Abstract #3271

Statistical paradigm for composite MR Angiography generated from multi-contrast MRI

Dahan Kim^1,2, Patrick Turski^2,3, Oliver Wieben^2,3,4, and Kevin M Johnson^2,3

¹Department of Physics, University of Wisconsin - Madison, Madison, WI, United States, ²Department of Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, ³Department of Radiology, University of Wisconsin - Madison, Madison, WI, United States, ⁴Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States

We present an innovative paradigm to overcome artifacts of individual MR angiography techniques by utilizing complimentary information existing across multi-contrast MR images. This technique applies Bayesian statistics to extract vessel likelihoods from each image type and generates a single ‘composite’ angiogram. Composite angiograms are computed utilizing black blood (BB), contrast enhanced MRA (CE-MRA), and phase contrast MRA (PC-MRA) images acquired in subjects with known neurovascular disease. The composite angiogram is demonstrated to improve vessel lumen depiction overcoming artifacts in individual source images from background enhancement, air cavities, and flow in CE-MRA, BB, and PC-MRA, respectively.

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