Evaluation of the correlation between diabetic retinopathy and diabetic ne-phropathy by emission computed tomography and clinical testing data via convolutional neural network
10.13389/j.cnki.rao.2024.0025
- VernacularTitle:通过卷积神经网络分析ECT成像和临床检验数据评估糖尿病视网膜病变和糖尿病肾病之间的相关性
- Author:
Juan TANG
1
;
Qinghua LI
;
Xiuying DENG
;
Ting LU
;
Guoqiang TANG
;
Zhiwu LIN
;
Xingde LIU
;
Xiaoli WU
;
Qilin FANG
;
Ying LI
;
Xiao WANG
;
Yan ZHOU
;
Biao LI
;
Chuanqiang DAI
;
Tao LI
Author Information
1. 641300 四川省资阳市,资阳市第一人民医院内分泌科
- Keywords:
convolutional neural network;
type 2 diabetes mellitus;
diabetic retinopathy;
diabetic nephropathy;
emission computed tomography
- From:
Recent Advances in Ophthalmology
2024;44(2):127-132
- CountryChina
- Language:Chinese
-
Abstract:
Objective To evaluate the relationship between diabetic nephropathy(DN)and diabetic retinopathy(DR)in patients with type 2 diabetes mellitus(T2DM)based on imaging and clinical testing data.Methods Totally 600 T2DM patients who visited the First People's Hospital of Ziyang from March 2021 to December 2022 were included.The fundus photography and fundus fluorescein angiography were performed on all these patients and their age,gender,T2DM duration,cardiovascular diseases,cerebrovascular disease,hypertension,smoking history,drinking history,body mass in-dex,systolic blood pressure,diastolic blood pressure and other clinical data were collected.The levels of fasting blood glu-cose(FPG),triglyceride(TG),total cholesterol(TC),high-density lipoprotein cholesterol(HDL-C),low-density lipo-protein cholesterol(LDL-C),glycosylated hemoglobin(HbA1c),24 h urinary albumin(UAlb),urinary albumin to creati-nine ratio(ACR),serum creatinine(Scr)and blood urea nitrogen(BUN)were measured.Logistic regression was used to analyze the risk factors associated with DR.DR staging was performed according to fundus images,and the convolutional neural network(CNN)algorithm was used as an image analysis method to explore the correlation between DR and DN based on emission computed tomography(ECT)and clinical testing data.Results The average lesion area rates of DR and DN detected by the CNN in the non-DR,mild-non-proliferative DR(NPDR),moderate-NPDR,severe-NPDR and pro-liferative DR(PDR)groups were higher than those obtained by the traditional algorithm(TCM).As DR worsened,the Scr,BUN,24 h UAlb and ACR gradually increased.Besides,the incidence of DN in the non-DR,mild-NPDR,moderate-NPDR,severe-NPDR and PDR groups was 1.67％,8.83％,16.16％,22.16％and 30.83％,respectively.Logistic regression analysis showed that the duration of T2DM,smoking history,HbA1c,TC,TG,HDL-C,LDL-C,24 h UAlb,Scr,BUN,ACR and glomerular filtration rate(GFR)were independent risk factors for DR.Renal dynamic ECT analysis demonstrated that with the aggravation of DR,renal blood flow perfusion gradually decreased,resulting in diminished renal filtration.Conclusion The application of CCN in the early stage DR and DN image analysis of T2DM patients will improve the diag-nosis accuracy of DR and DN lesion area.The DN is worsening as the aggravation of DR.
