Department of Ophthalmology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Curr Opin Ophthalmol. 2013 Mar;24(2):150-61. doi: 10.1097/ICU.0b013e32835d9e27.
With the rapid adoption of spectral domain optical coherence tomography (SDOCT) in clinical practice and the recent advances in software technology, there is a need for a review of the literature on glaucoma detection and progression analysis algorithms designed for the commercially available instruments.
Peripapillary retinal nerve fiber layer (RNFL) thickness and macular thickness, including segmental macular thickness calculation algorithms, have been demonstrated to be repeatable and reproducible, and have a high degree of diagnostic sensitivity and specificity in discriminating between healthy and glaucomatous eyes across the glaucoma continuum. Newer software capabilities such as glaucoma progression detection algorithms provide an objective analysis of longitudinally obtained structural data that enhances our ability to detect glaucomatous progression. RNFL measurements obtained with SDOCT appear more sensitive than time domain OCT (TDOCT) for glaucoma progression detection; however, agreement with the assessments of visual field progression is poor.
Over the last few years, several studies have been performed to assess the diagnostic performance of SDOCT structural imaging and its validity in assessing glaucoma progression. Most evidence suggests that SDOCT performs similarly to TDOCT for glaucoma diagnosis; however, SDOCT may be superior for the detection of early stage disease. With respect to progression detection, SDOCT represents an important technological advance because of its improved resolution and repeatability. Advancements in RNFL thickness quantification, segmental macular thickness calculation and progression detection algorithms, when used correctly, may help to improve our ability to diagnose and manage glaucoma.
随着谱域光学相干断层扫描（SD-OCT）在临床实践中的快速应用和软件技术的最新进展，需要对专为商业可用仪器设计的青光眼检测和进展分析算法的文献进行综述。
已证明，在青光眼连续体中，视盘周围视网膜神经纤维层（RNFL）厚度和黄斑厚度（包括节段性黄斑厚度计算算法）具有可重复性和可再现性，并且在区分健康眼和青光眼眼中具有很高的诊断灵敏度和特异性。较新的软件功能，如青光眼进展检测算法，为纵向获得的结构数据提供了客观分析，增强了我们检测青光眼进展的能力。SD-OCT 获得的 RNFL 测量值在检测青光眼进展方面似乎比时域 OCT（TD-OCT）更敏感；然而，与视野进展评估的一致性较差。
在过去几年中，已经进行了几项研究来评估 SDOCT 结构成像的诊断性能及其在评估青光眼进展中的有效性。大多数证据表明，SD-OCT 在青光眼诊断方面与 TDOCT 表现相似；然而，SD-OCT 可能更适合早期疾病的检测。就进展检测而言，SD-OCT 是一项重要的技术进步，因为它具有更高的分辨率和可重复性。正确使用 RNFL 厚度定量、节段性黄斑厚度计算和进展检测算法的进步，可能有助于提高我们诊断和管理青光眼的能力。
