Limbal-conjunctival autograft healing process-early postoperative OCT angiography study.

PURPOSE: To assess the normal healing process of limbal-conjunctival autograft (LCA) after pterygium removal during the early postoperative period using anterior segment optical coherence tomography angiography (OCTA). METHODS: Prospective case series of seven patients undergoing pterygium removal with LCA transplantation procedure, imaged with anterior segment OCTA, and anterior segment colour photos prior to the procedure and on postoperative day (POD) 1, 3, 7 and 30. Revascularization of the graft was analysed quantitatively and qualitatively to estimate patterns of blood vessel growth. Association between revascularization to graft thickness was also investigated. RESULTS: On POD 1, all autografts showed either minimal flow signal or no signal at all (Mean 7.1 ± 3.3%). Regrowth of blood vessels into the graft was detected on OCTA scans on POD3 (8.7 ± 3.6%) to 7 (14.3 ± 4.1%), as nonorganised vessels formation in their appearance. Blood vessels were seen growing in a centrifugal pattern towards the surrounding conjunctiva, originating from the underlying episcleral vessels. Revascularization flow signal was seen throughout nearly all graft extent on day 30 (21.6 ± 2.2%). Graft oedema was evident on the first week (Mean 611 ± 120 µm, 695 ± 84 µm, 639 ± 96 µm of POD 1, 3 and 7, respectively), reducing substantially by day 30 (300 ± 108 µm). CONCLUSIONS: OCTA imaging can be used to assess the LCA healing process during the early postoperative period. Revascularization occurring as early as 3-7 days post-surgery, seems to originate from the underlying episcleral vessels. Therefore, careful handling of the bare scleral surface during surgery may be prudent for achieving an adequate healing process.

Automatic Characterization of Retinal Blood Flow Using OCT Angiograms.

PURPOSE: To quantitatively characterize the retinal vascular network in healthy and pathological cases using optical coherence tomography angiography (OCTA) images. METHODS: The study included 56 eyes of 28 patients as follows: 26 healthy, 20 with diabetic retinopathy (DR), 6 with age-related macular degeneration (AMD), and 4 with retinal vein occlusion (RVO). For 33 eyes (16 healthy and 17 with DR), vessel density maps were provided by the OCTA machine. An automatic algorithm classified the image (as healthy, DR, AMD, or RVO) and provided quantitative information obtained from the angiograms, including global vessel density, global fractal dimension, and fovea avascular zone (FAZ) area. Classification results were compared with the diagnosis made by a retina specialist. The quantitative values were compared with the literature and to values provided by the OCTA machine. RESULTS: The success rate of classification was 83.9%. Vessel densities obtained by our algorithm (in healthy and DR cases) were significantly lower than the values reported in previous studies using OCTA. Similarly, they were much lower than the values provided by the OCTA machine. However, vessel densities in the healthy cases were similar to or higher than (depending on the retinal layer) the recently published values that may be considered as gold standard. Our values of fractal dimension were similar to those previously reported. CONCLUSIONS: Our algorithm provides significantly improved vessel density values compared with previous studies. We believe our algorithm successfully omits false vessels. TRANSLATIONAL RELEVANCE: Accurately assessing retinal vessel density enables better evaluation of retinal disorders.