Article
Medicine, General & Internal
Zhenquan Wu, Wenjia Cai, Hai Xie, Shida Chen, Yanbing Wang, Baiying Lei, Yingfeng Zheng, Lin Lu
Summary: In this study, an AI system was developed to predict vision-threatening conditions in high myopia based on fundus photographs. The deep learning model showed superior performance compared to ophthalmologists and comparable performance to retinal specialists. The application of this system can save cost and is more suitable for use in less developed areas.
FRONTIERS IN MEDICINE
(2022)
Review
Engineering, Biomedical
K. C. Pavithra, Preetham Kumar, M. Geetha, Sulatha V. Bhandary
Summary: Diabetic Macular Edema (DME) is a serious complication of Diabetic Retinopathy (DR) and it is the leading cause of vision loss in diabetics. DME is characterized by the accumulation of fluid in the macula due to leaky blood vessels. Advanced imaging techniques such as Color Fundus Photography (CFP) and Optical Coherence Tomography (OCT) can detect the presence of DME at different stages of DR. This review article discusses the latest automated DME detection methods using traditional Machine Learning (ML) and Deep Learning (DL) techniques with retinal fundus or OCT images.
BIOCYBERNETICS AND BIOMEDICAL ENGINEERING
(2023)
Article
Pharmacology & Pharmacy
Thibaud Mathis, Batoul El Ameen, Cristina Vartin, Yasmine Serrar, Frederic Matonti, Aditya Sudhalkar, Alper Bilgic, Amina Rezkallah, Laurent Kodjikian
Summary: This study examined the validity of using anatomical criteria alone to make retreatment decisions in patients with DME, compared to the gold standard that incorporates visual acuity. The OCT-guided strategy yielded equivalent results to the gold standard in 82.7% of cases, with variations in sensitivity and specificity based on the patient's treatment regimen.
Article
Medicine, General & Internal
Yun Bai, Jing Li, Lianjun Shi, Qin Jiang, Biao Yan, Zhenhua Wang
Summary: The study proposes a lightweight model (DME-DeepLabV3+) for extracting diabetic macular edema in OCT images, utilizing DeepLabV3+ architecture with MobileNetV2 backbone, improved ASPP for high-level feature extraction, and a decoder for feature fusion and refinement. The DME-DeepLabV3+ model shows better extraction performance compared to other models, with higher accuracy and F1-score.
FRONTIERS IN MEDICINE
(2023)
Review
Ophthalmology
Suchetha Manikandan, Rajiv Raman, Ramachandran Rajalakshmi, S. Tamilselvi, R. Janani Surya
Summary: Diabetic macular edema (DME) is a significant cause of visual impairment, and deep learning methods have been developed for its detection. However, the performance of these algorithms varies, raising doubts about their clinical utility. This survey provides an overview of DME detection methods using deep learning, aiming to inform research groups, healthcare professionals, and diabetic patients about the applications of this technology in retinal image detection and classification. The study analyzed various deep learning models, their precision, capacity to detect anomalies with limited training data, concepts, and challenges. The overall performance of the models evaluated in this study yielded promising results.
INDIAN JOURNAL OF OPHTHALMOLOGY
(2023)
Review
Ophthalmology
Suchetha Manikandan, Rajiv Raman, Ramachandran Rajalakshmi, S. Tamilselvi, Janani Surya
Summary: Diabetic macular edema (DME) is a common cause of visual impairment in the working-age group, and deep learning methods have been developed to detect DME from retinal and optical coherence tomography (OCT) images. This survey provides a comprehensive overview of macular edema detection methods, including cutting-edge research, and aims to provide relevant information to research groups, healthcare professionals, and diabetic patients. The study analyzed various deep learning models and their performance in detecting DME, showing high overall sensitivity for both OCT and fundus image detection.
INDIAN JOURNAL OF OPHTHALMOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Huan-Yu Hsu, Yu-Bai Chou, Ying-Chun Jheng, Zih-Kai Kao, Hsin-Yi Huang, Hung-Ruei Chen, De-Kuang Hwang, Shih-Jen Chen, Shih-Hwa Chiou, Yu-Te Wu
Summary: This study proposes a modified U-net deep learning algorithm to segment fluid and the ellipsoid zone (EZ) from OCT images of patients with diabetic macular edema (DME). The model achieves high performance in segmenting these features and correlates EZ disruption with best corrected visual acuity (BCVA).
Article
Engineering, Electrical & Electronic
Jun Wu, Yaxin Zhang, Zhitao Xiao, Fang Zhang, Lei Geng
Summary: In this paper, an attention mechanism based on residual convolution module U-Net (RCU-Net) is proposed for the automatic segmentation of the retinal layer and cystoid edema lesions in DME. By fusing the residual structure and CBAM for feature extraction, the network can effectively learn different levels of information. Experimental results show that the proposed method achieves high accuracy and MIoU in DME segmentation.
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
(2023)
Article
Medicine, General & Internal
Fabao Xu, Shaopeng Liu, Yifan Xiang, Jiaming Hong, Jiawei Wang, Zheyi Shao, Rui Zhang, Wenjuan Zhao, Xuechen Yu, Zhiwen Li, Xueying Yang, Yanshuang Geng, Chunyan Xiao, Min Wei, Weibin Zhai, Ying Zhang, Shaopeng Wang, Jianqiao Li
Summary: This study utilizes generative adversarial network (GAN) to generate and evaluate individualized post-therapeutic optical coherence tomography (OCT) images based on pre-therapeutic images, aiming to predict the short-term response of anti-vascular endothelial growth factor (VEGF) therapy for diabetic macular edema (DME). Results show that the synthetic OCT images generated by the GAN model are comparable to the actual images and can accurately predict edema resorption.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Medicine, General & Internal
Xingguo Wang, Yanyan Zhang, Yuhui Ma, William Robert Kwapong, Jianing Ying, Jiayi Lu, Shaodong Ma, Qifeng Yan, Quanyong Yi, Yitian Zhao
Summary: In this study, a new automated framework driven by deep learning was introduced to extract three-dimensional parameters from retinal OCT images for quantification of retinal HRF in DME patients. The results revealed significant differences in the amount and volume of HRF subtypes and showed that the distance between HRF and retinal pigmented epithelium decreased after treatment. The improvement in central macular thickness was positively correlated with the distance from HRF subtypes to the fovea.
FRONTIERS IN MEDICINE
(2023)
Article
Medicine, General & Internal
Haifan Huang, Liangjiu Zhu, Weifang Zhu, Tian Lin, Leonoor Inge Los, Chenpu Yao, Xinjian Chen, Haoyu Chen
Summary: The study developed an algorithm using deep learning technology to detect and quantify HRDs on OCT for DME patients. The algorithm showed stronger correlation and higher ICC with rater 1 compared to inter-rater agreement, providing an objective and repeatable tool for OCT analysis in clinical practice and research.
FRONTIERS IN MEDICINE
(2021)
Article
Ophthalmology
Carolina Arruabarrena, Antonio Rodriguez-Miguel, German Allendes, Carlos Vera, Beatriz Son, Miguel A. Teus
Summary: Combining spectral domain optical coherence tomography with monoscopic fundus photography using a nonmydriatic camera (MFP-NMC) can improve the accuracy of diabetic macular edema (DME) referrals.
RETINA-THE JOURNAL OF RETINAL AND VITREOUS DISEASES
(2023)
Article
Computer Science, Information Systems
Amit Kumar, Anand Shanker Tewari
Summary: Diabetic macular edema (DME) is an expansion of the disease diabetic retinopathy (DR) that can lead to irreversible vision loss for diabetic individuals at high risk. This paper introduces a method called SEDense to classify the severity of DME grades using pre-processed images. SEDense outperforms other state-of-the-art models and achieves an accuracy of 88.35% in classifying DME grades, reducing the burden on ophthalmologists in diagnosis.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Medicine, General & Internal
Carolina Arruabarrena, Antonio Rodriguez-Miguel, Fernando de Aragon-Gomez, Purificacion Escamez, Ingrid Rosado, Miguel A. Teus
Summary: The purpose of this study was to establish normative data for macular thickness and volume in a diabetic population. The researchers used spectral-domain optical coherence tomography (SD-OCT) to observe and compare macular thickness and volume between diabetic patients and a reference population. The results showed that diabetic patients had thinner macular thickness and volume compared to the reference population.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Medicine, General & Internal
Xue Bai, Rui Hua
Summary: The study found that fluorescein angiography had a higher accuracy in detecting the severity of diabetic retinopathy and macular leakages compared to optical coherence tomography. Central foveal thickness is not a sensitive parameter for detecting latent DMEs.
FRONTIERS IN MEDICINE
(2021)
Article
Engineering, Biomedical
Akinori Mitani, Abigail Huang, Subhashini Venugopalan, Greg S. Corrado, Lily Peng, Dale R. Webster, Naama Hammel, Yun Liu, Avinash V. Varadarajan
NATURE BIOMEDICAL ENGINEERING
(2020)
Article
Ophthalmology
Sukhum Silpa-Archa
Summary: A sutureless and equipment-free technique for contact lens wide-angle viewing system during vitreoretinal surgery was proposed. The technique allows the surgeon to control the contact lens with three fingers and move it freely, providing a clear view of the retina.
RETINA-THE JOURNAL OF RETINAL AND VITREOUS DISEASES
(2023)
Article
Ophthalmology
Sukhum Silpa-Archa, Worapon Ittharat, Peranut Chotcomwongse, Janine M. Preble, C. Stephen Foster
Summary: Changes in choroidal volume in recurrent VKH patients were demonstrated using EDI-OCT. Choroidal parameters significantly decreased when inflammation subsided, with central choroidal volume potentially serving as a biomarker for detecting choroidal morphological change.
CURRENT EYE RESEARCH
(2021)
Article
Ophthalmology
Sukhum Silpa-archa, Akkaranisorn Dejkong, Kwanchanoke Kumsiang, Peranut Chotcomwongse, Janine M. Preble, C. Stephen Foster
INTERNATIONAL JOURNAL OF OPHTHALMOLOGY
(2020)
Article
Rheumatology
Kittiwan Sumethkul, Indhira Urailert, Tassanee Kitumnuaypong, Sungchai Angthararak, Sukhum Silpa-Archa
Summary: This study investigated the incidence, risk factors, and time to diagnosis of rheumatologic disease in patients with isolated inflammatory eye diseases. The results showed that bilateral eye involvement in IED was a significant risk factor for the development of rheumatologic disease, and positive ANA could predict rheumatologic disease in patients with retinal vasculitis and optic neuritis.
CLINICAL RHEUMATOLOGY
(2022)
Article
Ophthalmology
Sukhum Silpa-archa, Tararat Hoopholerb, Charles Stephen Foster
Summary: The purpose of this study was to determine the sensitivity and specificity of syphilis antibody tests in vitreous samples and propose an algorithm using vitreous syphilis antibody as a supplementary test to confirm syphilitic uveitis (SU). The results showed that EIA and FTA-ABS IgG were the most sensitive and specific tests for detecting syphilis antibodies in vitreous.
Review
Virology
Sukhum Silpa-Archa, Wararee Sriyuttagrai, C. Stephen Foster
Summary: There are still many research challenges and unanswered questions in relation to Epstein-Barr virus-associated uveitis, including the presence of viral DNA in asymptomatic patients, its pathogenicity in uveitis eyes, and the effectiveness of antiviral therapy. A retrospective review was conducted on data collected from a Thai hospital's Ophthalmology Department, revealing that patients with EBV infection may also be co-infected with other pathogens. Most cases showed clinical improvement with systemic acyclovir and ganciclovir treatment, and the majority of patients achieved a cure for the EBV infection.
JOURNAL OF CLINICAL VIROLOGY
(2022)
Article
Ophthalmology
Kengadhevi Yogeswaran, Joao M. Furtado, Bahram Bodaghi, Janet M. Matthews, Justine R. Smith
Summary: Ocular toxoplasmosis is a common global infection. This study provides an overview of the current management approach for ocular toxoplasmosis based on a survey completed by uveitis-specialised ophthalmologists from 48 countries. The findings include clinical features, diagnostic methods, treatment options, and follow-up practices. The majority of respondents used clinical examination and serology for diagnosis, and oral trimethoprim-sulfamethoxazole was the most commonly used first-line therapy. Follow-up and prophylaxis against recurrence were also discussed.
BRITISH JOURNAL OF OPHTHALMOLOGY
(2023)
Article
Health Care Sciences & Services
Fernando G. Vieira, Subhashini Venugopalan, Alan S. Premasiri, Maeve McNally, Aren Jansen, Kevin McCloskey, Michael P. Brenner, Steven Perrin
Summary: This study developed a machine learning-based objective measure for assessing the severity of ALS disease. By analyzing voice samples and accelerometer data, the researchers trained models to predict ALS scores related to speech and limb functions. The results showed that these models can accurately predict ALS functional scores and have the potential to evaluate drug effects.
NPJ DIGITAL MEDICINE
(2022)
Article
Ophthalmology
Sukhum Silpa-Archa, Withawat Sapthanakorn, C. Stephen Foster
Summary: This study aims to identify prognostic factors for poor visual outcomes in patients with isolated retinal vasculitis and investigate the outcome of immunosuppressive treatment without the use of antituberculosis drugs. Through retrospective chart review and statistical analysis, logMAR visual acuity at the initial visit and outer retinal disruption were found to be significantly associated with poor visual outcomes. Immunosuppressive treatment without antituberculosis drugs seems to be a promising regimen for selected patients with presumed tuberculous retinal vasculitis.
RETINA-THE JOURNAL OF RETINAL AND VITREOUS DISEASES
(2022)
Article
Ophthalmology
Yodpong Chantarasorn, Kochapong Rasmidatta, Itsara Pokawattana, Sukhum Silpa-archa
Summary: This study aimed to evaluate the effects of the cortisol inhibitor ketoconazole on the resolution of subretinal fluid (SRF) in patients with central serous chorioretinopathy (CSCR) and analyze the correlation between choroidal thickness and steroid hormones. The results showed that ketoconazole significantly shortened the resolution time of CSCR and reduced the proportion of eyes receiving rescue therapy. Additionally, high cortisol levels were significantly associated with choroidal thickness.
CLINICAL OPHTHALMOLOGY
(2022)
Article
Medicine, General & Internal
Natsuda Kaothanthong, Jirawut Limwattanayingyong, Sukhum Silpa-archa, Mongkol Tadarati, Atchara Amphornphruet, Panisa Singhanetr, Pawas Lalitwongsa, Pantid Chantangphol, Anyarak Amornpetchsathaporn, Methaphon Chainakul, Paisan Ruamviboonsuk
Summary: By comparing the performance of deep learning (DL) in the classification of OCT images of macular diseases between automated classification alone and in combination with automated segmentation, it was found that applying DL for segmentation prior to classification can improve the accuracy of classification.
Review
Ophthalmology
Sukhum Silpa-archa, Jirawut Limwattanayingyong, Mongkol Tadarati, Atchara Amphornphruet, Paisan Ruamviboonsuk
Summary: Capacity building for screening and treatment of diabetic retinopathy focuses on nonophthalmologists, aiming to maintain a certain level of sensitivity and specificity for their practices. Collaboration between different organizations is key to improving the quality and quantity of medical professionals in low-income countries.
INDIAN JOURNAL OF OPHTHALMOLOGY
(2021)
Article
Ophthalmology
Sukhum Silpa-archa, Kwanchanoke Kumsiang, Janine M. Preble
Summary: The study described the incidence, clinical characteristics, and treatment outcomes of endophthalmitis after pars plana vitrectomy (PPV) with recycled single-use devices. The rate of endophthalmitis in patients who underwent 23-gauge PPV was comparable to those who underwent 25-gauge PPV. With a standardized protocol for instrument sterilization, endophthalmitis rates in those using recycled single-use instruments were within the range of previously published results.
INTERNATIONAL JOURNAL OF RETINA AND VITREOUS
(2021)