Smartphone-based Fundus Imaging Research Articles

Diabetic retinopathy screening using MII Ret Cam assisted smartphone-based fundus imaging

BackgroundDiabetes Mellitus is a tremendous health implication and is proposed to be the seventh leading cause of death in 2030 by WHO. Diabetic retinopathy is one of the top complications of diabetes leading to preventable blindness. This investigation highlights the importance of timely screening and counseling using MII Ret cCam-assisted smartphone-based fundus imaging. Our study is a boon for bed-ridden and seriously ill patients who could not be evaluated on a fundus camera. MethodsThis is an observational prospective study conducted at the Ophthalmology unit, wards, and intensive care unit (ICU) of a single tertiary teaching hospital between 1 May to 31 November 2022. A total of 268 subjects with diabetes were included. The fundus of all the diabetic patients during the study period were examined by a single-trained ophthalmologist. Those diagnosed with diabetic retinopathy were taken for acquisition of fundus picture with MII Ret Cam. Images were captured using Apple iPhone 5s and 20D mounted in MII Ret Cam device. ResultsOut of 268 subjects (536 eyes) screened during the study period,86 patients (154 eyes) were found to have DR. Maleto Female ratio was 1.4:1. The mean age was 56.37 ± 15.26 years and the mean duration of diabetes was 10.60 ± 6.97 years. Grading of DR revealed proliferative diabetic retinopathy (PDR) to be the topmost (n=84 eyes, 54.5%), followed by mild non-proliferative diabetic retinopathy (NPDR) in 26 eyes (16%) and moderate NPDR in 24 eyes (15%) while severe NPDR was seen in 10 eyes (6.5%) and very severe NPDR was found in 8 eyes (5.2%) and diabetic papillopathy in 2 eyes. Grading of vitreous hemorrhage revealed Grade 1 in one eye (1.8%); Grade 2 in 19 eyes (34.54%); Grade 3 in 33 eyes (60%) and Grade 4 in 2 eyes (3.63%). Grading of macular edema according to the distribution of hard exudates as Grade 1(No Clinically significant macular edema) in 33 eyes (34.37%) and Grade 2 (Clinically significant macular edema) in 63 eyes (65.62%). The duration of diabetes had a direct association with the occurrence of DR, 13patients (15.1%) had a duration of diabetes less than five years; 31patients(36%) had a duration of diabetes between 6 years to 10 years; 28 patients (32.6%) had a duration between 11 years to 20 years. 14 patients (16.3%) had a duration of more than twenty years. The Mean duration of diabetes in Group I was 11.40+/- 7.09 years and was 9.10+/- 6.48 in Group II. The mean HbA1c in Group I is 7.44+/- 1.24 and 6.54 +/- 1.09 in Group II. The mean fasting blood sugar in Group I was 130.87 +/- 29.57 and 106.62+/- 29.85 in Group II. The mean of random blood sugar was 202.15 +/- 60.84 in Group I and 155.13 +/- 55.95 in Group II. Results are suggestive of the association of DR occurrence with fasting, random blood sugar, duration of diabetes, and HbA1c. ConclusionsDiabetic Retinopathy Screening using MII Ret Cam assisted Smartphone-based fundus imaging may be a useful device to screen for referable and vision-threatening diabetic retinopathy. MII Ret Cam is portable equipment and is easily accessible to counsel patients in resource-limited countries.

Smart Phone based Fundus Imaging for Diabetic Retinopathy Detection

INTRODUCTION: Diabetic retinopathy (DR) is one of the consequences of diabetes which if untreated may lead to loss of vision. Generally, for DR detection, retinal images are obtained using a traditional fundus camera. A recent trend in the acquisition of eye fundus images is the usage of smartphones to acquire images.
 OBJECTIVES: This paper focuses on the study of existing works which incorporated smartphones for obtaining fundus images and various devices available in the market. Also, the common datasets used for carrying out DR detection using smartphone-based fundus images as well as the classification models used for the diagnosis of DR are explored.
 METHODS: A search of information was carried out on articles based on DR detection from fundus images published in the state-of-the-art literatures.
 RESULTS: Majority of the works uses SBFI devices like 20D lens, EyeExaminer etc. to obtain fundus image. The common databases used for the study are EyePACS, Messidor, etc. and the classification models mostly rely on deep learning frameworks.
 CONCLUSION: The use of smartphones for capturing fundus images for DR detection are explored. Smartphone devices, datasets used for the study and currently available classification models for SBFI based DR detection are discussed in detail. This paper portrays various approaches currently being employed in SBFI based DR detection.

Efficacy of Smartphone-Based Telescreening for Retinopathy of Prematurity With and Without Artificial Intelligence in India

Retinopathy of prematurity (ROP) telemedicine screening programs have been found to be effective, but they rely on widefield digital fundus imaging (WDFI) cameras, which are expensive, making them less accessible in low- to middle-income countries. Cheaper, smartphone-based fundus imaging (SBFI) systems have been described, but these have a narrower field of view (FOV) and have not been tested in a real-world, operational telemedicine setting. To assess the efficacy of SBFI systems compared with WDFI when used by technicians for ROP screening with both artificial intelligence (AI) and human graders. This prospective cross-sectional comparison study took place as a single-center ROP teleophthalmology program in India from January 2021 to April 2022. Premature infants who met normal ROP screening criteria and enrolled in the teleophthalmology screening program were included. Those who had already been treated for ROP were excluded. All participants had WDFI images and from 1 of 2 SBFI devices, the Make-In-India (MII) Retcam or Keeler Monocular Indirect Ophthalmoscope (MIO) devices. Two masked readers evaluated zone, stage, plus, and vascular severity scores (VSS, from 1-9) in all images. Smartphone images were then stratified by patient into training (70%), validation (10%), and test (20%) data sets and used to train a ResNet18 deep learning architecture for binary classification of normal vs preplus or plus disease, which was then used for patient-level predictions of referral warranted (RW)- and treatment requiring (TR)-ROP. Sensitivity and specificity of detection of RW-ROP, and TR-ROP by both human graders and an AI system and area under the receiver operating characteristic curve (AUC) of grader-assigned VSS. Sensitivity and specificity were compared between the 2 SBFI systems using Pearson χ2testing. A total of 156 infants (312 eyes; mean [SD] gestational age, 33.0 [3.0] weeks; 75 [48%] female) were included with paired examinations. Sensitivity and specificity were not found to be statistically different between the 2 SBFI systems. Human graders were effective with SBFI at detecting TR-ROP with a sensitivity of 100% and specificity of 83.49%. The AUCs with grader-assigned VSS only were 0.95 (95% CI, 0.91-0.99) and 0.96 (95% CI, 0.93-0.99) for RW-ROP and TR-ROP, respectively. For the AI system, the sensitivity of detecting TR-ROP sensitivity was 100% with specificity of 58.6%, and RW-ROP sensitivity was 80.0% with specificity of 59.3%. In this cross-sectional study, 2 different SBFI systems used by technicians in an ROP screening program were highly sensitive for TR-ROP. SBFI systems with AI may be a cost-effective method to improve the global capacity for ROP screening.

Smartphone-based fundus imaging for evaluation of Retinopathy of Prematurity in a low-income country: A pilot study.

To evaluate the feasibility of a novel and simple smart phone-based Retinopathy of Prematurity (ROP) screening approach in a resource-constrained setting. This cross-sectional validation study was conducted at the Department of Ophthalmology and Neonatal Intensive Care Unit (NICU) of The Aga Khan University Hospital, Pakistan, from January 2022 to April 2022. A total of 63 images of eyes with active ROP (stage-1, 2, 3, 4 and/or plus or pre-plus disease) were included in this study. The stage of ROP was documented by the principal investigator using an indirect ophthalmoscope and retinal images were obtained using this novel technique. These images were shared with two masked ROP experts who rated the image quality and determined the stage of ROP and presence of plus disease. Their reports were compared with the initial findings reported by principal investigator using indirect ophthalmoscope. We reviewed 63 images for image quality, stage of ROP and presence of plus disease. There was significant agreement between the gold standard and the Rater-1 and 2 for the presence of plus disease (Cohen's kappa was 0.84 and 1.0) and the stage of the disease (Cohen's kappa 0.65 and 1.0). There was significant agreement between the Rater for presence of plus disease and any stage of ROP (Cohen's κ: 0.84 and 0.65 for plus disease and any stage of the ROP, respectively). Rater-1 and 2 rated 96.83% and 98.41% images as excellent / acceptable respectively. High quality retinal images can be captured with a smartphone and 28D lens without using any additional adapter equipment. This approach of ROP screening can form basis of telemedicine for ROP in resource constrained areas.

Estimation of best corrected visual acuity based on deep neural network

In this study, we investigated a convolutional neural network (CNN)-based framework for the estimation of the best-corrected visual acuity (BCVA) from fundus images. First, we collected 53,318 fundus photographs from the Gyeongsang National University Changwon Hospital, where each fundus photograph is categorized into 11 levels by retrospective medical chart review. Then, we designed 4 BCVA estimation schemes using transfer learning with pre-trained ResNet-18 and EfficientNet-B0 models where both regression and classification-based prediction are taken into account. According to the results of the study, the predicted BCVA by CNN-based schemes is close to the actual value such that 94.37% of prediction accuracy can be achieved when 3 levels of difference can be tolerated during prediction. The mean squared error and R^2 score were measured as 0.028 and 0.654, respectively. These results indicate that the BCVA can be predicted accurately for extreme cases, i.e., the level of BCVA is close to either 0.0 or 1.0. Moreover, using the Guided Grad-CAM, we confirmed that the macula and the blood vessel surrounding the macula are mainly utilized in the prediction of BCVA, which validates the rationality of the CNN-based BCVA estimation schemes since the same area is also exploited during the retrospective medical chart review. Finally, we applied the t-distributed stochastic neighbor embedding to examine the characteristics of CNN-based BCVA estimation schemes. The developed BCVA estimation schemes can be employed to obtain the objective measurement of BVCA as well as the medical screening of people with poor access to medical care through smartphone-based fundus imaging.

Smartphone-based fundus imaging: applications and adapters

Smartphone-based fundus imaging (SBFI) is an innovative and low-cost alternative for color fundus photography. Since the first reports on this topic more than 10years ago alarge number of studies on different adapters and clinical applications have been published. The aim of this review article is to provide an overview on the development of SBFI and adapters and clinical applications published so far. Aliterature search was performed using the MEDLINE and Science Citation Index Expanded databases without time restrictions. Overall, 11 adapters were included and compared in terms of exemplary image material, field of view, acquisition costs, weight, software, application range, smartphone compatibility and certification. Previously published SBFI applications are screening for diabetic retinopathy, glaucoma and retinopathy of prematurity as well as the application in emergency medicine, pediatrics and medical education/teaching. Image quality of conventional retinal cameras is in general superior to SBFI. First approaches on automatic detection of diabetic retinopathy through SBFI are promising and the use of automatic image processing algorithms enables the generation of wide-field image montages. SBFI is aversatile, mobile, low-cost alternative to conventional equipment for color fundus photography. In addition, it facilitates the delegation of ophthalmological examinations to assistance personnel in telemedical settings, could simplify retinal documentation, improve teaching, and improve ophthalmological care, particularly in countries with low and middle incomes.

Learning curve evaluation upskilling retinal imaging using smartphones

Smartphone-based fundus imaging (SBFI) is a low-cost approach for screening of various ophthalmic diseases and particularly suited to resource limited settings. Thus, we assessed how best to upskill alternative healthcare cadres in SBFI and whether quality of obtained images is comparable to ophthalmologists. Ophthalmic assistants and ophthalmologists received a standardized training to SBFI (Heine iC2 combined with an iPhone 6) and 10 training examinations for capturing central retinal images. Examination time, total number of images, image alignment, usable field-of-view, and image quality (sharpness/focus, reflex artifacts, contrast/illumination) were analyzed. Thirty examiners (14 ophthalmic assistants and 16 ophthalmologists) and 14 volunteer test subjects were included. Mean examination time (1st and 10th training, respectively: 2.17 ± 1.54 and 0.56 ± 0.51 min, p < .0001), usable field-of-view (92 ± 16% and 98 ± 6.0%, p = .003) and image quality in terms of sharpness/focus (p = .002) improved by the training. Examination time was significantly shorter for ophthalmologists compared to ophthalmic assistants (10th training: 0.35 ± 0.21 and 0.79 ± 0.65 min, p = .011), but there was no significant difference in usable field-of-view and image quality. This study demonstrates the high learnability of SBFI with a relatively short training and mostly comparable results across healthcare cadres. The results will aid implementing and planning further SBFI field studies.

A Novel Device for Smartphone-Based Fundus Imaging and Documentation in Clinical Practice: Comparative Image Analysis Study.

BackgroundSmartphone-based fundus imaging allows for mobile and inexpensive fundus examination with the potential to revolutionize eye care, particularly in lower-resource settings. However, most smartphone-based fundus imaging adapters convey image quality not comparable to conventional fundus imaging.ObjectiveThe purpose of this study was to evaluate a novel smartphone-based fundus imaging device for documentation of a variety of retinal/vitreous pathologies in a patient sample with wide refraction and age ranges.MethodsParticipants’ eyes were dilated and imaged with the iC2 funduscope (HEINE Optotechnik) using an Apple iPhone 6 in single-image acquisition (image resolution of 2448 × 3264 pixels) or video mode (1248 × 1664 pixels) and a subgroup of participants was also examined by conventional fundus imaging (Zeiss VISUCAM 500). Smartphone-based image quality was compared to conventional fundus imaging in terms of sharpness (focus), reflex artifacts, contrast, and illumination on semiquantitative scales.ResultsA total of 47 eyes from 32 participants (age: mean 62.3, SD 19.8 years; range 7-93; spherical equivalent: mean –0.78, SD 3.21 D; range: –7.88 to +7.0 D) were included in the study. Mean (SD) visual acuity (logMAR) was 0.48 (0.66; range 0-2.3); 30% (14/47) of the eyes were pseudophakic. Image quality was sufficient in all eyes irrespective of refraction. Images acquired with conventional fundus imaging were sharper and had less reflex artifacts, and there was no significant difference in contrast and illumination (P<.001, P=.03, and P=.10, respectively). When comparing image quality at the posterior pole, the mid periphery, and the far periphery, glare increased as images were acquired from a more peripheral part of the retina. Reflex artifacts were more frequent in pseudophakic eyes. Image acquisition was also possible in children. Documentation of deep optic nerve cups in video mode conveyed a mock 3D impression.ConclusionsImage quality of conventional fundus imaging was superior to that of smartphone-based fundus imaging, although this novel smartphone-based fundus imaging device achieved image quality high enough to document various fundus pathologies including only subtle findings. High-quality smartphone-based fundus imaging might represent a mobile alternative for fundus documentation in clinical practice.

Smartphone-Based Fundus Imaging-Where Are We Now?

With the advent of smartphone-based fundus imaging (SBFI), a low-cost alternative to conventional digital fundus photography has become available. SBFI allows for a mobile fundus examination, is applicable both with and without pupil dilation, comes with built-in connectivity and post-processing capabilities, and is relatively easy to master. Furthermore, it is delegable to paramedical staff/technicians and, hence, suitable for telemedicine. Against this background a variety of SBFI applications have become available including screening for diabetic retinopathy, glaucoma, and retinopathy of prematurity and its applications in emergency medicine and pediatrics. In addition, SBFI is convenient for teaching purposes and might serve as a surrogate for direct ophthalmoscopy. First wide-field montage techniques are available and the combination of SBFI with machine learning algorithms for image analyses is promising. In conclusion, SBFI has the potential to make fundus examinations and screenings for patients particularly in low- and middle-income settings more accessible and, therefore, aid tackling the burden of diabetic retinopathy, glaucoma, and retinopathy of prematurity screening. However, image quality for SBFI varies substantially and a reference standard for grading appears prudent. In addition, there is a strong need for comparison of different SBFI approaches in terms of applicability to disease screening and cost-effectiveness.

Diabetic Retinopathy Screening Using Smartphone-Based Fundus Imaging in India

Early detection and treatment can prevent irreversible blindness from diabetic retinopathy (DR), which is the leading cause of visual impairment among working-aged adults worldwide. Some 80% of affected persons live in low- and middle-income countries, yet lack of resources has largely prevented DR screening implementation in these world regions. Smartphone-based fundus imaging (SBFI) allows for low-cost mobile fundus examination using an adapter on a smartphone; however, key aspects such as image quality, diagnostic accuracy, and comparability of different approaches have not been systematically assessed to date. Evaluation of diagnostic technology. A total of 381 eyes of 193 patients with diabetes were recruited at outreach eye clinics in South India. We compared 4 technically different approaches of SBFI (3 approaches based on direct and 1 approach based on indirect ophthalmoscopy) in terms of image quality and diagnostic accuracy for DR screening. Image quality (sharpness/focus, reflex artifacts, contrast, and illumination), field-of-view, examination time, and diagnostic accuracy for DR screening were analyzed against conventional fundus photography and clinical examination. Smartphone-based fundus imaging based on indirect ophthalmoscopy yielded the best image quality (P < 0.01), the largest field-of-view, and the longest examination time (111 vs. 68-86 seconds, P < 0.0001). Agreement with the reference standard (Cohen's kappa 0.868) and sensitivity/specificity to detect DR were highest for the indirect SBFI approach (0.79/0.99 for any DR and 1.0/1.0 for severe DR, 0.79/1.0 for diabetic maculopathy). Smartphone-based fundus imaging can meet DR screening requirements in an outreach setting; however, not all devices are suitable in terms of image quality and diagnostic accuracy. Smartphone-based fundus imaging might aid in alleviating the burden of DR screening in low- and middle-income countries, and these results will allow for a better selection of SBFI devices in field trials for DR screening.

MII RetCam assisted smartphone-based fundus imaging (MSFI)—A boon for paediatric retinal imaging

MII RetCam assisted smartphone-based fundus imaging (MSFI)—A boon for paediatric retinal imaging

Non-contact smartphone-based fundus imaging compared to conventional fundus imaging: a low-cost alternative for retinopathy of prematurity screening and documentation

Retinopathy of prematurity (ROP) is a frequent cause of treatable childhood blindness. The current dependency of telemedicine-based ROP screening on cost-intensive equipment does not meet the needs in economically disadvantaged regions. Smartphone-based fundus imaging (SBFI) allows for affordable and mobile fundus examination and, therefore, could facilitate cost-effective telemedicine-based ROP screening in low-resources settings. We compared non-contact SBFI and conventional contact fundus imaging (CFI) in terms of feasibility for ROP screening and documentation. Twenty-six eyes were imaged with both SBFI and CFI. Field-of-view was smaller (ratio of diameters, 1:2.5), level of detail was equal, and examination time was longer for SBFI as compared to CFI (109.0 ± 57.8 vs. 75.9 ± 36.3 seconds, p < 0.01). Good agreement with clinical evaluation by indirect funduscopy was achieved for assessment of plus disease and ROP stage for both SBFI (squared Cohen’s kappa, 0.88 and 0.81, respectively) and CFI (0.86 and 0.93). Likewise, sensitivity/specificity for detection of plus disease and ROP was high for both SBFI (90%/100% and 88%/93%, respectively) and CFI (80%/100% and 100%/96%). SBFI is a non-contact and low-cost alternative to CFI for ROP screening and documentation that has the potential to considerably improve ROP care in middle- and low-resources settings.

Commentary: Retinopathy of prematurity screening made simple - Smartphone-based fundus imaging.

Commentary: Retinopathy of prematurity screening made simple - Smartphone-based fundus imaging.

Smartphone-based monochromatic green filter fundus imaging

Smartphone-based monochromatic green filter fundus imaging

基于智能手机的眼底成像系统

基于智能手机的眼底成像系统

MII Ret Cam: A Boon towards Retinal Disease Imaging andDocumentation

Purpose: The aim is to present the experience of fundus photo documentation by using MII Ret Cam. Methods: This study was conducted over a period of 3 months, at a tertiary eye care centre of Western Odisha from March 2017 to May 2017. It includes 100 patients with retinal pathology. Fundus evaluation was done using MII Ret Cam. The concern App has utilised for demographic data record and image storage. Results: The Make In India MII Ret Cam is an inexpensive, innovative imaging technique enabling easy and efficacious documentation of the fundus picture. It captures good quality fundus images of both central and peripheral retina. By using the smartphone and computer peripherals, images have used for future reference and printouts handed over to the patients. Conclusion: MII Retcam is an affordable smartphone-based fundus imaging technique. It helps clinicians to document and monitor diseases affecting both central and peripheral retina. It helps the patients to understand their disease and clinicians to convince their patients regarding the need of treatment.

The Diabetic Retinopathy Screening Workflow: Potential for Smartphone Imaging.

Complications of diabetes mellitus, namely diabetic retinopathy and diabetic maculopathy, are the leading cause of blindness in working aged people. Sufferers can avoid blindness if identified early via retinal imaging. Systematic screening of the diabetic population has been shown to greatly reduce the prevalence and incidence of blindness within the population. Many national screening programs have digital fundus photography as their basis. In the past 5 years several techniques and adapters have been developed that allow digital fundus photography to be performed using smartphones. We review recent progress in smartphone-based fundus imaging and discuss its potential for integration into national systematic diabetic retinopathy screening programs. Some systems have produced promising initial results with respect to their agreement with reference standards. However further multisite trialling of such systems' use within implementable screening workflows is required if an evidence base strong enough to affect policy change is to be established. If this were to occur national diabetic retinopathy screening would, for the first time, become possible in low- and middle-income settings where cost and availability of trained eye care personnel are currently key barriers to implementation. As diabetes prevalence and incidence is increasing sharply in these settings, the impact on global blindness could be profound.

Fundus Photography in the 21st Century--A Review of Recent Technological Advances and Their Implications for Worldwide Healthcare.

The introduction of fundus photography has impacted retinal imaging and retinal screening programs significantly. Fundus cameras play a vital role in addressing the cause of preventive blindness. More attention is being turned to developing countries, where infrastructure and access to healthcare are limited. One of the major limitations for tele-ophthalmology is restricted access to the office-based fundus camera. Recent advances in access to telecommunications coupled with introduction of portable cameras and smartphone-based fundus imaging systems have resulted in an exponential surge in available technologies for portable fundus photography. Retinal cameras in the near future would have to cater to these needs by featuring a low-cost, portable design with automated controls and digitalized images with Web-based transfer. In this review, we aim to highlight the advances of fundus photography for retinal screening as well as discuss the advantages, disadvantages, and implications of the various technologies that are currently available.

Smartphone-based fundus camera device (MII Ret Cam) and technique with ability to image peripheral retina.

To demonstrate an inexpensive smartphone-based fundus camera device (MII Ret Cam) and technique with ability to capture peripheral retinal pictures. A fundus camera was designed in the form of a device that has slots to fit a smartphone (built-in camera and flash) and 20-D lens. With the help of the device and an innovative imaging technique, high-quality fundus videos were taken with easy extraction of images. The MII Ret Cam and innovative imaging technique was able to capture high-quality images of peripheral retina such as ora serrata and pars plana apart from central fundus pictures. Our smartphone-based fundus camera can help clinicians to monitor diseases affecting both central and peripheral retina. It can help patients understand their disease and clinicians convincing their patients regarding need of treatment especially in cases of peripheral lesions. Imaging peripheral retina has not been demonstrated in existing smartphone-based fundus imaging techniques. The device can also be an inexpensive tool for mass screening.