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

Scientific Session: Fingerprinting

Tuesday, May 10, 2016
Summit 1
13:30 - 15:30
Moderators: Mariya Doneva, Ricardo Otazo

Pseudo Steady State Free Precession for MR-Fingerprinting
Jakob Assländer1, Steffen Glaser2, and Jürgen Hennig1
1Dept. of Radiology - Medical Physics, University Medical Center Freiburg, Freiburg, Germany, 2Dept. of Chemistry, Technische Universität München, Munich, Germany
This work discusses steady state issues in SSFP-based fingerprinting sequences. It is shown that variations of the flip angle destroy the steady state, causing instabilities with respect to intra-voxel dephasing. A pseudo steady state can be achieved by adapting TR and TE to a given flip angle pattern, restoring the typical SSFP behavior. Furthermore, an iterative reconstruction algorithm for fingerprinting data is proposed.

Towards Judging the Encoding Capability of Magnetic Resonance Fingerprinting Sequences
Karsten Sommer1, Thomas Amthor1, Peter Koken1, Mariya Doneva1, and Peter Börnert1
1Philips Research Europe, Hamburg, Germany
A key question of magnetic resonance fingerprinting (MRF) is the appropriate choice of sequence parameters to achieve a high sensitivity to the tissue parameters of interest. In this contribution, different candidates for a measure of MRF sequence encoding capability are evaluated. While interpretation of measures that rely on local or global dot products proved difficult, a ‘brute force’ Monte Carlo approach showed good agreement with experimental results. By restricting this Monte Carlo method to small local dictionaries, substantial acceleration could be achieved.

In Vivo Optimized Fast MR Fingerprinting in the Human Brain
Ouri Cohen1,2, Mathieu Sarracanie1,3, Matthew S. Rosen1,3, and Jerome L. Ackerman1,2
1Athinoula A. Martinos Center, Charlestown, MA, United States, 2Radiology, Massachusetts General Hospital, Boston, MA, United States, 3Physics, Harvard University, Cambridge, MA, United States
In this work we demonstrate an in vivo human brain application of a previously described schedule optimization method for rapid MR Fingerprinting. The method is validated in a phantom by comparison to a spin-echo sequence. The optimized schedule allowed acquisition of a single slice in 2.4 seconds without the use of any k-space undersampling. 

MR Fingerprinting with Chemical Exchange (MRF-X) for In Vivo Multi-Compartment Relaxation and Exchange Rate Mapping
Jesse Ian Hamilton1, Anagha Deshmane1, Mark Griswold1,2, and Nicole Seiberlich1,2
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Radiology, University Hospitals, Cleveland, OH, United States
MR Fingerprinting with Chemical Exchange (MRF-X) is presented for in vivo quantification of relaxation times, volume fraction, and exchange rate for tissues with two compartments. Data are presented in healthy volunteers in both brain and leg skeletal muscle and compared with previously reported measurements.

Low Rank Matrix Completion-based Reconstruction for Undersampled Magnetic Resonance Fingerprinting Data
Mariya Doneva1, Thomas Amthor1, Peter Koken1, Karsten Sommer1, and Peter Börnert1
1Philips Research Europe, Hamburg, Germany
In this work, we present a method for reconstruction of undersampled Magnetic Resonance Fingerprinting (MRF) data based on low rank matrix completion, which is performed entirely in k-space and has low computational cost. The method shows significant improvement in the MRF parameter maps accuracy compared to direct matching from undersampled data, potentially enabling more robust highly accelerated MR Fingerprinting.

Spiral MRF at 7T with simultaneous B1 estimation
Guido Buonincontri1, Rolf Schulte2, Mirco Cosottini3,4, Stephen Sawiak5, and Michela Tosetti4,6
1INFN Pisa, Pisa, Italy, 2GE Global Research, Munich, Germany, 3Department of Radiology, University of Pisa, Pisa, Italy, 4IMAGO7 Foundation, Pisa, Italy, 5Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom, 6IRCCS Stella Maris, Pisa, Italy
MR fingerprinting (MRF) can be used to rapidly estimate quantitative parameters in MRI. However, the homogeneity of the transmission radiofrequency field (B1+) can introduce errors in the measurements. Here, we modified spiral MRF acquisitions and included the effects of B1+ directly in the reconstruction framework. We could obtain B1-corrected T1 and T2 maps without using an extra scan. These advances are demonstrated in human brain images at 7T.

AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting
Christopher C. Cline1,2, Xiao Chen1, Boris Mailhe1, Qiu Wang1, and Mariappan Nadar1
1Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States, 2Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
We propose an accelerated iterative reconstruction for magnetic resonance fingerprinting (AIR-MRF) with comprehensive integration of temporal compression of fingerprints and accelerated dictionary matching with approximate nearest neighbor search. Faster and more accurate MRF reconstruction was achieved, as demonstrated by simulations with a numerical phantom.

The Partial Volume Problem in MR Fingerprinting from a Bayesian Perspective
Debra F. McGivney1, Anagha Deshmane2, Yun Jiang2, Dan Ma1, and Mark A. Griswold1
1Radiology, Case Western Reserve University, Cleveland, OH, United States, 2Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
Magnetic resonance fingerprinting (MRF) is a technique that allows us to produce quantitative maps of tissue parameters such as T1 and T2 relaxation times, however it is susceptible to artifacts due to the partial volume effect. The aim of this work is to provide a blind solution to the partial volume problem in MRF using the Bayesian statistical framework. A complete description of the algorithm is presented as well as applications to in vivo data.

MR Fingerprinting Reconstruction with Kalman Filter
Xiaodi Zhang1,2, Rui Li1, and Xiaoping Hu2
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, People's Republic of, 2The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
The reconstruction of MR fingerprinting currently relies on matching with a dictionary. In this paper, we describe an alternative method using Kalman filter instead of dictionary in the reconstruction. The method is shown to allow the reconstruction of MR Fingerprinting without the use of dictionary and achieves better results.

Analysis of estimation error from system imperfection in MRF
Taehwa Hong1, Min-Oh Kim1, Dongyeob Han1, and Dong-Hyun Kim1
1Electrical and Electronic engineering, Yonsei university, Seoul, Korea, Republic of
MR fingerprinting (MRF) is a rapid method for quantifying multiple tissue properties. However, estimation errors can increase when systematic imperfections including RF and gradient coils exist. In this study, we analyzed estimation errors from non-ideal slice profile and gradient delay by simulation. Our results showed that these systematic imperfections can cause significant errors in parameter estimation.

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