基于前段光学相干断层成像的宫腔镜前房角分级建模。

Eye and vision (London, England) Pub Date : 2020-06-02 eCollection Date: 2020-01-01 DOI:10.1186/s40662-020-00196-1
Yingying Dai, Shaodan Zhang, Meixiao Shen, Yuheng Zhou, Mengyi Wang, Jie Ye, Dexi Zhu
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引用次数: 3

摘要

背景:通过前段光学相干断层扫描(as - oct)定量评估前房角(ACA)结构,并建立一个模型来评估角宽度。方法:采用角镜对各象限的ACAs进行评估,采用Scheie分级系统进行分级,并将其分为小角(SA)、中角(MA)和大角(LA) 3个等级。采用AS-OCT成像,测量巩膜骨刺角开口距离(AODSS)、巩膜骨刺前750 μm角开口距离(AOD750)、巩膜骨刺前750 μm角开口面积(TISA750)和新定义的光相交距离(LID)等ACA结构参数。使用ACA结构数据构建有序逻辑回归模型,将ACAs分配到三个角度等级之一。然后对模型的有效性进行了检验。结果:53名受试者共纳入169个象限进行分析,其中111个象限纳入建模数据,58个象限纳入检验数据。方差分析两两比较SA、MA和LA的测量参数为:AOD750(0.174±0.060 vs. 0.249±0.068 vs. 0.376±0.114 mm);P 2;结论:基于as - oct的多ACA分级模型是一种快速、高空间分辨率的非接触ACA评估方法,可为闭角诊断提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Modeling of gonioscopic anterior chamber angle grades based on anterior segment optical coherence tomography.

Modeling of gonioscopic anterior chamber angle grades based on anterior segment optical coherence tomography.

Modeling of gonioscopic anterior chamber angle grades based on anterior segment optical coherence tomography.

Modeling of gonioscopic anterior chamber angle grades based on anterior segment optical coherence tomography.

Background: To quantitatively assess anterior chamber angle (ACA) structure by anterior segment optical coherence tomography (AS-OCT) and develop a model to evaluate angle width as defined by gonioscopy.

Methods: The ACAs of each quadrant were evaluated by gonioscopy, classified by the Scheie grading system, and assigned into one of the three grades: small angle (SA), moderate angle (MA), and large angle (LA). The eyes were imaged by AS-OCT, and ACA structural parameters including angle opening distance at the scleral spur (AODSS) and at 750 μm anterior to the scleral spur (AOD750), trabecular-iris space area at 750 μm anterior to the scleral spur (TISA750), and a newly defined parameter "light intersection distance" (LID), were measured. The ACA structural data were used to construct an ordered logistic regression model for assignment of ACAs to one of the three angle grades. The validity of the model was then tested.

Results: A total of 169 quadrants from 53 subjects were included in the analysis, of which 111 quadrants were included in the modeling data and 58 in the testing data. In pairwise comparisons of SA, MA, and LA by ANOVA, the measured parameters were as follows: AOD750 (0.174 ± 0.060 vs. 0.249 ± 0.068 vs. 0.376 ± 0.114 mm; P < 0.001), TISA750 (0.075 ± 0.035 vs. 0.117 ± 0.036 vs. 0.181 ± 0.062 mm2; P < 0.001), and LID (- 0.300 ± 0.187 vs. -0.085 ± 0.170 vs. 0.122 ± 0.156 mm; P < 0.001). The ACA grading model based on LID showed a relatively high correction rate of 72.4%, and the model efficiency, calculated using the receiver operating characteristic, showed an area under the curve of 0.740. Weighted kappa statistics showed a good agreement for multiple ACA grades (0.772).

Conclusions: The AS-OCT-based multiple ACA grades model was demonstrated as a non-contact approach for ACA assessment with high speed and high spatial resolution, providing guidance for diagnosis of angle closure.

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