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作 者:杨冰冰 曲晓霞 王倩[1] 李婷[1] 鲜军舫[1] YANG Bingbing;QU Xiaoxia;WANG Qian;LI Ting;XIAN Junfang(Department of Radiology,Beijing Tongren Hospital,Capital Medical University,Beijing 100730,China)
机构地区:[1]首都医科大学附属北京同仁医院放射科,北京100730
出 处:《磁共振成像》2022年第11期37-41,共5页Chinese Journal of Magnetic Resonance Imaging
基 金:国家自然科学基金(编号:81571649、81701666、81871340、81901719、82071906);北京市医院管理中心“登峰”计划专项(编号:DFL20190203);北京市医院管理局临床医学发展专项(编号:ZYLX201704)。
摘 要:青光眼是全球首位不可逆致盲性眼病,最常见类型为原发性开角型青光眼(primary open-angle glaucoma, POAG),由于发病机制不清,因此治疗效果不佳。近年来,包含多模态MRI在内的神经影像学研究表明:POAG是一种神经退行性病变,视觉传导通路及视路以外脑区的结构、功能、血流灌注及代谢等都发生了广泛改变,且与POAG患者病情严重程度相关。未来更加需要多中心大样本量前瞻性队列研究,采用机器学习、深度学习方法将多模态MRI数据融合,进一步研究中枢神经系统改变之间的相互关系及其与视网膜改变和视觉障碍的相关性,为早期诊断和治疗提供更加明确的依据。本文系统综述了POAG患者脑MRI研究进展和价值,同时提出存在的问题与未来研究思路,旨在为该领域研究提供参考。Glaucoma is the most frequent cause of irreversible blindness worldwide. As the most prevalent type of glaucoma, primary open-angle glaucoma(POAG) is facing challenges in pathogenesis, diagnosis, and management. In recent years, neuroimaging studies including multimodal MRI have shown that POAG is considered as a neurodegenerative disease. Alterations of brain structure, function, blood perfusion, and metabolism involving visual pathway and other brain regions were shown, which were correlated with the severity of the disease in POAG patients. In the future, multi-center prospective cohort studies with large sample sizes will be more needed, and multi-modal MRI data will be analyzed with machine learning and deep learning methods to investigate the relationship between changes in the central nervous system and their correlation with retinal changes and visual disorders, to provide a more explicit basis for early diagnosis and treatment. Therefore, MRI findings of the brain in patients with POAG and the potential role in the pathogenesis and diagnosis of POAG, as well as probable solutions to the unsolved problems, were systematically reviewed, aiming to provide a reference for the researchers in this field.
关 键 词:原发性开角型青光眼 脑 磁共振成像 多模态 进展
分 类 号:R445.2[医药卫生—影像医学与核医学] R775.2[医药卫生—诊断学]
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