Deconvolution of Signal Decay and Recovery of T2* Information

In magnetic resonance imaging (MRI), an accurate knowledge of the effective transverse relaxation time (T2*) is required for a multitude of applications, such as BOLD-effect imaging in functional MRI, susceptibility weighted imaging (SWI) and mapping of proton density, to name only a few. The precise determination of the T2* values of tissue is, however, often hampered by the presence of macroscopic and mesoscopic inhomogeneities of the static field B0. These can be caused, for example, by imperfect shimming or susceptibility changes at tissue-air and tissue-bone interfaces. Although there are several methods to compensate for these disturbances while scanning, they demand either additional measurement time or non-standard hardware. An efficient correction of field inhomogeneity effects by post-processing is more advantageous.

A voxel-by-voxel correction of the effect of field inhomogeneities thus needs to be performed. The conventionally used model - signal decaying exponentially with the echo time - loses its validity in the presence of intra-voxel field gradients. The deviations are particularly large when using ultra high magnetic fields (4T, 7T or 9.4T).

The main aim of this project is to find valid methods for correcting the field inhomogeneity effects and gaining information about the tissue T2*. This is done by applying innovative methods in post-processing and developing more complex models for describing the signal behaviour with time.

Deconvolution of Signal Decay and Recovery of T2* Information


The image shows a typical signal decay from a voxel with strong field inhomogeneities. The signal behaves non-exponentially with time due to the large susceptibility changes in the environment of the selected voxel. This leads to corrupted T2*- and zero-time magnetization (M0) values in the case of a simple, mono-exponential decay fit (blue, dashed line), whereas a more complex model accurately describes the signal decay and delivers quantitative tissue parameters

Last Modified: 04.08.2022