Mesh : Humans Amblyopia / physiopathology pathology Female Male Retinal Vessels / diagnostic imaging pathology Visual Acuity / physiology Algorithms Adult Young Adult Adolescent Child Fractals Microvascular Density

来  源:   DOI:10.1167/tvst.13.5.21   PDF(Pubmed)

Abstract:
UNASSIGNED: This study aimed to investigate the possible relationship between retinal vascular abnormalities and amblyopia by analyzing vascular structures of fundus images.
UNASSIGNED: In this observational study, retinal fundus images were collected from 36 patients with unilateral amblyopia, 33 patients with bilateral amblyopia, and 36 healthy control volunteers. We developed a customized training algorithm based on U-Net to digitalize the vasculature in the fundus images to quantify vascular density (area and fractal dimension), skeleton length, and number of bifurcation points. For statistical comparisons, this study divided participants into two groups. The amblyopic eyes and the fellow eyes of patients with unilateral amblyopia formed the paired group, while bilateral amblyopic patients and healthy controls formed the independent group.
UNASSIGNED: In the paired group, the vascular area (P = 0.007), vascular fractal dimension (P = 0.007), and vascular skeleton length (P = 0.002) of the amblyopic eyes were significantly smaller than those of the fellow eyes. In the independent group, significant decreases in the vascular fractal dimension (P = 0.006) and skeleton length (P = 0.048) were observed in bilateral amblyopia compared to control. The vascular area was also significantly correlated with best-corrected visual acuity in amblyopic eyes.
UNASSIGNED: This study demonstrated that retinal vascular density and skeleton length in amblyopic eyes were significantly smaller compared to control, indicating an association between the changes in retinal vascular features and the state of amblyopia.
UNASSIGNED: Our algorithm presents amblyopic retinal vascular changes that are more biologically interpretable for both clinicians and researchers.
摘要:
本研究旨在通过分析眼底图像的血管结构,探讨视网膜血管异常与弱视之间的可能关系。
在这项观察性研究中,收集36例单侧弱视患者的视网膜眼底图像,双侧弱视33例,和36名健康对照志愿者。我们开发了一种基于U-Net的定制训练算法,将眼底图像中的血管数字化,以量化血管密度(面积和分形维数),骨架长度,和分叉点的数量。对于统计比较,这项研究将参与者分为两组.单侧弱视患者的弱视眼睛和同伴眼睛组成配对组,而双侧弱视患者和健康对照者组成独立组。
在配对组中,血管面积(P=0.007),血管分形维数(P=0.007),弱视眼的血管骨骼长度(P=0.002)明显小于同伴眼。在独立小组中,与对照组相比,双侧弱视的血管分形维数(P=0.006)和骨骼长度(P=0.048)显著降低.弱视眼的血管面积也与最佳矫正视力显着相关。
这项研究表明,弱视眼的视网膜血管密度和骨骼长度明显小于对照组,表明视网膜血管特征的变化与弱视状态之间存在关联。
我们的算法提出了弱视视网膜血管的变化,这些变化对于临床医生和研究人员来说都更具生物学意义。
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