Abstract
AIMS: To find potential relation between retrobulbar vessels and fundus microvessels and to detect sensitive and effective clinical indicators in predicting the progress of diabetic retinopathy (DR), ocular hemodynamics were measured using superb microvascular imaging (SMI) and ultrawide-field optical coherence tomography angiography (UWF-OCTA). METHODS: Observational, cross-sectional study evaluating ocular hemodynamics in patients with DR by SMI (Aplio i900, Canon Medical) and UWF-OCTA (BM-400 K BMizar, Tupai Medical Technology). The peak systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index (RI) of the central retinal artery (CRA), posterior ciliary artery (PCA), and ophthalmic artery (OA) were measured by SMI. UWF-OCTA evaluated the fundus vascular parameters. A correlation analysis was used to determine the correlation between SMI and UWF-OCTA parameters. RESULTS: One hundred thirty-nine eyes of 139 diabetic patients were included: 29 without DR (NDR), 36 with mild to moderate nonproliferative DR (M-NPDR), 37 with severe NPDR (S-NPDR), and 37 with proliferative DR (PDR). PSV and EDV of retrobulbar vessels decreased from NDR to S-NPDR while increasing PDR. RI of OA showed a decreasing trend in the progression of DR, but other vessels didn't show the same trend. ROC curve analysis showed that CRA(PSV), CRA(EDV), PCA(EDV), OA(PSV,) and OA(EDV) had diagnostic value distinguishing M-NPDR and S-NPDR. The correlation analysis observed a significant association between the SMI parameters of CRA and PCA and UWF-OCTA parameters. CRA hemodynamics were more associated with fundus vascular parameters, especially the retina, in the NDR group than in the M-NPDR group. In contrast, PCA consistently correlated with fundus vascular parameters, especially in the choroid, from the NDR to the M-NPDR group. However, OA showed a poor correlation with OCTA parameters. CONCLUSION: The velocity of retrobulbar vessels, mainly the CRA, may serve as a valuable predictor for assessing the progress of DR. The use of SMI in diabetic patients may help identify patients at risk of developing retinopathy.