Dr.-Ing. Konrad Scheffler

Portrait of Konrad Scheffler

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 213
22529 Hamburg
- Postanschrift -

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

Tel.: 040 / 7410 25813
E-Mail: konrad.scheffler(at)tuhh.de
E-Mail: ko.scheffler(at)uke.de

Research Interests

  • Magnetic Particle Imaging
  • Image Reconstruction
  • Image Processing

Curriculum Vitae

Konrad Scheffler studied Technomathematics between 2015 and 2021 in Hamburg and graduated with a master's degree thesis on "Enhancing matrix compression using convoluted tensor products of Chebyshev polynomials". He joined the group of Tobias Knopp for Biomedical Imaging at the University Medical Center Hamburg-Eppendorf (UKE) and the Hamburg University of Technology in 2021 as a PhD student and finished his PhD in 2025 on the topic "On Algorithmical Methods Facilitating Clinical Translation of Magnetic Particle Imaging".

Journal Publications

[164760]
Title: MPI tracer interactions and their effect on signal stability.
Written by: L. Moor, S. Scheibler, L. Gerken, K. Scheffler, F. Thieben, T. Knopp, I. Herrmann, and F. Starsich
in: <em>International Journal on Magnetic Particle Imaging</em>. (2022).
Volume: <strong>8</strong>. Number: (1),
on pages: 1-3
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DOI: 10.18416/IJMPI.2022.2203056
URL: https://doi.org/10.18416/IJMPI.2022.2203056
ARXIVID:
PMID:

[www]

Note: inproceedings

Abstract: Nanoparticles tend to agglomerate following their in vivo or in vitro application. This leads to particle interaction and, for magnetic particle imaging (MPI) tracers, to magnetic coupling phenomena. Here, we investigate these effects and their influence on magnetic particle spectroscopy (MPS) and MPI signal stability. Highly magnetic flame-made Zn-ferrites with controlled interparticle distance are suggested as a stable MPI tracer system. Due to their pre-aggregated morphology, additional agglomeration does not substantially alter their magnetic response. This is in strong contrast to frequently investigated polymer-coated iron oxide nanoparticles, which show a massive MPS signal loss in a biologically relevant dispersion medium compared to water. This effect is also shown during MPI and renders these tracers inapplicable to further applications. Our flame-made Zn-ferrites, on the other hand, show sufficient signal stability, which allows their detailed quantification via MPI.

Conference Publications

[164760]
Title: MPI tracer interactions and their effect on signal stability.
Written by: L. Moor, S. Scheibler, L. Gerken, K. Scheffler, F. Thieben, T. Knopp, I. Herrmann, and F. Starsich
in: <em>International Journal on Magnetic Particle Imaging</em>. (2022).
Volume: <strong>8</strong>. Number: (1),
on pages: 1-3
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.18416/IJMPI.2022.2203056
URL: https://doi.org/10.18416/IJMPI.2022.2203056
ARXIVID:
PMID:

[www]

Note: inproceedings

Abstract: Nanoparticles tend to agglomerate following their in vivo or in vitro application. This leads to particle interaction and, for magnetic particle imaging (MPI) tracers, to magnetic coupling phenomena. Here, we investigate these effects and their influence on magnetic particle spectroscopy (MPS) and MPI signal stability. Highly magnetic flame-made Zn-ferrites with controlled interparticle distance are suggested as a stable MPI tracer system. Due to their pre-aggregated morphology, additional agglomeration does not substantially alter their magnetic response. This is in strong contrast to frequently investigated polymer-coated iron oxide nanoparticles, which show a massive MPS signal loss in a biologically relevant dispersion medium compared to water. This effect is also shown during MPI and renders these tracers inapplicable to further applications. Our flame-made Zn-ferrites, on the other hand, show sufficient signal stability, which allows their detailed quantification via MPI.