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NIR-II window tracking of hyperglycemia induced intracerebral hemorrhage in cerebral cavernous malformation deficient mice.

ABSTRACT: Second near infrared (NIR-II) window fluorescence imaging between 1000 and 1700 nm with reduced scattering and autofluorescence and deep tissue light penetration allows early and non-invasive determination of vascular pathologies. Here, we demonstrate in vivo NIR-II imaging techniques for tracking hyperglycaemia-induced Intracerebral Hemorrhage (ICH) and Blood Brain Barrier (BBB) hyperpermeability in Cerebral Cavernous Malformation (CCM) deficient mice (CCM1+/-). We synthesised PEGylated Ag₂S quantum dots (QDs) with a bright fluorescent emission peak centred at 1135 nm under an 808 nm NIR light for dynamic imaging of cerebral vasculature in mice and determined the development of ICH and BBB impairment in hyperglycaemic CCM1+/- mice. In vivo optical imaging was conducted with micro-CT (including k-mean cluster analysis) as well as in vivo permeability assays using FITC-dextran perfusion and IgG staining, respectively. The increased BBB permeability in CCM1+/- mice was further demonstrated to be associated with a high-glucose-caused decrease of CCM1 expressions. This study validates that deep-penetrating NIR-II QDs can be used for the tracking of ICH and BBB hyperpermeability in transgenic mice models of cerebral vascular anomalies.

SUBMITTER: Parchur AK

PROVIDER: S-EPMC9272591 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:RATIONALE:The clinical course of cerebral cavernous malformations is highly unpredictable, with few cross-sectional studies correlating proinflammatory genotypes and plasma biomarkers with prior disease severity. OBJECTIVE:We hypothesize that a panel of 24 candidate plasma biomarkers, with a reported role in the physiopathology of cerebral cavernous malformations, may predict subsequent clinically relevant disease activity. METHODS AND RESULTS:Plasma biomarkers were assessed in nonfasting peripheral venous blood collected from consecutive cerebral cavernous malformation subjects followed for 1 year after initial sample collection. A first cohort (N=49) was used to define the best model of biomarker level combinations to predict a subsequent symptomatic lesional hemorrhagic expansion within a year after the blood sample. We generated the receiver operating characteristic curves and area under the curve for each biomarker individually and each weighted linear combination of relevant biomarkers. The best model to predict lesional activity was selected as that minimizing the Akaike information criterion. In this cohort, 11 subjects experienced symptomatic lesional hemorrhagic expansion (5 bleeds and 10 lesional growths) within a year after the blood draw. Subjects had lower soluble CD14 (cluster of differentiation 14; P=0.05), IL (interleukin)-6 (P=0.04), and VEGF (vascular endothelial growth factor; P=0.0003) levels along with higher plasma levels of IL-1? (P=0.008) and soluble ROBO4 (roundabout guidance receptor 4; P=0.03). Among the 31 weighted linear combinations of these 5 biomarkers, the best model (with the lowest Akaike information criterion value, 25.3) was the weighted linear combination including soluble CD14, IL-1?, VEGF, and soluble ROBO4, predicting a symptomatic hemorrhagic expansion with a sensitivity of 86% and specificity of 88% (area under the curve, 0.90; P<0.0001). We then validated our best model in the second sequential independent cohort (N=28). CONCLUSIONS:This is the first study reporting a predictive association between plasma biomarkers and subsequent cerebral cavernous malformation disease clinical activity. This may be applied in clinical prognostication and stratification of cases in clinical trials.

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NIR-II window tracking of hyperglycemia induced intracerebral hemorrhage in cerebral cavernous malformation deficient mice.

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