Macular pigment optical density and measurement technology based on artificial intelligence: a narrative review - Yu-Xuan Yuan; Hong-Yun Wu; Wen-Jin Yuan; Yi-Lin Zhong; Zhe Xu (International Journal of Ophthalmology)
Macular pigment (MP) is a crucial pigment in the macular region. It plays an important role in filtering blue light, and exhibits anti-inflammatory and antioxidant properties. Macular pigment optical density (MPOD) is a key indicator for assessing the density of MP in the macular area and is closely associated with eye diseases, including age-related macular degeneration, diabetic retinopathy, and glaucoma. This review aims to explore the clinical significance of MPOD and its research value in ophthalmology and other medical fields. It summarizes the current MPOD measurement techniques, categorizing them into two main types (in vivo and in vitro), and discusses their respective advantages and limitations. Additionally, given the advancements in artificial intelligence (AI) and deep-learning technologies that offer new opportunities for improving MPOD assessment, this review analyzes the significant potential and future prospects of AI-based fundus image analysis in MPOD measurement. The goal of AI-based analysis is to provide faster and more accurate detection methods, thereby promoting further research and new clinical applications of MPOD in the field of ophthalmology.