Development of a multiple convolutional neural network-facilitated diagnostic screening program for immunofluorescence images of IgA nephropathy and idiopathic membranous nephropathy

doi:10.1093/ckj/sfad153

	Development of a multiple convolutional neural network-facilitated diagnostic screening program for immunofluorescence images of IgA nephropathy and idiopathic membranous nephropathy
	Xia, Peng 1; Lv, Zhilong 2,3; Wen, Yubing 1; Zhang, Baichuan 4; Zhao, Xuesong 1; Zhang, Boyao 4; Wang, Ying 1; Cui, Haoyuan 1; Wang, Chuanpeng 1; Zheng, Hua 1; Qin, Yan 1; Sun, Lijun 5; Ye, Nan 5; Cheng, Hong 5; Yao, Li 6; Zhou, Hua 7; Zhen, Junhui 8; Hu, Zhao 9; Zhu, Weiguo 10; Zhang, Fa 2; Li, Xuemei 1; Ren, Fei 2; Chen, Limeng 1
	2023-07-18
发表期刊	CLINICAL KIDNEY JOURNAL
ISSN	2048-8505
页码	11
摘要	Background Immunoglobulin A nephropathy (IgAN) and idiopathic membranous nephropathy (IMN) are the most common glomerular diseases. Immunofluorescence (IF) tests of renal tissues are crucial for the diagnosis. We developed a multiple convolutional neural network (CNN)-facilitated diagnostic program to assist the IF diagnosis of IgAN and IMN. Methods The diagnostic program consisted of four parts: a CNN trained as a glomeruli detection module, an IF intensity comparator, dual-CNN (D-CNN) trained as a deposition appearance and location classifier and a post-processing module. A total of 1573 glomerular IF images from 1009 patients with glomerular diseases were used for the training and validation of the diagnostic program. A total of 1610 images of 426 patients from different hospitals were used as test datasets. The performance of the diagnostic program was compared with nephropathologists. Results In >90% of the tested images, the glomerulus location module achieved an intersection over union >0.8. The accuracy of the D-CNN in recognizing irregular granular mesangial deposition and fine granular deposition along the glomerular basement membrane was 96.1% and 93.3%, respectively. As for the diagnostic program, the accuracy, sensitivity and specificity of diagnosing suspected IgAN were 97.6%, 94.4% and 96.0%, respectively. The accuracy, sensitivity and specificity of diagnosing suspected IMN were 91.7%, 88.9% and 95.8%, respectively. The corresponding areas under the curve (AUCs) were 0.983 and 0.935. When tested with images from the outside hospital, the diagnostic program showed stable performance. The AUCs for diagnosing suspected IgAN and IMN were 0.972 and 0.948, respectively. Compared with inexperienced nephropathologists, the program showed better performance. Conclusion The proposed diagnostic program could assist the IF diagnosis of IgAN and IMN. Lay Summary A multiple convolutional neural network-facilitated diagnostic program was designed to deliver fast and accurate diagnostic suggestions of immunofluorescence images from immunoglobulin A nephropathy and idiopathic membranous nephropathy (IMN). The accuracy, sensitivity and specificity of diagnosing suspected IgAN were 97.6%, 94.4% and 96.0%, respectively. The accuracy, sensitivity and specificity of diagnosing suspected IMN were 91.7%, 88.9% and 95.8%, respectively. The corresponding areas under the curve were 0.983 and 0.935. When tested with images from the outside hospital, the diagnostic program showed stable performance.
关键词	convolutional neural network idiopathic membranous nephropathy IgA nephropathy immunofluorescence
DOI	10.1093/ckj/sfad153
收录类别	SCI
语种	英语
WOS研究方向	Urology & Nephrology
WOS类目	Urology & Nephrology
WOS记录号	WOS:001050624500001
出版者	OXFORD UNIV PRESS
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21350
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ren, Fei; Chen, Limeng
作者单位	1.Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Nephrol, State Key Lab Complex Severe & Rare Dis, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing, Peoples R China 4.Beijing Zhijian Life Technol, Beijing, Peoples R China 5.Capital Med Univ, Beijing Anzhen Hosp, Dept Nephrol, Beijing, Peoples R China 6.China Med Univ, Hosp 1, Dept Nephrol, Shenyang, Peoples R China 7.China Med Univ, Shengjing Hosp, Dept Nephrol, Shenyang, Peoples R China 8.Shandong Univ, Qilu Hosp, Dept Pathol, Jinan, Peoples R China 9.Shandong Univ, Qilu Hosp, Dept Nephrol, Jinan, Peoples R China 10.Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Informat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Xia, Peng,Lv, Zhilong,Wen, Yubing,et al. Development of a multiple convolutional neural network-facilitated diagnostic screening program for immunofluorescence images of IgA nephropathy and idiopathic membranous nephropathy[J]. CLINICAL KIDNEY JOURNAL,2023:11.
APA	Xia, Peng.,Lv, Zhilong.,Wen, Yubing.,Zhang, Baichuan.,Zhao, Xuesong.,...&Chen, Limeng.(2023).Development of a multiple convolutional neural network-facilitated diagnostic screening program for immunofluorescence images of IgA nephropathy and idiopathic membranous nephropathy.CLINICAL KIDNEY JOURNAL,11.
MLA	Xia, Peng,et al."Development of a multiple convolutional neural network-facilitated diagnostic screening program for immunofluorescence images of IgA nephropathy and idiopathic membranous nephropathy".CLINICAL KIDNEY JOURNAL (2023):11.