkups could be an effective measure for the prevention of visual impairment in the older population.

Retinal Vascular Imaging in Vascular Cognitive Impairment: Current and Future Perspectives

Vascular cognitive disorders are heterogeneous and increasingly recognized entities with intricate correlation to neurodegenerative conditions. Retinal vascular analysis is a noninvasive approach to study cerebrovascular pathology, with promise to assist particularly during early disease phases. In this article, we have systematically summarized the current understanding, potential applications, and inevitable limitations of retinal vascular imaging in patients with vascular cognitive impairment. In addition, future directions in the field with support from automated technology using deep learning methods and their existing challenges are emphasized.

Potential Utility of Retinal Imaging for Alzheimer's Disease: A Review

The ensuing upward shift in demographic distribution due to the increase in life expectancy has resulted in a rising prevalence of Alzheimer's disease (AD). The heavy public burden of AD, along with the urgent to prevent and treat the disease before the irreversible damage to the brain, calls for a sensitive and specific screening technology to identify high-risk individuals before cognitive symptoms arise. Even though current modalities, such as positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarker, showed their potential clinical uses in early detection of AD, the high cost, narrow isotope availability of PET probes and invasive characteristics of CSF biomarker limited their broad utility. Therefore, additional tools for detection of AD are needed. As a projection of the central nervous system (CNS), the retina has been described as a "window to the brain" and a novel marker for AD. Low cost, easy accessibility and non-invasive features make retina tests suitable for large-scale population screening and investigations of preclinical AD. Furthermore, a number of novel approaches in retina imaging, such as optical coherence tomography (OCT), have been developed and made it possible to visualize changes in the retina at a very fine resolution. In this review, we outline the background for AD to accelerate the adoption of retina imaging for the diagnosis and management of AD in clinical practice. Then, we focus on recent findings on the application of retina imaging to investigate AD and provide suggestions for future research directions.

An automated method for retinal arteriovenous nicking quantification from color fundus images

Retinal arteriovenous (AV) nicking is one of the prominent and significant microvascular abnormalities. It is characterized by the decrease in the venular caliber at both sides of an artery-vein crossing. Recent research suggests that retinal AV nicking is a strong predictor of eye diseases such as branch retinal vein occlusion and cardiovascular diseases such as stroke. In this study, we present a novel method for objective and quantitative AV nicking assessment. From the input retinal image, the vascular network is first extracted using the multiscale line detection method. The crossover point detection method is then performed to localize all AV crossing locations. At each detected crossover point, the four vessel segments, two associated with the artery and two associated with the vein, are identified and two venular segments are then recognized through the artery-vein classification method. The vessel widths along the two venular segments are measured and analyzed to compute the AV nicking severity of that crossover. The proposed method was validated on 47 high-resolution retinal images obtained from two population-based studies. The experimental results indicate a strong correlation between the computed AV nicking values and the expert grading with a Spearman correlation coefficient of 0.70. Sensitivity was 77% and specificity was 92% (Kappa κ = 0.70) when comparing AV nicking detected using the proposed method to that detected using a manual grading method, performed by trained photographic graders.