Department of Internal Medicine, University of Texas Medical Branch at Galveston, 301 University Blvd, Galveston, TX 77555, USA.
Department of Ophthalmology and Visual Sciences, University of Texas Medical Branch at Galveston, 301 University Blvd, Galveston, TX 77555, USA.
Sensors (Basel). 2022 Mar 22;22(7):2447. doi: 10.3390/s22072447.
Optical Coherence Tomography (OCT) is an adaptable depth-resolved imaging modality capable of creating a non-invasive 'digital biopsy' of the eye. One of the latest advances in OCT is optical coherence tomography angiography (OCTA), which uses the speckle variance or phase change in the signal to differentiate static tissue from blood flow. Unlike fluorescein angiography (FA), OCTA is contrast free and depth resolved. By combining high-density scan patterns and image processing algorithms, both morphometric and functional data can be extracted into a depth-resolved vascular map of the retina. The algorithm that we explored takes advantage of the temporal-spatial relationship of the speckle variance to improve the contrast of the vessels in the en-face OCT with a single frame. It also does not require the computationally inefficient decorrelation of multiple A-scans to detect vasculature, as used in conventional OCTA analysis. Furthermore, the spatial temporal OCTA (ST-OCTA) methodology tested offers the potential for post hoc analysis to improve the depth-resolved contrast of specific ocular structures, such as blood vessels, with the capability of using only a single frame for efficient screening of large sample volumes, and additional enhancement by processing with choice of frame averaging methods. Applications of this method in pre-clinical studies suggest that the OCTA algorithm and spatial temporal methodology reported here can be employed to investigate microvascularization and blood flow in the retina, and possibly other compartments of the eye.
光学相干断层扫描（OCT）是一种适应性强的深度分辨成像方式，能够对眼睛进行非侵入性的“数字活组织检查”。OCT 的最新进展之一是光相干断层扫描血管造影术（OCTA），它利用信号中的散斑方差或相位变化来区分静态组织和血流。与荧光素血管造影（FA）不同，OCTA 是无对比且深度分辨的。通过结合高密度扫描模式和图像处理算法，可以将形态和功能数据提取为视网膜的深度分辨血管图。我们探索的算法利用了散斑方差的时空关系，以提高单次帧中 en-face OCT 中血管的对比度。它也不需要像传统的 OCTA 分析那样，通过多个 A 扫描的去相关来检测血管，这是计算效率低下的。此外，所测试的时空 OCTA（ST-OCTA）方法提供了事后分析的潜力，以提高特定眼部结构（如血管）的深度分辨对比度，其仅使用单个帧即可对大样本量进行高效筛选，并通过选择帧平均方法进行处理来进一步增强。该方法在临床前研究中的应用表明，本文报道的 OCTA 算法和时空方法可用于研究视网膜中的微血管化和血流，以及可能的眼部其他部位。
