Development and validation of novel retina biomarkers and artificial intelligence models for Beh?et disease uveitis prediction
作者全名：Lu, Ao; Li, Keyan; Guo, Suo; Zhang, Xinle; Su, Guannan; Yang, Peizeng
作者地址：[Lu, Ao; Li, Keyan; Guo, Suo; Zhang, Xinle; Su, Guannan; Yang, Peizeng] Chongqing Med Univ, Affiliated Hosp 1, Natl Clin Res Ctr Ocular Dis, Chongqing Branch,Municipal Div, Chongqing, Peoples R China; [Yang, Peizeng] Chongqing Med Univ, Affiliated Hosp 1, 1 Youyi Rd, Chongqing 400016, Peoples R China
通信作者：Yang, PZ (通讯作者)，Chongqing Med Univ, Affiliated Hosp 1, 1 Youyi Rd, Chongqing 400016, Peoples R China.
来源：BIOMEDICAL SIGNAL PROCESSING AND CONTROL
ESI学科分类：ENGINEERING
WOS号：WOS:001222937400001
JCR分区：Q1
影响因子：4.9
年份：2024
卷号：94
期号：
开始页：
结束页：
文献类型：Article
关键词：Uveitis; Artificial intelligence; Machine learning; Radiomics; Beh & ccedil;et disease
摘要：Objective: The aim of this study was to develop and validate quantitative diagnostic biomarkers and artificial intelligence (AI) models for Beh & ccedil;et disease uveitis (BU). Methods: We conducted a single -center retrospective study using AI-based algorithms to evaluate OCT angiography (OCTA) fundus scans from 62 BU patients and 61 healthy individuals. Results: From the 837 radiomic features derived from the OCTA scans, the top 20 features were utilized for AI modeling. The neural network (NN) model displayed the highest area under the receiver operating characteristic curve (AUC) of 0.900 in the test set. The integration of clinical data further enhanced the model ' s performance, leading to an AUC of 0.908 in the temporal validation cohort. Conclusion: Our research demonstrates that the radiomic score and the clinical integrated score can independently serve as diagnostic biomarkers for BU for future potential clinical translational research. Significance: The AI models we developed show great promise for clinical and translational research, marking progress towards fulfilling the demand for quantitative imaging biomarkers in BU diagnosis. However, further validation and evaluation are crucial to confirm their real-world applicability in clinical settings.
基金机构：National Natural Science Foundation Key Program [82230032, 81930023]; Key Project of Chongqing Science and Technology Bureau [CSTC2021jscx-gksb-N0010]; Chongqing Outstanding Scientists Project; Chongqing Chief Medical Scientist Project; Chongqing Science and Technology Bureau Mountaineering Project [cyyy-xkdfjh-lcyj-202303, cyyy-xkdfjh-cgzh- 202302]; [cyyy-xkdfjh-jcyj-202301]
基金资助正文：This study was supported by the National Natural Science Foundation Key Program (82230032) , National Natural Science Foundation Key Program (81930023) , Key Project of Chongqing Science and Technology Bureau (CSTC2021jscx-gksb-N0010) , Chongqing Outstanding Scientists Project (2019) , Chongqing Chief Medical Scientist Project (2018) , and Chongqing Science and Technology Bureau Mountaineering Project (cyyy-xkdfjh-jcyj-202301, cyyy-xkdfjh-lcyj-202303, cyyy-xkdfjh-cgzh- 202302) .
