Universal slit-lamp–mounted mobile adapter with 20 D lens for fundus photography: “Litter to glitter”

Fundus photography is an arduous task as it involves using 90 D in one hand and a smartphone attached on an eyepiece of a slit-lamp biomicroscope in the other hand. Similarly, with a 20 D lens, the filming distance is adjusted by moving the lens or mobile forward or backward, which makes it difficult to adjust and focus the image in busy ophthalmology outpatient departments (OPDs). Moreover, fundus camera costs thousands of dollars. Authors describe a novel technique of performing fundus photography with a 20 D lens and a universal slit-lamp–mounted mobile adapter made from trash. By the use of this simple, yet frugal innovation, primary care physicians or ophthalmologists without a fundus camera can easily snap a fundus photo and subject it to digital analysis by retina specialists across the world. This will help in simultaneous ocular examination and fundus photos taken via mounted 20 D on a slit lamp itself and also reduce the need for unnecessary retina referrals to tertiary eye care centers.

Application of deep learning artificial intelligence in the auxiliary diagnosis of age-related macular degeneration / 国际眼科杂志(Guoji Yanke Zazhi)

Since the advent of artificial intelligence(AI), it has been increasingly applied and rapidly developed in various fields. In the field of medicine, image features can be automatically extracted and the performance of feature learning and classification can be completed with the help of AI. In the field of ocular fundus disease, AI can give a diagnosis of age-related maculopathy by analyzing and identifying fundus photography and optical coherence tomography with an accuracy rate similar to that of ophthalmologists. In the future, AI may assist physicians in making a diagnosis of age-related macular degeneration, aid basic hospital in screening and curb its progression in the early stage of the disease. However, the technique has problems such as uncertain model recognition performance, opaque operation process, and excessive amount of clinical data required, which still cannot be widely used in the clinic. In recent years, a lot of research has been done in China in the application of deep learning with AI to assist diagnosis of ophthalmic diseases, and the results show that AI combined with imaging analysis of ophthalmic diseases has such characteristics as objectivity, efficiency and accuracy. In this article, studies on deep learning in the auxiliary diagnosis of age-related maculopathy are reviewed, and the progress on its application and the limitations that exist are analyzed, so as to provide more information on the use and extension of AI in this disease.

Progress in imaging and functional assessment of myopic fundus tessellation changes / 国际眼科杂志(Guoji Yanke Zazhi)

Myopia has become a serious global burden of visual impairment and blindness, and the World Health Organization has included the prevention and treatment of myopia in its global blindness prevention program. Many ocular pathological alterations that follow from advanced myopia could cause visual impairment and even blindness in severe situations. Myopia is becoming more prevalent and has a greater impact on young people. Myopia's social repercussions are becoming more widely known. One of the several fundus alterations linked to myopia is tessellated fundus, which is the earliest lesion in the natural course of myopic fundus lesions and an important clinical marker for the development of retinopathy. Currently, there are several different methods of grading fundus tessellation, all of which are graded subjectively by fundus color photography. One can investigate the morphological characteristics and functional status of the tessellated fundus with ophthalmoscope, fundus photography, optical coherence tomography, electroretinogram, microperimetry and other modal images. In this study, the imaging properties and common applications of the tessellated fundus are reviewed to provide appropriate resources for clinical ophthalmology.

El teléfono inteligente en la obtención de imágenes en oftalmología y su aplicación en el aprendizaje / The Smartphone in Ophthalmology Imaging and its Application in Learning

La imagen es parte de la columna vertebral en la medicina y que llega a su máximo punto en la Oftalmología. La importancia de la fotografía ocular va desde registrar condiciones médicas específicas, rastrear la progresión de enfermedades y crear ilustraciones para la publicación y la enseñanza; en resumen, una herramienta indispensable para el diagnóstico. Los aditamentos que en la presente publicación mostramos, son el resultado de una investigación de desarrollo que se realizó en el Instituto Cubano de Oftalmología "Ramón Pando Ferrer", durante el año 2021 con el objetivo de crear aditamentos que, acoplados a los teléfonos inteligentes, permiten tomar imágenes en el área de la Oftalmología utilizando la tecnología de impresión 3D. Inicialmente se identificaron los lugares que permitan crear imágenes en la especialidad con un aditamento y el teléfono inteligente, posteriormente se procederá a diseñar los aditamentos de acuerdo a las características del lugar donde se van a utilizar y finalmente mostramos la utilidad de los prototipos diseñados en la práctica docente(AU)

Imaging is part of the backbone in medicine and it reaches its peak in Ophthalmology. The importance of ocular photography ranges from recording specific medical conditions, tracking disease progression, and creating illustrations for publication and teaching; in short, an indispensable tool for diagnosis. The attachments, which we show in the present publication, are the result of a development research that was carried out at the Cuban Institute of Ophthalmology "Ramón Pando Ferrer" during the year 2021 with the aim of creating attachments that, coupled to smartphones, allow taking images in the area of Ophthalmology using 3D printing technology. Initially we identified the places that allow creating images in the specialty with an attachment and the smartphone, then we will proceed to design the attachments according to the characteristics of the place where they will be used and finally we show the usefulness of the designed prototypes in the teaching practice(AU)

Comparação da eficácia da retinografia colorida e da angiografia fluorescente no diagnóstico da retinopatia diabética / Comparing efficacy of fundus photography and fluorescein angiography in the diagnosis of diabetic retinopathy

RESUMO Objetivo: Avaliar a efetividade da retinografia colorida e a da angiografia fluorescente no diagnóstico e no rastreio da retinopatia diabética. Métodos: Estudo retrospectivo, com base na análise de resultados de ambos os exames de 398 pacientes diabéticos. Resultados: Os resultados da angiografia coincidiram com os da retinografia em 77,4% dos casos, e não houve diferença significativa no estadiamento e na identificação da retinopatia pelos dois métodos. Conclusão: Não houve diferença significativa em relação à capacidade diagnóstica da doença pelos métodos descritos, demonstrando não existir benefício em indicar a angiografia como avaliação inicial do paciente diabético.

ABSTRACT Objective: To assess effectiveness of fundus photography and fluorescein angiography in diagnosis and screening of diabetic retinopathy. Methods: A retrospective study of 398 diabetic patients, based on analysis of results of both tests. Results: Results of fluorescein angiography and fundus photography coincided in 77.4% of cases, and there was no significant difference in staging and identification of retinopathy by both methods. Conclusion: There was no significant difference between both methods regarding the capacity to diagnose the disease, showing no benefit in indicating fluorescein angiography as initial assessment of diabetic patients.

Research progress of artificial intelligence in glaucoma / 国际眼科杂志(Guoji Yanke Zazhi)

@#Currently, the early diagnosis of glaucoma and monitoring of disease progression is difficult and requires assessment of structural(fundus photo/ optical coherence tomography scan)and functional damage(visual fields)of the optic nerve head(ONH). It requires the clinical knowledge of glaucoma experts and is highly labor intensive. Artificial intelligence(AI)applications have been proposed to improve the understanding of glaucoma and help to reduce the time and manpower required for such clinical tasks. With the advent of deep learning(DL), many tools for ophthalmological image enhancement, segmentation and classification have also emerged. Especially in the last three years, a large number of algorithms suitable for analyzing the ONH structure and/or function, which have been proposed to help in glaucoma detection. AI tools have also been developed to predict the early progression of the disease. Bring the possibility of personalized precision treatment. However, these algorithms are yet to be tested in the real world. This review summarizes the diverse landscape of AI algorithms developed for glaucoma. We also discuss the current limitations and challenges that we need to overcome.

Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy

Purpose: To evaluate the sensitivity and specificity of smartphone-based nonmydriatic (NM) retinal camera in the detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) in a tertiary eye care facility. Methods: Patients with diabetes underwent retinal photography with a smartphone-based NM fundus camera before mydriasis and standard 7-field fundus photography with a desktop mydriatic fundus camera after mydriasis. DR was graded using the international clinical classification of diabetic retinopathy system by two retinal expert ophthalmologists masked to each other and to the patient's identity. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to detect DR and STDR by NM retinal imaging were assessed. Results: 245 people had gradable images in one or both eyes. DR and STDR were detected in 45.3% and 24.5%, respectively using NM camera, and in 57.6% and 28.6%, respectively using mydriatic camera. The sensitivity and specificity to detect any DR by NM camera was 75.2% (95% confidence interval (CI) 68.1–82.3) and 95.2% (95%CI 91.1–99.3). For STDR the values were 82.9% (95% CI 74.0–91.7) and 98.9% (95% CI 97.3–100), respectively. The PPV to detect any DR was 95.5% (95% CI 89.8–98.5) and NPV was 73.9% (95% CI 66.4–81.3); PPV for STDR detection was 96.7% (95% CI 92.1–100)) and NPV was 93.5% (95% CI 90.0–97.1). Conclusion: Smartphone-based NM retinal camera had fairly high sensitivity and specificity for detection of DR and STDR in this clinic-based study. Further studies are warranted in other settings.

Serial Follow-up of Commotio Retinae Using Ultra-wide Field Imaging

PURPOSE: To quantify the size of commotio retinae and investigate its spontaneous resolution over time using ultra-wide field (UWF) color fundus photography.METHODS: We analyzed serial UWF color fundus photographs of 33 eyes of 33 ocular trauma patients with commotio retinae. Total visible retinal areas and the areas of commotio retinae were measured at baseline, 3 days, 1 week, and 4 weeks from the initial traumatic event.RESULTS: The median time of observation was 10.8 ± 12.1 (4-44) weeks. Spontaneous resolution of commotio retinae was observed in all patients, and no patients experienced any complications during the follow-up period. The mean percentage of commotio retinae at 3 days significantly decreased compared to the baseline (8.51 ± 9.66% versus 12.23 ± 10.39%; p < 0.001), and more decreased at 1 week (1.04 ± 2.75%; p < 0.001), but no significant differences were observed between 1 week and 4 weeks (0.00 ± 0.00%; p = 0.219). The spontaneous resolution percentages during the first 3 days, between 3 days and 1 week, and during the next 4 weeks were 12.97 ± 13.44%/day, 19.62 ± 9.22%/day, and 0.87 ± 1.87%/day, respectively (p = 0.192 and p < 0.001, respectively). The resolution rate was higher during the first 1 week.CONCLUSIONS: We quantified the size of commotio retinae using UWF color fundus photography. Most patients with commotio retinae resolved spontaneously during the first 1 week following trauma, and all cases completely resolved at 1 month without any complications.

A preliminary study of a deep learning assisted diagnostic system with an artificial intelligence for detection of retina disease / 国际眼科杂志(Guoji Yanke Zazhi)

@#AIM:To evaluate the application value of artificial intelligence diagnosis system for fundus disease screening based on deep learning.<p>METHODS:A total of 1 345 patients(2 690 eyes)in our hospital were recruited from July 2018 to December 2018. The accuracy, specificity, consistency and sensitivity of the artificial intelligence diagnosis system were determined by comparison with ophthalmologist diagnosis and artificial intelligence diagnosis system which based on multi-layer deep convolution neural network learning. <p>RESULTS:The accuracy of artificial intelligence diagnosis system is 62.82%. There are 1-5(1.38±0.67)diagnoses among the patients, among which the accuracy of one diagnosis is 56.09%, the accuracy of two diagnosis is 77.96%, the accuracy of three diagnosis is 84.61%, the accuracy of four diagnosis is 86.95%, and the accuracy of five diagnosis is 60.00%; The consistency kappa value without obvious abnormality and leopard pattern fundus was 0.044 and 0.169 respectively. The sensitivity was 3.00% and 99.6% respectively, the specificity was 99.7% and 14.2% respectively. The consistency Kappa value of other diagnosis was as high as 0.57-1.00, the sensitivity was as high as 65.1%-100%, and the specificity was as high as 93.0%-100%. <p>CONCLUSION:This study shows that the artificial intelligence diagnosis system based on multi-layer deep convolution neural network learning is a reliable alternative to diagnose retina diseases, and it is expected to become an effective screening tool for primary medical treatment.

Retinal cafe-au-lait macules: A rare retinal finding in a patient with neurofibromatosis type 1

We report the retinal and choroidal manifestations using multimodal imaging in a patient with Neurofibromatosis type 1 (NF-1). In this report, we describe the occurrence of a new retinal finding which we label as retinal caf�-au-lait macules. Also, we describe the superiority of multicolour imaging in comparison to colour fundus photography for identifying the retinal manifestations in NF-1.

Trash to treasure Retcam

Digital fundus imaging is being used in diagnosis, documentation, and sharing of many retinal diseases and hence forms an essential part of ophthalmology. The use of smartphones for the same has been ever increasing. There is a need for simpler devices to couple the 20D lens and smartphone so as to take fundus photographs which can help in fundus documentation. This article describes a simple inexpensive technique of preparing a smartphone fundus photography device (Trash To Treasure (T3) Retcam) from the used materials in the clinics within minutes. This article will also review the optical principles of the T3 Retcam and describe the step–by–step method to record good-quality retinal image/videos. This inexpensive device is made by recycling and modifying the plastic hand sanitizer bottle in the clinics/hospitals which can be used for documenting, diagnosing, screening, and academic purposes.

Research status and prospect of deep learning algorithm-based artificial intelligence in assisted diagnosis of diabetic retinopathy / 中华实验眼科杂志

Based on deep learning algorithm, big stride development has been made about artificial intelligence ( AI) technology,both in its basic theory and clinical ophthalmic image analysis. AI can diagnose diabetic retinopathy ( DR) automatically by using color fundus photography. Compared with other ophthalmic diseases, DR assisted diagnosis with AI might be far more advanced technic. Benefited from advantage of fast diagnostic speed,high accuracy and accordingly saved human resources, great potential can be expected in AI-assisted DR screening and grading. However,as a recently developed interdisciplinary technology,deep learning-based AI-aided DR screening system still needs multidisciplinary cooperation and resources sharing to get further development,such as overcoming data standardization, real-world verification and productization issues. Although challenges coexist, AI applied in ophthalmology clinical practice can be realized with technical development and widespread concern of society.

Automated analysis of microaneurysm lesions in standard seven-field color fundus photography / 上海交通大学学报（医学版）

Objective • To evaluate the accuracy and efficiency of the automated supervised machine-learning algorithm for microaneurysm lesion detection in seven-field color fundus photography. Methods • A total of 616 seven-field color fundus photographs were obtained from 44 patients with diabetic retinopathy (DR) from Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from 2014 to 2016. Using the microaneurysm detection algorithm developed in this study, the automated identification and labeling of microaneurysm lesions in the standard seven-field color photography of DR were performed. The results were compared with manual labeling by ophthalmologists to evaluate the sensitivity and efficiency of the automated algorithm. Results • In the standard seven-field fundus color photographic image library, the automated algorithm achieved sensitivity of 94.15% in total and 93.09% in the optic disc field (F1), 94.84% in the macula field (F2), 95.16% in the temporal to macula field (F3), 94.99% in the superior temporal field (F4), 93.77% in the inferior temporal field (F5), 92.40% in the superior nasal field (F6) and 93.75% in the inferior nasal field (F7), and specificity of 98.05% in total and 98.02% in F1, 98.06% in F2, 97.97% in F3, 97.91% in F4, 98.07% in F5, 98.03% in F6 and 98.23% in F7. The cost of time per image was (9.2± 0.6) s, 93.2% less time than manual labeling. Conclusion • The automated microaneurysm detection algorithm can accurately and efficiently identify microaneurysm lesions in color fundus photography.

Effect of non-mydriatic fundus photography in screening diabetic retinopathy / 国际眼科杂志(Guoji Yanke Zazhi)

@#AIM:To observe and analyze the effect of non-mydriatic fundus photography in screening diabetic retinopathy(DR), so as to provide the basis for clinical screening.<p>METHODS:In our hospital from December 2016 to November 2017, 120 patients(240 eyes)was diagnosed as diabetes(DM), which were treated as the subjects of observation. By the same operator with non-mydriatic fundus photography, fundus photography and 7 range fundus fluorescein angiography(FFA)after mydriasis were taken. Taking the international clinical classification of diabetic retinopathy(DR)as the standard, the above three examinations were review, grade and record by the same physician by blind method. The fundus fluorescein angiography as the gold standard, the other two results were compared to detect the sensitivity, specificity, Youden index, Kappa value of the two for DR with different grade.<p>RESULTS: There was 70.0% eyes diagnosed as diabetic retinopathy after screened by fundus angiography, 66.7% by post-mydriatic fundus photography, 65.0% by non-mydriatic fundus photography. The grading results of diabetic retinopathy screened by different methods were basically consistent, with no significant difference(<i>P</i>>0.05). When screening for diabetic retinopathy of different degrees, the sensitivity and specificity of the non-mydriatic group were 92.9% and 90.3%, respectively. There was no significant difference between the results of the non-mydriatic group and the non-mydriatic group. Compared with the gold standard group(FFA), the Youden index(83.14%)was close to 1, with high reliability; Kappa=0.81, and the validation was consistent. When screening for moderately nonproliferative diabetic retinopathy, the sensitivity and specificity of non-mydriatic fundus photography were 90.6% and 95.5%; there was no significant difference between the results of non-mydriatic and the results of fundus photography after mydriasis. Compared to the gold standard group, the Youden index was 86.09%, the reliability is high, Kappa=0.86, and the test was consistency. <p>CONCLUSION:Non-mydriatic fundus photography can be used as a simple and accurate method for screening diabetic retinopathy. It is simple and easy to carry out without risk. It is easy to train specialist technicians for multi-point operation. With the help of today's convenient network, the image is transmitted to an experienced ophthalmologist for reading and diagnosis, which is convenient and fast, so that the patient can be diagnosed and treated nearby, which has positive significance for the society.

Application of new fundus imaging in diabetic retinopathy / 中华眼底病杂志

Diabetic retinopathy (DR) is one of the most common causes of visual impairment and blindness in diabetic patients.It is particularly important to set up simpler,safer,non-invasive and highly effective methods for diagnosis as well as monitoring DR.A variety of new fundus imaging techniques show great advantages in early diagnosis,treatment and monitoring of DR in recent years,The main characteristics of wide-field scanning laser imaging system is achieving a large range of retinal image in a single photograph and without mydriasis.It provides several options for color images,FFA and FAF,which satisfy to detect the retina,choroid and vascular structure.Multi spectral fundus imaging system is suitable for DR screening,because it is able to recognize the typical characteristics of DR,such as microaneurysms,hemorrhage and exudation,and is non-invasive and convenient.OCT angiography is a quantitative examination that provides foveal avascular zone area,macular blood flow density,which provides strong evidence for DR diagnosis.The improvement of these new techniques will help us to build up a personalized evaluation system of DR.

Measurement of size of pigmented choroidal nevus: Superiority of multicolor imaging compared to conventional color fundus photography

Choroidal nevi are benign fundus lesions that require regular follow with documentation. Conventional color fundus photography (CFP) has traditionally been used to images these lesions. Multicolor imaging (MCI) available on Spectralis spectral domain optical coherence tomography system is increasingly been tested vis-à-vis conventional CFP in various retinal diseases. We present data of the right eye of a 59-year-old gentleman with choroidal nevus who underwent conventional CFP as well as MCI. Nevus appeared orange red on MCI and its size appeared larger than the same measured on conventional CFP. We also report infrared reflectance and near infrared autofluorescence features of choroidal nevus.

The diagnostic accuracy of single- and five-field fundus photography in diabetic retinopathy screening by primary care physicians

Purpose: The aim is to evaluate the diagnostic accuracy of digital fundus photography in diabetic retinopathy (DR) screening at a single university hospital. Methods: This was a cross-sectional hospital-based study. One hundred and ninety-eight diabetic patients were recruited for comprehensive eye examination by two ophthalmologists. Five-field fundus photographs were taken with a digital, nonmydriatic fundus camera, and trained primary care physicians then graded the severity of DR present by single-field 45° and five-field fundus photography. Sensitivity and specificity of DR grading were reported using the findings from the ophthalmologists' examinations as a gold standard. Results: When fundus photographs of the participants' 363 eyes were analyzed for the presence of DR, there was substantial agreement between the two primary care physicians, ? = 0.6226 for single-field and 0.6939 for five-field photograph interpretation. The sensitivity and specificity of DR detection with single-field photographs were 70.7% (95% Confidence interval [CI]; 60.2%–79.7%) and 99.3% (95% CI; 97.4%–99.9%), respectively. Sensitivity and specificity for five-field photographs were 84.5% (95% CI; 75.8%–91.1%) and 98.6% (95% CI; 96.5%–99.6%), respectively. The receiver operating characteristic was 0.85 (0.80–0.90) for single-field photographs and 0.92 (0.88–0.95) for five-field photographs. Conclusion: The sensitivity and specificity of fundus photographs for DR detection by primary care physicians were acceptable. Single- and five-field digital fundus photography each represent a convenient screening tool with acceptable accuracy.