TRADITIONAL POSTER - ismrm

Poster Sessions
MRI of Conductivity
Hall B Thursday 13:30-15:30
2864. Propagating RF Phase: A New Contrast to Detect Local Changes in Conductivity
Astrid L.H.M.W. van Lier 1 , Alexander J. Raaijmakers 1 , David O. Brunner 2 , Dennis W.J. Klomp 3 , K. P.
Pruessmann 2 , Jan J.W. Lagendijk 1 , Cornelis A.T. van den Berg 1
1 Radiotherapy, UMC Utrecht, Utrecht, Netherlands; 2 Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland;
3 Radiology, UMC Utrecht, Utrecht, Netherlands
From basic EM (electromagnetic) theory we know that the wavelength, thus the propagating phase, depends on the permitivity and conductivity. Analysis,
based on simulations, showed that local changes in the conductivity, have the largest effect on the propagating phase in the physiological range. We
demonstrated that it is possible to measure the effect both in phantoms and in vivo, with results comparable to results of EM simulations. This new contrast
mechanism might be useful for the detection of conducting malignancies, such as breast tumours.
2865. In Vivo Quantitative Conductivity Imaging Based on B1 Phase Information
Tobias Voigt 1 , Ulrich Katscher 2 , Olaf Doessel 1
1 Institute of Biomedical Engineering, University of Karlsruhe, Karlsruhe, Germany; 2 Philips Research Europe, Hamburg, Germany
In this work, in vivo conductivity values of human tissue are obtained using standard MRI. Conductivity is a new and quantitative contrast for MRI. It can be
obtained in 3D within 5 min by means of phase-based reconstruction presented in this abstract. Phase-based reconstruction is motivated analytically and
validated in FDTD simulations and in in vivo experiments.
2866. Estimation of the Anisotropy of Electric Conductivity Via B1 Mapping
Ulrich Katscher 1 , Tobias Voigt 2 , Christian Findeklee 1
1 Philips Research Europe, Hamburg, Germany; 2 Institute of Biomedical Engineering, University of Karlsruhe, Karlsruhe, Germany
Electric conductivity might be used as diagnostic information due to its ability to reflect the grade of tissue damage. In general, the conductivity is given by a
tensor including anisotropic cases of conductivity, as can be found in vivo in tissue with preferred cell direction like muscles or nerves. Measuring
conductivity, characterizing the underlying cell structure, might increase diagnostic information. The recently presented “Electric Properties Tomography”
(EPT) is able to determine tissue conductivity in vivo by post-processing B1 maps. This study demonstrates the ability of EPT to estimate also the anisotropy
of the conductivity using an electrically anisotropic phantom.
Parallel Imaging
Hall B Monday 14:00-16:00
2867. Title: Reconstruction of Sparsely-Sampled Dynamic MRI Data Using Iterative “Error Energy” [1]
Reduction
Sumati Krishnan 1 , David Moratal 2 , Lei-Hou Hamilton 3 , Senthil Ramamurthy 4 , Marijn Eduard Brummer 4
1 Emory University, Atlanta, GA, United States; 2 2Universitat Politècnica de València, Valencia, Spain; 3 Georgia Institute of
Technology, Atlanta, GA, United States; 4 Emory University, Atlanta, GA, United States
A well-known reconstruction method, based on “error energy” reduction [1], is adapted to sparsely sampled dynamic cardiac MRI. Inherent temporally
band-limited properties of known static regions in the FOV, are used to recover additional resolution from information embedded in the acquired k-t
samples. The algorithm converges as the error due to residual dynamic content in the static region is minimized. Reconstructions equivalent to direct matrixinversion
[2] are achieved with significantly reduced computational costs, while convergence properties are related to the sampling patterns. The proposed
iterative method has potential applications for a variety of non-Cartesian grids as well as sparse-sampling patterns.
2868. Null Space Imaging: A Novel Gradient Encoding Strategy for Highly Efficient Parallel Imaging
Leo Tam 1 , Jason Peter Stockmann 1 , Robert Todd Constable, 12
1 Biomedical Engineering, Yale University, New Haven, CT, United States; 2 Diagnostic Radiology & Neurosurgery, Yale University,
New Haven, CT, United States
Null Space Imaging (NSI) defines nonlinear encoding gradients to complement the spatial localization abilities of a parallel receiver array. To complement
coil sensitivities, gradients should encode where coil sensitivities poorly distinguish signal. The singular value decomposition analyzes coil sensitivities to
generate a complete basis set of vectors spanning the null space of sensitivities. By interpreting the orthogonal vectors in the null space as a complementary
gradient set, NSI enables highly accelerated (R=16) parallel imaging as demonstrated by simulated spin echo experiments. NSI suggest complementary
gradient design is a powerful concept for parallel imaging requiring only a limited set of receivers.
2869. GPU Accelerated Iterative SENSE Reconstruction of Radial Phase Encoded Whole-Heart MRI
Thomas Sangild Sørensen 1 , Claudia Prieto 2 , David Atkinson 3 , Michael Schacht Hansen 4 , Tobias
Schaeffter 2
1 Aarhus Univeristy, Aarhus N, Denmark; 2 King's College London; 3 University College London; 4 National Institutes of Health
Isotropic whole-heart imaging has become an important protocol in simplifying cardiac MRI. The acquisition time can however be a prohibiting factor. To
reduce acquisition times a 3D scheme combining Cartesian sampling in the readout direction with radial sampling in the phase encoding plane was recently
suggested. It allows high undersampling factors in the phase encoding plane when obtaining data with a 32-channel coil array and employing non-Cartesian