TRADITIONAL POSTER - ismrm

Poster Sessions
2926. Robust Field Map Estimation Using Both Global and Local Minimia
Hojin Kim 1,2 , Kyung Sung 1 , Brian Andrew Hargreaves 1
1 Department of Radiology, Stanford University, Stanford, CA, United States; 2 Electrical Engineering, Stanford University, Stanford,
CA, United States
In the least-squares fat/water separation techniques, the residual or cost runction that is minimized contains exactly one or two local minimum, depending on
the relative amount of fat and water, and water-fat phase difference. Separation algorithms attempt to find which minimum provides true field-map, but may
converge to the incorrect local minimum. Based on this principle, this work proposes a robust field-map estimation technique by tracking two minima at
each pixel through region growing process and suggesting more secure way of determining an initial seed for region growing.
2927. Optimization of Flip Angle to Allow Tradeoffs in T1 Bias and SNR Performance for Fat Quantification
Catherine D. G. Hines 1 , Takeshi Yokoo 2 , Mark Bydder 2 , Claude B. Sirlin 2 , Scott B. Reeder 1,3
1 Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States; 2 Radiology, University of California-San
Diego, San Diego, CA, United States; 3 Radiology, University of Wisconsin-Madison, Madison, WI, United States
Chemical shift based water-fat separation methods used to quantify fat in tissue are usually based on rapid 2D or 3D spoiled gradient echo methods. In order
to avoid bias from differences in T1 between water and fat, a low flip angle is typically used to minimize this source bias. Reducing the flip angle reduces
SNR performance, however. In this work, we present an algorithm to maximize the flip angle (to maximize SNR) while maintaining a user-defined
allowable error in fat-fraction from T1 related bias. Experimental validation is also shown.
2928. Volumetric Adiposity Imaging Over the Entire Abdomen and Pelvis in a Single Breath-Hold Using
IDEAL at 3.0T
Aziz Hatim Poonawalla 1 , Ann Shimakawa 2 , Huanzhou Yu 2 , Charles McKenzie 3 , Jean Brittain 2 , Scott
Reeder 1,4
1 Radiology, University of Wisconsin, Madison, WI, United States; 2 GE Healthcare, Waukesha, WI, United States; 3 Medical
Biophysics, University of Western Ontario, London, Ontario, Canada; 4 Medical Physics, University of Wisconsin, Madison, WI,
United States
We have demonstrated the capability to acquire high-spatial resolution 3D volumetric images of the entire abdomen and pelvis, using a highly-accelerated
chemical-shift-based water-fat separation technique and a 32-channel coil at 3.0T. The high-quality fat and fat-fraction images obtained by this technique
provide unprecedented visualization and delineation of the adipose depot boundaries, with sufficient spatial resolution to allow 3D reformatting for optimal
segmentation. This new technique will greatly facilitate rapid quantitative assessment of visceral adipose tissue volume, VAT/SCAT ratio, and total adipose
volume within a single-breath-hold acquisition without the need for ionizing radiation.
2929. Preliminary Results of IDEAL Fat/water Separation at 9.4T
Sébastien Bär 1 , Wilfried Reichardt 1 , Jochen Leupold 1
1 Dept. of Diagnostic Radiology, Medical Physics, University Hospital Freiburg, Freiburg, Germany
IDEAL has emerged as a promising mehtod for rapid fat/water separation. Here we present our first results on the feasibilty of this method on ex-vivo rat
images at 9.4T.
Dynamic MR, Superresolution, Off-Resonance & Tissue Orientation
Hall B Thursday 13:30-15:30
2930. System Dynamics Estimation for Kalman Filtering with Radial Acquisition
Mahdi Salmani Rahimi 1 , Steve R. Kecskemeti 2 , Walter F. Block 1,3 , Orhan Unal 3
1 Biomedical Engineering, University of Wisconsin, Madison, WI, United States; 2 Physics, University of Wisconsin, Madison, WI,
United States; 3 Medical Physics, University of Wisconsin, Madison, WI, United States
A novel method has been proposed to use adaptive Kalman filtering and causal DCF based tornado filtering together to reconstruct undersampled MR
images for dynamic and time resolved applications. Existing Kalman method uses an initialization scan or a sliding window to estimate system dynamics. In
this work, we used tornado filter to infer motion maps for the Kalman process. This helps us to have a better estimation of image changes at every time
frame and therefore a more accurate reconstruction. Simulations have been done on a cardiac phantom using radial projections and results were compared to
existing techniques.
2931. Deterministic Comparisons of Nonlinear Acceleration Methods Using a Realistic Digital Phantom
Leah Christine Henze 1 , Catherine J. Moran 2 , Matthew R. Smith 2 , Frederick Kelcz 3 , Dan Xu 4 , Kevin F.
King 4 , Alexey Samsonov 3 , Walter F. Block, 12
1 Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States; 2 Department of Medical
Physics, University of Wisconsin-Madison, Madison, WI, United States; 3 Department of Radiology, University of Wisconsin-
Madison, Madison, WI, United States; 4 Global Applied Science Lab, General Electric Healthcare, Milwaukee, WI, United States
Several different accelerated imaging methods exist that can improve the acquisition of dynamic data. Clinical adoption of many of these methods has been
slow, partially due to the difficulty in conclusively proving the extent to which a specific method provides additional diagnostic information that would not
otherwise have been available. We have created a realistic digital phantom from which k-space data for a DCE exam can be simulated and reconstructed by
both Cartesian and non Cartesian acceleration methods. We use the phantom to quantitatively analyze and compare the performance of multiple accelerated
imaging methods.