ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore

Scientific Session: Characterizing Field Environment in the MR Scanner: B0, B1 & Gradients

Thursday, May 12, 2016
Room 331-332
13:30 - 15:30
Moderators: Priti Balchandani, Qi Duan

  13:30
0930.   
B0-Atlas with Field-Probe Guidance: Application in Real-Time Field Control
Simon Gross1, Yolanda Duerst1, Laetitia Maëlle Vionnet1, Christoph Barmet1,2, and Klaas Paul Pruessmann1
1Institute for Biomedical Engineering, ETH and University of Zurich, Zurich, Switzerland, 2Skope Magnetic Resonance Inc., Zurich, Switzerland
A novel model for the prediction of B0-maps from external field measurements is presented. It is based on the joint analysis of training data from simultaneously acquired B0-maps and magnetic field evolution measured with NMR field probes. A first application to real-time shim feedback is demonstrated. 

 
  13:42
 
0931.   
Model-based rapid field map prediction for dynamic shimming applications
Yuhang Shi1, Johanna Vannesjo1, Karla L. Miller1, and Stuart Clare1
1Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
This work presents a rapid field map prediction method based on the individual subject's quick localizer scan and a large brain field map database to accelerate the field map acquisition stage for dynamic shimming applications. Our model-based method is able to better identify the steep change in the field associated with some slices in the lower part of the brain, however a low-resolution field map performs better for the rest of the brain.

 
  13:54
 
0932.   
Fast B0 first order inhomogeneity estimation using radial acquisition
Ali Aghaeifar1,2, Alexander Loktyushin1, Christian Mirkes1,3, Axel Thielscher1, and Klaus Scheffler1,3
1Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2IMPRS for Cognitive and Systems Neuroscience, Tübingen, Germany, 3Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
B0 field inhomogeneity is a major source of distortion in MR images. Current approaches to dynamic shimming require extra acquisition time or external hardware. We propose a method that estimates first order shim errors by using projections of radial acquisition. The errors can be estimated from three projections multiple times in each measurement, which makes the method highly robust. The proposed method is evaluated in simulation and in vivo. Obtained results show a strong agreement between applied and measured first order shim errors.

 
  14:06
 
0933.   
BMART: B0 Mapping using Rewind Trajectories
Corey Allan Baron1 and Dwight G. Nishimura1
1Electrical Engineering, Stanford University, Stanford, CA, United States
B0 inhomogeneity leads to image artifacts and/or blurring. These issues can be addressed by using a B0 map, which typically requires an extra scan. In addition to the longer total scan time required, motion occurring between the acquisition of the imaging data and B0 map can lead to misregistration. The proposed method utilizes images reconstructed from rewind trajectories to construct a B0 map. In pulse sequences that already use gradient rewinds (e.g., bSSFP), a B0 map that is inherently registered to the imaging data can be created with no additional scan time.

 
  14:18
 
0934.   
Broadband Frequency Mapping with Balanced SSFP
Oliver Bieri1,2, Grzegorz Bauman1,2, and Carl Ganter3
1Radiology, University Hospital Basel, Basel, Switzerland, 2Biomedical Engineering, University of Basel, Basel, Switzerland, 3Diagnostic Radiology, Technical University Munich, Munich, Germany
A new method for accurate and fast broadband frequency mapping with balanced steady state free precession is introduced. The method mitigates the need for advanced phase unwrapping algorithms from a matrix pencil analysis of sequentially shifted echo times. Typically, the new method offers a spectral resolution in the range of Hertz with a sensitivity range in the order of several thousands of Hertz.

 
  14:30
 
0935.   
Determination of Relative B1+ Sensitivities Using Accelerated Simultaneous Excitation with Multiple Transmit Channels and Controlled Aliasing
Iulius Dragonu1, Craig Buckley1, Peter Weale1, Matthew D Robson2, and Aaron T Hess2
1Siemens Healthcare Ltd, Frimley, Camberley, United Kingdom, 2University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), John Radcliffe Hospital, Headington, United Kingdom
Radiofrequency shimming with multiple channel excitation is a well established method to increase the transverse magnetic field homogeneity and reduce SAR at high magnetic field strength(≥7T). To harness the benefits of a parallel transmit system, the magnitude and relative phase of each transmit channel must be determined during a calibration scan. We propose a new strategy to accelerate the acquisition of such calibration images by simultaneously exciting several transmit channels and reconstructing the calibration images using the technique similar to simultaneous multi-slice acquisitions.

 
  14:42
 
0936.   
Combining B1 mapping with TIAMO for fast and accurate multi-channel RF shimming in 7 Tesla body MRI
Sascha Brunheim1,2, Stephan Orzada1, Soeren Johst1, Marcel Gratz1,2, Maximilian N. Voelker1, Oliver Kraff1, Martina Floeser3, Andreas K. Bitz3, Mark E. Ladd1,3, and Harald H. Quick1,2
1Erwin L. Hahn Institute for Magentic Resonance Imaging, University Duisburg-Essen, Essen, Germany, 2High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany, 3Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
With current methods the mitigation of transmit field inhomogeneity at ultrahigh field by multi-channel RF shimming with conventional methods is relatively time consuming. This applies in particular for parallel transmit/receive in-vivo body imaging within breath-hold and during organ motion. Therefore, we propose a new technique merging fast acquired relative single channel maps and the spatial-dependent flip-angle distribution of two complementary shims to define absolute transmit coil maps for fast and accurate RF shim calculation. The performance of this technique is validated against established methods in phantom measurements and its reliability is shown in comparison to simulation data serving as reference.

 
  14:54
 
0937.   
Silent, Free-Breathing B1+ Mapping using DREAM
Kay Nehrke1 and Peter Börnert1,2
1Philips Research, Hamburg, Germany, 2Radiology, LUMC, Leiden, Netherlands
To improve the workflow for B1+ calibration on a dual transmit MRI system, the DREAM B1+ mapping sequence has been streamlined for acoustic noise reduction and free-breathing acquisition using a standard external respiratory motion sensor. About 10 dB reduction in sound pressure level were achieved by optimizing the echo order with respect to gradient strength reduction. Feasibility was shown in volunteer experiments on abdominal  B1+ mapping.

 
  15:06
 
0938.   
DREAM Based Receive Sensitivity Correction
Wyger Brink1 and Andrew Webb1
1Radiology, Leiden University Medical Center, Leiden, Netherlands
Imaging methods at high fields can suffer from receive non-uniformities from the body coil, particularly when the body coil is used as a reference for intensity correction. In this work we show that the DREAM B1 mapping sequence can be used for receive uniformity correction in RF-shimmed whole-body imaging at 3T.

 
  15:18
 
0939.   
Simultaneous Estimation of Auto-calibration Data and Gradient Delays in non-Cartesian Parallel MRI using Low-rank Constraints
Wenwen Jiang1, Peder E.Z Larson2, and Michael Lustig3
1Bioengineering, UC Berkeley/ UCSF, Berkeley, CA, United States, 2Radiology and Biomedical Imaging, UCSF, San francisco, CA, United States, 3Electrical Engineering and Computer Science, UC Berkeley, Berkeley, CA, United States
Gradient timing delay errors in non-Cartesian trajectories often induce spurious image artifacts. More importantly, misaligned k-space center data results in auto-calibration errors for parallel imaging methods. We propose a general approach that simultaneously estimates consistent calibration data and corrects for gradient delays. We pose the joint estimation problem as a low-rank minimization problem, and solve it using a Gauss-Newton method. We demonstrate the feasibility of the proposed method by simulation and phantom experiments.
 

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