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深度学习自动量化纵向 OCT 扫描显示,接受 C3 抑制治疗的地图样萎缩患者的 RPE 丢失率降低,完整黄斑区保留和孤立光感受器变性的预测价值。

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.

机构信息

NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust & UCL, Institute of Ophthalmology, London, UK.

Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands.

出版信息

Br J Ophthalmol. 2024 Mar 20;108(4):536-545. doi: 10.1136/bjo-2022-322672.

Abstract

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.

摘要

目的

评估使用经过验证的深度学习模型对自动光学相干断层扫描 (OCT) 分割在评估 C3 抑制对地理萎缩 (GA) 面积的影响中的作用;OCT 上 GA 的组成特征(光感受器变性 (PRD)、视网膜色素上皮 (RPE) 丧失和高透过性);以及未受影响的健康黄斑区面积。确定 GA 生长的 OCT 预测生物标志物。

方法

使用深度学习模型对 FILLY 试验进行事后分析,用于光谱域 OCT (SD-OCT) 自动分割。246 名患者按 1:1:1 随机分为培格塞他单抗每月 (PM)、培格塞他单抗每两个月 (PEOM) 和假治疗 (合并) 治疗 12 个月和 6 个月的无治疗监测。仅纳入接受海德堡 SD-OCT 的参与者 (n=197,每位参与者一只眼)。主要疗效终点为 12 个月时各治疗组中 GA 面积作为完整 RPE 和外层视网膜萎缩 (cRORA) 的平方根变化,次要终点包括 RPE 丧失、高透过性、PRD 和完整黄斑区。

结果

PM 治疗的眼睛在 12 个月和 18 个月时 cRORA 进展的平均变化明显较慢(0.151 和 0.277 mm,p=0.0039;0.251 和 0.396 mm,p=0.039)和 RPE 丧失(0.147 和 0.287 mm,p=0.0008;0.242 和 0.410 mm,p=0.00809)。PEOM 与 sham 相比,在 12 个月时 RPE 丧失的平均变化明显较慢 (p=0.0313)。PM 与 sham 相比,在 12 个月和 18 个月时保留了完整的黄斑区面积(p=0.0095 和 p=0.044)。PRD 单独和完整的黄斑区面积是 12 个月时 cRORA 生长减少的预测因素(系数 0.0195,p=0.01 和 0.00752,p=0.02)。

结论

OCT 证据表明,培格塞他单抗总体上减缓了 cRORA 的进展,特别是 RPE 丧失,同时保护了剩余的光感受器,并减缓了健康视网膜向 iRORA 的进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91f5/10958254/d71d165dd3a3/bjo-2022-322672f01.jpg

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