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Abstract #4914

Manifold-based Respiratory Phase Estimation Enables Motion and Distortion Correction of Free-Breathing Cardiac Diffusion Tensor MRI

Jaume Coll-Font1,2,3, Shi Chen1, Robert Eder1, Yilin Fan4, Qiao Joyce Han1, Maaike van den Boomen1,2,3, David Sosnovik1,2,3, Choukri Mekkaoui2,3, and Christopher T. Nguyen1,2,3
1Cardiology, Massachusetts General Hospital, Charlestown, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 4Massachusetts Insitute of Technology, Cambridge, MA, United States

Synopsis

For in-vivo cardiac diffusion-tensor MRI (DT-MRI), respiratory motion and B0 field inhomogeneities produce misalignment and geometric distortion in diffusion weighted images acquired with conventional single shot echo planar imaging. We propose using Laplacian Eigenmaps (LE), a dimensionality reduction method, to retrospectively estimate the respiratory phase of DWI and facilitate both distortion correction (DisCo) and motion compensation (MoCo). LE-based DisCo and MoCo reduces geometric distortion by 13.2% while producing computationally efficient image alignment. Furthermore, preliminary results indicate the LE-based DisCo and MoCo can be applied with only acquiring a single set of b-value averages.

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Keywords