Dana RamadanMaster Student
The use of fMRI has provided a vast understanding of the outer big brain vessels. The comparatively unexplored microvessels are relevant to fully understand brain activation and can be measured by using higher field strengths (≥ 7 T). At these field strengths the sensitivity increases and with it the necessity to optimize the cortex alignment. The aim of this project under the supervision of Jonas Bause is to compare two fMRI sequences at 9.4 T to further understand the origin of the signal and its dependence on the orientation of the cortex.
Functional magnetic resonance imaging (fMRI), though widely applied, requires a better understanding of the origin of its underlying blood oxygenation level dependent (BOLD) signal. The partially unknown contribution of many factors to the BOLD effect makes it difficult to attribute it entirely to brain activity. To increase spatial specificity of the BOLD signal, high and ultra-high field (UHF) strengths are used. At UHF the signal-to-noise ratio (SNR), the resolution and thus the heterogeneity of voxels containing blood, tissue or cerebrospinal fluid (CSF) are enhanced.
As expected from simulations, experiments have shown a dependence of gradient echo (GE) echo planar imaging (EPI) signal fluctuation on the vein orientation and thus cortical orientation to B0, due to the distinct geometry of the vessels to the cortical architecture. While this effect is observed with EPI, Monte Carlo simulations of the mouse parietal cortex predict that the balanced steady state free precession (bSSFP) signal fluctuation shows a different dependence on cortical orientation to B0, which might be evidence of the smaller contribution of the large surface vessels on the bSSFP signal and thus its sensitivity to smaller vessels.
In my work, a pipeline is created to compare segmented 3D GE-EPI and bSSFP in their resting state BOLD signal dependence on the cortical orientation. The signal dependence on the cortical orientation is further investigated in the different cortical depths, performing laminar analysis.
Master of Science, University of Tübingen (Sep 2018 – Mar 2022)
Major: Biomedical Technologies
Specialization: Bioimaging and Nanoanalytics and Biophysics
Master Thesis: Max Planck Institute for Biological Cybernetics, Department for High-Field Magnetic Resonance, Title: Dependence of EPI and bSSFP resting state fMRI signals on the cortical orientation relative to B0 at 9.4 Tesla
Bachelor of Science, University of Stuttgart and University of Tübingen (Mar 2019)
Major: Biomedical Engineering
Bachelor Thesis: Werner Siemens Imaging Center, Department for Preclinical Imaging at the University of Tübingen, Title: In vitro and in vivo glucose quantification using Magnetic Resonance Spectroscopy