Abstract
AIM: To determine whether chronic smoking affects fundus blood flow density using optical coherence tomography angiography (OCTA) based on artificial intelligence (AI). METHODS: All participants underwent a comprehensive ophthalmological examination in this study. The subjects were categorized into two groups: control and smoker. Fundus data obtained through the novel OCTA device were compared. RESULTS: Utilizing deep learning denoising techniques removed background noise and smoothed vessel surfaces. OCTA showed a significant decrease in fundus blood flow density after AI-based denoising on the right eyes of 36 smokers (36 males, average age 44.17±9.85y) and age- and sex-matched participants who never smoked. The thickness of the retina in both control and smoker groups failed to show any statistically significant differences. Smoking was associated with decreased blood flow density in the macula and the optic disk. CONCLUSION: Utilizing AI-based denoising to improve the sensitivity of OCTA images can be highly beneficial.