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Kidney Int ; 98(2): 355-365, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32600826

RESUMO

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.


Assuntos
Injúria Renal Aguda , Insuficiência Renal Crônica , Traumatismo por Reperfusão , Injúria Renal Aguda/diagnóstico por imagem , Animais , Modelos Animais de Doenças , Rim/diagnóstico por imagem , Camundongos , Microvasos/diagnóstico por imagem , Traumatismo por Reperfusão/diagnóstico por imagem
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