Work

Fundus blood flow density changes in the smoking population by artificial intelligence-based optical coherence tomography angiography

Year: 2025

Type: article

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.

Source: International Journal of Ophthalmology

DOI: 10.18240/ijo.2025.09.01

Authors: Ling-Yu Zhang, Qiang Zhou, Yu Zhang, Yan Liu, Zhi-Liang Wang, Pei Zhang

Institutions: Tianjin Medical University Eye Hospital, Tianjin Medical University, Fudan University, Huashan Hospital

Language: English

Topic: Retinal Imaging and Analysis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,800