Dr.-Ing. Matthias Gräser

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 212
22529 Hamburg

Technische Universität Hamburg (TUHH)
Institut für Biomedizinische Bildgebung
Gebäude E, Raum 4.044
Am Schwarzenberg-Campus 3
21073 Hamburg

Tel.: 040 / 7410 25812
E-Mail: matthias.graeser(at)tuhh.de
E-Mail: ma.graeser(at)uke.de

Research Interests

  • Magnetic Particle Imaging
  • Low Noise Electronics
  • Inductive Sensors
  • Passive Electrical Devices

Curriculum Vitae

Matthias Gräser submitted his Dr.-Ing. thesis in january 2016 at the institute of medical engineering (IMT) at the university of Lübeck and is now working as a Research Scientist at the institute for biomedical imaging (IBI) at the technical university in Hamburg, Germany.  Here he develops concepts for Magnetic-Particle-Imaging (MPI) devices. His main aim is to improve the sensitivity of the imageing devices and improve resolution and application possibilities of MPI technology.

In 2011 Matthias Gräser started to work at the IMT as a Research Associate in the Magnetic Particle Imaging Technology (MAPIT) project. In this project he devolped the analog signal chains for a rabbit sized field free line imager. Additionally he developed a two-dimensional Magnetic-Particle-Spectrometer. This device can apply various field sequences and measure the particle response with a very high signal-to-noise ratio (SNR).

The dynamic behaviour of magnetic nanoparticles is still not fully understood. Matthias Gräser investigated the particle behaviour by modeling the particle behaviour with stochastic differential equations. With this model it is possible to simulate the impact of several particle parameters and field sequences on the particle response .

In 2010 Matthias Gräser finished his diploma at the Karlsruhe Institue of Technology (KIT). His diploma thesis investigated the nerve stimulation of magnetic fields in the range from 4 kHz to 25 kHz.

Journal Publications

[140971]
Title: Monitoring Intracranial Cerebral Hemorrhage Using Multicontrast Real-Time Magnetic Particle Imaging.
Written by: P. Szwargulski, M. Wilmes, E. Javidi, F. Thieben, M. Graeser, M. Koch, C. Gruettner, G. Adam, C. Gerhard, T. Magnus, T. Knopp, and P. Ludewig
in: <em>ACS Nano</em>. -- (2020).
Volume: <strong>14</strong>. Number: (10),
on pages: 13913-13923
Chapter:
Editor:
Publisher: Future Medicine Ltd:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1021/acsnano.0c06326
URL: https://doi.org/10.1021/acsnano.0c06326
ARXIVID:
PMID: 32941000

[www] [BibTex] [pmid]

Note: article, PMID: 32941000, openaccess

Abstract: 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.

Conference Proceedings

[140971]
Title: Monitoring Intracranial Cerebral Hemorrhage Using Multicontrast Real-Time Magnetic Particle Imaging.
Written by: P. Szwargulski, M. Wilmes, E. Javidi, F. Thieben, M. Graeser, M. Koch, C. Gruettner, G. Adam, C. Gerhard, T. Magnus, T. Knopp, and P. Ludewig
in: <em>ACS Nano</em>. -- (2020).
Volume: <strong>14</strong>. Number: (10),
on pages: 13913-13923
Chapter:
Editor:
Publisher: Future Medicine Ltd:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1021/acsnano.0c06326
URL: https://doi.org/10.1021/acsnano.0c06326
ARXIVID:
PMID: 32941000

[www] [BibTex] [pmid]

Note: article, PMID: 32941000, openaccess

Abstract: 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.