Khyber Eye Foundation Hospital, Peshawar, Pakistan.
Zhonghsan Ophthalmic Centre, San-Yat Sen University, Guangzhou, China.
J Ayub Med Coll Abbottabad. 2021 Jul-Sep;33(3):441-446.
Optical Coherence Tomography Angiography (OCTA) is dye less microvascular visualizing technique. In study we binaries OCTA images of macular vessels in healthy and diabetic subjects without macular oedema using Adobe Photoshop CS3 extended version.
Prospective, single centered, observational study total of 58 eyes of 108 Diabetic Retinopathy (DR) subjects and 20 eyes of 40 normal subjects with mean age of 58.3±10.5 range (40-82) were included in our study. Ten eyes with Non-Diabetic Retinopathy (NDR), twenty-nine eyes with Non-Proliferative Diabetic Retinopathy (NPDR) (mild-10, moderate-7 and severe-12) and nineteen eyes with Proliferative Diabetic Retinopathy (PDR)are studied with images obtained using OCTA between September 2016 to June 2017. Scan area of 6×6 mm was selected to find morphological changes in the superficial retinal layers and deep retinal layers. Captured OCTA images were binarized using automated thresholding algorithm. Macular Vessel Density (MVD) (%) and Foveal Avascular Zone area (mm2) measured for superficial and deep retinal vessel arcade. For comparison, analysis of variance and Kruskal-Wallis test are applied.
Diabetic eyes were grouped according to their severity level. MVD and FAZ are compared in all groups. Results are significantly lower in all groups except in controls and NDR. Significant decrease is observed in vascular density of most layers with progress in retinopathy.
Adobe Photoshop CS3 extended version is an excellent tool for image binarization. Calculating FAZ area and MVD using OCTA images agreed closely with clinical grading system. Application of this method can be helpful in monitoring disease progression.
光学相干断层扫描血管造影（OCTA）是一种无染料的微血管可视化技术。在研究中，我们使用 Adobe Photoshop CS3 扩展版对无黄斑水肿的健康和糖尿病患者的黄斑血管进行了 OCTA 图像二值化处理。
前瞻性、单中心、观察性研究，共纳入 108 例糖尿病视网膜病变（DR）患者的 58 只眼和 40 例正常对照者的 20 只眼，平均年龄为 58.3±10.5 岁（40-82 岁）。10 只眼为非糖尿病性视网膜病变（NDR），29 只眼为非增生性糖尿病性视网膜病变（NPDR）（轻度 10 只，中度 7 只，重度 12 只），19 只眼为增生性糖尿病性视网膜病变（PDR）。于 2016 年 9 月至 2017 年 6 月间使用 OCTA 采集图像。选择 6×6mm 的扫描区以发现浅层视网膜和深层视网膜的形态变化。使用自动阈值算法对捕获的 OCTA 图像进行二值化。测量浅层和深层视网膜血管弓的黄斑血管密度（MVD）（%）和中央无血管区面积（FAZ）（mm2）。为了进行比较，应用方差分析和 Kruskal-Wallis 检验。
根据严重程度将糖尿病眼分组。比较所有组的 MVD 和 FAZ。除对照组和 NDR 外，所有组的结果均显著降低。随着视网膜病变的进展，大多数层的血管密度均显著下降。
Adobe Photoshop CS3 扩展版是图像二值化的优秀工具。使用 OCTA 图像计算 FAZ 面积和 MVD 与临床分级系统密切相关。该方法的应用有助于监测疾病进展。
