Yoshida Miyo, Murakami Tomoaki, Nishikawa Keiichi, Ishihara Kenji, Mori Yuki, Tsujikawa Akitaka
Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Ophthalmol Sci. 2024 Sep 7;5(1):100603. doi: 10.1016/j.xops.2024.100603. eCollection 2025 Jan-Feb.
To evaluate the severity scales of diabetic macular ischemia (DMI) by analyzing the quantity and distribution of capillary nonperfusion using OCT angiography (OCTA) images.
A single-center, prospective case series.
Three hundred one eyes from 301 patients with diabetic retinopathy.
We acquired 3 × 3-mm swept-source OCTA images and created en face images within a central 2.5-mm circle. The circle was divided into 15 × 15-pixel squares and nonperfusion squares (NPSs) were defined as those without retinal vessels. Eyes with high-dimensional spatial data were arranged on a 2-dimensional space using the uniform manifold approximation and projection (UMAP) algorithm and classified by clustering into 5 groups: , , , , and .
Development of a severity scale for DMI.
Eyes arranged on a 2-dimensional UMAP space were divided into 5 clusters, based on the similarity of nonperfusion area distribution. Nonperfusion square counts in the deep layer increased in eyes of the , , , and groups in a stepwise manner. In contrast, there were no significant changes in superficial NPS counts between eyes of the and groups. In the intermediate stage, eyes of the group exhibited higher NPS counts in the central sector of the superficial layer compared with those of the group. The foveal avascular zone extended into the temporal subfield of the deep layer in eyes of the group. Eyes of the group had significantly poorer visual acuity that was more frequently accompanied with proliferative diabetic retinopathy.
The application of dimensionality reduction and clustering has facilitated the development of a novel severity scale for DMI based on the distribution of capillary nonperfusion in OCTA images.
The authors have no proprietary or commercial interest in any materials discussed in this article.
通过使用光学相干断层扫描血管造影（OCTA）图像分析毛细血管无灌注的数量和分布，评估糖尿病性黄斑缺血（DMI）的严重程度分级。
单中心前瞻性病例系列研究。
301例糖尿病视网膜病变患者的301只眼。
我们获取了3×3 mm的扫频源OCTA图像，并在中央2.5 mm的圆内创建了正面图像。该圆被划分为15×15像素的正方形，无灌注正方形（NPS）被定义为没有视网膜血管的正方形。使用均匀流形近似和投影（UMAP）算法将具有高维空间数据的眼睛排列在二维空间中，并通过聚类分为5组： 、 、 、 、 。
制定DMI严重程度分级标准。
根据无灌注区域分布的相似性，排列在二维UMAP空间中的眼睛被分为5个聚类。在 、 、 、 组的眼中，深层的无灌注正方形计数呈逐步增加。相比之下， 组和 组的眼之间表层NPS计数没有显著变化。在中期， 组的眼在表层中央区域的NPS计数高于 组。 组的眼中，黄斑无血管区延伸至深层的颞侧子区域。 组的眼视力明显较差，且更常伴有增殖性糖尿病视网膜病变。
降维和聚类的应用有助于基于OCTA图像中毛细血管无灌注的分布制定一种新的DMI严重程度分级标准。
作者对本文讨论的任何材料均无所有权或商业利益。
