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[摘要]
目的:探讨眼底炫彩成像(MCI)联合光相干断层扫描成像(OCT)在视网膜动脉阻塞(RAO)的快速诊断及分类中的应用。
方法:对本院2018-02/2020-07诊断为RAO的患者19例19眼进行回顾性研究。所有患者在经过眼科检查后确诊为RAO,均为单眼发病,其中视网膜中央动脉阻塞(CRAO)13眼,视网膜分支动脉阻塞(BRAO)5眼,睫状视网膜动脉残留的CRAO 1眼。所有患者行最佳矫正视力、裂隙灯、OCT、MCI、FFA及视野检查及分析。
结果:经裂隙灯检查,12眼(63%)出现瞳孔对光反射迟钝或消失,16眼(84%)可发现全部或部分后极部视网膜苍白水肿,10眼(53%)可发现视网膜动脉变细。行FFA检查的患者为10例(53%),其余9例未行检查,其中6例患有严重的系统性疾病,2例拒绝检查、1例有药物过敏史。所有患者经MCI及OCT检查可发现特征性眼底表现,OCT特征性改变为弥漫性内层视网膜反射增强与MCI图像绿色缺血区域形成严密的一对一关系。
结论:联合MCI及OCT检查可快速确诊RAO,而且结合两者的图像特征可更精确辨认出视网膜缺血区域,有助于疾病分类及预后判断。
[Key word]
[Abstract]
AIM: To investigate the application of rapid diagnosis and classification of retinal artery occlusion(RAO)by multicolor imaging(MCI)with optical coherence tomography(OCT).
METHODS: Totally 19 patients(19 eyes)who were diagnosed with RAO in our hospital were retrospectively analyzed. All of the patients were diagnosed of RAO after ophthalmologic examination, including 13 eyes of central retinal artery occlusion(CRAO), 5 eyes of branch retinal artery occlusion(BRVO)and 1 eye of RAO with sparing of cilioretinal artery. The best corrected visual acuity, slit lamp, OCT, MCI, FFA and visual field were performed on the patients, and the examination results and image data were analyzed.
RESULTS: Totally 12(63%)eyes showed dullness or disappearance of pupil response to light, 16(84%)eyes showed total or partial paleness and edema in the posterior pole of retina, and 10(53%)eyes showed narrowing of retinal artery by slit-lamp examination. FFA examination was performed in 10 cases(53%). However 9 cases were not examined, including 6 cases with serious systemic diseases, 2 cases rejecting to be checked and 1 case with drug allergy. All the patients showed specific manifestations in both MCI and OCT examination, and the typical highly reflectivity of inner retinal layers in OCT formed tight one-to-one relationship with the green ischemic area in MCI.
CONCLUSION: RAO can be diagnosed quickly by MCI combined with OCT, and their image characteristics can accurately identify the retinal ischemic areas, which can help for disease classification and prognosis.
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