scholarly journals Magnetic Particle Imaging for Highly Sensitive, Quantitative, and Safein VivoGut Bleed Detection in a Murine Model

ACS Nano ◽  
2017 ◽  
Vol 11 (12) ◽  
pp. 12067-12076 ◽  
Author(s):  
Elaine Y. Yu ◽  
Prashant Chandrasekharan ◽  
Ran Berzon ◽  
Zhi Wei Tay ◽  
Xinyi Y. Zhou ◽  
...  
Keyword(s):  
Murine Model ◽  
Magnetic Particle ◽  
Magnetic Particle Imaging ◽  
Highly Sensitive ◽  
Particle Imaging

scholarly journals Ex vivo magnetic particle imaging of vascular inflammation in abdominal aortic aneurysm in a murine model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Dilyana B. Mangarova ◽  
Julia Brangsch ◽  
Azadeh Mohtashamdolatshahi ◽  
Olaf Kosch ◽  
Hendrik Paysen ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Murine Model ◽  
Magnetic Particle ◽  
Ex Vivo ◽  
Vascular Inflammation ◽  
Magnetic Particle Imaging ◽  
Abdominal Aortic ◽  
Particle Imaging

scholarly journals Highly sensitive magnetic particle imaging of vulnerable atherosclerotic plaque with active myeloperoxidase-targeted nanoparticles

Theranostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 506-521
Author(s):  
Wei Tong ◽  
Hui Hui ◽  
Wenting Shang ◽  
Yingqian Zhang ◽  
Feng Tian ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Magnetic Particle ◽  
Vulnerable Atherosclerotic Plaque ◽  
Targeted Nanoparticles ◽  
Magnetic Particle Imaging ◽  
Highly Sensitive ◽  
Particle Imaging

Darstellung von Instrumenten zur Magnetic Particle Imaging (MPI) gesteuerten kardiovaskulären Intervention

2012 ◽  
Vol 184 (02) ◽  
Author(s):  
J Haegele ◽  
J Rahmer ◽  
B Gleich ◽  
C Bontus ◽  
J Borgert ◽  
...  
Keyword(s):  
Magnetic Particle ◽  
Magnetic Particle Imaging ◽  
Particle Imaging

Reduzierung von Artefakten für Stammzellmonitoring in Magnetic Particle Imaging

2016 ◽  
Vol 188 (S 01) ◽  
Author(s):  
K Them ◽  
J Salamon ◽  
M Kaul ◽  
C Lange ◽  
H Ittrich ◽  
...  
Keyword(s):  
Magnetic Particle ◽  
Magnetic Particle Imaging ◽  
Particle Imaging

Magnetic Particle Imaging: Dynamische Darstellung einer Ballondilatation im Gefäßmodell in Echtzeit

2017 ◽  
Vol 189 (S 01) ◽  
pp. S1-S124
Author(s):  
S Herz ◽  
P Vogel ◽  
D Philipp ◽  
T Kampf ◽  
J Kunz ◽  
...  
Keyword(s):  
Magnetic Particle ◽  
Magnetic Particle Imaging ◽  
Particle Imaging

Magnetic Particle Imaging – Visuelle Stenosequantifizierung am Phantom-Model

2019 ◽  
Author(s):  
P Dietrich ◽  
P Vogel ◽  
M Rückert ◽  
T Bley ◽  
S Herz
Keyword(s):  
Magnetic Particle ◽  
Phantom Model ◽  
Magnetic Particle Imaging ◽  
Particle Imaging

scholarly journals Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dennis Pantke ◽  
Florian Mueller ◽  
Sebastian Reinartz ◽  
Fabian Kiessling ◽  
Volkmar Schulz
Keyword(s):  
Flow Velocity ◽  
Magnetic Particle ◽  
Imaging Techniques ◽  
Radiation Risk ◽  
Medical Application ◽  
Velocity Estimation ◽  
Magnetic Particle Imaging ◽  
Measurable Velocity ◽  
Depth Dependency ◽  
Particle Imaging

AbstractChanges in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.

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