EPI in the Brain: From DTI to fMRI
Lipeng Ning1
1Harvard Medical School, BWH, Boston, MA, United States

Synopsis

Keywords: Neuro: Brain Connectivity, Contrast mechanisms: Diffusion, Contrast mechanisms: fMRI

In this course, we first describe several echo planar imaging techniques, including parallel imaging and simultaneous multi-slice imaging. We then overview the physics and modeling techniques for diffusion MRI, including diffusion tensor imaging and advanced microstructural modeling techniques. Further, we will provide an overview of neural physiology related to functional MRI, data acquisition and modeling techniques.

Background

Echo planar imaging techniques have broad applications in probing brain networks to improve the characterization of diseases. Imaging acceleration techniques, such as parallel and simultaneous multislice imaging, have been developed to significantly reduce the scan time and make advanced imaging techniques feasible in clinical scanners. Diffusion MRI acquired using spin-echo echo-planar imaging is sensitive to the water diffusion in brain tissue, providing information about microscopic cellular organizations and white matter pathways. On the other hand, functional MRI is sensitive to blood oxygenation level-dependent (BOLD) signals that provide information to estimate functional connectivity and effective connectivity of brain networks.

Purpose

The purpose of this course is to present the data acquisition, processing, and analysis techniques for diffusion MRI and functional MRI. We will introduce diffusion tensor imaging (DTI) techniques for modeling diffusion MRI and advanced models for microstructure analysis. We will also introduce functional MRI processing and analysis techniques and applications in clinical research.

Outline

This course will cover:
A brief overview of spin echo and gradient echo EPI sequences;
A review of parallel imaging and simultaneous multislice imaging techniques;
Diffusion MRI sequence and physics;
Diffusion tensor imaging and advanced microstructure models;
Functional MRI, BOLD signal, and hemodynamics response function;
Functional connectivity and advanced brain network modeling techniques.

Acknowledgements

No acknowledgement found.

References

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Proc. Intl. Soc. Mag. Reson. Med. 32 (2024)