4.8 Article

Monitoring Intracranial Cerebral Hemorrhage Using Multicontrast Real-Time Magnetic Particle Imaging

期刊

ACS NANO
卷 14, 期 10, 页码 13913-13923

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.0c06326

关键词

magnetic particle imaging; intracranial hemorrhage; stroke imaging; nanoparticles; nanomedicine; cerebrovascular disease; animal models of human disease

资金

  1. Forschungszentrums Medizintechnik Hamburg (FMTHH) by the Hertie-Stiftung (Hertie Academy of Clinical Neuroscience)
  2. German Research Foundation (DFG) [GR 5287/2-1, KN 1108/7-1, DFG FOR 2879, LU 1924/1-1, MA 4375/6-1, SFB 1328]
  3. Hermann and Lily Schilling Stiftung
  4. BMBF of the EuroNanoMed III [13XP5060B]

向作者/读者索取更多资源

Magnetic particle imaging (MPI) is an innovative radiation-free tomographic imaging method providing excellent temporal resolution, contrast, sensitivity, and safety. Mobile human MPI prototypes suitable for continuous bedside monitoring of whole-brain perfusion have been developed. However, for the clinical translation of MPI, a crucial gap in knowledge still remains: while MPI can visualize the reduction in blood flow and tissue perfusion in cerebral ischemia, it is unclear whether MPI works in intracranial hemorrhage. Our objective was to investigate the capability of MPI to detect intracranial hemorrhage in a murine model. Intracranial hemorrhage was induced through the injection of collagenase into the striatum of C57BL/6 mice. After the intravenous infusion of a long-circulating MPI-tailored tracer consisting of superparamagnetic iron oxides, we detected the intracranial hemorrhage in less than 3 min and could monitor hematoma expansion in real time. Multicontrast MPI can distinguish tracers based on their physical characteristics, core size, temperature, and viscosity. By employing in vivo multicontrast MPI, we were able to differentiate areas of liquid and coagulated blood within the hematoma, which could provide valuable information in surgical decision making. Multicontrast MPI also enabled simultaneous imaging of hemorrhage and cerebral perfusion, which is essential in the care of critically ill patients with increased intracranial pressure. We conclude that MPI can be used for real-time diagnosis of intracranial hemorrhage. This work is an essential step toward achieving the clinical translation of MPI for point-of-care monitoring of different stroke subtypes.

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