Imaging Modalities Employed in Diabetic Retinopathy Screening: A Review and Meta-Analysis

Abstract

Introduction: Urbanization has caused dramatic changes in lifestyle, and these rapid transitions have led to an increased risk of noncommunicable diseases, such as type 2 diabetes. In terms of cost-effectiveness, screening for diabetic retinopathy is a critical aspect in diabetes management. The aim of this study was to review the imaging modalities employed for retinal examination in diabetic retinopathy screening. Methods: The PubMed and Web of Science databases were the main sources used to investigate the medical literature. An extensive search was performed to identify relevant articles concerning “imaging”, “diabetic retinopathy” and “screening” up to 1 June 2021. Imaging techniques were divided into the following: (i) mydriatic fundus photography, (ii) non-mydriatic fundus photography, (iii) smartphone-based imaging, and (iv) ultrawide-field imaging. A meta-analysis was performed to analyze the performance and technical failure rate of each method. Results: The technical failure rates for mydriatic and non-mydriatic digital fundus photography, smartphone-based and ultrawide-field imaging were 3.4% (95% CI: 2.3–4.6%), 12.1% (95% CI: 5.4–18.7%), 5.3% (95% CI: 1.5–9.0%) and 2.2% (95% CI: 0.3–4.0%), respectively. The rate was significantly different between all analyzed techniques (p < 0.001), and the overall failure rate was 6.6% (4.9–8.3%; I2 = 97.2%). The publication bias factor for smartphone-based imaging was significantly higher than for mydriatic digital fundus photography and non-mydriatic digital fundus photography (b = −8.61, b = −2.59 and b = −7.03, respectively; p < 0.001). Ultrawide-field imaging studies were excluded from the final sensitivity/specificity analysis, as the total number of patients included was too small. Conclusions: Regardless of the type of the device used, retinal photographs should be taken on eyes with dilated pupils, unless contraindicated, as this setting decreases the rate of ungradable images. Smartphone-based and ultrawide-field imaging may become potential alternative methods for optimized DR screening; however, there is not yet enough evidence for these techniques to displace mydriatic fundus photography.

The Role of Medical Image Modalities and AI in the Early Detection, Diagnosis and Grading of Retinal Diseases: A Survey

“…Consequently, standard 30° fundus photography remains the best choice for fundus imaging [ 10 , 13 ]. Stereoscopic fundus photography can be used to obtain a stereo image created by merging photographs taken at two slightly different positions from both eyes to enable the perception of depth [ 11 , 13 , 25 ]. Despite the potential value of stereoscopic fundus photography, its clinical value is controversial due to several limitations.…”

“…The photographer’s experience has an impact on the technique, and the left and right images must be equally sharp and have the same illumination in each image in the pair [ 12 , 26 ]. Image interpretation is time consuming and requires special goggles or optical viewers to fuse the image stereoscopically and achieve depth [ 11 , 25 ].…”

“…Ultra-widefield scanning laser ophthalmoscopy was developed by combining confocal scanning laser ophthalmoscopy with a concave elliptical mirror. It can record a wider view of the retina of up to 200° in a single image with an acquisition time of less than one second, without the need for pupil dilatation [ 25 , 57 ]. The use of ultra-widefield scanning laser ophthalmoscopy is still limited due to its high cost [ 12 ].…”

“…Their technique provided the location of the detected anomalies. Ghosh et al [ 25 ] applied data augmentation, normalization, and denoising preprocessing stages. Then, a 28-layer CNN was applied for the grading of DR using fundus images.…”

Artificial Intelligence and Medicine

“…The DL approach was employed to analyze retinal pictures in order to achieve automatic diabetic retinopathy screening and severity rating (20,21). The AI method's sensitivity and specificity for diagnosing serious lesions were 100% and 88.4%, respectively.…”