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利用光学相干断层扫描对泪膜脂质层进行 En Face 成像的分类及其与临床参数的相关性。

Classification of Tear Film Lipid Layer En Face Maps Obtained Using Optical Coherence Tomography and Their Correlation With Clinical Parameters.

机构信息

Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria.

Christian Doppler Laboratory for Ocular and Dermal Effects of Thiomers, Medical University of Vienna, Austria.

出版信息

Cornea. 2023 Apr 1;42(4):490-497. doi: 10.1097/ICO.0000000000003172. Epub 2022 Nov 21.

DOI:10.1097/ICO.0000000000003172
PMID:36730374
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9973450/
Abstract

PURPOSE

The purpose of this study was to investigate the correlation between the pattern of optical coherence tomography (OCT) en face maps of the tear film lipid layer (TFLL) and lipid layer thickness (LLT), fluorescein breakup time (FBUT), and Schirmer I test values in healthy subjects.

METHODS

Measurements from four clinical data sets were retrospectively analyzed, and TFLL patterns were classified into 3 categories: homogeneous (HOM), wavy (WAV), or dotted (DOT) appearance. Linear mixed model analyses were performed. Intraclass correlation coefficients and index of qualitative variation were computed to investigate interrater and intrasubject variabilities.

RESULTS

For the LLT, a significant difference between HOM and DOT ( P < 0.001, β HOMvsDOT = -6.42 nm) and WAV and DOT ( P = 0.002, β WAVvsDOT = -4.04 nm) was found. Furthermore, the difference between WAV and DOT regarding FBUT ( P < 0.001, β WAVvsDOT = -3.065 seconds) was significant, while no significant differences between any of the classes with respect to the Schirmer I test values were found. An intraclass correlation coefficient of 89.0% reveals a good interrater reliability, and an index of qualitative variation of 60.0% shows, on average, a considerable variability in TFLL pattern class for repeated measurements over 1 hour.

CONCLUSIONS

A new classification method for OCT en face maps of the TFLL is presented. Significant differences between patterns were found with respect to LLT and FBUT. A dotted pattern on dark background appears to be the most stable type of TFLL. The analysis of OCT en face maps of the TFLL provides complimentary information to conventional imaging methods and might give new insights into the characteristics of the TFLL.

摘要

目的

本研究旨在探讨健康受试者泪膜脂质层(TFLL)光学相干断层扫描(OCT)截面图的模式与脂质层厚度(LLT)、荧光素破裂时间(FBUT)和泪液分泌试验(Schirmer I 试验)值之间的相关性。

方法

回顾性分析了 4 组临床数据集,将 TFLL 模式分为 3 类:均匀(HOM)、波浪形(WAV)或点状(DOT)。采用线性混合模型分析。计算组内相关系数和定性变异指数以评估组内和组间的变异性。

结果

对于 LLT,HOM 与 DOT(P<0.001,β HOMvsDOT=-6.42nm)和 WAV 与 DOT(P=0.002,β WAVvsDOT=-4.04nm)之间存在显著差异。此外,WAV 与 DOT 之间的 FBUT 差异具有统计学意义(P<0.001,β WAVvsDOT=-3.065 秒),而任何类别之间的 Schirmer I 试验值均无显著差异。组内相关系数为 89.0%,表明观察者之间的可靠性较好,定性变异指数为 60.0%,表明在 1 小时内重复测量时,TFLL 模式的平均变异性较大。

结论

提出了一种新的 TFLL OCT 截面图分类方法。发现不同模式在 LLT 和 FBUT 方面存在显著差异。暗背景下的点状模式似乎是最稳定的 TFLL 类型。分析 TFLL 的 OCT 截面图可为传统成像方法提供补充信息,并可能为 TFLL 的特征提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c0b/9973450/b42cf1c10c37/cornea-42-490-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c0b/9973450/b42cf1c10c37/cornea-42-490-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c0b/9973450/b42cf1c10c37/cornea-42-490-g001.jpg

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Deep learning differentiates between healthy and diabetic mouse ears from optical coherence tomography angiography images.深度学习可从光学相干断层扫描血管造影图像中区分健康和糖尿病小鼠的耳朵。
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The refractive index of the human cornea: A review.人眼角膜的折射率:综述。
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