In recent years, analysis of choroidal and retinal vessels has become easier with the introduction of the OCT-A, an improvement over OCT. OCT-A is a non-invasive imaging technique that relies on the movement of blood cells in the vessels, and it has become a relevant diagnostic tool in clinical practice. OCT-A allows visualization of vessel structure and flow. However, currently, there is no standardized method for analyzing the images, and physicians primarily interpret them qualitatively rather than quantitatively. In a medical retina office, the ability to identify new vessels beneath the retina is crucial in deciding whether to initiate intravitreous treatment. In other pathologies, assessing the flow may be more useful in effectively monitoring patients during follow-up.

Another challenge is that different OCT-A devices utilize different algorithms to generate vascular chorio-retinal maps based on the OCT signal they receive. Consequently, different OCT-A devices may produce varying values for vessel density. Various methods have been described in the literature to address this issue.

Lupidi et al., with the aim of quantitatively analyzing blood flow, developed an automated quantitative technique for visualizing and analyzing macular vascular perfusion using optical coherence tomography angiography (OCT-A). They analyzed and compared the superficial capillary plexus with the deep capillary plexus, and significant differences were found for the perimetry, surface and major axis of the foveal avascular zone. They improved the software, known as AngioQuant™, facilitating a highly reliable and reproducible quantitative assessment of various findings that were previously limited to qualitative analysis [12].

Hosari et al. conducted a study to assess the reliability of macular microvasculature measurements using Heidelberg Spectralis II optical coherence tomography angiography (OCT-A) in conjunction with the semiautomated vessel density software EA-Tool. They evaluated the vessel density by dividing the OCT image in 12 segments for the superficial vascular plexus, intermediate capillary plexus and deep capillary plexus. Thanks to this combination, they found good or even excellent ICCs in 75% of all analyzed segments of the vascular layers [13].

Our proposed method analyses Swept-Source (Topcon, DRI OCT Triton) OCT-A images by exploiting the premise that black pixels indicate no flow, white pixels represent high flow, and gray pixels represent varying degrees of blood cell movement within vessels.

For each image, each pixel was assigned to a subgroup based on its value. Subsequently, a curve was generated to summarize all the data obtained from each subgroup. The analysis focuses only on the gray pixels, excluding the black pixels representing no flow, and the white pixels indicating high flow, thereby considering only the intermediate flow levels.

When analyzing the microvasculature in the ONH, less inter-image variability was observed in the 70 μm superficial area of the optic disc, which includes the RPC and vitreous layers for the analysis of the optic disc, and in the superficial and choriocapillaris layers for macular blood flow assessment in both glaucomatous and healthy eyes. These layers may be the focus for the analysis of blood flow defects and could serve as promising parameters for diagnosing glaucomatous damage and early biomarkers in glaucoma pathogenesis. The selective vascularization at these layers could be regarded as a potential biomarker to identify eyes at risk of developing glaucomatous optic neuropathy before functional alterations become apparent in perimetric examinations. However, currently, there is no real clinical parameter available. This study aims to confirm the feasibility of using the distribution of gray levels to derive a clinical metric. The next step involves utilizing reliable data to establish such a metric. Moreover, this clinical parameter may serve as a biomarker for depicting ocular diseases.

There are some limitations to the current study. Firstly, the quality of the images is affected by the collaboration of the subjects, which is crucial for this type of analysis. Saccades in the image pose a problem for the analysis since the pixels are interpreted as chorio-retina flow rather than eye movements. Therefore, any lines resulting from saccades should be excluded from the analysis to ensure an accurate interpretation of the data.

The small number of eyes enrolled in the control and glaucoma groups may be considered a limitation. However, a large cohort is not always necessary in reproducibility studies. The focus of reproducibility studies is typically on assessing the consistency and reliability of the measurements rather than generalizability to a larger population. Nonetheless, it is valuable to acknowledge the sample size as a potential limitation when interpreting the study’s findings.

Furthermore, this study did not account for potential confounding factors such as age, systemic comorbidities, or medication use, which could influence ocular blood flow and introduce bias.

By addressing these limitations, future studies can build upon the current findings and provide further insights into the assessment of OCT-A in glaucoma research.

The current findings argue for a pathogenetic role of ocular blood flow [3] and confirm that OCT-A could be a useful technique to detect early glaucoma [14].

Further studies could explore the reproducibility of the method by acquiring images on different days. In our study, we focused on investigating the intra-subject variability, but in the future, it would be valuable to study inter-subject variability as well. Additionally, by increasing the sample size, a comparison between healthy subjects and glaucoma patients could be conducted to assess potential differences.

The developed analysis program could also be utilized to quantify flow within the retinochoroidal microvasculature based on the percentage of white pixels, providing insights into potential quantitative differences in vascularization between glaucomatous and healthy eyes. Additionally, investigating the correlation between blood flow measurements and global indices from visual field tests could help understand the relationship between vascular integrity of the optic nerve and functional progression in glaucomatous patients, shedding light on whether vascular alterations are causes or effects of optic nerve damage in glaucoma.

In conclusion, utilizing Swept-Source (Topcon, DRI OCT Triton) OCT-A images our study has identified an easy and reproducible method that appears to be fast and can assist physicians in assessing macular and ONH perfusion.