Department of Ophthalmology, Medical School, University of Crete, Heraklion, Greece.
Laboratory of Vision and Optics, Medical School, University of Crete, Heraklion, Greece.
Can J Ophthalmol. 2018 Jun;53(3):199-206. doi: 10.1016/j.jcjo.2017.09.029. Epub 2017 Dec 13.
To assess the morphology of perifoveal capillary network with quantitative parameters in young patients with diabetes mellitus type I (DM I) using an algorithm.
Fifty-three images (33 eyes of 33 DM I patients and 20 eyes of 20 non-DM controls) were chosen retrospectively from the University Hospital of Heraklion digital fluorescein angiography database. An additional group consisting of patients with advanced DR abnormalities was included in our analysis to investigate whether our method detects alterations when they are present. The developed algorithm allows the user to manually trace the perifoveal capillary network by selecting with the cursor in a 5° × 5° subimage field of the original image, including the foveal avascular zone (FAZ), and provides measurements of the capillary density, the branch point density, and the FAZ surface in this subarea.
The age in the patient group was 19 ± 5 years; age was 21 ± 8 years for the control group. Patients had a history of DM I for 11 ± 5 years. The mapping revealed a perifoveal capillary density of 2.494 ± 0.559 deg in the DM I group versus 2.974 ± 0.442 deg in the control group (p = 0.005). The branch point density was 3.041 ± 0.919 branch points/deg and 3.613 ± 1.338 branch points/deg in each group, respectively (p = 0.128). The FAZ area was 0.216 ± 0.061 deg in the diabetic group and 0.208 ± 0.060 deg in the control group (p = 0.672).
The selected quantitative parameters tend to increase or decrease in diabetic patients, in agreement with previous studies. Among the parameters, capillary density may represent the most sensitive metric for the detection of very early diabetic changes. Further improvement of the method could contribute to the development of an automated processing tool for capillary network quantitative assessment.
使用算法评估 I 型糖尿病(DM I)年轻患者的周边黄斑毛细血管网形态,并用定量参数进行评估。
回顾性地从伊拉克利翁大学医院数字荧光血管造影数据库中选择了 53 张图像(33 只眼睛的 33 例 DM I 患者和 20 只眼睛的 20 例非 DM 对照者)。我们的分析还包括了一组患有晚期 DR 异常的患者,以研究我们的方法是否能够在出现异常时检测到变化。开发的算法允许用户通过在原始图像的 5°×5°子图像字段中用光标手动选择周边黄斑毛细血管网,包括无血管区(FAZ),并在此子区域中提供毛细血管密度、分支点密度和 FAZ 表面的测量值。
患者组的年龄为 19 ± 5 岁;对照组的年龄为 21 ± 8 岁。患者患 I 型糖尿病的时间为 11 ± 5 年。定位显示,DM I 组周边黄斑毛细血管密度为 2.494 ± 0.559 deg,对照组为 2.974 ± 0.442 deg(p = 0.005)。分支点密度分别为每组 3.041 ± 0.919 个分支点/deg 和 3.613 ± 1.338 个分支点/deg(p = 0.128)。糖尿病组 FAZ 面积为 0.216 ± 0.061 deg,对照组为 0.208 ± 0.060 deg(p = 0.672)。
所选的定量参数在糖尿病患者中倾向于增加或减少,这与之前的研究一致。在这些参数中,毛细血管密度可能是检测早期糖尿病变化最敏感的指标。该方法的进一步改进可能有助于开发毛细血管网络定量评估的自动处理工具。