Susceptibility mapping as a means to visualize veins and quantify oxygen saturation.
OBJECTIVE
To create an orientation-independent, 3D reconstruction of the veins in the brain using susceptibility mapping.


METHODS
High-resolution, high-pass filtered phase images usually used for susceptibility weighted imaging (SWI) were used as a source for local magnetic field behavior. These images were subsequently postprocessed using an inverse procedure to generate susceptibility maps of the veins. Regularization and interpolation of the data in k-space of the phase images were used to reduce reconstruction artifacts. To understand the effects of artifacts, and to fine-tune the methodology, simulations of blood vessels were performed with and without noise.


RESULTS
With sufficient resolution, major veins in the brain could be visualized with this approach. The usual geometry-dependent phase dipole effects are removed by this processing, leaving basically images of the veins. Different sized vessels show a different level of contrast depending on their partial volume effects. Vessels that are 8 mm or 16 mm in size show quantitative values expected for normal oxygen saturation levels. Smaller vessels show smaller values due to errors in the methodology and due to partial volume effects. Larger vessels show a bias toward a reduced susceptibility approaching 90% of the expected value. Limitations of the method and artifacts related to different sources of errors are demonstrated.


CONCLUSIONS
Susceptibility maps can successfully create venograms of the brain with varying levels of contrast-to-noise depending on the size of the vessel. Partial volume effects render this approach more useful as an imaging tool or a visualization tool, although certain larger vessels have measured susceptibilities close to expected values associated with normal blood oxygen saturation levels.
Haacke
E M
EM
Department of Radiology, Wayne State University, Detroit, Michigan 48201, USA. nmrimaging@aol.com
Tang
J
J
Neelavalli
J
J
Cheng
Y C N
YC
D000465:Algorithms; D001921:Brain / Q000098:blood supply*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008962:Models, Theoretical; D010092:Oximetry; D010101:Oxygen Consumption / Q000502:physiology; D014680:Veins / Q000502:physiology*
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