Microvascular research · 2025
Association between posterior vitreous detachment stage and quantitative neovascularization morphology in proliferative diabetic retinopathy using wide-field swept-source optical coherence tomography angiography.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
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.
Xu Zikang, Chen Ruoyu, Li Jing, Huang Danling, Li Taozheng, Liang Huilin, Xu Zhicong, Huang Jiayi, Gui Mi, Hojas I M, Zhuang Xuenan, Zhang Liang
Аннотация
PURPOSE: To investigate the association between posterior vitreous detachment (PVD) and the progression of proliferative diabetic retinopathy (PDR) by analyzing the morphological evolution of neovascularization (NV) across PVD stages using swept-source optical coherence tomography angiography (SS-OCTA).
METHODS: This retrospective study assessed PVD stages via SS-OCT. Quantitative analysis of SS-OCTA images was performed with ImageJ and AngioTool to extract NV morphological features including perimeter, MaxFeret, MiniFeret, Feret ratio (FR), maximum vessel caliber, vessel dispersion, fractal dimension index (FDI), vessel area (VA), vessel density, total vessel length (TVL), average vessel length (AVL), total number of junctions (TNJ), junction density (JD), total number of endpoints, endpoint density (ED), and mean lacunarity (MEL) to assess NV size, activity, and complexity. Analysis of NV morphology and PVD association via Generalized Linear Mixed Model.
RESULTS: Significant differences (P < 0.05) in multiple NV parameters were observed across PVD stages in the 74 included eyes. At stage 4, most parameters reached their minima, except for JD and ED, which peaked. Trend analysis revealed inverted U-shaped trajectories for size (perimeter, MaxFeret, MiniFeret, VA), activity (TNJ, TVL, AVL), and complexity (FDI) parameters with PVD progression. In contrast, JD and ED followed U-shaped trends. All inflection points clustered between stages 1 and 2.
CONCLUSIONS: NV morphology in PDR evolves systematically from a highly intricate and extensive structure in early PVD (Stage 1 or 2) to a simplified and localized architecture in stage 4. Concomitant alterations in NV activity and complexity likely occur, providing morphological insights into PVD's role in PDR.
METHODS: This retrospective study assessed PVD stages via SS-OCT. Quantitative analysis of SS-OCTA images was performed with ImageJ and AngioTool to extract NV morphological features including perimeter, MaxFeret, MiniFeret, Feret ratio (FR), maximum vessel caliber, vessel dispersion, fractal dimension index (FDI), vessel area (VA), vessel density, total vessel length (TVL), average vessel length (AVL), total number of junctions (TNJ), junction density (JD), total number of endpoints, endpoint density (ED), and mean lacunarity (MEL) to assess NV size, activity, and complexity. Analysis of NV morphology and PVD association via Generalized Linear Mixed Model.
RESULTS: Significant differences (P < 0.05) in multiple NV parameters were observed across PVD stages in the 74 included eyes. At stage 4, most parameters reached their minima, except for JD and ED, which peaked. Trend analysis revealed inverted U-shaped trajectories for size (perimeter, MaxFeret, MiniFeret, VA), activity (TNJ, TVL, AVL), and complexity (FDI) parameters with PVD progression. In contrast, JD and ED followed U-shaped trends. All inflection points clustered between stages 1 and 2.
CONCLUSIONS: NV morphology in PDR evolves systematically from a highly intricate and extensive structure in early PVD (Stage 1 or 2) to a simplified and localized architecture in stage 4. Concomitant alterations in NV activity and complexity likely occur, providing morphological insights into PVD's role in PDR.