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Combining retinal nerve fiber layer thickness with individual retinal blood vessel locations allows modeling of central vision loss in glaucoma

机译:结合视网膜神经纤维层厚度和单个视网膜血管位置,可以模拟青光眼的中心视力丧失

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摘要

Purpose: To assess whether modeling of central vision loss (CVL) due to glaucoma by optical coherence tomography (OCT) retinal nerve fiber (RNF) layer thickness (RNFLT) can be improved by including the location of the major inferior temporal retinal artery (ITA), a known correlate of individual RNF geometry. Methods: Pattern deviations of the two locations of the Humphrey 24-2 visual field (VF) known to be specifically vulnerable to glaucomatous CVL and OCT RNFLT on the corresponding circumpapillary sector around the optic nerve head within the radius of 1.73mm were retrospectively selected from 428 eyes of 428 patients of a large clinical glaucoma service. ITA was marked on the 1.73mm circle by a trained observer. Linear regression models were fitted with CVL as dependent variable and VF mean deviation (MD) plus either of (1) RNFLT, (2) ITA, and (3) their combination, respectively, as regressors. To assess CVL over all levels of glaucoma severity, the three models were compared to a null model containing only MD. A Baysian model comparison was performed with the Bayes Factor (BF) as measure of strength of evidence (BF<3: no evidence, 3-20: positive evidence, >20: strong evidence over null model). Results: Neither RNFLT (BF=0.9) nor ITA (BF=1.4) alone provided positive evidence over the null model, but their combination resulted in a model with strong evidence (BF=21.4). Conclusion: While the established circumpapillary RNFLT sector, based on population statistics, could not satisfactorily model CVL, the inclusion of a retinal parameter related to individual eye anatomy yielded a strong structure-function model.
机译:目的:评估是否可以通过包括颞下主要视网膜动脉(ITA)的位置来改善由青光眼引起的由青光眼引起的中心视力丧失(CVL)的建模,视网膜神经纤维(RNFLT)层厚度(RNFLT) ),即各个RNF几何形状的已知关联。方法:回顾性地从1.73mm半径范围内的视神经乳头周围相应的乳头状扇形区上的已知特别容易受到青光眼CVL和OCT RNFLT影响的Humphrey 24-2视野的两个位置的模式偏差。 428名大型青光眼临床患者的428只眼。 ITA由训练有素的观察员标记在1.73mm圆圈上。线性回归模型拟合了CVL作为因变量和VF平均偏差(MD)加上(1)RNFLT,(2)ITA和(3)它们的组合作为回归变量。为了评估青光眼严重程度所有水平的CVL,将这三个模型与仅包含MD的无效模型进行了比较。使用贝叶斯因子(BF)作为证据强度的度量进行了贝叶斯模型比较(BF <3:无证据; 3-20:阳性证据;> 20:相对于无效模型的有力证据)。结果:单独的RNFLT(BF = 0.9)和ITA(BF = 1.4)都没有提供比无效模型更明确的证据,但是将它们组合在一起可以得到具有强大证据的模型(BF = 21.4)。结论:尽管根据人群统计数据建立的环状乳头RNFLT部门不能令人满意地建立CVL模型,但是包含与个体眼睛解剖结构相关的视网膜参数产生了强大的结构功能模型。

著录项

  • 来源
    《Ophthalmic technologies XXVII》|2017年|100451m.1-100451m.5|共5页
  • 会议地点 San Francisco(US)
  • 作者单位

    Jilin University of Finance and Economics, Changchun, China,Harvard Medical School, Boston, MA, USA;

    Harvard Medical School, Boston, MA, USA;

    Harvard Medical School, Boston, MA, USA,University of Massachusetts, Lowell, MA, USA;

    Harvard Medical School, Boston, MA, USA,Jilin University, Changchun, China;

    Harvard Medical School, Boston, MA, USA,Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    optical coherence tomography; glaucoma; retinal nerve fiber layer thickness;

    机译:光学相干断层扫描;青光眼;视网膜神经纤维层厚度;
  • 入库时间 2022-08-26 13:44:36

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