机构：[1]Department of Ophthalmology,Peking Union Medical College Hospital, Chinese Academy ofMedical Sciences,Beijing, China andKey Lab of Ocular Fundus Diseases, Chinese Academy of Medical Sciences, Beijing, China.[2]Department of Research, VoxelCloud, Shanghai, China.[3]Tonghua Eye Hospital of Jilin Province, Tonghua, Jilin, China.[4]Department of Ophthalmology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.首都医科大学附属天坛医院[5]Eye Hospital of Shandong First Medical University (Shandong Eye Hospital), Jinan, Shandong, China.[6]Department of Ophthalmology, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China.[7]Department of Ophthalmology, The Second Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei, China.[8]Department of Ophthalmology, Xi’an No. 1 Hospital, Xian, Shanxi, China.[9]Eye Center, Renmin Hospital ofWuhan University,Wuhan, Hubei, China.[10]Department of Ophthalmology, The Fourth People’s Hospital of Shenyang, China Medical University, Shenyang, Liaoning, China.[11]Department of Ophthalmology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.外科科室眼科昆明医科大学附属第一医院[12]Department of Ophthalmology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei, China.[13]Department of Ophthalmology, The First Hospital of China Medical University, Shenyang, Liaoning, China.[14]Department of Ophthalmology, Guizhou Provincial People’s Hospital, Guiyang, Guizhou, China.[15]Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China.[16]Eye Center, Beijing Tsinghua Changgung Hospital, Beijing, China and School of Clinical Medicine, Tsinghua University, Beijing, China.[17]Department of Ophthalmology, The Affiliated Hospital of Inner Mongolia Medical University, Huhhot, Inner Mongolia, China.[18]Department of Ophthalmology, Hainan Hospital of PLA General Hospital, Sanya, Hainan, China.[19]Department of Ophthalmology, The Second Affiliated Hospital, Harbin Medical Medical, Harbin, Heilongjiang, China.[20]Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.[21]Department of Ophthalmology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.[22]Department of Ophthalmology, The First Affiliated Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.[23]Department of Ophthalmology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.[24]Department of Ophthalmology, Bayinguoleng People’s Hospital, Korla, Xinjiang, China.[25]Microsoft Research Asia (Shanghai), Shanghai, China.[26]Singapore Eye Research Institute, Singapore and National Eye Centre, Singapore, Singapore.[27]Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.[28]Tsinghua Medicine, Tsinghua University, Beijing, China.
To address challenges in screening for chronic kidney disease (CKD), we devised a deep learning-based CKD screening model named UWF-CKDS. It utilizes ultra-wide-field (UWF) fundus images to predict the presence of CKD. We validated the model with data from 23 tertiary hospitals across China. Retinal vessels and retinal microvascular parameters (RMPs) were extracted to enhance model interpretability, which revealed a significant correlation between renal function and RMPs. UWF-CKDS, utilizing UWF images, RMPs, and relevant medical history, can accurately determine CKD status. Importantly, UWF-CKDS exhibited superior performance compared to CTR-CKDS, a model developed using the central region (CTR) cropped from UWF images, underscoring the contribution of the peripheral retina in predicting renal function. The study presents UWF-CKDS as a highly implementable method for large-scale and accurate CKD screening at the population level.
基金：
National Natural Science Foundation of China (National Science Foundation of China) [2022-PUMCH-B-101]; National High Level Hospital Clinical Research Funding, China [82271112]; National Natural Science Foundation of China
语种：
外文
WOS：
PubmedID：
中科院(CAS)分区：
出版当年[2025]版：
无
最新[2023]版：
大类|1 区医学
小类|1 区卫生保健与服务1 区医学：信息
JCR分区：
出版当年[2024]版：
无
最新[2023]版：
Q1HEALTH CARE SCIENCES & SERVICESQ1MEDICAL INFORMATICS
第一作者机构：[1]Department of Ophthalmology,Peking Union Medical College Hospital, Chinese Academy ofMedical Sciences,Beijing, China andKey Lab of Ocular Fundus Diseases, Chinese Academy of Medical Sciences, Beijing, China.
共同第一作者：
通讯作者：
通讯机构：[2]Department of Research, VoxelCloud, Shanghai, China.[16]Eye Center, Beijing Tsinghua Changgung Hospital, Beijing, China and School of Clinical Medicine, Tsinghua University, Beijing, China.[27]Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.[28]Tsinghua Medicine, Tsinghua University, Beijing, China.
推荐引用方式(GB/T 7714)：
Zhao Xinyu,Gu Xingwang,Meng Lihui,et al.Screening chronic kidney disease through deep learning utilizing ultra-wide-field fundus images[J].NPJ DIGITAL MEDICINE.2024,7(1):doi:10.1038/s41746-024-01271-w.
APA：
Zhao, Xinyu,Gu, Xingwang,Meng, Lihui,Chen, Yongwei,Zhao, Qing...&Chen, Youxin.(2024).Screening chronic kidney disease through deep learning utilizing ultra-wide-field fundus images.NPJ DIGITAL MEDICINE,7,(1)
MLA：
Zhao, Xinyu,et al."Screening chronic kidney disease through deep learning utilizing ultra-wide-field fundus images".NPJ DIGITAL MEDICINE 7..1(2024)
医学