Objective To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on OCT (photoreceptor degeneration (PRD), retinal pigment epithelium (RPE) loss and hypertransmission); and the area of unaffected healthy macula. To identify OCT predictive biomarkers for GA growth. Methods Post hoc analysis of the FILLY trial using a deep-learning model for spectral domain OCT (SD-OCT) autosegmentation. 246 patients were randomised 1:1:1 into pegcetacoplan monthly (PM), pegcetacoplan every other month (PEOM) and sham treatment (pooled) for 12 months of treatment and 6 months of therapy-free monitoring. Only participants with Heidelberg SD-OCT were included (n=197, single eye per participant). The primary efficacy endpoint was the square root transformed change in area of GA as complete RPE and outer retinal atrophy (cRORA) in each treatment arm at 12 months, with secondary endpoints including RPE loss, hypertransmission, PRD and intact macular area. Results Eyes treated PM showed significantly slower mean change of cRORA progression at 12 and 18 months (0.151 and 0.277 mm, p=0.0039; 0.251 and 0.396 mm, p=0.039, respectively) and RPE loss (0.147 and 0.287 mm, p=0.0008; 0.242 and 0.410 mm, p=0.00809). PEOM showed significantly slower mean change of RPE loss compared with sham at 12 months (p=0.0313). Intact macular areas were preserved in PM compared with sham at 12 and 18 months (p=0.0095 and p=0.044). PRD in isolation and intact macula areas was predictive of reduced cRORA growth at 12 months (coefficient 0.0195, p=0.01 and 0.00752, p=0.02, respectively) Conclusion The OCT evidence suggests that pegcetacoplan slows progression of cRORA overall and RPE loss specifically while protecting the remaining photoreceptors and slowing the progression of healthy retina to iRORA.

中文翻译：

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纵向 OCT 扫描的深度学习自动量化显示，接受 C3 抑制治疗的地理萎缩患者的 RPE 损失率降低、黄斑区完整保留以及孤立性感光器变性的预测价值


目的 使用经过验证的深度学习模型评估自动光学相干断层扫描 (OCT) 分割的作用，以评估 C3 抑制对地理萎缩 (GA) 区域的影响； OCT 上 GA 的组成特征（光感受器变性 (PRD)、视网膜色素上皮 (RPE) 损失和超透射）；以及未受影响的健康黄斑区域。确定 GA 生长的 OCT 预测生物标志物。方法 使用谱域 OCT (SD-OCT) 自动分割的深度学习模型对 FILLY 试验进行事后分析。 246 名患者按照 1:1:1 的比例随机分为 pegcetacoplan 每月治疗 (PM)、pegcetacoplan 每隔一个月治疗 (PEOM) 和假治疗（合并），接受 12 个月的治疗和 6 个月的无治疗监测。仅纳入使用海德堡 SD-OCT 的参与者（n=197，每位参与者单眼）。主要疗效终点是 12 个月时每个治疗组中 GA 面积作为完全 RPE 和外层视网膜萎缩 (cRORA) 的平方根转换变化，次要终点包括 RPE 损失、超透射、PRD 和完整黄斑区域。结果 经过 PM 治疗的眼睛在 12 个月和 18 个月时显示 cRORA 进展平均变化显着减慢（分别为 0.151 和 0.277 毫米，p=0.0039；分别为 0.251 和 0.396 毫米，p=0.039）和 RPE 损失（0.147 和 0.287 毫米，p=0.0008）。 ；0.242 和 0.410 毫米，p=0.00809)。 12 个月时，与假手术相比，PEOM 显示 RPE 损失的平均变化明显较慢 (p=0.0313)。 12 个月和 18 个月时，与假手术相比，PM 中保留了完整的黄斑区域（p=0.0095 和 p=0.044）。孤立和完整黄斑区域的 PRD 可预测 12 个月时 cRORA 生长的减少（系数 0.0195，p=0.01 和 0.00752，p=0。分别为 02）结论 OCT 证据表明，pegcetacoplan 可以整体减缓 cRORA 的进展，特别是 RPE 损失，同时保护剩余的光感受器并减缓健康视网膜向 iRORA 的进展。