利用毛细血管周围神经纤维层的扇形模式分析区分多发性硬化症和青光眼

IF 2.6 3区 医学 Q2 OPHTHALMOLOGY Translational Vision Science & Technology Pub Date : 2024-11-04 DOI:10.1167/tvst.13.11.11
Po-Han Yeh, Ou Tan, Elizabeth Silbermann, Elizabeth White, Dongseok Choi, Aiyin Chen, Eliesa Ing, Dennis Bourdette, Jie Wang, Yali Jia, David Huang
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引用次数: 0

摘要

目的:通过神经纤维层(NFL)变薄模式区分多发性硬化症(MS)和青光眼:多发性硬化症患者根据 2017 年麦克唐纳标准进行诊断;青光眼患者有圆盘边缘变薄或 NFL 缺损,伴有或不伴有周边缺损。毛细血管周围 NFL 厚度分为八个部分,并计算相对于标准参考值的减少百分比(减少百分比)。多发性硬化症眼和青光眼眼根据最差区域 NFL 变薄的严重程度进行分组:显著减少(5%)。我们设计了四个诊断指标,并使用接收者操作特征曲线下面积(AROC)和准确性来评估指标:我们在两个中心招募了 58 名对照组受试者(58 只眼)、56 名多发性硬化症受试者(112 只眼)和 92 名青光眼受试者(92 只眼)。在多发性硬化症患者眼中,颞上部和颞下部的百分比下降最为明显。而在青光眼患者中,则出现在颞下部、鼻下部和颞上部。在显著降低组中,颞区模式指数具有最佳的 AROC(0.96,0.91-1.00)和准确性(92.6%)。在边缘缩减组中,它的AROC(0.88,0.78-0.99)和准确率(76.7%)都很好:结论:以正常参考值的百分比对 NFL 减少进行归一化,可突出 MS 和青光眼的特征模式。定量模式指数能有效区分这两种疾病:光学相干断层扫描通过分析视网膜神经纤维层缩减百分比模式,提高了视神经病变鉴别诊断的实用性。
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Differentiating Multiple Sclerosis and Glaucoma With Sectoral Pattern Analysis of Peripapillary Nerve Fiber Layer.

Purpose: To distinguish between multiple sclerosis (MS) and glaucoma by nerve fiber layer (NFL) thinning patterns.

Methods: MS patients were diagnosed by the 2017 McDonald Criteria; glaucoma patients had disc rim thinning or an NFL defect, with or without perimetric defect. The peripapillary NFL thickness was divided into eight sectors, and percentage reduction (% reduction) was calculated relative to normative reference values. The MS and glaucoma eyes were grouped based on the severity of NFL thinning in the worst sector: significant reduction (<1 percentile of normal reference), borderline reduction (1%∼5%), and no reduction (>5%). We devised four diagnostic indexes, and the area under the curve of receiver operating characteristics (AROC) and accuracy were used to evaluate the indexes.

Results: We enrolled 58 control subjects (58 eyes), 56 MS subjects (112 eyes), and 92 glaucoma subjects (92 eyes) at two centers. The most pronounced percent reduction in MS eyes occurred in the temporal-upper and temporal-lower sectors. In glaucoma eyes, this occurred in the inferior-temporal, inferior-nasal, and superior-temporal sectors. The temporal pattern index had the best AROC (0.96, 0.91-1.00) and accuracy (92.6%) in the significant reduction group. It had good AROC (0.88, 0.78-0.99) and accuracy (76.7%) in the borderline reduction group.

Conclusions: Normalizing NFL reduction as a percentage of normal reference accentuated patterns characteristic of MS and glaucoma. Quantitative pattern indexes were effective in differentiating the two diseases.

Translational relevance: The utility of optical coherence tomography in the differential diagnosis of optic neuropathies is enhanced by analyzing the retinal nerve fiber layer percentage reduction pattern.

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来源期刊
Translational Vision Science & Technology
Translational Vision Science & Technology Engineering-Biomedical Engineering
CiteScore
5.70
自引率
3.30%
发文量
346
审稿时长
25 weeks
期刊介绍: Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO. The journal covers a broad spectrum of work, including but not limited to: Applications of stem cell technology for regenerative medicine, Development of new animal models of human diseases, Tissue bioengineering, Chemical engineering to improve virus-based gene delivery, Nanotechnology for drug delivery, Design and synthesis of artificial extracellular matrices, Development of a true microsurgical operating environment, Refining data analysis algorithms to improve in vivo imaging technology, Results of Phase 1 clinical trials, Reverse translational ("bedside to bench") research. TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.
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