Quantitative Analysis of Retinal Microvascular Perfusion and Novel Biomarkers of the Treatment Response in Diabetic Macular Edema. (17th November 2020) - Park, Young Gun; Park, Young-Hoon
Abstract : Purpose . We aimed to assess the changes of retinal microvascular parameters using optical coherence tomography angiography (OCTA) between diabetes macular edema (DME) and controls. We assessed the changes between the baseline microvascular parameters and final treatment response in patients with DME, initially treated with intravitreal dexamethasone (DEX) implant followed by antivascular endothelial growth factor (VEGF) injections on an as-needed basis. Methods . This retrospective study included 90 DME patients and 24 healthy control subjects. All subjects had their best-corrected visual acuity (BCVA) and central macular thickness (CMT) measured at baseline and after 12 months. Vessel density (VD) in the superficial capillary plexus (SCP) and deep capillary plexus (DCP) and the deep/superficial flow ratio at baseline were analyzed. A subgroup analysis was used to compare the treatment response. A poor-response group was defined by five or more retreatments at 12 months. Results . BCVA and CMT showed a significant improvement at 12 months (all p < 0.001 ). The VD in the whole and parafoveal areas of the DCP was significantly reduced in DME patients compared to that in controls (all p < 0.05 ). The DCP/SCP flow ratio was also significantly reduced in the DME group (1.08 ± 0.03 vs. 1.05 ± 0.02, p = 0.001 ). In the subgroup analysis, the VD in the foveal and whole DCP areas was significantly lower in the poor-response group than that in the good-response group (p = 0.043 and p = 0.048, respectively). The DCP/SCP flow ratio was also significantly lower in the poor-response group (p = 0.011 ). Conclusion . DME correlated with significant retinal microvascular impairment in the DCP. A decreased DCP/SCP flow ratio was observed in patients with DME that exhibited a poor treatment response. Retinal microvascular parameters could predict the treatment response in DME and help optimize clinical outcomes.