Ring-Peeling: A Novel Fovea-sparing Internal Limiting Membrane Peeling Technique for Myopic Foveoschisis with Foveal Detachment

中央凹 限制 医学 内界膜 眼科 光学 材料科学 黄斑裂孔 视力 物理 机械工程 工程类 视网膜 玻璃体切除术
作者
Jiao Lyu,Dian Jiao,Peiquan Zhao
出处
期刊:Retina-the Journal of Retinal and Vitreous Diseases [Lippincott Williams & Wilkins]
标识
DOI:10.1097/iae.0000000000004527
摘要

Purpose: To introduce a novel fovea-sparing internal limiting membrane (ILM) “Ring-peeling” technique and evaluate its effectiveness for treating myopic foveoschisis (MFS) with foveal detachment via pars plana vitrectomy (PPV). Methods: This technique was applied to 12 eyes (11 patients). During PPV, a 1-disc diameter (DD)-wide ILM flap was created, with its inner edge at least ¼ DD from the foveola. The flap was peeled tangentially toward the fovea and parallel to the inner retinal curvature. When the flap narrowed to half its original width, it was centrifugally extended. Intraoperative ILM peeling performance, postoperative anatomical and visual outcomes were measured. Results: During PPV, an ILM shield was preserved on the fovea in all eyes. In 10 eyes (83.3%), ILM peeling was continuous and based on a single ILM flap. After a follow-up of 20.2 ± 7.1 months, schisis cavities resolved and the fovea reattached in all eyes. The external limiting membrane was retrieved in 9 eyes (75%). BCVA improved in all eyes compared to preoperative levels, with 3 eyes achieving a BCVA above 20/50. Conclusion: This technique enhances the certainty of preserving an ILM shield on the fovea and achieves good postoperative visual and anatomical outcomes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
丰富语蕊应助甜叶菊采纳,获得30
刚刚
changjinglu发布了新的文献求助10
刚刚
1秒前
FashionBoy应助三岁采纳,获得10
1秒前
1秒前
1秒前
2秒前
duoduo发布了新的文献求助10
2秒前
2秒前
上官若男应助Leo93采纳,获得10
2秒前
搜集达人应助zyj采纳,获得10
2秒前
Kerwin完成签到,获得积分10
3秒前
流星雨应助mannich采纳,获得10
3秒前
3秒前
3秒前
vv完成签到,获得积分10
3秒前
3秒前
Anton完成签到,获得积分10
4秒前
Singularity发布了新的文献求助10
4秒前
4秒前
Giao完成签到,获得积分10
4秒前
aaaa应助Doris采纳,获得30
4秒前
十二发布了新的文献求助10
4秒前
五五五完成签到,获得积分10
5秒前
5秒前
lareina发布了新的文献求助10
5秒前
5秒前
xuan发布了新的文献求助10
5秒前
有梦想的人不睡觉完成签到,获得积分10
6秒前
Yuuuuu完成签到,获得积分10
6秒前
酷波er应助虚幻火龙果采纳,获得10
6秒前
6秒前
清秀曼寒发布了新的文献求助10
6秒前
6秒前
张教授发布了新的文献求助10
6秒前
7秒前
脑洞疼应助duoduo采纳,获得10
7秒前
dihou111发布了新的文献求助10
7秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7582814
求助须知:如何正确求助?哪些是违规求助? 9161698
关于积分的说明 19604367
捐赠科研通 7164974
什么是DOI,文献DOI怎么找? 3266192
关于科研通互助平台的介绍 2431125
邀请新用户注册赠送积分活动 2257468