Macular pigment optical density and measurement technology based on artificial intelligence: a narrative review

MPOD and AI-based measurement ·Review Article· Macular pigment optical density and measurement technology based on artificial intelligence: a narrative review Yu-Xuan Yuan1, Hong-Yun Wu2, Wen-Jin Yuan3, Yi-Lin Zhong2, Zhe Xu2 1 School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, Gansu Province, China 2 Ophthalmology Department, Ganzhou People’s Hospital, Ganzhou 341000, Jiangxi Province, China 3 Department of Cardiology, Ganzhou People’s Hospital, Ganzhou 341000, Jiangxi Province, China Co-first Authors: Yu-Xuan Yuan and Hong-Yun Wu C o r re s p o n d e n c e t o : H o n g - Yu n Wu a n d Z h e X u . Ophthalmology Department, Ganzhou People’s Hospital, Ganzhou 341000, Jiangxi Province, China. wuhy77@126. com; Received: 2024-11-23 Accepted: 2025-01-21 Abstract ● 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. ● KEYWORDS: macular pigment optical density; clinical application; measurement technology; artificial intelligence DOI:10.18240/ijo.2025.06.23 Citation: Yuan YX, Wu HY, Yuan WJ, Zhong YL, Xu Z. Macular 1152 pigment optical density and measurement technology based on artificial intelligence: a narrative review. Int J Ophthalmol 2025;18(6):1152-1162 INTRODUCTION he macular pigment (MP) is primarily concentrated in the macular region of the retina and is composed of three carotenoids, namely lutein, zeaxanthin, and mesozeaxanthin[1-2]. The density of MP is typically represented by macular pigment optical density (MPOD)[2-3]. It has been demonstrated that MP plays a role in filtering blue light, reducing inflammation, and combating oxidative stress[1,4-8]. MPOD is closely associated with the onset and progression of several ocular diseases, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma, which highlights its broad research and clinical application value[3,9-10]. Methods for measuring MPOD can be categorized in vivo and in vitro techniques[10-11]. In vitro methods include microdensitometry and high-performance liquid chromatography (HPLC)[11]. In vivo methods can be further divided into subjective and objective techniques[11-12]. Subjective methods include heterochromatic flicker photometry (HFP), color matching, and minimum motion photometry, while objective methods encompass fundus reflectometry (FR), fundus autofluorescence (FAF), resonance Raman spectroscopy (RRS), and visual evoked potential (VEP) based on electrophysiology[3,13-15]. Among these techniques, HFP is regarded as the standard method for measuring MPOD due to its extensive clinical application and reliability[15]. However, all methods have advantages, disadvantages, and limitations, making it challenging for MPOD to fully realize its potential in the prevention and treatment of ocular diseases. In recent years, with the rapid advancement in use of deeplearning algorithms for medical image analysis, artificial intelligence-based fundus image recognition technology has created new possibilities for MPOD measurement[16]. This approach not only promises to enhance measurement accuracy and efficiency, but also overcome certain limitations of traditional techniques. The present study investigates the relationship between MPOD and various ocular diseases, as T Int J Ophthalmol, Vol. 18, No. 6, Jun. 18, 2025 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: well as its value in ophthalmology and other medical research fields. Additionally, this study emphasizes the importance of MPOD measurement, evaluates the limitations of current techniques, and explores the potential of artificial intelligencebased fundus image MPOD measurement, with the hope of providing a faster and more accurate detection method for the clinical application and further development of MPOD research. MPOD AND ITS APPLICATIONS Macular Pigment and Macular Pigment Optical Density The macula, located in the central optical region of the posterior pole of the retina, is a vital area for maintaining visual functions (e.g., fine vision and color perception), and appears yellow due to its high concentration of MP[2]. As the primary functional component of the macular region, MP is concentrated in the Henle fiber layer, the inner nuclear layer of the retina, the axons of cone cells, and the outer segments of rod cells[4-6], and is mainly composed of three lutein-related carotenoids, namely lutein, zeaxanthin, and meso-zeaxanthin[1]. MP helps maintain the normal function and morphology of the macula and protect ocular health. Moreover, MP act as a blue-light filter by absorbing 40%-90% of high-energy shortwavelength blue light[5,7], reducing oxidative damage from blue light within the eye and thereby protecting the retina from photochemical damage[1]. MP also quenches singlet oxygen and related reactive oxygen species to reduce oxidative stressinduced damage to photoreceptor cells, thereby preserving healthy vision[4,6,8]. Additionally, it has been reported that MP can inhibit ocular inflammation by reducing inflammatory factors and regulating the expression of related genes [7]. Therefore, it has been suggested that supplementing with lutein, zeaxanthin, and other antioxidant blends may help improve eye health[17-18]. MP density is expressed as MPOD, which linearly correlates with the total amount of MP, i.e., the product of its concentration, the length of the light transmission path, and the area[2,19]. MPOD is measured in optical density units, ranging from 0 to 1, with one optical density unit corresponding to approximately 0.025 nanograms of MP covering one square millimeter of retinal tissue[7,20]. In addition to MPOD, serum lutein levels, and dietary intake of lutein are also commonly used as indicators of MP levels. However, these indicators do not fully account for potential confounding factors in the processes of lutein digestion, (...truncated)