Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

Ziyao Meng¹, Zhouyu Guan², Shujie Yu², Yilan Wu³, Yaoning Zhao³, Jie Shen⁴, Cynthia Ciwei Lim⁵, Tingli Chen⁶, Dawei Yang⁷, An Ran Ran⁷, Feng He⁸, Haslina Hamzah⁸, Sarkaaj Singh⁹, Anis Syazwani Abd Raof⁹, Jian Wen Samuel Lee-Boey⁹, Soo-Kun Lim⁹, Xufang Sun¹⁰, Shuwang Ge¹¹, Gang Xu¹¹, Hua Su¹², Yang Cheng¹³, Feng Lu¹⁴, Xiaofei Liao¹⁴, Hai Jin¹⁴, Chenxin Deng¹⁵, Lei Ruan¹⁵, Cuntai Zhang¹⁵, Chan Wu¹⁶, Rongping Dai¹⁶, Yixiao Jin³, Wenxiao Wang¹⁷, Tingyao Li¹, Ruhan Liu¹, Jiajia Li¹, Jia Shu¹, Yuwei Lu², Xiangning Wang¹⁸, Qiang Wu¹⁸, Yiming Qin¹, Jin Tang¹⁹, Xiaohua Sheng²⁰, Qiong Jiao²¹, Xiaokang Yang²², Minyi Guo¹, Gareth J McKay²³, Ruth E Hogg²³, Gerald Liew²⁴, Evelyn Yi Lyn Chee²⁵, Wynne Hsu²⁵, Mong Li Lee²⁵, Simon Szeto⁷, Andrea O Y Luk²⁶, Juliana C N Chan²⁶, Carol Y Cheung⁷, Gavin Siew Wei Tan⁸, Yih-Chung Tham²⁷, Ching-Yu Cheng²⁷, Charumathi Sabanayagam²⁸, Lee-Ling Lim²⁹, Weiping Jia², Huating Li³⁰, Bin Sheng³¹, Tien Yin Wong³²

Affiliations

¹ Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
² Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China.
³ Beijing Visual Science and Translational Eye Research Institute (BERI), Beijing Tsinghua Changgung Hospital Eye Center, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
⁴ Medical Records and Statistics Office, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁵ Department of Renal Medicine, Singapore General Hospital, SingHealth-Duke Academic Medical Centre, Singapore, Singapore.
⁶ Department of Ophthalmology, Shanghai Health and Medical Center, Wuxi, China.
⁷ Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
⁸ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
⁹ Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.
¹⁰ Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
¹¹ Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹² Department of Nephrology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹³ Department of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹⁴ National Engineering Research Centre for Big Data Technology and System, Services Computing Technology and System Laboratory, Cluster and Grid Computing Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
¹⁵ Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹⁶ Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
¹⁷ Key Laboratory of River Basic Digital Twinning of Ministry of Water Resources, Macau University of Science and Technology, Macau Special Administrative Region, China.
¹⁸ Department of Ophthalmology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
¹⁹ Department of Clinical Laboratory, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²⁰ Department of Nephrology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²¹ Department of Pathology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²² MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
²³ Centre for Public Health, School of Medicine, Dentistry, and Biomedical Sciences, Queen's University Belfast, Belfast, UK.
²⁴ Westmead Institute for Medical Research, University of Sydney, NSW, Australia.
²⁵ School of Computing, National University of Singapore, Singapore.
²⁶ Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
²⁷ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Centre for Innovation and Precision Eye Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore.
²⁸ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore.
²⁹ Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia; Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
³⁰ Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China. Electronic address: huarting99@sjtu.edu.cn.
³¹ Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address: shengbin@sjtu.edu.cn.
³² Beijing Visual Science and Translational Eye Research Institute (BERI), Beijing Tsinghua Changgung Hospital Eye Center, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Beijing Key Laboratory of Intelligent Diagnostic Technology and Devices for Major Blinding Eye Diseases, Tsinghua Medicine, Tsinghua University, Beijing, China. Electronic address: wongtienyin@tsinghua.edu.cn.

PMID: 40312169
DOI: 10.1016/j.landig.2025.02.008

Free article

Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

Ziyao Meng et al. Lancet Digit Health. 2025 May.

Free article

. 2025 May;7(5):100868.

doi: 10.1016/j.landig.2025.02.008. Epub 2025 Apr 30.

Authors

Affiliations

¹ Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
² Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China.
³ Beijing Visual Science and Translational Eye Research Institute (BERI), Beijing Tsinghua Changgung Hospital Eye Center, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
⁴ Medical Records and Statistics Office, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁵ Department of Renal Medicine, Singapore General Hospital, SingHealth-Duke Academic Medical Centre, Singapore, Singapore.
⁶ Department of Ophthalmology, Shanghai Health and Medical Center, Wuxi, China.
⁷ Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
⁸ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
⁹ Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.
¹⁰ Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
¹¹ Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹² Department of Nephrology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹³ Department of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹⁴ National Engineering Research Centre for Big Data Technology and System, Services Computing Technology and System Laboratory, Cluster and Grid Computing Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
¹⁵ Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
¹⁶ Department of Ophthalmology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
¹⁷ Key Laboratory of River Basic Digital Twinning of Ministry of Water Resources, Macau University of Science and Technology, Macau Special Administrative Region, China.
¹⁸ Department of Ophthalmology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
¹⁹ Department of Clinical Laboratory, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²⁰ Department of Nephrology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²¹ Department of Pathology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²² MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
²³ Centre for Public Health, School of Medicine, Dentistry, and Biomedical Sciences, Queen's University Belfast, Belfast, UK.
²⁴ Westmead Institute for Medical Research, University of Sydney, NSW, Australia.
²⁵ School of Computing, National University of Singapore, Singapore.
²⁶ Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
²⁷ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Centre for Innovation and Precision Eye Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore.
²⁸ Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore.
²⁹ Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia; Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region, China.
³⁰ Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China. Electronic address: huarting99@sjtu.edu.cn.
³¹ Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Institute for Proactive Healthcare, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Centre for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China; MOE Key Laboratory of AI, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address: shengbin@sjtu.edu.cn.
³² Beijing Visual Science and Translational Eye Research Institute (BERI), Beijing Tsinghua Changgung Hospital Eye Center, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Beijing Key Laboratory of Intelligent Diagnostic Technology and Devices for Major Blinding Eye Diseases, Tsinghua Medicine, Tsinghua University, Beijing, China. Electronic address: wongtienyin@tsinghua.edu.cn.

PMID: 40312169
DOI: 10.1016/j.landig.2025.02.008

Abstract

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images.

Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care System for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD; and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up.

Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838-0·846) on the internal validation dataset and AUCs of 0·791-0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825-0·966) on the internal validation dataset and AUCs of 0·733-0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD with higher sensitivity (89·8% vs 66·3%, p<0·0001). In the longitudinal study, participants with isolated diabetic nephropathy and participants with NDKD identified by DeepDKD had a significant difference in renal function outcomes (proportion of estimated glomerular filtration rate decline: 27·45% vs 52·56%, p=0·0010).

Interpretation: Among diverse multi-ethnic populations with diabetes, a retinal image-based AI-deep learning system showed its potential for detecting DKD and differentiating isolated diabetic nephropathy from NDKD in clinical practice.

Funding: National Key R & D Program of China, National Natural Science Foundation of China, Beijing Natural Science Foundation, Shanghai Municipal Key Clinical Specialty, Shanghai Research Centre for Endocrine and Metabolic Diseases, Innovative research team of high-level local universities in Shanghai, Noncommunicable Chronic Diseases-National Science and Technology Major Project, Clinical Special Program of Shanghai Municipal Health Commission, and the three-year action plan to strengthen the construction of public health system in Shanghai.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests CCL declares honoraria paid to their institution from Boehringer Ingelheim, AstraZeneca, and Sebia. TC is supported by the Clinical Special Program of Shanghai Municipal Health Commission (20224044) and the three-year action plan to strengthen the construction of public health system in Shanghai (2023-2025 GWVI-11.1-28). XY is supported by the Shanghai Municipal Science and Technology Major Project (2021SHZDZX0102). REH is supported by Optos and Novartis. GL is supported by the Australian National Health and Medical Research Council (571012). SS received consulting fees from Bayer, Astella, and Roche; payment or honoraria from Bayer and Roche; and support for attending meetings and travel from Bayer and Roche. AOYL received research grants from Amgen, Bayer, Biogen, Boehringer Ingelheim, MSD, Novo Nordisk, Roche, Health Bureau, and Hong Kong Research Grants Council outside of the submitted work; travelling support from the International Diabetes Federation and the Asian Association for the Study of Diabetes for attending conferences; serves as the President of the Hong Kong Association for the Study of Obesity; and is a council member of Hong Kong Society of Endocrinology, Diabetes and Metabolism. GSWT received research grants from Artificial Intelligence Singapore, the Health Services Research Grant from the National Medical Research Council, the Clinician Scientist Award-Investigator Grant from the National Medical Research Council, and the Large Collaborative Grant from the National Medical Research Council; consulting fees from AbbVie-Allergan, Bayer, Haag-Steit, Leica, Novartis, Roche, Rxilient, and Zeiss; payment or honoraria from Bayer, Haag-Steit, Leica, Novartis, Roche, Rxilient, and Zeiss; and stock from Eyris. C-YC received consulting fees from Medi-Whale. L-LL declares grants paid to institution from AstraZeneca and Abbott; payment or honoraria from AstraZeneca, Boehringer Ingelheim, Novo Nordisk, ZP Therapeutics, Sanofi, Viatris, and Novartis. WJ is supported by the Shanghai Municipal Key Clinical Specialty, Shanghai Research Centre for Endocrine and Metabolic Diseases (2022ZZ01002), and the Chinese Academy of Engineering (2022-XY-08). HL is supported by the Excellent Young Scientists Fund of the National Natural Science Foundation of China (82022012) and the General Fund of the National Natural Science Foundation of China (81870598), and the Innovative research team of high-level local universities in Shanghai (SHSMU-ZDCX20212700). BS is supported by the General Program of the National Natural Science Foundation of China (62272298) and the National Key R & D Program of China (2022YFC2407000). TYW is supported by the National Key R & D Program of China (2022YFC2502800) and the National Natural Science Foundation of China (8238810007); has received consulting fees from AbbVie, Aldropika Therapeutics, Bayer, Boehringer Ingelheim, Carl Zeiss, Genentech, Iveric Bio, Novartis, Opthea, Quaerite Bipharm Research, Plano, Roche, Sanofi, and Shanghai Henlius; and is a co-founder of companies EyRiS and VISRE. All other authors declare no competing interests.

References

Publication types

Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

LinkOut - more resources

Full Text Sources
- ClinicalKey
- Elsevier Science
Medical
- MedlinePlus Health Information

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

Affiliations

Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

Authors

Affiliations

Abstract

Conflict of interest statement

References

Publication types

MeSH terms

LinkOut - more resources

Full Text Sources

Medical