• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

光谱域光学相干断层扫描图像中视乳头周围视网膜神经纤维层和黄斑神经节细胞复合体分割误差的患病率及相关因素

Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images.

作者信息

Miki Atsuya, Kumoi Miho, Usui Shinichi, Endo Takao, Kawashima Rumi, Morimoto Takeshi, Matsushita Kenji, Fujikado Takashi, Nishida Kohji

机构信息

Department of Ophthalmology, Osaka University Graduate School of Medicine, Osaka, Japan.

出版信息

J Glaucoma. 2017 Nov;26(11):995-1000. doi: 10.1097/IJG.0000000000000771.

DOI:10.1097/IJG.0000000000000771
PMID:28858152
Abstract

PURPOSE

To determine the prevalence of errors in segmentation of the peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell complex (GCC) boundary in spectral-domain optical coherence tomography (SDOCT) images, and to identify factors associated with the errors.

MATERIALS AND METHODS

Peripapillary RNFL circle scans and macular 3-dimensional scans of consecutive cases imaged with SDOCT (RS-3000 Advance; Nidek, Gamagori, Japan) were retrospectively reviewed by a glaucoma specialist. Images with signal strength index (SSI)<6 were excluded. Threshold for segmentation failure was determined as 15 degrees in the RNFL scans and 1/24 of the scanned area in the GCC scans. Relationships between segmentation failure and clinical factors were statistically evaluated with univariable and multivariable analyses.

RESULTS

This retrospective cross-sectional study included 207 eyes of 117 subjects (mean age, 58.5±16.5 y). Segmentation failure was found in 20.7% of the peripapillary RNFL scans, 16.6% of the 9 mm GCC scans, and 6.9% of the 6 mm GCC scans in SDOCT images. In multivariable logistic regression analyses, low SSI, large disc area, and disease type significantly correlated with RNFL segmentation failure, whereas SSI was the only baseline factor that was significantly associated with GCC segmentation failure.

CONCLUSIONS

Although segmentation failure was common in both RNFL and GCC scans, it was less frequently observed in GCC scans. SSI, disc area, and disease type were significantly associated with segmentation failure. Predictive performance of baseline factors for failure was poor, underlining the importance of reviewing raw OCT images before using OCT parameters.

摘要

目的

确定光谱域光学相干断层扫描(SDOCT)图像中视乳头周围视网膜神经纤维层(RNFL)和黄斑神经节细胞复合体(GCC)边界分割错误的发生率,并识别与这些错误相关的因素。

材料与方法

由一名青光眼专家对使用SDOCT(RS - 3000 Advance;日本Nidek公司,蒲郡市)成像的连续病例的视乳头周围RNFL环形扫描和黄斑三维扫描进行回顾性分析。排除信号强度指数(SSI)<6的图像。将RNFL扫描中分割失败的阈值确定为15度,GCC扫描中为扫描区域的1/24。采用单变量和多变量分析对分割失败与临床因素之间的关系进行统计学评估。

结果

这项回顾性横断面研究纳入了117名受试者的207只眼(平均年龄58.5±16.5岁)。在SDOCT图像中,视乳头周围RNFL扫描的分割失败率为20.7%,9mm GCC扫描为16.6%,6mm GCC扫描为6.9%。在多变量逻辑回归分析中,低SSI、大视盘面积和疾病类型与RNFL分割失败显著相关,而SSI是与GCC分割失败显著相关的唯一基线因素。

结论

虽然RNFL和GCC扫描中分割失败都很常见,但在GCC扫描中观察到的频率较低。SSI、视盘面积和疾病类型与分割失败显著相关。基线因素对分割失败的预测性能较差,这突出了在使用OCT参数之前查看原始OCT图像的重要性。

相似文献

1
Prevalence and Associated Factors of Segmentation Errors in the Peripapillary Retinal Nerve Fiber Layer and Macular Ganglion Cell Complex in Spectral-domain Optical Coherence Tomography Images.光谱域光学相干断层扫描图像中视乳头周围视网膜神经纤维层和黄斑神经节细胞复合体分割误差的患病率及相关因素
J Glaucoma. 2017 Nov;26(11):995-1000. doi: 10.1097/IJG.0000000000000771.
2
Effect of scan quality on diagnostic accuracy of spectral-domain optical coherence tomography in glaucoma.扫描质量对频域光学相干断层扫描诊断青光眼准确性的影响。
Am J Ophthalmol. 2014 Mar;157(3):719-27.e1. doi: 10.1016/j.ajo.2013.12.012. Epub 2013 Dec 15.
3
Diagnostic Capability of Peripapillary Three-dimensional Retinal Nerve Fiber Layer Volume for Glaucoma Using Optical Coherence Tomography Volume Scans.利用光学相干断层扫描容积扫描技术,通过视乳头周围三维视网膜神经纤维层容积对青光眼进行诊断的能力
Am J Ophthalmol. 2017 Oct;182:180-193. doi: 10.1016/j.ajo.2017.08.001. Epub 2017 Aug 12.
4
Diagnostic ability of retinal ganglion cell complex, retinal nerve fiber layer, and optic nerve head measurements by Fourier-domain optical coherence tomography.频域光学相干断层扫描测量视网膜神经节细胞复合体、视网膜神经纤维层和视盘的诊断能力。
Graefes Arch Clin Exp Ophthalmol. 2011 Jul;249(7):1039-45. doi: 10.1007/s00417-010-1585-5. Epub 2011 Jan 15.
5
Evaluation of Retinal Nerve Fiber Layer and Ganglion Cell Complex Thickness in Unilateral Exfoliation Syndrome Using Optical Coherence Tomography.使用光学相干断层扫描评估单侧剥脱综合征患者的视网膜神经纤维层和神经节细胞复合体厚度
J Glaucoma. 2016 Jun;25(6):523-7. doi: 10.1097/IJG.0000000000000383.
6
Factors associated with variability in retinal nerve fiber layer thickness measurements obtained by optical coherence tomography.光学相干断层扫描获得的视网膜神经纤维层厚度测量值变异性的相关因素。
Ophthalmology. 2007 Aug;114(8):1505-12. doi: 10.1016/j.ophtha.2006.10.061. Epub 2007 Mar 23.
7
Three-dimensional imaging of the macular retinal nerve fiber layer in glaucoma with spectral-domain optical coherence tomography.青光眼黄斑视网膜神经纤维层的三维光谱域光学相干断层扫描成像
Invest Ophthalmol Vis Sci. 2010 Oct;51(10):5062-70. doi: 10.1167/iovs.09-4954. Epub 2010 May 12.
8
The Association Between Clinical Features Seen on Fundus Photographs and Glaucomatous Damage Detected on Visual Fields and Optical Coherence Tomography Scans.眼底照片上所见临床特征与视野及光学相干断层扫描检测到的青光眼性损害之间的关联
J Glaucoma. 2017 May;26(5):498-504. doi: 10.1097/IJG.0000000000000640.
9
Evaluating the effect of pupil dilation on spectral-domain optical coherence tomography measurements and their quality score.评估瞳孔散大对频域光学相干断层扫描测量结果及其质量评分的影响。
BMC Ophthalmol. 2015 Dec 11;15:175. doi: 10.1186/s12886-015-0168-y.
10
Diagnostic accuracy of ganglion cell complex substructures in different stages of primary open-angle glaucoma.原发性开角型青光眼不同阶段神经节细胞复合体亚结构的诊断准确性
Can J Ophthalmol. 2017 Aug;52(4):355-360. doi: 10.1016/j.jcjo.2017.01.003. Epub 2017 Feb 20.

引用本文的文献

1
High Prevalence of Artifacts in Optical Coherence Tomography With Adequate Signal Strength.光学相干断层扫描在信号强度足够的情况下存在较高的伪影发生率。
Transl Vis Sci Technol. 2024 Aug 1;13(8):43. doi: 10.1167/tvst.13.8.43.
2
Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection.青光眼护理进展:将人工智能整合到诊断、管理和病情进展检测中。
Bioengineering (Basel). 2024 Jan 26;11(2):122. doi: 10.3390/bioengineering11020122.
3
Artificial intelligence in ophthalmology.人工智能在眼科学中的应用。
Rom J Ophthalmol. 2023 Jul-Sep;67(3):207-213. doi: 10.22336/rjo.2023.37.
4
Variation in Retinal Nerve Fiber Layer and Ganglion Cell Complex Associated With Optic Nerve Head Size in Healthy Eyes.健康眼中与视神经头大小相关的视网膜神经纤维层和节细胞层的变化。
Transl Vis Sci Technol. 2023 Mar 1;12(3):26. doi: 10.1167/tvst.12.3.26.
5
Application of Artificial Intelligence to Improve Imaging in Ophthalmology.人工智能在改善眼科成像中的应用。
J Ophthalmic Vis Res. 2023 Feb 21;18(1):1-2. doi: 10.18502/jovr.v18i1.12719. eCollection 2023 Jan-Mar.
6
Measurement of retinal nerve fiber layer thickness with a deep learning algorithm in ischemic optic neuropathy and optic neuritis.深度学习算法在缺血性视神经病变和视神经炎中测量视网膜神经纤维层厚度。
Sci Rep. 2022 Oct 12;12(1):17109. doi: 10.1038/s41598-022-22135-x.
7
Comparison of Ganglion Cell Layer and Ganglion Cell/Inner Plexiform Layer Measures for Detection of Early Glaucoma.神经节细胞层与神经节细胞/内丛状层测量值在早期青光眼检测中的比较。
Ophthalmol Glaucoma. 2023 Jan-Feb;6(1):58-67. doi: 10.1016/j.ogla.2022.06.008. Epub 2022 Jun 30.
8
Deep Learning for Glaucoma Detection and Identification of Novel Diagnostic Areas in Diverse Real-World Datasets.深度学习在青光眼检测中的应用及在多样化真实世界数据集新诊断领域的识别。
Transl Vis Sci Technol. 2022 May 2;11(5):11. doi: 10.1167/tvst.11.5.11.
9
Rationale and Development of an OCT-Based Method for Detection of Glaucomatous Optic Neuropathy.基于 OCT 的青光眼视神经病变检测方法的原理与发展。
J Glaucoma. 2022 Jun 1;31(6):375-381. doi: 10.1097/IJG.0000000000002005. Epub 2022 Feb 28.
10
Automated Detection of Glaucoma With Interpretable Machine Learning Using Clinical Data and Multimodal Retinal Images.使用临床数据和多模态视网膜图像的可解释机器学习进行青光眼的自动检测。
Am J Ophthalmol. 2021 Nov;231:154-169. doi: 10.1016/j.ajo.2021.04.021. Epub 2021 May 2.