Ultrasound super-resolution imaging provides a noninvasive assessment of renal microvasculature changes during mouse acute kidney injury

超声超分辨率成像可无创评估小鼠急性肾损伤期间肾脏微血管的变化

阅读:5
作者:Qiyang Chen, Jaesok Yu, Brittney M Rush, Sean D Stocker, Roderick J Tan, Kang Kim

Abstract

Acute kidney injury (AKI) is a risk factor for the development of chronic kidney disease (CKD). One mechanism for this phenomenon is renal microvascular rarefaction and subsequent chronic impairment in perfusion. However, diagnostic tools to monitor the renal microvasculature in a noninvasive and quantitative manner are still lacking. Ultrasound super-resolution imaging is an emerging technology that can identify microvessels with unprecedented resolution. Here, we applied this imaging technique to identify microvessels in the unilateral ischemia-reperfusion injury mouse model of AKI-to-CKD progression in vivo. Kidneys from 21 and 42 day post- ischemia-reperfusion injury, the contralateral uninjured kidneys, and kidneys from sham-operated mice were examined by ultrasound super-resolution and histology. Renal microvessels were successfully identified by this imaging modality with a resolution down to 32 μm. Renal fibrosis was observed in all kidneys with ischemia-reperfusion injury and was associated with a significant reduction in kidney size, cortical thickness, relative blood volume, and microvascular density as assessed by this imaging. Tortuosity of the cortical microvasculature was also significantly increased at 42 days compared to sham. These vessel density measurements correlated significantly with CD31 immunohistochemistry (R2=0.77). Thus, ultrasound super-resolution imaging provides unprecedented resolution and is capable of noninvasive quantification of renal vasculature changes associated with AKI-to-CKD progression in mice. Hence, this technique could be a promising diagnostic tool for monitoring progressive kidney disease.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。