Enhancing stroke risk and prognostic timeframe assessment with deep learning and a broad range of retinal biomarkers (2024)

Li Linxin, Scott Catherine A., Rothwell Peter M., et al., Trends in stroke incidence in high-income countries in the 21st century, Stroke (2020).

Johnson Catherine Owens, Nguyen Minh, Roth Gregory A, Nichols Emma, Alam Tahiya, Abate Degu, Abd-Allah Foad, Abdelalim Ahmed, Abraha Haftom Niguse, Abu-Rmeileh Niveen ME, et al., Global, regional, and national burden of stroke, 1990–2016: a systematic analysis for the global burden of disease study 2016, Lancet Neurol 18 (5) (2019) 439–458.

Feigin Valery L, Owolabi Mayowa O, Abd-Allah Foad, Akinyemi Rufus O, Bhattacharjee Natalia V, Brainin Michael, Cao Jackie, Caso Valeria, Dalton Bronte, Davis Alan, et al., Pragmatic solutions to reduce the global burden of stroke: a world stroke organization–lancet neurology commission, Lancet Neurol 22 (12) (2023) 1160–1206.

Ikeme Shelly, Kottenmeier Emilie, Uzochukwu Goldfield, Brinjikji Waleed, Evidence-based disparities in stroke care metrics and outcomes in the United States: a systematic review, Stroke 53 (3) (2022) 670–679.

Wannamethee S Goya, Shaper A Gerald, Lennon Lucy, Morris Richard W, Metabolic syndrome vs framingham risk score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus, Arch Internal Med 165 (22) (2005) 2644–2650.

Piepoli Massimo F, Hoes Arno W, Agewall Stefan, Albus Christian, Brotons Carlos, Catapano Alberico L, Cooney Marie-Therese, Corrà Ugo, Cosyns Bernard, Deaton Christi, et al., Guidelines: Editor’s choice: 2016 European guidelines on cardiovascular disease prevention in clinical practice: The sixth joint task force of the European society of cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of 10 societies and by invited experts) developed with the special contribution of the European association for cardiovascular prevention & rehabilitation (EACPR), Eur Heart J 37 (29) (2016) 2315.

Allon Raviv, Aronov Michael, Belkin Michael, Maor Elad, Shechter Michael, Fabian Ido Didi, Retinal microvascular signs as screening and prognostic factors for cardiac disease: a systematic review of current evidence, Am J Med 134 (1) (2021) 36–47.

Li Jiaqi, Imano Hironori, Kitamura Akihiko, Kiyama Masahiko, Yamagishi Kazumasa, Tanaka Mari, Ohira Tetsuya, Sankai Tomoko, Umesawa Mitsumasa, Muraki Isao, et al., Retinal microvascular abnormalities and risks of incident stroke and its subtypes: The circulatory risk in communities study, J Hypertens 40 (4) (2022) 732–740.

Guo Shaohua, Yin Songtao, Tse Gary, Li Guangping, Su Long, Liu Tong, Association between caliber of retinal vessels and cardiovascular disease: a systematic review and meta-analysis, Curr Atheroscler Rep 22 (2020) 1–13.

Cheung Carol Yim-lui, Ikram M Kamran, Chen Christopher, Wong Tien Yin, Imaging retina to study dementia and stroke, Prog Retin Eye Res 57 (2017) 89–107.

Drobnjak Dragana, Munch Inger Christine, Glümer Charlotte, Faerch Kristine, Kessel Line, Larsen Michael, Veiby Nina CBB, et al., Retinal vessel diameters and their relationship with cardiovascular risk and all-cause mortality in the inter99 eye study: a 15-year follow-up, J Ophthalmol 2016 (2016).

Guo Vivian Yawei, Chan Juliana Chung Ngor, Chung Harriet, Ozaki Risa, So Wingyee, Luk Andrea, Lam Augustine, Lee Jack, Zee Benny Chung-Ying, Retinal information is independently associated with cardiovascular disease in patients with type 2 diabetes, Sci Rep 6 (1) (2016) 19053.

Dumitrascu Oana M, Demaerschalk Bart M, Sanchez Cristina Valencia, Almader-Douglas Diana, O’Carroll Cumara B, Aguilar Maria I, Lyden Patrick D, Kumar Gyanendra, Retinal microvascular abnormalities as surrogate markers of cerebrovascular ischemic disease: a meta-analysis, J Stroke Cerebrovasc Dis 27 (7) (2018) 1960–1968.

Hughes Alun D, Falaschetti Emanuela, Witt Nicholas, Wijetunge Sumangali, Thom Simon A McG, Tillin Therese, Aldington Steve J, Chaturvedi Nish, Association of retinopathy and retinal microvascular abnormalities with stroke and cerebrovascular disease, Stroke 47 (11) (2016) 2862–2864.

Sandoval-Garcia Emmanuel, McLachlan Stela, Price Anna H, MacGillivray Thomas J, Strachan Mark WJ, Wilson James F, Price Jackie F, Retinal arteriolar tortuosity and fractal dimension are associated with long-term cardiovascular outcomes in people with type 2 diabetes, Diabetologia 64 (10) (2021) 2215–2227.

Liu Baoyi, Hu Yijun, Ma Guixian, Xiao Yu, Zhang Bin, Liang Yingying, Zhong Pingting, Zeng Xiaomin, Lin Zhanjie, Kong Huiqian, et al., Reduced retinal microvascular perfusion in patients with stroke detected by optical coherence tomography angiography, Front Aging Neurosci 13 (2021).

Hu Kaiyan, Jiang Mengyao, Zhou Qi, Zeng Weiting, Lan Xuhong, Gao Qianqian, Mei Fan, Zhao Li, Chen Fei, Wu Anhu, et al., Association of diabetic retinopathy with stroke: a systematic review and meta-analysis, Front Neurol 12 (2021).

Barrot Joan, Real Jordi, Vlacho Bogdan, Romero-Aroca Pedro, Simó Rafael, Mauricio Didac, Mata-Cases Manel, Castelblanco Esmeralda, Mundet-Tuduri Xavier, Franch-Nadal Josep, Diabetic retinopathy as a predictor of cardiovascular morbidity and mortality in subjects with type 2 diabetes, Front Med 9 (2022).

Wong Ka-Ho, Hu Katherine, Peterson Cecilia, Sheibani Nazanin, Tsivgoulis Georgios, Majersik Jennifer J, de Havenon Adam H, Diabetic retinopathy and risk of stroke: a secondary analysis of the ACCORD eye study, Stroke 51 (12) (2020) 3733–3736.

Castelblanco Esmeralda, Granado-Casas Minerva, Hernández Marta, Pinyol Montserrat, Correig Eudald, Julve Josep, Rojo-López Marina Idalia, Alonso Núria, Avogaro Angelo, Ortega Emilio, et al., Diabetic retinopathy predicts cardiovascular disease independently of subclinical atherosclerosis in individuals with type 2 diabetes: A prospective cohort study, Front Cardiovasc Med 9 (2022).

Poplin Ryan, Varadarajan Avinash V, Blumer Katy, Liu Yun, McConnell Michael V, Corrado Greg S, Peng Lily, Webster Dale R, Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning, Nat Biomed Eng 2 (3) (2018) 158–164.

Coronado Ivan, Abdelkhaleq Rania, Yan Juntao, Marioni Sergio Salazar, Jagolino-Cole Amanda, Channa Roomasa, Pachade Samiksha, Sheth Sunil A, Giancardo Luca, Towards stroke biomarkers on fundus retinal imaging: a comparison between vasculature embeddings and general purpose convolutional neural networks, in: 2021 43rd annual international conference of the IEEE engineering in medicine & biology society, EMBC, IEEE, 2021, pp. 3873–3876.

Rim Tyler Hyungtaek, Lee Chan Joo, Tham Yih-Chung, Cheung Ning, Yu Marco, Lee Geunyoung, Kim Youngnam, Ting Daniel SW, Chong Crystal Chun Yuen, Choi Yoon Seong, et al., Deep-learning-based cardiovascular risk stratification using coronary artery calcium scores predicted from retinal photographs, Lancet Digit Health 3 (5) (2021) e306–e316.

Zhu Zhuoting, Hu Wenyi, Chen Ruiye, Xiong Ruilin, Wang Wei, Shang Xianwen, Chen Yifan, Kiburg Katerina, Shi Danli, He Shuang, et al., Retinal age gap as a predictive biomarker of stroke risk, BMC Med 20 (1) (2022) 466.

Qu Yimin, Zhuo Yuanyuan, Lee Jack, Huang Xingxian, Yang Zhuoxin, Yu Haibo, Zhang Jinwen, Yuan Weiqu, Wu Jiaman, Owens David, et al., Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis, Front Neurol 13 (2022).

Diaz-Pinto Andres, Ravikumar Nishant, Attar Rahman, Suinesiaputra Avan, Zhao Yitian, Levelt Eylem, Dall’Armellina Erica, Lorenzi Marco, Chen Qingyu, Keenan Tiarnan DL, et al., Predicting myocardial infarction through retinal scans and minimal personal information, Nat Mach Intell 4 (1) (2022) 55–61.

Zhou Yukun, Chia Mark A, Wagner Siegfried K, Ayhan Murat S, Williamson Dominic J, Struyven Robbert R, Liu Timing, Xu Moucheng, Lozano Mateo G, Woodward-Court Peter, et al., A foundation model for generalizable disease detection from retinal images, Nature (2023) 1–8.

Mellor Joseph, Jiang Wenhua, Fleming Alan, McGurnaghan Stuart J, Blackbourn Luke, Styles Caroline, Storkey Amos J, McKeigue Paul M, Colhoun Helen M, Group Scottish Diabetes Research Network Epidemiology, et al., Can deep learning on retinal images augment known risk factors for cardiovascular disease prediction in diabetes? A prospective cohort study from the national screening programme in Scotland, Int J Med Inform 175 (2023).

Zhou Yukun, Wagner Siegfried K, Chia Mark A, Zhao An, Xu Moucheng, Struyven Robbert, Alexander Daniel C, Keane Pearse A, et al., AutoMorph: Automated retinal vascular morphology quantification via a deep learning pipeline, Transl Vis Sci Technol 11 (7) (2022) 12.

Zhou Yukun, Chen Zailiang, Shen Hailan, Zheng Xianxian, Zhao Rongchang, Duan Xuanchu, A refined equilibrium generative adversarial network for retinal vessel segmentation, Neurocomputing 437 (2021) 118–130.

Zhou Yukun, Xu Moucheng, Hu Yipeng, Lin Hongxiang, Jacob Joseph, Keane Pearse A, Alexander Daniel C, Learning to address intra-segment misclassification in retinal imaging, in: Medical image computing and computer assisted intervention–MICCAI 2021: 24th international conference, Strasbourg, France, September 27–October 1, 2021, proceedings, part i 24, Springer, 2021, pp. 482–492.

Xie Enze, Wang Wenhai, Yu Zhiding, Anandkumar Anima, Alvarez Jose M, Luo Ping, SegFormer: Simple and efficient design for semantic segmentation with transformers, Adv Neural Inf Process Syst 34 (2021) 12077–12090.

Orlando José Ignacio, Fu Huazhu, Breda João Barbosa, Van Keer Karel, Bathula Deepti R, Diaz-Pinto Andrés, Fang Ruogu, Heng Pheng-Ann, Kim Jeyoung, Lee JoonHo, et al., Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs, Med Image Anal 59 (2020).

Bajwa Muhammad Naseer, Singh Gur Amrit Pal, Neumeier Wolfgang, Malik Muhammad Imran, Dengel Andreas, Ahmed Sheraz, G1020: A benchmark retinal fundus image dataset for computer-aided glaucoma detection, in: 2020 international joint conference on neural networks, IJCNN, IEEE, 2020, pp. 1–7.

Kovalyk Oleksandr, Morales-Sánchez Juan, Verdú-Monedero Rafael, Sellés-Navarro Inmaculada, Palazón-Cabanes Ana, Sancho-Gómez José-Luis, PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment, Sci Data 9 (1) (2022) 291.

Sengupta Sourya, Singh Amitojdeep, Leopold Henry A, Gulati Tanmay, Lakshminarayanan Vasudevan, Ophthalmic diagnosis using deep learning with fundus images–A critical review, Artif Intell Med 102 (2020).

Gao Xiaoyi Raymond, Wu Fengze, Yuhas Phillip T, Rasel Rafiul Karim, Chiariglione Marion, Automated vertical cup-to-disc ratio determination from fundus images for glaucoma detection, Sci Rep 14 (1) (2024) 4494.

Wang Meng, Chen Ni, Sun Bai-chao, Guo Chun-Bao, Zhang Shuang, Huang Ming-Jie, Zhou Ben-Gang, Wang Xiang-yu, Huang Zheng-Biao, Association between glaucoma and risk of stroke: A systematic review and meta-analysis, Front Neurol 13 (2023).

Cen Ling-Ping, Ji Jie, Lin Jian-Wei, Ju Si-Tong, Lin Hong-Jie, Li Tai-Ping, Wang Yun, Yang Jian-Feng, Liu Yu-Fen, Tan Shaoying, et al., Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks, Nat Commun 12 (1) (2021) 4828.

Cugati Sudha, Cumming Robert G, Smith Wayne, Burlutsky George, Mitchell Paul, Wang Jie Jin, Visual impairment, age-related macular degeneration, cataract, and long-term mortality: the blue mountains eye study, Arch Ophthalmol 125 (7) (2007) 917–924.

Foong Athena WP, Saw Seang-Mei, Loo Jing-Liang, Shen Sunny, Loon Seng-Chee, Rosman Mohamad, Aung Tin, Tan Donald TH, Tai E Shyong, Wong Tien Y, Rationale and methodology for a population-based study of eye diseases in malay people: The Singapore malay eye study (SiMES), Ophthalmic Epidemiol. 14 (1) (2007) 25–35.

Katz Or, Presil Dan, Cohen Liz, Nachmani Roi, Kirshner Naomi, Hoch Yaacov, Lev Tsvi, Hadad Aviel, Hewitt Richard John, Owens David R, Evaluation of a new neural network classifier for diabetic retinopathy, J Diabetes Sci Technol 16 (6) (2022) 1401–1409.

Wang Gengyuan, Huang Yuancong, Ma Ke, Duan Zhengyu, Luo Zhongzhou, Xiao Peng, Yuan Jin, Automatic vessel crossing and bifurcation detection based on multi-attention network vessel segmentation and directed graph search, Comput Biol Med 155 (2023).

Sun Caixia, Chen Tingli, Cong Jing, Wu Xinyuan, Wang Jing, Yuan Yuanzhi, Changes in retinal vascular bifurcation in eyes with myopia, BMC Ophthalmol 22 (1) (2022) 1–8.

Liu Zhuang, Mao Hanzi, Wu Chao-Yuan, Feichtenhofer Christoph, Darrell Trevor, Xie Saining. A convnet for the 2020s. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2022, p. 11976–86.

Radenović Filip, Tolias Giorgos, Chum Ondřej, Fine-tuning CNN image retrieval with no human annotation, IEEE Trans Pattern Anal Mach Intell 41 (7) (2018) 1655–1668.

Nguyen Uyen TV, Bhuiyan Alauddin, Park Laurence AF, Kawasaki Ryo, Wong Tien Y, Wang Jie J, Mitchell Paul, Ramamohanarao Kotagiri, Automated quantification of retinal arteriovenous nicking from colour fundus images, in: 2013 35th annual international conference of the IEEE engineering in medicine and biology society, EMBC, IEEE, 2013, pp. 5865–5868.

Roy Pallab Kanti, Nguyen Uyen TV, Bhuiyan Alauddin, Ramamohanarao Kotagiri, An effective automated system for grading severity of retinal arteriovenous nicking in colour retinal images, in: 2014 36th annual international conference of the IEEE engineering in medicine and biology society, IEEE, 2014, pp. 6324–6327.

Goff David C Jr., Lloyd-Jones Donald M, Bennett Glen, Coady Sean, D’agostino Ralph B, Gibbons Raymond, Greenland Philip, Lackland Daniel T, Levy Daniel, O’donnell Christopher J, et al., 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American college of cardiology/American heart association task force on practice guidelines, Circulation 129 (25_suppl_2) (2014) S49–S73.

Sudlow Cathie, Gallacher John, Allen Naomi, Beral Valerie, Burton Paul, Danesh John, Downey Paul, Elliott Paul, Green Jane, Landray Martin, et al., UK biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age, PLoS Med 12 (3) (2015).

Chua Sharon Yu Lin, Thomas Dhanes, Allen Naomi, Lotery Andrew, Desai Parul, Patel Praveen, Muthy Zaynah, Sudlow Cathie, Peto Tunde, Khaw Peng Tee, et al., Cohort profile: design and methods in the eye and vision consortium of UK biobank, BMJ Open 9 (2) (2019).

DeLong Elizabeth R., DeLong David M., Clarke-Pearson Daniel L., Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach, Biometrics (1988) 837–845.

Dumitrascu Oana M, Demaerschalk Bart M, Sanchez Cristina Valencia, Almader-Douglas Diana, O’Carroll Cumara B, Aguilar Maria I, Lyden Patrick D, Kumar Gyanendra, Retinal microvascular abnormalities as surrogate markers of cerebrovascular ischemic disease: a meta-analysis, J Stroke Cerebrovasc Dis 27 (7) (2018) 1960–1968.

Girach Zain, Sarian Arni, Maldonado-García Cynthia, Ravikumar Nishant, Sergouniotis Panagiotis I, Rothwell Peter M, Frangi Alejandro F, Julian Thomas H, Retinal imaging for the assessment of stroke risk: a systematic review, J Neurol (2024) 1–13.

Aminizadeh Sarina, Heidari Arash, Dehghan Mahshid, Toumaj Shiva, Rezaei Mahsa, Navimipour Nima Jafari, Stroppa Fabio, Unal Mehmet, Opportunities and challenges of artificial intelligence and distributed systems to improve the quality of healthcare service, Artif Intell Med (2024).

Czakó Cecilia, Kovács Tibor, Ungvari Zoltan, Csiszar Anna, Yabluchanskiy Andriy, Conley Shannon, Csipo Tamas, Lipecz Agnes, Horváth Hajnalka, Sándor Gábor László, et al., Retinal biomarkers for Alzheimer’s disease and vascular cognitive impairment and dementia (VCID): implication for early diagnosis and prognosis, Geroscience 42 (2020) 1499–1525.

García-Bermúdez Mariana Yolotzin, Vohra Rupali, Freude Kristine, Wijngaarden Peter van, Martin Keith, Thomsen Maj Schneider, Aldana Blanca Irene, Kolko Miriam, Potential retinal biomarkers in Alzheimer’s disease, Int J Mol Sci 24 (21) (2023) 15834.

Ge Yi-Jun, Xu Wei, Ou Ya-Nan, Qu Yi, Ma Ya-Hui, Huang Yu-Yuan, Shen Xue-Ning, Chen Shi-Dong, Tan Lan, Zhao Qian-Hua, et al., Retinal biomarkers in Alzheimer’s disease and mild cognitive impairment: A systematic review and meta-analysis, Ageing Res Rev 69 (2021).

Csincsik Lajos, MacGillivray Thomas J, Flynn Erin, Pellegrini Enrico, Papanastasiou Giorgos, Barzegar-Befroei Neda, Csutak Adrienne, Bird Alan C, Ritchie Craig W, Peto Tunde, et al., Peripheral retinal imaging biomarkers for Alzheimer’s disease: a pilot study, Ophthalmic Res 59 (4) (2018) 182–192.

Zhang Shiran, Chen Ruiye, Wang Yan, Hu Wenyi, Kiburg Katerina V, Zhang Junyao, Yang Xiaohong, Yu Honghua, He Mingguang, Wang Wei, et al., Association of retinal age gap and risk of kidney failure: A UK biobank study, Am J Kidney Dis 81 (5) (2023) 537–544.

Xu Xiayu, Gao Bin, Ding Wenxiang, Wang Qiong, Zhang Maiye, Tan Tao, Sun Fei, Lei Jianqin, Ji Qiuhe, Xu Feng, Retinal image measurements and their association with chronic kidney disease in Chinese patients with type 2 diabetes: the NCD study, Acta Diabetol 58 (2021) 363–370.

Aronov Michael, Allon Raviv, Stave Danielle, Belkin Michael, Margalit Eyal, Fabian Ido Didi, Rosenzweig Barak, Retinal vascular signs as screening and prognostic factors for chronic kidney disease: a systematic review and meta-analysis of current evidence, J Pers Med 11 (7) (2021) 665.

Mustafar Ruslinda, Hishamuddin Khairun Amalin Mohd, Mohd Rozita, Kamaruzaman Lydia, Halim Wan Haslina Wan Abdul, Hsien Yong Meng, Sze Tan Kuan, Zaki Wan Mimi Diyana Wan, Ali Aziah, Bain Arbaiyah, Retinal changes and cardiac biomarker assessment in relation to chronic kidney disease: a single centre study, BMC Nephrol 24 (1) (2023) 338.

Holm Sven, Russell Greg, Nourrit Vincent, McLoughlin Niall, DR HAGIS—a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients, J Med Imaging 4 (1) (2017).

Zhang Jiong, Dashtbozorg Behdad, Bekkers Erik, Pluim Josien PW, Duits Remco, ter Haar Romeny Bart M, Robust retinal vessel segmentation via locally adaptive derivative frames in orientation scores, IEEE Trans Med Imaging 35 (12) (2016) 2631–2644.

Porwal Prasanna, Pachade Samiksha, Kamble Ravi, Kokare Manesh, Deshmukh Girish, Sahasrabuddhe Vivek, Meriaudeau Fabrice, Indian diabetic retinopathy image dataset (IDRiD): a database for diabetic retinopathy screening research, Data 3 (3) (2018) 25.

Staal Joes, Abràmoff Michael D, Niemeijer Meindert, Viergever Max A, Van Ginneken Bram, Ridge-based vessel segmentation in color images of the retina, IEEE Trans Med Imaging 23 (4) (2004) 501–509.

Mao Jingxin, Ma Xiaoyu, Bi Yanlong, Zhang Rongqing, TJDR: A high-quality diabetic retinopathy pixel-level annotation dataset, 2023, arXiv preprint arXiv:2312.15389.