基于OCT高危人群糖尿病筛查方法OA北大核心CSTPCD
Method of diabetes screening in high-risk population based on OCT
为了能够筛查出高危人群中潜在糖尿病患者,使患者得到早期治疗和减少并发症产生,提出了一种基于光学相干层析成像(OCT)的高危人群糖尿病无创筛查方法.首先将 3 维OCT图像进行区域划分,利用主成分分析法,将众多血糖敏感区域散射系数转变为一个综合指标S,进而归一化得到 0 min~120 min不同时刻的相对量Si(i=0,1,2…,120);然后将健康、轻度糖尿病、重度糖尿病人群在 0 min~120 min不同时刻的血糖归一化经验值;最后通过 8 例临床对照实验验证了方法的可行性,得到了准确的筛查结果.结果表明,判定阈值 1 为 0.47,阈值 2 为 0.78;将S120 与阈值 1、阈值 2 进行比较,得到 0<S120<0.47 为健康,0.47<S120<0.78 为轻度糖尿病,0.78<S120<1 为重度糖尿病.该方法具有较高的实用性,对于利用光学无创手段筛查高危人群糖尿病具有重要的意义.
In order to screen potential diabetes patients in high-risk groups,a non-invasive screening method for diabetes in high-risk groups based on optical coherence tomography(OCT)is proposed,and the patients could be early treated and reduce complications.This method first divided the 3-D OCT image into many small regions.Due to the different correlations between blood glucose changes and scattering coefficients in different regions,the principal component analysis was used to transform the scattering coefficients of these blood glucose sensitive regions into a comprehensive indicator S.Then S was normalized at different times of 0 min~120 min to obtain the relative quantity Si(i=0,1,2,…,120),with a relative quantity of S120 at 120 min.According to the experience value of normalized blood glucose of healthy subjects,moderate diabetes,and severe diabetes in 0 min~120 min,the judgment threshold 1 and threshold 2 is 0.47 and 0.78,respectively.If 0<S120<0.47,0.47<S120<0.78,and 0.78<S120<1,the subject is healthy,moderate diabetes and severe diabetes,respectively.This method is high practicability and has great significance for screening diabetes in high-risk groups with optical non-invasive methods.
何松;苏亚;姚晓天;郝鹏;崔省伟;蔡开明;孙金豪
河北大学 物理科学与技术学院,保定 071002,中国||河北省光学感知技术创新中心,保定 071002,中国河北省光学感知技术创新中心,保定 071002,中国
电子信息工程
医用光学生物技术无创血糖检测光学相干层析成像糖尿病筛查主成分分析
medical opticsbiotechnologynoninvasive blood glucose detectionoptical coherence tomographydiabetes screeningprincipal component analysis
《激光技术》 2024 (003)
312-317 / 6
国家自然科学基金资助项目(62105091);河北省重点研发计划资助项目(20542201D);河北省自然科学基金资助项目(F2020201041;F2021201016);河北大学自然科学多学科交叉研究计划资助项目(DXK202204)
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