Costanzo Eliana, Giannini Daniela, De Geronimo Daniele, Fragiotta Serena, Varano Monica, Parravano Mariacristina
IRCCS-Fondazione Bietti, Rome, Italy.
Ophthalmology Unit, Department NESMOS, Sant' Andrea Hospital, University of Rome "La Sapienza", Rome, Italy.
J Clin Med. 2023 Feb 6;12(4):1303. doi: 10.3390/jcm12041303.
The aim was to evaluate predictive value of baseline optical coherence tomography (OCT) and OCT angiography (OCTA) parameters in diabetic macular edema (DME) treated with dexamethasone implant (DEXi).
OCT and OCTA parameters were collected: central macular thickness (CMT), vitreomacular abnormalities (VMIAs), intraretinal and subretinal fluid (mixed DME pattern), hyper-reflective foci (HRF), microaneurysms (MAs) reflectivity, ellipsoid zone disruption, suspended scattering particles in motion (SSPiM), perfusion density (PD), vessel length density, and foveal avascular zone. Responders' (RES) and non-responders' (n-RES) eyes were classified considering morphological (CMT reduction ≥ 10%) and functional (BCVA change ≥ 5 ETDRS letters) changes after DEXi. Binary logistic regression OCT, OCTA, and OCT/OCTA-based models were developed.
Thirty-four DME eyes were enrolled (18 treatment-naïve). OCT-based model combining DME mixed pattern + MAs + HRF and OCTA-based model combining SSPiM and PD showed the best performance to correctly classify the morphological RES eyes. In the treatment-naïve eyes, VMIAs were included with a perfect fit for n-RES eyes.
The presence of DME mixed pattern, a high number of parafoveal HRF, hyper-reflective MAs, SSPiM in the outer nuclear layers, and high PD represent baseline predictive biomarkers for DEXi treatment responsiveness. The application of these models to treatment-naïve patients allowed a good identification of n-RES eyes.
目的是评估基线光学相干断层扫描（OCT）和OCT血管造影（OCTA）参数在接受地塞米松植入物（DEXi）治疗的糖尿病性黄斑水肿（DME）中的预测价值。
收集OCT和OCTA参数：中心黄斑厚度（CMT）、玻璃体黄斑异常（VMIAs）、视网膜内和视网膜下液（混合性DME模式）、高反射灶（HRF）、微动脉瘤（MAs）反射率、椭圆体带破坏、运动中的悬浮散射颗粒（SSPiM）、灌注密度（PD）、血管长度密度和黄斑无血管区。根据DEXi治疗后形态学（CMT降低≥10%）和功能（最佳矫正视力变化≥5个ETDRS字母）变化，对有反应者（RES）和无反应者（n-RES）的眼睛进行分类。建立基于OCT、OCTA和OCT/OCTA的二元逻辑回归模型。
纳入34只DME眼（18只初治眼）。基于OCT的模型（结合DME混合模式+MAs+HRF）和基于OCTA的模型（结合SSPiM和PD）在正确分类形态学有反应的眼睛方面表现最佳。在初治眼中，VMIAs纳入对无反应者眼睛的拟合效果极佳。
DME混合模式、大量黄斑旁HRF、高反射性MAs、外核层中的SSPiM以及高PD的存在代表了DEXi治疗反应性的基线预测生物标志物。将这些模型应用于初治患者可很好地识别无反应者的眼睛。
