m+Medelevator.RU
← Поиск публикаций
Progress in retinal and eye research · 2025

Characterizing Bruch's membrane: State-of-the-art imaging, computational segmentation, and biologic models in retinal disease and health.

СтатьяОбзорНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Ong Joshua, Selvam Amrish, Driban Matthew, Zarnegar Arman, Morgado Mendes Antunes Da Silva Susana Isabel, Joy Jincy, Rossi Ethan A, Vande Geest Jonathan Pieter, Sahel José-Alain, Chhablani Jay

Аннотация

The Bruch's membrane (BM) is an acellular, extracellular matrix that lies between the choroid and retinal pigment epithelium (RPE). The BM plays a critical role in retinal health, performing various functions including biomolecule diffusion and RPE support. The BM is also involved in many retinal diseases, and insights into BM dysfunction allow for further understanding of the pathophysiology of various chorioretinal pathologies. Thus, characterization of the BM serves as an important area of research to further understand its involvement in retinal disease. In this article, we provide a review of various advancements in characterizing and visualizing the BM. We provide an overview of the BM in retinal health, as well as changes observed in aging and disease. We then describe current state-of-the-art imaging modalities and advances to further visualize the BM including various types of optical coherence tomography imaging, near-infrared reflectance (NIR), and autofluorescence imaging and tissue matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS). Following advances in imaging of the BM, we describe animal, cellular, and synthetic models that have been developed to further visualize the BM. Following this section, we provide an overview of deep learning in retinal imaging and describe advances in computational and artificial intelligence (AI) techniques to provide automated segmentation of the BM and BM opening. We conclude this section considering the clinical implications of these segmentation techniques. Ultimately, the diverse advances aimed to further characterize the BM may allow for deeper insights into the involvement of this critical structure in retinal health and disease.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты