Multi-targeted 1H/19F MRI unmasks specific danger patterns for emerging cardiovascular disorders

Ulrich Flögel (), Sebastian Temme, Christoph Jacoby, Thomas Oerther, Petra Keul, Vera Flocke, Xiaowei Wang, Florian Bönner, Fabian Nienhaus, Karlheinz Peter, Jürgen Schrader, Maria Grandoch, Malte Kelm and Bodo Levkau
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Ulrich Flögel: Heinrich Heine University
Sebastian Temme: Heinrich Heine University
Christoph Jacoby: Heinrich Heine University
Thomas Oerther: Bruker BioSpin
Petra Keul: Heinrich Heine University
Vera Flocke: Heinrich Heine University
Xiaowei Wang: Baker Heart and Diabetes Institute
Florian Bönner: University Hospital Düsseldorf
Fabian Nienhaus: University Hospital Düsseldorf
Karlheinz Peter: Baker Heart and Diabetes Institute
Jürgen Schrader: Heinrich Heine University
Maria Grandoch: Heinrich Heine University
Malte Kelm: Heinrich Heine University
Bodo Levkau: Heinrich Heine University

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: Abstract Prediction of the transition from stable to acute coronary syndromes driven by vascular inflammation, thrombosis with subsequent microembolization, and vessel occlusion leading to irreversible myocardial damage is still an unsolved problem. Here, we introduce a multi-targeted and multi-color nanotracer platform technology that simultaneously visualizes evolving danger patterns in the development of progressive coronary inflammation and atherothrombosis prior to spontaneous myocardial infarction in mice. Individual ligand-equipped perfluorocarbon nanoemulsions are used as targeting agents and are differentiated by their specific spectral signatures via implementation of multi chemical shift selective 19F MRI. Thereby, we are able to identify areas at high risk of and predictive for consecutive development of myocardial infarction, at a time when no conventional parameter indicates any imminent danger. The principle of this multi-targeted approach can easily be adapted to monitor also a variety of other disease entities and constitutes a technology with disease-predictive potential.

Date: 2021
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DOI: 10.1038/s41467-021-26146-6

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