An optimized segmentation and quantification approach in microvascular imaging for OCTA-based neovascular regression monitoring

Abstract

BackgroundQuantification of neovascularization changes in terms of neovascular complex (NVC) acquired from the optical coherence tomography angiography (OCTA) imaging is extremely important for diagnosis and treatment monitoring of proliferative diabetic retinopathy (PDR). However, only few vessel extraction methods have so far been reported to quantify neovascular changes in NVC with proliferative diabetic retinopathy PDR based on OCTA images.MethodsHere we propose an optimized approach to segment blood vessels, which is based on an improved vascular connectivity analysis (VCA) algorithm and combined with morphological characterization and elimination of noise and artifacts. The length and width of vessels are obtained in the quantitative assessment of microvascular network. The feasibility of the proposed method is further studied by a treatment monitoring and statistical analysis process, as we have monitored and statistically analyzed the changes of NVC based on sampled OCTA images of PDR patients (N = 14) after treatment by intravitreal injection of conbercept.ResultsThe proposed method has demonstrated better performance in accuracy compared with existing algorithms and can thus be used for PRD treatment monitoring. Following the PDR treatment monitoring study, our data has shown that from the 1st day to 7th day of treatment, the averaged (arithmetic mean) length of NVC has been substantially shortened by 36.8% (P < 0.01), indicating significant effects of treatment. Meanwhile, the averaged (arithmetic mean) width of NVC from the 1st day to 7th day of treatment has been increased by 10.2% (P < 0.05), indicating that most of the narrow neovascularization has been reduced.ConclusionThe results and analysis have confirmed that the proposed optimization process by the improved VCA method is both effective and feasible to segment and quantify the NVC with lower noise and fewer artifacts. Thus, it can be potentially applied to monitor the fibrovascular regression during the treatment period.Clinical Trial Registration This trial is registered with the Chinese Clinical Trial Registry (Registered 27 December 2017, http://www.chictr.org.cn, registration number ChiCTR-IPR-17014160).