Conference paper

About the performance of multi-dimensional radial self-navigation incorporating compressed sensing for free-breathing coronary MRI

Respiratory motion is a major challenge in cardiac magnetic resonance imaging (MRI) and contemporary state-of-the-art motion compensation strategies like diaphragmatic navigators still suffer from sub-optimal time efficiency. In response, k-space- based one-dimensional self-navigation techniques have recently been developed that extract respiratory-induced motion of the heart directly from the imaging data themselves for subsequent motion correction on a beat-to-beat basis [1]. This affords the advantage of 100% scan efficiency while meticulous plan scanning and navigator placement can be avoided. In the present study, this concept was advanced to the next level by implementing an image- based self-navigation technique that incorporates compressed sensing and allowing for multi- dimensional motion correction. The new approach was investigated using computer simulations of a moving heart phantom before it was implemented on a 3T human scanner. In 12 healthy adult human subjects, the performance of this methodology was then quantitatively ascertained in comparison to free-breathing coronary MRI, both with and without conventional respiratory navigators.

    Keywords: LTS2 ; CIBM-SPC ; LTS5


    • EPFL-CONF-174581

    Record created on 2012-01-31, modified on 2017-05-12

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