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非灌注区域检测中的蓝光反射成像:多模态分析的见解

Blue light reflectance imaging in non-perfusion areas detection: insights from multimodal analysis.

作者信息

Leitão Guerra Ricardo, Barbosa Gabriel Castilho Sandoval, Leitão Guerra Cezar, Badaro Emmerson, Roisman Luiz, Lucatto Luiz Filipe, Novais Eduardo

机构信息

Orbit Ophthalmo Learning, Salvador, Brazil.

Leitão Guerra - Oftalmologia, Salvador, Brazil.

出版信息

Int J Retina Vitreous. 2024 Nov 4;10(1):84. doi: 10.1186/s40942-024-00602-z.

DOI:10.1186/s40942-024-00602-z
PMID:39497220
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11533372/
Abstract

DESIGN

A retrospective, cross-sectional image analysis using a convenience sample.

SUBJECTS

Five cases selected based on the availability of comprehensive imaging data.

METHODS

This study involved a retrospective review of images from five cases, focusing on the use of retinal monochromatic blue light reflectance (BLR) imaging to detect non-perfusion areas. Two cases of sickle-cell retinopathy demonstrated peripheral retinal non-perfusion identified through widefield fluorescein angiography. Three other cases-one with branch retinal vein occlusion, one with branch retinal artery occlusion, and one presenting paracentral acute middle maculopathy showed focal macular non-perfusion detected by structural OCT and OCTA. The areas of nonperfused retinal tissue, confirmed by fluorescein angiography, OCT, and OCTA, were then correlated with findings from the BLR image. This correlation aimed to identify any potential associations between these imaging modalities.

MAIN OUTCOME MEASURES

Enhance understanding of the utilization of retinal monochromatic BLR images as a non-perfusion biomarker.

RESULTS

The perfusion defects identified through fluorescein angiography were qualitatively correlated with hypo-reflective regions observed in the BLR images. A notable correlation was also observed between the OCTA deep capillary plexus findings and the BLR images. Additionally, areas of retinal thinning identified on structural OCT thickness maps corresponded with the hypo-reflective regions in the BLR images. This indicates the potential of BLR in identifying non-perfused retinal areas.

CONCLUSIONS

This study reinforces the evidence, through OCT, OCTA, and angiographic correlation, that the BLR can effectively identify areas of retinal non-perfusion in a non-invasive manner. Further research is warranted to assess the method's sensitivity, specificity, and limitations. While the interaction of blue light with the retina, leading to specular reflections and scattering, is established, this research represents a pioneering effort in suggesting which specific retinal structures may be implicated in this phenomenon. This novel insight opens avenues for deeper exploration into the underlying mechanisms and potential clinical applications of utilizing the BLR imaging technique for assessing retinal vascular abnormalities.

摘要

设计

采用便利样本的回顾性横断面图像分析。

研究对象

根据综合影像数据的可获取性选取5例病例。

方法

本研究对5例病例的影像进行回顾性分析,重点关注视网膜单色蓝光反射率(BLR)成像在检测无灌注区方面的应用。2例镰状细胞性视网膜病变病例经广角荧光素血管造影显示周边视网膜无灌注。另外3例病例——1例视网膜分支静脉阻塞、1例视网膜分支动脉阻塞以及1例中心性旁急性黄斑病变,经结构光学相干断层扫描(OCT)和光学相干断层扫描血管造影(OCTA)检测显示黄斑局灶性无灌注。经荧光素血管造影、OCT和OCTA证实的视网膜无灌注组织区域,随后与BLR图像的结果进行关联分析。这种关联旨在确定这些成像方式之间的任何潜在关联。

主要观察指标

加深对视网膜单色BLR图像作为无灌注生物标志物应用的理解。

结果

通过荧光素血管造影确定的灌注缺损与BLR图像中观察到的低反射区域在质量上相关。在OCTA深层毛细血管丛结果与BLR图像之间也观察到显著相关性。此外,结构OCT厚度图上确定的视网膜变薄区域与BLR图像中的低反射区域相对应。这表明BLR在识别视网膜无灌注区域方面具有潜力。

结论

本研究通过OCT、OCTA及血管造影相关性分析进一步证实,BLR能够以非侵入性方式有效识别视网膜无灌注区域。有必要开展进一步研究以评估该方法的敏感性、特异性及局限性。虽然蓝光与视网膜相互作用导致镜面反射和散射已得到证实,但本研究率先提出了可能与该现象相关的具体视网膜结构。这一新颖见解为深入探索利用BLR成像技术评估视网膜血管异常的潜在机制及临床应用开辟了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/61a671b5311b/40942_2024_602_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/eea2fb89a40b/40942_2024_602_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/074dad68c31c/40942_2024_602_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/914e82579350/40942_2024_602_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/b5999f1eb61c/40942_2024_602_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/fc93b0cf64c6/40942_2024_602_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/ec8088ff6de1/40942_2024_602_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/900d4ad18873/40942_2024_602_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/61a671b5311b/40942_2024_602_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/eea2fb89a40b/40942_2024_602_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/074dad68c31c/40942_2024_602_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/914e82579350/40942_2024_602_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/b5999f1eb61c/40942_2024_602_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/fc93b0cf64c6/40942_2024_602_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/ec8088ff6de1/40942_2024_602_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/900d4ad18873/40942_2024_602_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1330/11533372/61a671b5311b/40942_2024_602_Fig8_HTML.jpg

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