Ximeng Zhang

Master's Student

Thesis Topic: Comparative Literature Review of DCE MRI Analysis Frameworks and Tracer Kinetic Modeling Approaches

Supervisors: Erik Gösche, Dr. Sebastian Bickelhaupt (UKER, medical supervisor), Prof Dr. Florian Knoll

Description

This master thesis focuses on a comparative literature review of dynamic contrast-enhanced MRI (DCE MRI) analysis frameworks and tracer kinetic modeling approaches. DCE MRI is a powerful tool for evaluating tissue perfusion and vascular permeability. The thesis analyses fundamental models like the Tofts/Kermode [1] and Sourbron/Buckley [2] frameworks to provide a solid theoretical foundation. It compares various analysis frameworks, such as ROCKETSHIP [3] and Firevoxel [4], along with different tracer kinetic models like the Patlak and Tofts models. Practical tasks include translating key functions from the ROCKETSHIP framework from MATLAB to Python to enhance practical skills. The thesis ultimately evaluates the strengths and limitations of current approaches, contributing to the development of future DCE MRI methods.

References

[1] Paul S. Tofts and Allan G. Kermode, “Measurement of the Blood-Brain Barrier Permeability and Leakage Space Using Dynamic MR Imaging. 1. Fundamental Concepts,” Magnetic Resonance in Medicine 17, no. 2 (1991): 357–67, https://doi.org/10.1002/mrm.1910170208.
[2] S. P. Sourbron and D. L. Buckley, “Tracer Kinetic Modelling in MRI: Estimating Perfusion and Capillary Permeability,” Physics in Medicine & Biology 57, no. 2 (December 2011): R1, https://doi.org/10.1088/0031-9155/57/2/R1.
[3] Samuel R. Barnes et al., “ROCKETSHIP: A Flexible and Modular Software Tool for the Planning, Processing and Analysis of Dynamic MRI Studies,” BMC Medical Imaging 15, no. 1 (June 16, 2015): 19, https://doi.org/10.1186/s12880-015-0062-3.
[4] Artem Mikheev and Henry Rusinek, “FireVoxel – Research Software for Medical Imaging,” accessed March 22, 2024, https://firevoxel.org/.
[5] C. S. Patlak, R. G. Blasberg, and J. D. Fenstermacher, “Graphical Evaluation of Blood-to-Brain Transfer Constants from Multiple-Time Uptake Data,” Journal of Cerebral Blood Flow and Metabolism: Official Journal of the International Society of Cerebral Blood Flow and Metabolism 3, no. 1 (March 1983): 1–7, https://doi.org/10.1038/jcbfm.1983.1.