Quantitative Microvascular Change Analysis Using a Semi-Automated Software in Macula-off Rhegmatogenous Retinal Detachment Assessed by Swept-Source Optical Coherence Tomography Angiography

利用半自动软件对黄斑脱离性裂孔性视网膜脱离进行定量微血管变化分析,该分析通过扫频源光学相干断层扫描血管造影术进行评估。

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Abstract

Objective: To analyze the performance of custom semi-automated software for quantitative analysis of retinal capillaries in eyes with macula-off rhegmatogenous retinal detachment (RRD) and the role of these microvascular measures as potential biomarkers of postoperative visual outcomes. Methods: A prospective, observational, and single-center study was conducted on consecutive patients who underwent 25G pars-plana vitrectomy for primary uncomplicated macula-off RRD. Optical coherence tomography angiography (OCTA) was performed in the fellow and RRD eyes before surgery and in months 1, 3, and 6 after surgery. The preoperative values of the fellow eyes were used as surrogates of macula-off ones. The primary endpoints were the mean vessel diameter index (VDI); vessel area density (VAD); and vessel skeleton density (VSD) at month 6. Results: Forty-four eyes (44 patients) were included in the study. Considering the fellow eyes as a surrogate of preoperative values of macula-off eyes, VDI in superficial (SCP) and deep (DCP) capillary plexuses was significantly reduced at month 6 (p = 0.0087 and p = 0.0402, respectively); whereas VSD in SCP increased significantly from preoperative values (p = 0.0278). OCTA built-in software parameters were significantly reduced from month 1 to month 6 in both SCP and DCP (p values ranged between 0.0235 and <0.0001). At month 6, 25 (56.8%) eyes achieved a best-corrected visual acuity BCVA ≥ 0.3 (LogMAR). The greater the preoperative BCVA, the greater the probability of achieving good visual outcomes (Odds ratio: 11.06; p = 0.0037). However, none of the OCTA parameters were associated with the probability of achieving a BCVA improvement ≥ 0.3. Conclusions: Quantitative evaluation of capillary density and morphology through OCTA and semi-automated software represents a valuable tool for clinical assessment and managing the disease comprehensively.

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