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

Electronic Poster Session: Acquisition, Reconstruction & Analysis 2

4196 -4219 Sparse & Low-Rank MRI: Theory & Applications
4220 -4243 Novel Reconstruction Methods
4244 -4267 Motion Correction
4268 -4291 Mapping & Manipulating Fields
4292 -4315 Contrast Mechanisms & Artefacts: System Imperfections & Implants
4316 -4339 Image Processing & Analysis

Exhibition Hall 

10:30 - 11:30

    Computer #

1 Rapid high-resolution T1 mapping using highly accelerated radial steady-state free-precession acquisition
Zhitao Li1, Benjamin Paul Berman2, Jean-Philippe Galons3, Ali Bilgin4,5, Maria I. Altbach3, and Diego R. Martin3
1Electrical and Computer Engineering, The University of Arizona, Tucson, AZ, United States, 2Program in Applied Mathematics, the University of Arizona, Tucson, AZ, United States, 3Department of Medical Imaging, the University of Arizona, Tucson, AZ, United States, 4Electrical and Computer Engineering, the University of Arizona, Tucson, AZ, United States, 5Biomedical Engineering, the University of Arizona, Tucson, AZ, United States
A golden angle radial steady-state free-precession technique and a principle component based iterative algorithm are developed for the reconstruction of high resolution T1 maps from highly undersampled data. The total acquisition time is < 3 seconds per slice.


2 Concentration time-course Model-based Angiogram SEparation (MASE) for dynamic contrast-enhanced magnetic resonance angiography
Eun Ji Lim1,2 and Jaeseok Park2
1Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of, 2Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of
Dynamic contrast-enhanced (DCE) 3D MRA has been widely used for diagnostic assessment of vascular morphology and hemodynamics in a clinical routine. It acquires a series of time-resolved images, revealing details on contrast dynamics. To extract angiograms while eliminating unwanted background tissues, subtraction between the reference (pre-contrast) and DCE images in each time frame is typically employed. However, in the presence of non-stationary background signal transition such as subject motion and time-varying magnetic field, subtraction results in incomplete background suppression and noise amplification. Due to the inherent, subtraction sparsity in either between the reference and each dynamic image or between neighboring time frames, compressed sensing (CS) is well suited to DCE MRA to enhance spatial and temporal resolution. Nevertheless, these approaches remain suboptimal due to the inherent limitation of subtraction. In this work, we propose a new, DCE MRA method called “concentration time-course Model-based Angiogram SEparation (MASE)”, in which DCE signals in the temporal direction are directly modeled and reconstructed with sparsity priors while background signals are attenuated.


3 Entangled Compressed Sensing for Highly Accelerated 4D Flow MRI
Adrian Emmanuel Georg Huber1, Christian Binter1, Claudio Santelli1, and Sebastian Kozerke1
1Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
Entangled denoising (eSPARSE) was developed for highly undersampled 4D Flow MRI, combining both k-t SPARSE-SENSE and 3D-L1-Wavelets. Undersampling factors of 8 and 10 were studied in healthy volunteers. The proposed algorithm improves the reconstruction of fluid vector fields in the aorta compared to k-t SPARSE-SENSE. The relative RMSE velocity is reduced by up to 16% for an undersampling rate of R = 8 and by up to 19% for R = 10. Entangled denoising (eSPARSE) is a promising approach to accelerate 4D Flow MRI while preserving key features of the flow field.


4 High resolution CBV assessment with PEAK-EPI and PS-SPIRiT-EPI
Rebecca Ramb1, Anthony G. Christodoulou2,3, Irina Mader4, Maxim Zaitsev1, Zhi-Pei Liang2, and Jürgen Hennig1
1University Medical Center Freiburg, Dept. of Radiology - Medical Physics, Freiburg, Germany, 2Beckman Institute, Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 3Heart Institute and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 4University Medical Center Freiburg, Dept. of Neuroradiology - Freiburg Brain Imaging, Freiburg, Germany
This work is to provide perfusion parameters such as cerebral blood volume at high spatial resolution, for detailed delineation of tumor borders and to guide stereotactic surgery biopsies in locating the most aggressive tumorous tissue. This is achieved with an k-t-undersampled EPI acquisition and PEAK-GRAPPA reconstruction. Additionally, an advanced iterative reconstruction method is developed incorporating partial separability constraint into parallel imaging with SPIRiT kernels (PS-SPIRiT). Two half-dose first-pass perfusion acquisitions in tumor patients allow direct comparison of the standard clinical protocol with the proposed acquisition and reconstruction schemes. 


5 Sliding-window Reconstruction Strategy for Accelerating the Acquisition of MR Fingerprinting
Xiaozhi Cao1, Congyu Liao1, Zhixing Wang1, Huihui Ye1, Ying Chen1, Hongjian He1, Song Chen1, Hui Liu2, and Jianhui Zhong1
1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou,Zhejiang, China, People's Republic of, 2MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, People's Republic of
The original MRF method uses one spiral interleaf acquired within each time point to reconstruct one image, leading to dramatic fluctuation in the signal evolution caused by undersampling error. In this work, a sliding window is utilized to select multiple interleaves to generate one full-sampled image for each step so that the fluctuation in signal evolution could be significantly alleviated. Therefore our proposed method can reach an expected result with reduced time points. The results demonstrate that the proposed method can reduce the acquisition time from about 11s to 5.6s or even less. 


6 Improving temporal resolution in fMRI using 3D spiral acquisition and low-rank plus sparse image reconstruction
Andrii Y Petrov1, Michael Herbst1,2, and V Andrew Stenger1
1Department of Medicine, University of Hawaii, Honolulu, HI, United States, 2Department of Radiology and Medical Physics, University Medical Center Freiburg, Freiburg, Germany
Recent advances in dynamic MRI propose low-rank plus sparse (L+S) matrix decomposition for image reconstruction from reduced data acquisition. The L+S method has been successfully applied to multiple applications including cardiac MRI, perfusion, angiography and recently to denoise resting-state fMRI data, suggesting that it might be promising for improving temporal resolution in task-based fMRI. We propose to use 3D spiral acquisition, undersampled in kz-t domain, and L+S method for image reconstruction. Our results indicate that proposed approach allows 4x acceleration for the data acquisition and improved statistical significance of activation maps in the S component from an increased temporal resolution and eliminating physiological noise in the L component.


7 Accelerated 3D Coronary Vessel Wall MR Imaging Based on Compressed Sensing with A Novel Block-Weighted Total Variation Regularization
Chen Zhongzhou1, Zhang Xiaoyong1, Zheng Hairong1, Liu Xin1, Fan Zhaoyang2, and Xie Guoxi1
1Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology,CAS, Shenzhen, China, People's Republic of, 2Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
Coronary vessel wall MR imaging has great potential to detect coronary plaques which can be important for heart disease diagnosis. However, the imaging is always time-consuming because it needs a large amount of data for clear vessel wall depiction. In this work, a novel method based on compressed sensing (CS) with block-weighted total variation (BWTV) was proposed to accelerate coronary vessel wall imaging. Simulation and in vivo experiment results demonstrated that the proposed method can significantly decrease the amount of data for image reconstruction without compromising the depiction of the tiny coronary vessel wall.  


8 Non-rigid Motion Correction using Localized PROPELLER and Low-Rank Minimization
Joseph Y. Cheng1, Mariya Doneva2, Tao Zhang1, John M. Pauly3, Shreyas S. Vasanawala1, and Michael Lustig2
1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering & Computer Sciences, University of California, Berkeley, CA, United States, 3Electrical Engineering, Stanford University, Stanford, CA, United States
A major obstacle in MRI is artifacts from patient motion. This is especially challenging for pediatric imaging where anesthesia is often required to obtain diagnostic image quality from uncooperative patients. Thus, we developed a PROPELLER-based method to correct for non-rigid motion. Simple localized motion is estimated for each spatial region by first applying a spatial window to the image data. Low-rank minimization is used to iteratively estimate the motion without the need of determining a reference motion state and to potentially enable higher-resolution navigation. The final image is constructed via autofocusing. This approach is demonstrated in free-breathing abdominal scans of healthy and patient volunteers. 


9 MRI acceleration using correlation imaging with tissue boundary sparsity
Yu Y. Li1
1Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
In MRI data acquisition, gradient encoding introduces a non-uniform distribution of tissue contrast and boundary information in k-space. As a result, data correlation increases with tissue boundary sparsity from the center to the outer k-space. The presented work investigates a new approach to accelerating MRI by taking advantage of non-uniform k-space data correlation. In this approach, k-space data are collected and reconstructed in a region-by-region fashion using a previously developed high-speed imaging framework, "correlation imaging"1,2. It is demonstrated that region-by-region correlation imaging can introduce a gain over parallel imaging in imaging acceleration by utilizing more information.


10 Projected Fast Iterative Soft-thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging
Xiaobo Qu1, Yunsong Liu1, Zhifan Zhan1, Jian-Feng Cai2, Di Guo3, and Zhong Chen1
1Department of Electronic Science, Xiamen University, Xiamen, China, People's Republic of, 2Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong SAR, Hong Kong,3School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China, People's Republic of
Redundant sparse representations can significantly improve the MRI image reconstruction with sparsity constraint. An appropriate sparse model is very important to improve image quality even with the same sparsifying transforms and undersampled data. We propose a new fast, stable, compatible and simple iterative thresholding algorithm to solve the analysis sparse models that can obviously improve the image reconstruction for tight-frame-based sparsifying transform in compressed sensing MRI.  We theoretically prove the convergence of the proposed projected fast iterative soft-thresholding algorithm (pFISTA). Numerical results show that pFISTA achieves better reconstruction than state-of-art FISTA for synthesis sparse model and more stable and compatible than the state-of-art SFISTA. 


11 On-scanner sparse sampling for high resolution structural imaging of the human brain at 7T
Matthan W.A. Caan1,2, Abdallah G. Motaal1, Bram F. Coolen1, Wouter V. Potters1, Kerry Zhang1, Pieter Buur2, and Aart J. Nederveen1
1Radiology, Academic Medical Center, Amsterdam, Netherlands, 2Spinoza Centre for Neuroimaging, Amsterdam, Netherlands
We aimed to increase spatial resolution while maintaining scanning time for 3D-T1 weighted imaging by on-scanner undersampling at 7T. A 3DT1-weighted structural scan with a resolution of 0.5 mm3was acquired with 4 times variable poisson disc compressed sensing (CS) undersampling. For comparison, scans with resolutions of 0.5 and 0.7 mm3 were acquired, with SENSE undersampling adapted to match scanning time.The CS-reconstructed scan showed  no streaking artifacts, was less hampered by noise in deep brain regions, had better contrast between gray matter and CSF and less partial voluming effects.


12 Promoting incoherence of radial x-f point spread functions using randomly perturbed golden angles
Mark Chiew1, Nadine N Graedel1, and Karla L Miller1
1FMRIB Centre, University of Oxford, Oxford, United Kingdom
In this work we propose a simple method for increasing the spatio-temporal incoherence of a golden angle radial time-series acquisition by mildly perturbing the golden angles with a random variable. Despite its quasi-random distribution of golden angle samples, x-f point spread function analysis reveals strong coherence along the frequency domain. When the golden angles are slightly jittered using a normal random variable with small variance, the x-f point spread functions take on a more diffuse, noise-like appearance, making the acquisition scheme more appropriate for k-t reconstruction methods relying on incoherence, while maintaining its favourable spatial properties. 


13 Accelerated Dynamic MRI Reconstruction with Sequential Low Rank Matrix Completion and Parallel Imaging
Eric G Stinson1, Stephen J. Riederer1, and Joshua D. Trzasko1
1Radiology, Mayo Clinic, Rochester, MN, United States
Multi-level (uniform + non-uniform) sampling for accelerated dynamic MRI either solves a computationally expensive full regression problem, or breaks the problem into two separate steps for each sampling operator.  Here, the latter approach is taken, with low-rank matrix completion used as a pre-processing step to complete the non-uniform sampling operator before SENSE reconstruction unfolds the effects of the uniform sampling operator.  It is shown that both spatial and temporal resolution are retained with LRMC + SENSE in comparison with more traditional pre-processing steps.


14 Optimized image reconstruction for high resolution cerebral blood volume mapping with Ferumoxytol
R. Marc Lebel1,2,3, Csanad G Varallyay4, and Edward A Neuwelt4
1GE Healthcare, Calgary, AB, Canada, 2Radiology, University of Calgary, Calgary, AB, Canada, 3Biomedical Engineering, University of Calgary, Calgary, AB, Canada, 4Neurology, Oregon Health and Science University, Portland, OR, United States
Quantitative or semi-quantitative mapping of cerebral blood volume typically involves complex modeling of a dynamic gadolinium-enhanced acquisition. Off-label use of ferumoxytol is being explored as a mechanism for high-resolution quantification of cerebral blood volume. Acquisition involves high-resolution pre- and post-contrast T2*-weighted scans; quantification is straightforward and does not require fitting. We present a multi-echo acquisition and optimal quantification algorithm for improved detection of ferumoxytol-based blood volume measurements. Our approach provides high dynamic range and minimal noise amplification.


15 Improved Temporal Resolution TWIST Reconstruction using Annihilating Filter-based Low-rank Hankel Matrix
Eun Ju Cha1, Kyong Hwan Jin1, Dong-Wook Lee1, Eung Yeop Kim2, Seung-Hong Choi3, and Jong Chul Ye1
1KAIST, Daegeon, Korea, Republic of, 2Gacheon Unversity Gil Medical Center, Incheon, Korea, Republic of, 3Seoul National University Hospital, Seoul, Korea, Republic of
In dynamic contrast enhanced (DCE) MRI, temporal and spatial resolution can be improved by time-resolved angiography with interleaved stochastic trajectories (TWIST). However, due to view sharing, the temporal resolution of TWIST is not a true one. To overcome this limitation, we employ recently proposed annihilating filter-based low rank Hankel matrix approach (ALOHA) that interpolates the missing k-space data by performing low-rank matrix completion of weighted Hankel matrix. In vivo results showed considerably better temporal resolution than standard TWIST reconstruction.


16 Accelerated Dynamic MRI Using Tensor Dictionaries Learning
Jinhong Huang1,2, Biaoshui Liu1, Gaohang Yu1,2, Yanqiu Feng1, and Wufan Chen1
1School of Biomedical Engineering and Guangdong Provincial Key Laboratory of Medical Image Processing, South Medical University, Guangzhou, China, People's Republic of, 2School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, China, People's Republic of
Conventional CS methods treat a 2D/3D image to be reconstructed as a vector. However, many data types do not lend themselves to vector data representation, and this vectorization based model may lose the inherent spatial structure property of original data and suffer from curse of dimensionality that occurs when working with high-dimensional data. In this work, we introduce a novel tensor dictionary learning method for dynamic MRI reconstruction. Numerical experiments on synthetic data and in vivo data show approximately 2 dB improvement in PSNR presented by the proposed scheme over existing method with overcomplete dictionary learning.


17 A combined Compressed Sensing Super-Resolution Diffusion and gSlider-SMS acquisition/reconstruction for rapid sub-millimeter whole-brain diffusion imaging
Lipeng Ning1,2, Kawin Setsompop2,3, and Yogesh Rathi1,2
1Brigham and Women's Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Massachusetts General Hospital, Boston, MA, United States
We introduce a new method for rapid acquisition of sub-millimeter whole-brain diffusion imaging. Our method combines the gSlider-SMS acquisition method and the compressed-sensing super-resolution reconstruction algorithm. We demonstrate that this proposed approach is able to increase the resolution to 860μm iso in an effective acquisition time of 12 min.


18 Accelerating MR measurement of liver steatosis using combined compressed sensing and parallel imaging: quantitative evaluation for clinical trials
Louis W Mann1, David M Higgins2, Carl N Peters1, Sophie Cassidy1, Ken K Hodson1, Anna Coombs1, Roy Taylor1, and Kieren Grant Hollingsworth1
1Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom, 2Philips Healthcare, Guildford, United Kingdom
We compared hepatic fat fractions quantified with accelerated magnetic resonance (MR) imaging reconstructed with combined compressed sensing and parallel imaging (CS-PI) with conventional acquisitions. Undersampled data at ratios of 2.6×, 2.9×, 3.8×, and 4.8× were prospectively acquired from eleven subjects with type 2 diabetes and a healthy control. Fat fraction maps were calculated using CS-PI and Bland-Altman analysis. Inter- and intrarater analysis was performed. The fat fractions from the accelerated acquisitions had tight 95% limits of with no bias. The fat fractions were acceptable up to a factor of 3.8×, shortening the breath-hold from 17.7s to 4.7s.


19 Under-sampled multi-shot diffusion data recovery using total variation regularized structured low-rank matrix completion
Merry Mani1, Mathews Jacob2, Douglas Kelley3, and Vincent Magnotta4
1Dept. of Psychiatry, University of Iowa, Iowa City, IA, United States, 2Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, United States, 3General Electric Healthcare Technologies, San Francisco, CA, United States, 4Dept. of Radiology, University of Iowa, Iowa City, IA, United States
Multi-shot diffusion imaging holds great potential for enabling high spatial resolution diffusion imaging as well as short echo time imaging to enhance studies at higher field strengths. However, the imaging throughput of multi-shot diffusion scheme is low. To increase the efficiency, under-sampled multi-shot acquisitions can be employed. However the conventional multi-shot diffusion-weighted imaging reconstructions that rely on motion-induced phase estimates are not appropriate for such acquisitions since the phase estimates will be highly corrupted due to the under-sampling. Here we propose a new total-variation regularized reconstruction for under-sampled multi-shot diffusion data using an annihilating filter bank formulation in a weighted k-space domain.  


20 Reconstruction Using Compressed Sensing with Edge Preservation for High Resolution MR Characterization of Myocardial Infarction: In-Vivo Preclinical Validation
Li Zhang1,2, Jennifer Barry2, Mihaela Pop1,2, and Graham A Wright1,2
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Sunnybrook Health Sciences Centre, Toronto, ON, Canada
Multi-contrast late enhancement (MCLE)1 images offer better visualization of myocardial infarction (MI) than conventional IR-FGRE. However, current MR images either with IR-FGRE or MCLE provide an inferior spatial resolution of 1.6-2.0mm in-plane with a slice thickness of 5-8mm in the clinical setting. Characterization of infarct heterogeneity requires high spatial resolution. We propose a novel method to reconstruct MCLE images at a high spatial resolution from a highly accelerated dataset acquired prospectively with three-dimensional (3D) MCLE. The method was validated in a preclinical model, producing an isotropic resolution of 1.5mm within a single breath-hold.


21 Accelerated MP2RAGE Imaging Using Sparse Iterative Reconstruction
Emilie Mussard1,2,3, Tom Hilbert1,2,3, Reto Meuli2, Jean-Philippe Thiran2,3, and Tobias Kober1,2,3
1Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland, 2Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 3LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
MP2RAGE is a T1 imaging method providing greatly reduced B1 bias as well as less T2* and PD-contributions. It requires, however, long acquisition time (standard protocol with GRAPPAx3: ~8min) which hampers its clinical application. This work proposes to use sparse iterative reconstruction techniques to shorten MP2RAGE acquisition times. Resulting images are benchmarked using contrast assessment, changes in obtained T1 values as well as evaluating the effect of undersampling on an automated brain morphometry algorithm. Acceptable penalty in image quality and morphometric outcome was achieved with up to 5-fold acceleration, yielding a measurement time of 3.8min compared to fully sampled 20min.


22 Estimation and Correction of Systematic Bias Inherent in Sparsely Undersampled Sodium Imaging of the Human Brain at High-Field
Yasmin Blunck1, Sonal Josan2, Brad A. Moffat3, Shawna Farquharson4, Roger J. Ordidge3, and Leigh A. Johnston1
1Electrical & Electronic Engineering, University of Melbourne, Melbourne, Australia, 2Siemens Healthcare, Melbourne, Australia, 3Anatomy & Neuroscience, University of Melbourne, Melbourne, Australia, 4Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
Sodium plays a vital role in various physiological processes and functions due to the delicate balance between intra- and extracellular sodium concentration. Disturbance to this electrochemical gradient is considered to be a sensitive, early indicator of cell breakdown and provide an insight into cellular integrity.  Iterative reconstruction of sparsely undersampled data has been shown to cause inaccuracies in the estimation of tissue sodium content. This work investigates the bias in sodium concentration estimates and presents a method for correction that recovers the quantitative property of sodium imaging for high undersampling factors.


23 Highly accelerated fat-fraction measurements for clinical trials in muscular dystrophy
Thomas Loughran1, David M Higgins2, Anna Coombs1, Michelle McCallum3, Volker Straub3, and Kieren Grant Hollingsworth1
1Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom, 2Philips Healthcare, Guildford, United Kingdom, 3Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom

Fat fraction measurement in muscular dystrophy is important for therapy trials. Accelerated acquisition reconstructed by combined compressed sensing and parallel imaging (CS-PI) can improve patient compliance. Eight patients with Becker muscular dystrophy were recruited and prospectively undersampled data at ratios of 3.65×, 4.94×, and 6.42× were acquired in addition to fully sampled data. The CS-PI reconstructions were of sufficient quality at 3.65× and 4.94× acceleration. Compared to fully sampled data, non-significant bias and 95% limits of agreement of 1.65%, 1.95% and 2.22% were found for the three CS-PI reconstructions, significantly outperforming conventional parallel imaging alone.


24 Evaluation of highly undersampled contrast-enhanced MR angiography (SPARSE CE-MRA) in intracranial applications
Marcel Gratz1,2, Marc Schlamann3,4, Sophia Göricke4, Stefan Maderwald2, and Harald H. Quick1,2
1High Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany, 2Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany, 3Neuroradiology, University Hospital Giessen and Marburg GmbH, Giessen, Germany, 4Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
Highly undersampled contrast-enhanced intracranial MR angiography (SPARSE CE-MRA) was evaluated regarding the vascular visibility and image quality in a clinical setting on a 3T MRI system for 23 patients with various pathologies. The overall performance is comparable to TOF MR angiography, yet with much shorter acquisition times and a high-resolution whole-head coverage in both arterial and venous phase. However, a strong dependence of the obtained MRA quality on the bolus timing of the contrast agent was found and needs to be properly addressed by the operators to minimize the arterio-venous overlap in the imagery for best diagnostic quality.
Exhibition Hall 

10:30 - 11:30

    Computer #

25 Magnetic Resonance Imaging Cross-Modality Synthesis
Yawen Huang1, Leandro Beltrachini1, Ling Shao2, and Alejandro Frangi1
1Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, United Kingdom, 2 Department of Computer Science and Digital Technologies, Northumbria University, Newcastle, United Kingdom
Multi-modality MRI protocols are becoming standard in the everyday clinical practise. The advantages of such acquisitions were shown to be fundamental in a wide range of applications, such as medical diagnosis and image segmentation. However, the implementation of these protocols tends to be time-consuming, consisting in one key limitation. In this paper we address this problem by presenting a novel method for synthesising any MRI modality from a single acquired image. This is done using machine learning techniques for dictionary learning. Results show that our approach can lead to significant performance over the state-of-the-art methods.


26 Fast Dynamic MRI from Undersampled Acquisitions Using Weighted, Adaptive Model Consistency Reconstruction (WI-MOCCO)
Julia Velikina1 and Alexey Samsonov2
1Medical Physics, University of Wisconsin, Madison, WI, United States, 2Radiology, University of Wisconsin, Madison, WI, United States
We describe next generation of Model Consistency COndition (MOCCO) reconstruction which makes use of new Weighted low-rank models and attains high image quality through Iterative model adaptation to complexity of the local temporal dynamics (WI-MOCCO). 


27 Accelerating Intravoxel Incoherent Motion Imaging of the Brain using k-b PCA
Georg Spinner1, Johannes Frieder Matthias Schmidt1, and Sebastian Kozerke1
1Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland
In vivo Intravoxel Incoherent Motion (IVIM) parameter mapping in the brain is particularly challenging because of inherent noise amplification of parallel imaging. To address this limitation, correlations in space and in the b-value dimension may be jointly exploited. To this end, an iterative approach of k-t PCA was adapted to allow image reconstruction from undersampled IVIM data. Reconstruction and parameter estimation errors of the proposed k-b PCA approach relative to parallel imaging were assessed. Mean absolute parameter errors of k-b PCA were lower compared to CG-SENSE (R=4): 1.3±1.9·10-4/1.8±2.0·10-4 mm2/s (D) 0.068±0.083/0.085±0.101 (f) and 6.4±16.9·10-2/7.6±18.3·10-2 mm2/s (D*). It is concluded that k-b PCA is a promising alternative to parallel imaging to reduce scan times while maintaining the quality of diffusion and perfusion parameter maps in brain exams.


28 An Improved Tissue-Fraction MRF (TF-MRF) with Additional Fraction Regularization
Xiaozhi Cao1, Congyu Liao1, Zhixing Wang1, Huihui Ye1, Ying Chen1, Hongjian He1, Song Chen1, Hui Liu2, and Jianhui Zhong1
1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou,Zhejiang, China, People's Republic of, 2MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, People's Republic of
MR fingerprinting has been used for estimating the intra-voxel tissue component fractions by resolving the equation Svoxel=Dw. In this study, potential fractions of interested components are used for building dictionary instead of T1 and T2, changing the solution of Svoxel =Dw into an optimization problem with regularization terms. The results demonstrate that the proposed method could provide more robust quantification of tissue composition and estimation of partial volume effects.


29 Effect of a Low-Rank Denoising Algorithm on Quantitative MRI-Based Measures of Liver Fat and Iron
Brian C Allen1, Felix Lugauer2, Dominik Nickel2, Lubna Bhatti1, Randa A Dafalla1, Brian M Dale3, Tracy A Jaffe1, and Mustafa R Bashir1,4
1Radiology, Duke University Medical Center, Durham, NC, United States, 2MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, 3MR R&D Collaborations, Siemens Healthcare, Cary, NC, United States, 4Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC, United States
Applying the described low-rank denoising algorithm to a liver fat/iron quantification technique reduces image noise in PDFF and R2* maps without adversely affecting mean values of the quantitative measures or reader assessment of edge sharpness.


30 Steady-State Magnetic Resonance Fingerprinting - Permission Withheld
Thomas Amthor1, Peter Koken1, Karsten Sommer1, Mariya Doneva1, and Peter Börnert1
1Philips Research Europe, Hamburg, Germany
We propose an acceleration technique for MR Fingerprinting measurements based on Cartesian or otherwise segmented sampling. We show that quick repetition of MR Fingerprinting sequences leads to stationary signal responses. Instead of waiting for the spin system to relax completely before the start of the next fingerprint sequence, we take the evolution of the spin system into account and calculate a dictionary of steady-state fingerprints. We present a Cartesian fingerprint measurement with a SENSE factor of four. Using our method, additional acceleration by more than a factor of two could be achieved, without reducing the match accuracy.


31 Reconstructing all physical quantities from time-domain data of a very short sequence
Alessandro Sbrizzi1, Annette van der Toorn1, Hans Hoogduin1, Peter R Luijten1, and Cornelis AT van den Berg1
1UMC Utrecht, Utrecht, Netherlands
Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) aims at reconstructing all physical quantities (T1,T2, PD, etc) directly from the data in the time-domain. By solving a large scale nonlinear inversion problem, the parameters can be inferred. The spatial encoding is entangled implicitly in the time response of the system. A very quick acquisition can be performed and processed to derive all system parameters, including electromagnetic field maps like B0 and B1.  We illustrate MR-STAT at high resolution for a realistic numerical phantom and we show high precision reconstructions of quantitative maps.


32 Acceleration of MR Fingerprinting with Low Rank and Sparsity Constraint
Congyu Liao1, Xiaozhi Cao1, Huihui Ye1, Ying Chen1, Hongjian He1, Song Chen1, Qiuping Ding1, Hui Liu2, and Jianhui Zhong1
1Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, China, People's Republic of, 2MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, People's Republic of
In this study, a low rank and sparsity based MRF reconstruction scheme (L&S MRF) is proposed for reducing the artifacts of each time point with a fraction of acquisition times.


33 Highly Accelerated Chemical Exchange Saturation Transfer (CEST) MRI Using Combination of Compressed Sensing and Sensitivity Encoding
Hye-Young Heo1,2, Yi Zhang1, Dong-Hoon Lee1, Shanshan Jiang1, Xuna Zhao1, and Jinyuan Zhou1,2
1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
Chemical exchange saturation transfer (CEST) imaging is a unique contrast enhancement technique that enables the indirect measurement of endogenous metabolites with water-exchangeable protons. The measurement of a complete Z-spectrum using standard imaging acquisition scheme is time consuming because a large number of the RF saturation frequency offset followed by MR signal readout is inevitable to obtain the full Z-spectrum. In this study, the feasibility of accelerated CEST imaging using combined CS and SENSE technique (CS-SENSE) was demonstrated in healthy volunteers and glioma patients at 3 T.


34 Multi-shot sensitivity encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS)
Merry Mani1, Mathews Jacob2, Douglas Kelley3, and Vincent Magnotta4
1Dept. of Psychiatry, University of Iowa, Iowa City, IA, United States, 2Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, United States, 3General Electric Healthcare Technologies, San Francisco, CA, United States, 4Dept of Radiology, University of Iowa, Iowa City, IA, United States
Multi-shot diffusion imaging holds great potential for enabling high spatial resolution diffusion imaging as well as short echo time imaging to enhance studies at higher field strengths. Conventional reconstructions rely on motion-induced phase estimates to recover the diffusion-weighted images from multi-shot acquisitions. Since a good estimate of phase cannot be obtained in many situations either due to noisy data or high under-sampling, these methods are unreliable in such situations. Here we propose a new reconstruction for multi-shot diffusion imaging that recovers the missing k-space data of the multiple shots by formulating the recovery as a structured low-rank matrix completion problem.


35 Two-step adaptive reconstruction of multichannel phase images
Peng Wu1 and Hua Guo1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, People's Republic of
Adaptive reconstruction (AR) can be used to combine multichannel images without acquiring coil sensitivity information. It can improve the SNRs of combined magnitude and phase images. But the reconstructed phase images may suffer from open-ended fringe artifacts when coil-sensitivity maps vary a lot. We propose a two-step adaptive reconstruction method to combine multichannel images. This method is shown to be more robust than the traditional AR method and can still maintain the high SNR.


36 Improved Time Fidelity in Sparse ADMM Reconstruction via Tempered Data Weighting - Permission Withheld
Eric A. Borisch1, Joshua D. Trzasko1, and Stephen J. Riederer1
1Mayo Clinic, Rochester, MN, United States
By adding an age-of-sample dependent weighting to the data fidelity penalty of an Alternating Direction Method of Multipliers sparse reconstruction of a view-shared accelerated acquisition, improved temporal fidelity is observed in a time-resolved motion-controlled phantom study.


37 Reference-guided CS-MRI with Gradient Orientation Priors
Xi Peng1, Shanshan Wang1, Qingyong Zhu1, and Dong Liang1
1Shenzhen Institutes of Advanced Technology, Shenzhen, China, People's Republic of
In various MR applications, a pre-scan is usually practicable that extra morphology information can be extracted from the reference image. However, with a reference image obtained from a different contrast mechanism, the signal variation in the reference may differ from that in the target image. In this work, we propose to exploit gradient orientation information, which is closely related to the anatomical structures but less dependent on the image contrast, to enable superior CS-based reconstruction. The proposed method was validated using multi-scan experiment data and is shown to provide high speed and high quality imaging.


38 Temporal point spread function interpretation of low rank, dictionary learning models in dynamic MRI
Sajan Goud Lingala1, Sampada Bhave2, Yinghua Zhu1, Krishna Nayak1, and Mathews Jacob2
1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 2Electrical and Computer Engineering, University of Iowa, Iowa city, IA, United States
A number of dynamic MRI applications have seen the adaptation of data-driven models for efficient de-noising and reconstruction from under-sampled data. In this work, we develop a novel temporal point spread function interpretation of two data-driven models: low rank, and dictionary-learning. Through this interpretation, we show (a) the low rank model to perform spatially invariant non-local view-sharing, and (b) the dictionary-learning model to perform spatially varying non-local view-sharing. Both the models can be viewed as efficient data-driven retrospective binning techniques. We provide demonstrations using the application of de-noising real-time MRI speech data. 


39 Kernelized Low-Rank: Improve Low-Rank with Adaptive Nonlinear Kernel for Dynamic MRI
Enhao Gong1, Tao Zhang1, Joseph Cheng1, Shreyas Vasanawala2, and John Pauly1
1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States
Low-Rank methods are widely applied to improve reconstruction for Dynamic Contrast Enhanced (DCE) MRI by imposing linear spatial-temporal correlation in global, local or multiple scales. This assumption does not fully capture the highly nonlinear spatial-temporal dynamics of DCE signals. We proposed a generalized Kernelized-Low-Rank model, assumed Low-Rank property after nonlinear transform and solved it by Regularizing singular-values with Adaptive Nonlinear Kernels. The proposed method captures the spatial-temporal dynamics as a sparser representation and achieves more accurate reconstruction results. Kernelized-Low-Rank model can be easily integrated to provide significant improvements to Global Low-Rank, Locally Low-Rank, LR+S and Multi-scale LR models.


40 Efficient algorithm for maximum likelihood estimate and confidence intervals of $$$T_1$$$ from multi-flip, multi-echo FLASH
M. Dylan Tisdall1,2 and André J. W. van der Kouwe1,2
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 2Radiology, Harvard Medical School, Boston, MA, United States
Multi-flip, multi-echo 3D FLASH is routinely used to estimate T1. We present a novel, efficient algorithm for finding both the ML estimate and a confidence interval for T1, given full, multi-channel data from such an experiment. Finding the ML estimate is based on minimizing a cost function. The ends of the CI are a threshold value for the same cost function, where the threshold is determined via Monte Carlo experiment based on the protocol and desired confidence level. Results from a phantom study are shown, demonstrating the value of CIs in interpreting the validity of the ML estimates.


41 Advances in Model-Based Reconstruction of High Resolution T1 maps
Volkert Roeloffs1, Xiaoqing Wang1, and Jens Frahm1
1Biomedizinische NMR Forschungs GmbH, Max Planck Institute for Biophysical Chemistry, Goettingen, Germany
Fast and accurate determination of T1 values can be accomplished by Look-Locker type MRI sequences. Here, we formulate T1 mapping as a nonlinear optimization problem which we subsequently solve by the iteratively regularized Gauss Newton (IRGN) method. Our choice of the model parameterization allows to exploit smoothness of the spatial flip angle distribution as additional prior knownledge. This model-based reconstruction allows accurate and precise reconstruction of high resolution T1 maps from radial, highly undersampled data as validated in phantom studies and demonstrated in the human brain.


42 Whole-Brain Gray Matter Imaging Exploiting Single-Slab 3D Dual-Echo TSE With Relaxation Modulation: Comparison With Double Inversion Recovery Gray Matter Imaging
Hyunyeol Lee1 and Jaeseok Park2
1Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea, Republic of, 2Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of
In this work we propose a novel, GM-selective single-slab 3D dual echo TSE with relaxation modulation (no long IR), in which white matter signals remain nulled before signal encoding while CSF signals are modulated to be cancelled during residual reconstruction between echoes with sparsity prior. We demonstrate the effectiveness of the proposed method over conventional DIR in that the former can achieve 1mm-isotropic whole-brain GM acquisition in 5-6 min. without apparent artifacts.   


43 Dynamic Tagged Liver MRI Exploiting Tag-Constrained Sampling and Separation: Assessment of Liver Stiffness
Hyunkyung Maeng1,2 and Jaeseok Park2
1Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of, 2Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of
It is important to assess liver stiffness and monitor the progression of fibrosis in patients with liver diseases using non-invasive imaging. Exploiting the fact that the motion of the heart during cardiac cycle is an intrinsic driving source to deform the liver, dynamic tagged MRI can be employed to measure the cardiac motion induced displacements using harmonic phase images and thereby evaluate the corresponding strain maps in the liver. In this work, we propose a novel framework of compressed sensing (CS) for dynamic tagged liver MRI, in which: 1) data is acquired using tag-constrained, incoherent undersampling in k-t space, 2) a time series of morphologies is decomposed into transient tag-only images and stationary tag-free liver images, 3) both morphological components are then reconstructed directly from the tag-constrained, undersampled k-t space, and 4) the transient tag-only images are employed to estimate time-varying displacements and the corresponding strain maps while the stationary tag-free liver images are used as a structural roadmap.


44 Dynamic Contrast-Enhanced MRA with Robust Background Suppression Exploiting Motion Subspace Learning and Sparsity Priors
Suhyung Park1 and Jaeseok Park2
1Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of, 2Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of
Dynamic contrast-enhanced magnetic resonance angiography(DCE-MRA) has been widely used for diagnostic assessment in clinical practices. To enhance the conspicuity of arteries relative to unwanted background tissues, subtraction between the pre-contrast and the post-contrast images was typically performed displaying maximum intensity projection images(MIP). Nevertheless, if there exists non-stationary signal transition due to time-drifting field inhomogeneity, and subject motion etc, the subtraction leads to incomplete background suppression, impairing the detectability of arteries as well as small vessel particularly at high reduction factors. In this work, we propose a novel DCE-MRA method exploiting motion subspace learning and sparsity priors for robust angiogram separation, in which the motion subspace is learned using partial Casorati matrix without any motion information while image reconstruction with sparsity priors is performed to jointly estimate motion-induced artifacts and DCE angiograms of interest under the framework of the decomposition. Simulation and experimental studies show that the proposed method is highly competitive with the competing methods including subtraction and fast reconstruction techniques.


45 High Spatiotemporal Resolution 3D Dynamic MRI using Spiral Acquisition and Compressed Sensing with L0 Homotopic Minimization
Lyu Li1, Sheng Fang2, Pascal Spincemaille3, Bida Zhang4, Yi Wang3,5, and Hua Guo1
1Center for Biomedical Imaging Research, Department of Biomedical Enginnering, School of Medicine, Tsinghua University, Beijing, China, People's Republic of, 2Institute of nuclear and new energy technology, Tsinghua University, Beijing, China, People's Republic of, 3Radiology, Weill Cornell Medical College, New York, NY, United States, 4Healthcare Department, Philips Research China, Shanghai, China, People's Republic of, 5Biomedical Engineering, Cornell University, New York, NY, United States
High spatiotemporal resolution 3D imaging is a desired technique for detecting dynamic information of detailed anatomy and getting accurate modeling parameters. In this abstract, we developed a method using golden angle spiral and compressed sensing with L0 homotopic minimization for high resolution 3D imaging. In this method, a high undersampling rate and high motion insensitivity can be achieved. In clinical applications such as dynamic contrast enhanced MRI, this new method is very promising to achieve high spatiotemporal resolution without breath-hold.


46 Improved Field-Map Estimation and Deblurring for MAVRIC-SL
Brady Quist1,2, Xinwei Shi1,2, Hans Weber1, and Brian A Hargreaves1,2
1Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States, 2Department of Electrical Engineering, Stanford University, Stanford, CA, United States
In order to image in the large B0 field inhomogeneity near metallic implants, multi-spectral imaging sequences, such as MAVRIC-SL, acquire images at multiple spectral bins to reduce distortion while imaging the entire anatomy. However, blurring is introduced when these overlapping bins are combined. While a deblurring method, which uses a field-map estimated from the bin images, does exist, the resulting images are subject to increased noise and distortion. Here we propose both a better field-map estimation method along with an improved deblurring algorithm, both of which are less sensitive to noise and help provide excellent deblurring without distortion.


47 Free-breathing 3D Cine Whole-heart Magnetic Resonance Imaging using Compressed Sensing Parallel Image Reconstruction - Permission Withheld
Mehdi Hedjazi Moghari1,2, Jonathan I Tamir 3, John Axerio-Cilies3, Tal Geva1,4, and Andrew J Powell1,4
1Pediatrics, Harvard Medical School, Boston, MA, United States, 2Cardiology, Boston Children's Hospital, Boston, MA, United States, 3Arterys, San Francisco, CA, United States, 4Cardiology, Boston Children’s Hospital, Boston, MA, United States
We developed and evaluated a variable density Poisson disc undersampling technique and compressed sensing image reconstruction algorithm for free-breathing 3D cine steady-state free precession whole-heart imaging. In 10 patients, we found good agreement between 3D cine and conventional breath-hold 2D cine imaging measurements of ventricular volumes. 


48 Accelerated 3D coronary MRA using non-rigid motion corrected regularized reconstruction
T. Correia1, G. Cruz1, R. M. Botnar1, and C. Prieto1
1Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
Accelerated 100% scan efficiency whole-heart 3D coronary MR angiography (CMRA) is achieved by combining undersampling and non-rigid motion correction in a unified regularized reconstruction. 3D undersampled CMRA is performed using a golden-step spiral-like Cartesian trajectory. Motion correction is achieved in two steps: beat-to-beat 2D translational correction with motion estimated from interleaved image navigators, and bin-to-bin 3D non-rigid correction with motion estimated from the data itself. A generalized matrix formalism with total variation regularization is used to perform the non-rigid correction directly in the reconstruction. This approach produces good quality images, comparable to those of a navigator-gated approach, but in a ~5x shorter scan time.
Exhibition Hall 

10:30 - 11:30

    Computer #

49 Impact of non-rigid registration and retrospective image correction (RETROICOR) on detecting BOLD fMRI vasomotor response in the breast
Tess E. Wallace1, Andrew J. Patterson2, Roie Manavaki1, Martin J. Graves1, and Fiona J. Gilbert1
1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
Physiological fluctuations and motion artifacts are expected to be dominant sources of noise in BOLD fMRI experiments to assess tumor oxygenation and angiogenesis. This work assesses the impact of a non-rigid registration algorithm and retrospective image correction (RETROICOR) on the detection of activation signals in the breast, both at resting state and in response to a modulated respiratory stimulus paradigm. Our results suggest that correction for motion artifacts is associated with a reduction in false-positive activation effects, which can be further improved by the addition of RETROICOR, confirming the importance of these physiological corrections in functional parameter estimation.


50 Prospective Motion Correction in Brain Imaging Using a Passive Magnetic Sensor
Mahamadou Diakite1, Steve Roys2, Taehoon Shin2, Jiachen Zhuo2, Jaydev P. Desai3, and Rao P. Gullapalli2
1Radiology, Center for Metabolic Imaging and Therapeutics, University of Maryland, School of Medicine, Parkville, MD, United States, 2Radiology, Center for Metabolic Imaging and Therapeutics, University of Maryland, School of Medicine, Baltimore, MD, United States, 3Department of Mechanical Engineering, University of Maryland, College Park, Maryland, United States, Baltimore, MD, United States
We present a prospective motion correction (PMC) technique using a miniature passive magnetic sensor. The motion sensor can virtually work with any imaging technique that is sensitive to motion. Especially techniques such as fMRI, DTI and spectroscopy sequences are likely to benefit greatly when dealing with non-cooperative subjects.

In this study, the GRE sequence was initially modified by adding three bipolar gradients along the read, phase, and slice-selection directions respectively. The bipolar gradients were used to trigger the position and orientation tracking sensor. A dynamic feedback loop mechanism was implemented into the sequence to receive the sensor position and orientation for real-time update of the imaging slice using an in-house developed application.  

We demonstrate that our PMC method in brain imaging using a passive magnetic sensor is capable of tracking the patient head motion with high accuracy.


51 Synchronization of longitudinal multi time-point breast DCE data using a group-wise registration approach - Permission Withheld
Chandan Aladahalli1, KS Shriram1, Dattesh Shanbhag1, Rakesh Mullick1, Reem Bedair2, Fiona Gilbert2, Andrew Patterson2, and Martin Graves2
1GE Global Research, Bengaluru, India, 2University of Cambridge, Cambridge, United Kingdom
Multi-parametric longitudinal imaging is an important tool to monitor therapy response at tumor locations. The key challenge in longitudinal data is the synchronization of volumes across time points, as large variations are seen due to therapy response, weight loss/gain, patient positioning, and surgery. We employ a group-wise registration approach to synchronize the longitudinal volumes and compare/contrast it with a more typical pair-wise registration approach. Group-wise approach results in consistent registration across time-points as it does not require a reference image. The group-wise non-rigid registration approach is demonstrated on longitudinal MRI data used for assessing breast tumor therapy response.


52 Outer volume suppression improves motion tracking and image quality in self-navigated whole heart cardiac MRI: results from a moving phantom and healthy volunteers
Andrew J Coristine1, Jerome Chaptinel1, Giulia Ginami1, Gabriele Bonanno1, Simone Coppo1, Ruud B van Heeswijk1, Davide Piccini1,2, and Matthias Stuber1,3
1Department of Radiology, University Hospital (CHUV) / University of Lausanne (UNIL), Lausanne, Switzerland, 2Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland,3CardioVascular Magnetic Resonance (CVMR) research centre, Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
In respiratory self-navigation (SN), static structures, such as the arms or chest wall, may complicate motion detection due to the superposition of signal originating from different tissues. Even if motion detection is successful, the subsequent motion correction may introduce streaking artefacts when applied to static structures. Suppressing signal from those tissues may therefore improve image quality. In this study, we address the hypothesis that SN coronary MRA will benefit from the introduction of an outer volume suppressing "2D-T -Prep", and present results from a moving cardiac phantom and 10 healthy volunteers.


53 Reconstruction of under-sampled Propeller gradient-echo image using projection onto convex sets based multiplexed sensitivity-encoding (POCSMUSE)
Hing-Chiu Chang1,2, Mei-Lan Chu2, and Nan-Kuei Chen2
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong, 2Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States
The Propeller technique is a useful acquisition scheme and reconstruction method to reduce motion artifact. However, the higher specific absorption rate (SAR) of RF pulse at high-field magnetic strength can limit the number of multiple slices for a given TR, which in turn reduces the efficiency of acquisition, especially for Propeller-FSE sequence. A possible solution is to reduce the echo-train-length with under-sampling of data of each blade. In this study, we propose to apply POCSMUSE instead of SENSE reconstruction and Propeller reconstruction, to reconstruct the image from all under-sampled blade data with reduced noise amplification. The data acquired from brain and liver using Propeller-GRE will be used to test purposed POCSMUSE algorithm.


54 Respiratory Motion Compensation for Simultaneous PET/MR Using Strongly Undersampled MR Data
Christopher M Rank1, Thorsten Heußer1, Andreas Wetscherek1, Martin T Freitag2, Heinz-Peter Schlemmer2, and Marc Kachelrieß1
1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
To allow for MR acquisition times as short as 1 minute per bed, we propose a new method for PET/MR respiratory motion compensation (MoCo), which is based on strongly undersampled radial MR data. We acquired simultaneous PET/MR data of the thorax of three patients. Motion vector fields were estimated with a newly-developed algorithm, which alternates between MR image reconstruction and motion estimation. Subsequent 4D MoCo PET reconstructions employing the motion vector field derived from strongly undersampled MR data yielded a considerable visual and quantitative improvement compared to standard 3D PET and 4D gated PET reconstructions.


55 Motion Correcting Complete MR-PET Exams Via Plot Tone Navigators
Thomas Koesters1, Ryan Brown1, Tiejun Zhao2, Mattias Fenchel3, Peter Speier3, Li Feng1, Yongxian Qian1, and Fernando Emilio Boada1
1Radiology, New York University, New York, NY, United States, 2Siemens Medical Systems, Malvern, PA, United States, 3Siemens Medical Systems, Erlangen, Germany
We demonstrate the use of an external RF signal as a mean to provide motion tracking information for motion-state sorting of k-space line during dynamic MRI scans.


56 High temporal resolution retrospective motion and $$$B_0$$$ correction using FIDNavs and segmented FatNavs at 7T. - Permission Withheld
Frédéric Gretsch1, Tobias Kober2,3,4, Maryna Waszak2,3,4, José P. Marques5, and Daniel Gallichan1
1CIBM, EPFL, Lausanne, Switzerland, 2Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland, 3Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 4LTS5, EPFL, Lausanne, Switzerland, 5Donders Centre for Cognitive Neuroimaging, Radboud University, Netherlands
FID navigators (FIDNavs) and a few lines of highly accelerated double-echo 3D fat navigators (FatNavs) were measured each TR of a high-resolution 3D-GRE acquisition. High temporal resolution $$$B_0$$$ variations and motion parameters could be estimated by the FIDNavs using the lower temporal resolution FatNavs to derive calibration data. The cardiac cycle pattern emerged clearly in these estimates and retrospectively corrected images were of clearly improved quality, thereby demonstrating the potential for this hybrid approach.


57 Self-navigated real-time motion tracking of the abdomen in free-breathing single-shot EPI data using the Extended Kalman Filter.
Nathan White1, Josh Kuperman1, Neal Corson1, Kazim Narisinh1, Hauke Bartsch1, David Karow1, Ajit Shankaranarayanan 2, and Anders Dale1,3
1Department of Radiology, University of California, San Diego, San Diego, CA, United States, 2Global Applied Sciences Lab, GE Healthcare, Menlo Park, CA, United States, 3Department of Neuroscience, University of California, San Diego, San Diego, CA, United States
Free-breathing single-shot EPI data in the abdomen is confounded by respiratory motion artifact. Previous work has demonstrated the utility of using the Extended Kalman Filter (EKF) for real-time image-based tracking of spiral-navigated scans in brain. This this study we demonstrate the feasibility of using the EKF framework for real-time self-navigated motion tracking in the abdomen. 


58 Motion-resolved 3D dynamic contrast enhanced liver MRI
Dominik Nickel1, Xiao Chen2, Boris Mailhe2, Qiu Wang2, Yohan Son3, Jeong Min Lee4, and Berthold Kiefer1
1Siemens Healthcare GmbH, Erlangen, Germany, 2Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States, 3Siemens Healthcare Ltd., Seoul, Korea, Republic of, 4Department of Radiology, Seoul National University Hospital, Seoul, Korea, Republic of
Free-breathing dynamic contrast-enhanced liver MRI is explored using a Cartesian spoiled Volume-Interpolated Breath-hold Examination (VIBE) GRE sequence that also acquires a navigation signal. Images are iteratively reconstructed using a hard-gating approach as well as resolving the motion-states using an additional dimension. With both approaches yielding promising results, the latter appears to be more motion robust at the cost of computational effort.


59 Prospective motion correction for MRI using EEG-equipment
Mads Andersen1,2, Kristoffer H. Madsen1, and Lars G. Hanson1,2
1Danish Research Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 2DTU Elektro, Technical University of Denmark, Lyngby, Denmark
A new prospective motion correction technique is presented that is based on signals from gradient switching, in an EEG-cap with interconnected electrodes the subject wears during scanning. The method has no line-of-sight limitations as optical methods, requires no interleaved navigator modules or additional hardware for sites already doing EEG-fMRI. Instead a training scan is performed were signals recorded with the EEG-system are correlated with motion parameters estimated by image realignment. Initial results from application of the method in a phantom are promising.


60 Motion Correction Using Orthogonal Images
Niranchana Manivannan1, Bradley D. Clymer1, Anna Bratasz2,3, and Kimerly A. Powell2,4
1Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States, 2Small Animal Imaging Shared Resources, The Ohio State University, Columbus, OH, United States, 3Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, United States, 4Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
In most small animal imaging studies both long axis (coronal or sagittal) and short axis (axial) images of the region of interest are obtained. The goal of this study is to explore whether combining two orthogonal views obtained with different slice-select directions could reduce the motion artifacts and improve image quality. The advantages of this method are that no a priori knowledge or external hardware is needed and it doesn’t increase the acquisition time. The results show that it is advantageous to use the available orthogonal image(s) to improve the image quality by reducing ghosting artifacts caused by motion.


61 Image Registration and Robust Fitting for Motion Insensitive Magnetic Resonance Fingerprinting (MRF)
Bhairav Bipin Mehta1, Dan Ma1, and Mark Alan Griswold1
1Radiology, Case Western Reserve University, Cleveland, OH, United States
Motion is one of the biggest challenges in clinical MRI. The recently introduced Magnetic Resonance Fingerprinting (MRF) has been shown to be less sensitive to motion. However, it is still susceptible to patient motion primarily occurring in the early stages of the acquisition. In this study, we propose a novel reconstruction algorithm for MRF, which uses robust fitting and image registration algorithms to decrease the motion sensitivity of MRF. The evaluation was performed in numerical phantoms with simulated rigid motion.


62 Dynamic, T2-Weighted, Single-Shot Fast Spin Echo with Variable Refocusing Flip Angle and Cylindrical Navigator for Retrospective Respiratory Compensation
Daniel V Litwiller1, Erik Tryggestad2, Kiaran McGee3, Yuji Iwadate4, Lloyd Estkowski5, and Ersin Bayram6
1Global MR Applications & Workflow, GE Healthcare, New York, NY, United States, 2Department of Radiation Oncology, Mayo Clinic, Rochester, MN, United States, 3Department of Radiology, Mayo Clinic, Rochester, MN, United States, 4Global MR Applications & Workflow, GE Healthcare, Hino, Tokyo, Japan, 5Global MR Applications & Workflow, GE Healthcare, Menlo Park, CA, United States, 6Global MR Applications & Workflow, GE Healthcare, Houston, TX, United States
Here we present a multi-slice, multi-phase, single-shot fast spin echo sequence with variable refocusing flip angle and interleaved cylindrical reference navigator for retrospective respiratory-guided image sorting for the purpose of managing motion in the context of MR-guided radiation therapy treatment planning.


63 Beyond high resolution MPRAGE: In vivo T1-weighted imaging at 7T with 250 µm isotropic resolution using prospective motion correction
Falk Lüsebrink1, Alessandro Sciarra1, Hendrik Mattern1, Renat Yakupov1, and Oliver Speck1,2,3,4
1Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany, 2Leibniz Institute for Neurobiology, Magdeburg, Germany, 3Center for Behavioral Brain Sciences, Magdeburg, Germany, 4German Center for Neurodegenerative Disease, Magdeburg, Germany
Increasing the spatial resolution is of major importance to structural imaging as this may build bridges to optical microscopy and may lead to superior diagnostics and segmentations. Increasing the spatial resolution with sufficient SNR usually prolongs time of acquisition. This inevitably introduces more motion artifacts even with experienced subjects. However, this can be compensated by prospective motion correction. Increasing the resolution to a few hundred micrometers inherently reduces SNR such that reconstruction by sum of squares is not adequate anymore. Here we demonstrate our work on the acquisition and reconstruction of the currently highest resolution in vivo MPRAGE at 7T. 


64 Low rank and sparsity on MR-based PET motion correction using simultaneous PET/MRI: a patient study
Yixin Ma1, Yoann Petibon2, Joyita Dutta2, Xucheng Zhu3, Rong Guo1, Georges El Fakhri2, Kui Ying1, and Jinsong Ouyang2
1Key laboratory of Particle and Radiation Imaging, Ministry of Education, Tsinghua University, Beijing, China, People's Republic of, 2Center for Advanced Medical Imaging Sciences, Division of Nuclear Medicine and Molecular Imaging, Department of Imaging, Massachusetts General Hospital, Boston, MA, United States, 3UCSF/UC Berkeley Bioengineering Graduate Group, University of California Berkeley, Berkeley, CA, United States
In this work, we exploited the low-rank and sparse properties of dynamic MRI data to accelerate the MR acquisition and assessed its impact on MR-based PET respiratory motion using a PET/MR oncologic patient study.  PET/MR motion correction workflow was accomplished, and good performance of partially sampled MR based motion correction attests the possibility of faster PET/MR data acquisition and better lesion estimation.


65 High Efficiency Coronary MRA: Beyond the Quiescent Period
Jianing Pang1, Yuhua Chen1,2, and Debiao Li1,3
1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States, 3Bioengineering, University of California, Los Angeles, CA, United States
Current motion compensation strategies for whole-heart coronary MRA only accept data acquired during specific motion phases, thus significantly reduce the imaging efficiency. In this work, we developed a reconstruction framework based on 4D coronary MRA that allowed one to increase the cardiac gating efficiency by accepting cardiac phases beyond the quiescent period, while minimizing the associated cardiac motion artifacts through non-rigid motion correction. Preliminary results from healthy subjects showed that the proposed method significantly improved the imaging efficiency, aSNR, and coronary sharpness compared with images reconstructed from the quiescent period. 


66 Motion Tracking using Nonlinear Gradient Fields: Experimental Verification and Oblique Slices
Emre Kopanoglu1, Haifeng Wang1, Gigi Galiana1, and Robert Todd Constable1,2
1Diagnostic Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States, 2Neurosurgery, Yale University, New Haven, CT, United States
Motion navigation using nonlinear gradient fields is demonstrated experimentally. The method makes use of the simultaneous multi-dimensional encoding capabilities of nonlinear gradient fields. A two-dimensional navigator image is obtained from a single-echo encoded using a nonlinear gradient field and multiple receiver coils. Without exceeding the maximum field generated by the linear gradient fields of a 3T scanner inside a 20cm isotropic field-of-view, the navigator can be acquired in under one millisecond, including its rewinder. The method can track both translational and rotational in-plane rigid body motion, as demonstrated in phantom experiments. Simulations show the method is applicable in oblique angles.


67 3D Stack-of-Stars Dixon Fat-Only Signal for Respiratory Motion Detection
Thomas Martin1,2, Andres Saucedo1, Tess Armstrong1, Holden Wu2, Danny Wang3, and Kyunghyun Sung2
1Biomedical Physics, UCLA, Los Angeles, CA, United States, 2Radiological Sciences, UCLA, Los Angeles, CA, United States, 3Neurology, UCLA, Los Angeles, CA, United States
Respiratory motion is one of the biggest confounders of liver DCE-MRI.  There are methods that use a 3D radial self-gated signal (SGS) to compensate for respiratory motion.  However, SGS includes both respiratory motion and contrast uptake in DCE-MRI, and it is not trivial to perfectly separate the two from SGS, leading to inaccuracies of respiratory motion. In this work, we propose a method to extract the respiratory motion only from SGS using golden angle radial acquisition with two-point Dixon separation. The proposed method utilizes the fact the fat-only SGS does not include contrast uptake while including the same respiratory motion.


68 Navigator-Free Motion Correction for Cartesian FSE
Yilong Liu1,2, Mengye Lyu1,2, Yanqiu Feng1,2, Victor B. Xie1,2, and Ed X. Wu1,2
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China, People's Republic of, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China, People's Republic of
A navigator-free motion correction method for Cartesian FSE is proposed for intermittent motion compensation. It first divides all shots into several motion-free groups, then estimates and corrects inter-group motion. In vivo imaging results show that this approach has decent performance in dealing with intermittent motion problems. Though only demonstrated with Cartesian acquisition, it is also applicable for non-Cartesian acquisitions, such as spiral and radial acquisitions.


69 Phantom pose detection with spherical navigator echoes for calibration of optical tracking systems in MRI
Denis Kokorin1, Cris Lovell-Smith1, Benjamin Knowles1, Michael Herbst1, Jürgen Hennig1, and Maxim Zaitsev1
1Medical Physics, University Medical Center Freiburg, Freiburg, Germany
In this work, we present a new k-space based approach for position and rotation detection to improve calibration of optical tracking systems used for prospective motion correction in MRI. 3D radial acquisition was employed to detect motion of a custom built phantom. The integrated method was tested for different motion types and showed a high precision along with a good robustness for rotation detection.


70 Respiratory Motion Corrected 3D Patch based Reconstruction of Under-sampled Data for Liver 4D DCE-MRI
Dongxiao Li1,2, Juerong Wu1, Kofi M. Deh2, Thanh D. Nguyen2, Martin R. Prince2, Yi Wang2,3, and Pascal Spincemaille2
1College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China, People's Republic of, 2Department of Radiology, Weill Cornell Medical College, New York, NY, United States, 3Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
Liver dynamic contrast enhanced MRI (DCE-MRI) requires high spatial and temporal resolution such that all relevant enhancement phases are clearly visualized. Image quality is compromised when breathing occurs during the acquisition. This abstract presents a novel 4D respiratory Motion corrected Patch based Reconstruction of Under-sampled Data (M-PROUD) which uses 3D patch based local dictionaries for sparse coding and simultaneously estimates 3D nonrigid motion. Results on in vivo data demonstrated that the proposed method can significantly reduce motion blurring artifacts and preserve more details at a sub-second temporal frame rate in free breathing liver 4D DCE-MRI.


71 Motion-Robust Abdominal DCE-MRI Using Respiratory-Gated Golden-Angle Radial Sparse Parallel MRI
Robert Grimm1, Dominik Nickel1, Qiu Wang2, Boris Mailhe2, Berthold Kiefer1, Kai Tobias Block3, and Tobias Heye4
1Siemens Healthcare GmbH, Erlangen, Germany, 2Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States, 3Radiology, New York University School of Medicine, New York City, NY, United States, 4Klinik für Radiologie und Nuklearmedizin, Universitätsspital Basel, Basel, Switzerland
Although the radial sampling scheme of GRASP DCE-MRI leads to inherent motion robustness, strong respiration can still impair the image quality of free-breathing abdominal examinations. We propose to combine GRASP with respiratory gating to minimize motion artifacts within and between temporal frames, without prolonging the reconstruction time and maintaining a high spatio-temporal resolution. A validation in 10 clinical patients confirmed the improved sharpness of the gated reconstruction.


72 Investigating the temporal stability of phase offsets at 7T for field mapping and multi-channel phase combination.
Barbara Dymerska1, Siegfried Trattnig1, and Simon Daniel Robinson1
1High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
A common assumption for phase combination and dynamic distortion correction is that phase offsets ($$$?_0$$$), i.e. the phase of coil sensitivities, are temporally stable. We investigate the validity of this assumption at 7T for long measurements (40min) and large head rotations (up to 12°) made with multi-channel coils. We show that changes in separate-channel $$$?_{0,ch}$$$ have little effect on the combined phase images (unwarping errors of 0.2 voxel, reduction in phase matching quality by 2%). We thus conclude that the assumption of $$$?_0$$$ temporal stability holds and methods based on this assumption should work at 7T with substantial motion.
Exhibition Hall 

11:30 - 12:30

    Computer #

1 Off-Resonance Map Extrapolation Using Image Inpainting
Ashley G Anderson III1 and James G Pipe1
1Imaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
An inpainting technique using the fast marching method was used to implement a fast, robust algorithm for extrapolating ?$$$\Delta f_0$$$ map data into low signal areas.


2 Measuring Magnetic Field Inhomogeneity From Spatial Distortion of Echo Planar Images
Peter Andrew Hardy1 and Erfan Akbari2
1Radiology, University of Kentucky, Lexington, KY, United States, 2Radiation Medicine, University of Kentucky, Lexington, KY, United States
We developed an imaging and analysis method to use the spatial distortion in echo planar images to estimate the magnetic field inhomogeneity. The method requires the acquisition of two images from an unmodified echo planar sequence with the direction of the phase encode reversed between the two. After combining the images appropriately an undistorted and a displacement image are produced. The displacement image is a map of the local magnetic field inhomogeneity.


3 Real time shimming over multiple regions across the DTI volume with motion correction using a multislab navigated DTI sequence
A Alhamud1, Ernesta M. Meintjes1, and André J.W. van der Kouwe2
1Human Biology,MRC/UCT Medical Imaging Research Unit, University of Cape Town, Cape Town, South Africa, 2Massachusetts General Hospital, Charlestown, MA, United States
Most DTI acquisitions are based on 2D multislice EPI sequences. The spatial distribution of the field inhomogeneity may differ from region to region within the DTI volume. While the scanner and traditional prospective shimming methods shim over the whole volume, this may not be optimal for DTI. Further, changes in the shim in different regions across DTI volume in the presence of subject motion are yet to be explored. In this work, we introduce a technique to measure and correct the changes in the static field from region to region and for different sized regions across the DTI volume


4 Multiband DREAM: Multi-Slice B1+ Mapping in a Single Shot
Kay Nehrke1, Arthur Felipe Nisti Grigoletto Borgonovi2, and Peter Börnert1,3
1Philips Research, Hamburg, Germany, 2Philips Healthcare, Best, Netherlands, 3Radiology, LUMC, Leiden, Netherlands
Simultaneous multi-slice imaging has been employed for the DREAM B1+ mapping approach, allowing a multi-slice B1+ map to be acquired in a fraction of a second. Basic feasibility has been shown in experiments on phantoms and in vivo using a clinical 3T MRI system. The presented approach potentially allows free-breathing multi-slice B1+ mapping, freezing respiratory motion in a short single shot acquisition window. 


5 Signal-domain optimization metrics for MPRAGE RF pulse design in parallel transmission at 7 Tesla
Vincent Gras1, Alexandre Vignaud1, Franck Mauconduit2, Michel Luong3, Alexis Amadon1, Denis Le Bihan1, and Nicolas Boulant1
1Neurospin, CEA/DSV/I2BM, Gif-sur-Yvette, France, 2Siemens Healthcare, Saint-Denis, France, 3IRFU, CEA/DSM, Gif-sur-Yvette, France
The standard approach to design radiofrequency pulses in MRI is to minimize the deviation of the flip angle from a target value. An alternative approach is proposed here for the MPRAGE sequence which uses the signal as a surrogate of the flip angle in the optimization of the excitation and inversion pulses. The results obtained in simulation and in the brain in vivo on a parallel transmission enabled 7T scanner show two possible applications of the method: an improvement in image quality or a significant reduction of the SAR at equivalent image quality.


6 Spiral trajectories for 2D parallel excitation of limited slice profiles
Denis Kokorin1, Jürgen Hennig1, and Maxim Zaitsev1
1Medical Physics, University Medical Center Freiburg, Freiburg, Germany
In this study, the feasibility of 2D spiral-encoded parallel excitation of limited slice profiles was investigated. The imaging experiments were performed in phantoms on a 3T MRI system with 8 RF channels for transmission and compared to 2D parallel excitation using EPI encoding. The resulting profiles revealed that 2D spiral-encoded parallel excitation is more robust against B1 deviations compared to EPI.


7 Transmit SENSE on a whole-body 10.5 Tesla system using 16 RF channels: initial results
Xiaoping Wu1, Gregor Adriany1, Eddie J. Auerbach1, Sebastian Schmitter1, Kamil Ugurbil1, and Pierre-Francois Van de Moortele 1
1CMRR, Radiology, University of Minnesota, Minneapolis, MN, United States
Increased signal to noise ratio and tissue contrast are strong incentive for pushing toward higher magnetic fields. However, as the magnetic field increases, transmit B1 fields become more and more non-uniform, leading to spatially varying contrast and local signal dropouts. This problem can be addressed with parallel RF transmission (pTx). We have recently made operational the first 10.5 Tesla whole body MRI scanner which holds promise for a wide range of biomedical applications. In this study, we assessed the performance of the installed 16-channel pTx system by designing 2D Transmit SENSE pulses. Our results suggest that high fidelity excitation patterns can be attained after correction of system imperfections. 


8 Optimization of the kT-points placement under explicit SAR and power constraints in the large flip angle regime
Vincent Gras1, Michel Luong2, Alexis Amadon1, and Nicolas Boulant1
1Neurospin, CEA/DSV/I2BM, Gif-sur-Yvette, France, 2IRFU, CEA/DSM, Gif-sur-Yvette, France
The kT-points parametrization is a powerful technique to mitigate the RF inhomogeneity at ultra-high field which can also be used to achieve homogeneous non-selective inversion profiles with less SAR than adiabatic RF pulses. The large flip angle regime thus is an interesting domain of application of the kT-points technique. However, to fully exploit it, it is necessary to optimize the placement of the kT-points in k-space. In this work, the simultaneous optimization of the RF and k-space trajectory coefficients is proposed and validated, whereby SAR and power constraints are handled explicitly.


9 Frequency shimming with local excitation coils improves fat suppression in breast MRI at 7 T
Tijl van der Velden1, Peter R Luijten1, and Dennis W.J. Klomp1
1Radiology, UMC Utrecht, Utrecht, Netherlands
Using multiple local excitation coils for different parts of the body, such as bilateral breast coils, opens up the possibility to perform frequency shimming: using multiple carrier frequencies to excite the different body parts without gradient based localization. In this work we demonstrate frequency shimming to improve fat suppressed breast MRI at 7 T.


10 A parallel transmit VERSE RF pulse design method using dynamic field monitoring
Mustafa Cavusoglu1, Klaas Paul Pruessmann1, and Shaihan Malik2
1Institute of Biomedical Engineering, ETH Zurich, Zurich, Switzerland, 2Kings Collage London, London, United Kingdom
Variable-rate selective excitation (VERSE) is a powerful method to control RF power and SAR that bounds to a key condition as retaining the RF-to-gradient amplitude ratio at each sample that preserves the rotational behavior of on-resonance spins (1). The maintenance of VERSE condition strictly depends on the fidelity of the local gradient fields implying that any deviation from the nominal VERSE’d gradients will modulate the spin rotations similar to off-resonances ultimately resulting excitation errors and the RF pulse to converge to a significantly different peak RF power.


11 3D volumetric parallel excitation at 9.4T using the trajectory container concept
Tingting Shao1, Nikolai I. Avdievich1, and Anke Henning1,2
1Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2Institute of Biomedical Engineering, University and ETH, Zürich, Switzerland
This work presents experimental results of 3D volumetric parallel excitation at a 9.4T human whole-body MRI scanner. The approach and concept of a “trajectory container” is adopted to match practical considerations. The “trajectory container” is used to shape the k space trajectory and restrict it to a limited traversing area in the k space and therefore to constrain the pulse duration. A simplified and direct way of the definition of the “trajectory container” is proposed and verified with promising experimental results.


12 Distortions during excitation and acquisition in zoomed DWI combined with parallel transmission
Denis Kokorin1, Jürgen Hennig1, and Maxim Zaitsev1
1Medical Physics, University Medical Center Freiburg, Freiburg, Germany
In this work, we discuss off-resonance effects observed in zoomed DWI combined with 2D pulses based on EPI trajectories. Our main focus is placed on the use of parallel excitation (PEX) for shortening 2D pulses and further minimizing the distortion. Experimental data were obtained using a 3T MRI system with an 8-channel TxArray extension and analyzed in detail. We conclude that the use of PEX improves the matching between excitation and acquisition in zoomed EPI applications.


13 Optimisation of Post-processing Correction of Transmit Field Inhomogeneity in R1 Maps by Relaxometry Modelling
Martina F Callaghan1, Frederic Dick2, Patrick Grabher3, Tim Keller4, Patrick Freund1,3,5, and Nikolaus Weiskopf1,5
1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, United Kingdom, 2Birkbeck/UCL Centre for Neuroimaging, London, United Kingdom, 3Spinal Cord Injury Center Balgrist, University Hospital Zurich, Zurich, Switzerland, 4Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, United States, 5Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
Unified segmentation based correction of R1 brain maps for RF transmit field inhomogeneities (UNICORT) has previously been shown to reduce bias in R1 maps caused by inhomogeneity in the RF transmit field (B1+). This approach simultaneously estimates the B1+ inhomogeneities and R1 values from the uncorrected R1 maps without the need for additional B1+ calibration data. It employs a probabilistic framework that incorporates a physically informed generative model of smooth transmit field inhomogeneities and their multiplicative effect on R1 estimates. However, different systems may require different priors, depending on the particular transmit coil used.  Here we show that these parameters can be estimated using a linear relaxometry model framework, without the need to acquire B1+ mapping data.


14 Single point based techniques for rapid and robust gradient measurement
Hyungseok Jang1,2 and Alan B McMillan1
1Department of Radiology, University of Wisconsin, Madison, WI, United States, 2Department of Electrical and Computer Engineering, University of Wisconsin, Madison, WI, United States
Accurate knowledge of the k-space trajectory is critical for artifact-free MR imaging, particularly in non-Cartesian imaging. In this study we propose a new gradient measurement technique based on single point imaging (SPI), which allows simple, rapid, and robust measurement of k-space trajectory. In the proposed technique, the zoom-in/out effect of SPI is used for k-space trajectory measurement. First, 1D SPI data are acquired from a targeted gradient in each axis, and then relative FOV scaling factors between encoding times are found, which represents relative k-space position. Improvements in image quality are demonstrated for UTE, spiral, and ramp-sampled IDEAL imaging.


15 Multi-slice spiral imaging trajectory mapping using high density 25-channel field probe array
Ying-Hua Chu1, Yi-Cheng Hsu1, and Fa-Hsuan Lin1
1Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
We use a dense 2D field probe array with 24 probes moving over a 3D volume to estimate magnetic field distribution dynamically and demonstrate that trajectory calibration is slice-dependent. The image reconstructed using measured dynamic magnetic field information 7 cm away shows similar l2 norm error as the image reconstructed without any dynamic magnetic field information.


16 Linear Gradient Characterization Using A Rapid Thin-slice Measurement
Ryan K Robison1 and James G Pipe1
1Imaging Research, Barrow Neurological Institute, Phoenix, AZ, United States
Gradient impulse response functions can predict gradient behavior in the presence of eddy currents and other sources of error. This work presents a rapid method for generating the 0th and 1st order gradient impulse response functions using existing software measurement techniques. The proposed method is applied to spiral imaging but could be similarly applied to EPI, projection reconstruction, or any other imaging sequence.


17 Chemical Shift based Fat-Water Separation using a Variational Approach for B0-field Correction
Andreas Lesch1, Kristian Bredies2, Clemens Diwoky3, and Rudolf Stollberger1,4
1Institute of Medical Engineering, Graz University of Technology, Graz, Austria, 2Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria, 3Institute of Molecular Biosciences, University of Graz, Graz, Austria, 4BioTechMed Graz, Graz, Austria
In this work we present an approach for chemical shift based fat/water-separation using variational methods for the estimation of the underlying B0-field inhomogeneity. We show that the fat/water-problem can be solved by the application of total-generalized-variation (TGV) regularization on the underlying B0-field to enforce piecewise smoothness. With this approach we are able to model huge B0-deviations as well as discontinuities in the B0-field at tissue boundaries with different susceptibility parallel to the main-field. This is shown on different datasets, including two of the ISMRM fat/water-challenge of 2012.


18 Reduction of Ghosting Due to Respiration Induced B0 Variation in Double Echo Steady State (DESS) Imaging in the Breast with a DC Navigator and Image Entropy Metric
Catherine J Moran1, Bragi Sveinsson1,2, Brady Quist2, Marcus T Alley1, Bruce Daniel1, and Brian A Hargreaves1
1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering, Stanford University, Stanford, CA, United States
The double echo steady state (DESS) acquisition has the potential to provide high-resolution and distortion-free T2 and diffusion-weighted images in the breast.  Initial investigations of DESS in the breast have been limited by the presence of ghosting artifacts. Respiratory-induced B0 variation is one source of these artifacts. A method utilizing an in-vivo time-varying off-resonance estimate along with an image entropy metric to assess the level of artifact is described and investigated for correction of ghosting due to respiration-induced B0 variation in DESS in the breast.


19 Gradient Pre-Emphasis Correction for First-order Concomitant Field on Head-only Asymmetric Gradient MRI System
Shengzhen Tao1, Paul T Weavers1, Joshua D Trzasko1, Yunhong Shu1, Seung-Kyun Lee2, Lou Frigo3, Scott Hinks3, and Matt A Bernstein1
1Radiology, Mayo Clinic, Rochester, MN, United States, 2GE Global Research, Niskayuna, NY, United States, 3GE Healthcare, Milwaukee, WI, United States
Based on Maxwell’s equation, the spatial encoding gradient fields must be accompanied by spatially-varying higher-order concomitant fields. Different from conventional gradient systems whose concomitant fields contain second-order and higher spatial dependence, some MRI platforms employ asymmetric gradient systems, and their concomitant fields also include zero- and first-order terms. The first-order terms cause artifacts including image blurring and ghosting in spiral acquisition and echo shifting in EPI. Here, an efficient gradient pre-emphasis scheme suitable for real-time implementation is demonstrated to simultaneously correct all the first-order concomitant fields with a real-time implementation on gradient firmware typically used for eddy current compensation. 


20 Gradient Unwarping: Reverse Engineering the Warpfield with Spherical Harmonics
Paul Polak1,2, David Lindner1, Jannis Hanspach1, Michael Dwyer1, Niels Bergsland1, Nicola Bertolino1,2, Robert Zivadinov1,2, and Ferdinand Schweser1,2
1Neurology, Buffalo Neuroimaging Analysis Center, State University of New York at Buffalo, Buffalo, NY, United States, 2Molecular and Translational Imaging, Clinical Translational Research Center, Buffalo, NY, United States
Gradient “unwarping” is the removal of image distortions caused by non-linearity of the imaging gradient fields. Exasperated by increasing distance from isocenter, the unwarping process is applied to every image by the manufacturer and generally is a “black-box” process occurring near the end of the image processing pipeline. This is problematic for researchers who source their data from a more primitive step, e.g. from raw k-space, since this data is generally “warped”. Presented here is a method to reverse engineer the spherical harmonic coefficients that describe the warp field and are used by the vendor’s black-box process, allowing the researcher to perform the gradient unwarping off-line as a post-processing step.


21 Rapid whole body B1 mapping using continuously moving table imaging at 3 Tesla
Saikat Sengupta1, David S Smith1, and Edward Brian Welch1
1Department of Radiology, Vanderbilt University, Nashville, TN, United States
In this abstract, we present an approach for rapid mapping of the whole body B1 field at 3 Tesla. We use a combination of dual interleaved TR B1 mapping with continuously moving table imaging to measure the B1 field in the whole body in 90 seconds. Considerable variation is observed in the B1 distribution in different sections of the body. This measurement will serve as the basis for dynamic B1field shimming with the moving table for whole body imaging in future work.  


22 Automatic Gradient Predistortion Applied to Clinical 2D-UTE
Kevin D Harkins1, Mary Katherine Manhard1,2, William A Grissom1,2,3, and Mark D Does1,2,3,4
1Institute of Image Science, Vanderbilt University, Nashville, TN, United States, 2Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 3Electrical Engineering, Vanderbilt University, Nashville, TN, United States, 4Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States
Transient gradient waveform errors can degrade MRI quality. This work presents an automatic implementation of gradient waveform predistortion, which has been applied to half-pulse excited 2D-ultrashort echo time imaging. The predistortion method reliably improves image quality and quantification of ultrashort T2 species by reducing out-of-slice signal that contaminates half-pulse excited images. 


23 Assessment of geometric distortion in six clinical scanners using a 3D-Printed Grid Phantom
Maysam M Jafar1, Christopher E Dean1, Malcolm J Birch1, and Marc E Miquel1
1Clinical Physics, Barts Health NHS Trust, City of London, United Kingdom
Major hardware-related geometric distortions in MRI arise from gradient field non-linearity and static field inhomogeneity.  For an accurate mapping of geometrical distortion in 3D, the number of control points must be sufficiently large to provide a comprehensive mapping of the spatial variation of distortion and the positional accuracy of these control points must be ensured. In this study, the spatial accuracy of coordinates in 3D space is assessed across six clinical MRI scanners at both 1.5T and 3T field strengths using a previously reported 3D-printed grid phantom. This is a cost-effective approach to determine the spatial accuracy of control points.


24 Characterising and Modelling Susceptibility Artifacts in the Mouse Brain at 9.4 T
Rosie Goodburn1, Nicholas Powell2,3, James O’Callaghan2, Simon Walker-Samuel2, and Karin Shmueli1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom, 3UCL Centre for Medical Imaging Computing, London, United Kingdom
Susceptibility artifacts hamper gradient-echo MRI of the mouse brain at 9.4 Tesla. Here, we characterised and modelled magnetic field maps aiming to improve preclinical mouse MRI. To characterise field perturbations, we measured and coregistered field maps in 7 mice to create a group-average field map. Next, a Fourier forward model was used to simulate a field map based on a susceptibility distribution constructed from the group-average magnitude image. The measured and modelled field maps showed similar qualitative field patterns, especially around the aural air cavities, but had quantitative differences. Work is ongoing to improve the accuracy of the model.
Exhibition Hall 

11:30 - 12:30

    Computer #

25 Zero Echo Time imaging of ocular tumours at 7T
Jan-Willem Beenakker1, Joep Wezel1, Gregorius Luyten1, Andrew Webb1, and Peter Boernert1,2
1Leiden University Medical Centre, Leiden, Netherlands, 2Philips Research Laboratories, Hamburg, Germany
MRI is becoming an increasingly valuable non-invasive tool in ocular tumour assessment and treatment planning. ophthalmology. High resolution images acquired at high field provide multi-dimensional information on tumour size. However, image quality is often compromised by eye motion which is often triggered by gradient noise In the present work the use of magnetization prepared 3D Zero Echo Time imaging (ZTE) is proposed, enabling for almost silent volumetric scanning at isotropic resolution. An initial validation showing the potential of the ZTE approach at 7T for is shown in volunteers and tumour patients.


26 In-vivo detection of oscillatory magnetic field with an oscillatory-selective detection (OSD)
Yuhui Chai1, Jingwei Sheng1, Bing Wu2, Yang Fan2, and Jia-Hong Gao1
1Center for MRI Research, Peking University, Beijing, China, People's Republic of, 2GE Healthcare, MR Research China, Beijing, China, People's Republic of
In-vivo detection of oscillatory magnetic field may lead to fundamental development of functional MR imaging. The recently developed spin-lock oscillatory excitation (SLOE) method exhibited sub-nanotesla level of sensitivity. However its application in vivo is troubled by main field inhomogeneity. In this work, an oscillatory-selective detection (OSD) is proposed to overcome this limitation and hence to improve sensitivity of in-vivo detection of oscillatory magnetic field. OSD has also been verified as a viable tool in mapping transcranial alternating current.


27 Simultaneous Spin Echo and Gradient Echo Imaging with Controlled Aliasing and Parallel Imaging Reconstruction
Mengye Lyu1,2, Victor B. Xie1,2, Patrick G. Peng1,2, Edward Hui3, and Ed X. Wu1
1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China, People's Republic of, 2Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China, People's Republic of, 3Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong SAR, China, People's Republic of
We propose a method to simultaneously acquire spin echo and gradient echo and form two images with distinct contrasts. The spin echo and gradient echo are created by phase-cycled RF pulses, so that they are shifted from each other in image space. In reconstruction, coil sensitivity information can be used to separate them. This study demonstrates the feasibility of extracting multiple echo components using controlled aliasing and parallel imaging reconstruction.


28 Single-shot T2 mapping through overlapping-echo detachment planar imaging (OLED) sequence
Congbo Cai1, Yuchuan Zhuang2, Shuhui Cai3, Jianhui Zhong2, and Zhong Chen3
1Department of Communication Engineering, Xiamen University, Xiamen, China, People's Republic of, 2Department of Imaging Sciences, University of Rochester, ROCHESTER, NY, United States,3Department of Electronics Science, Xiamen University, Xiamen, China, People's Republic of
Magnetic Resonance parameters mapping can provide useful quantitative information for characterization of tissue properties. However, the long acquisition time usually hinder the real-time MR parameter mapping. In this abstract, a novel single-shot T2 mapping method was proposed based on spin-echo EPI method. Two overlapping echo signals with the different T2 weighting were obtained simultaneously. A detachment algorithm based on joint sparsity constraint was proposed to separate the two echo signals. The robustness and efficiency of the sequence were demonstrated through phantom experiments. The reliable T2 mapping can be obtained in the order of milliseconds.


29 Simultaneous Quantification of T1, T2 and Diffusion with Diffusion-weighted drive-equilibrium prepared Magnetic Resonance Fingerprinting
Yun Jiang1, Jesse I. Hamilton1, Katherine L. Wright2, Dan Ma2, Nicole Seiberlich1, Vikas Gulani1,2, and Mark A. Griswold1,2
1Department of Biomedical Engineering, Case Western Reserve University, Clevleand, OH, United States, 2Department of Radiology, Case Western Reserve University, Clevleand, OH, United States
The purpose of this study is to develop a method for simultaneous quantification of T1, T2, and diffusion within the MR Fingerprinting (MRF) framework. Multiple diffusion-weighted driven-equilibrium modules are inserted into the MRF-FISP acquisition in this study. The results from the prostate show the promising ability of this combination of MRF-FISP and diffusion preparation modules to quantify relaxation parameters along with diffusion in one scan.


30 Multi-shot Magnetic Resonance Fingerprinting using Saturation Recovery Preparation Pulse
Xiao Chen1, Christopher C. Cline1,2, Boris Mailhe1, Qiu Wang1, and Mariappan S. Nadar1
1Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, United States, 2Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
In MRF, a single image is reconstructed from data collected from each short TR due to the non-repeatable magnetization history. The highly-undersampled single-shot imaging leads to high levels of noise and artifacts. In this study, an SR preparation module was introduced to MRF, enabling multi-shot MRF without a waiting time for magnetization recovery. The SR prepared multi-shot MRF can achieve similar or even better accuracy than the original single-shot IR prepared MRF with the same amount of data collected.


31 Optimizing MRI contrast with optimal control theory
Eric Van Reeth1, Hélène Ratiney1, Michael Tesch2, Steffen Glaser2, and Dominique Sugny3
1CREATIS, Université de Lyon ; CNRS UMR5220 ; Inserm U1044 ; INSA-Lyon ; Université Claude Bernard Lyon 1, Lyon, France, 2Department of Chemistry, Technische Universität München, Munich, Germany, 3Laboratoire Interdisciplinaire Carnot de Bourgogne (ICB), UMR 5209 CNRS-Université de Bourgogne, Dijon, France
Magnetic Resonance Imaging (MRI) uses the difference in tissue relaxation times to create contrast. Various image weightings can be obtained by tuning acquisition parameters which are usually empirically defined. In this article, optimal control theory is used to design excitation pulses that produce the optimal contrast between given tissues. The designed pulses are tested on numerical phantoms with and without magnetic field inhomogeneities and for the first time in vitro on a small-animal MRI. The reasonable match between simulation and real experiments is promising for the development of such pulses in further in vivo applications.


32 Correction of Phase Offset Induced From Eddy Current in MR Phase Contrast Cine Flow Measurement of Cerebrospinal Fluid in the Cervical Spine
Kwan-Jin Jung1, Andrea Willhite2, and Susan Harkema2
1Radiology, University of Louisville, Louisville, KY, United States, 2Neurosurgery, University of Louisville, Louisville, KY, United States
The phase offset in the phase contrast MR flow imaging was corrected using an image-based method in order to account for the spatially inhomogeneous and subject-dependent phase offset. The phase shift on the flow region was estimated iteratively from the phase shift of the stationary tissue using the low spatial distribution of the phase offset. This phase offset correction method with an automated segmentation and iterative estimation of the phase offset allowed us to study the cerebrospinal fluid flow in the spinal subarachnoid space of ten healthy and ten spinal cord injury participants reliably without elaborate manual effort.


33 MR artifacts removal using sparse + low rank decomposition of annihilating filter based Hankel matrix
Kyong Hwan Jin1, Dongwook Lee1, Paul Kyu Han1, Juyoung Lee1, Sung-Hong Park1, and Jong Chul Ye1
1Dept. of Bio and Brain Engineering, KAIST, Daejeon, Korea, Republic of
In this paper, we propose a sparse and low-rank decomposition of annihilating filter-based Hankel matrix for removing MR artifacts such as motion, RF noises, or herringbone artifacts. Based on the observation that some MR artifacts are originated from k-space outliers, we employ a recently proposed image modeling method using annihilating filter-based low-rank Hankel matrix approach (ALOHA) to decompose the sparse outliers from the low-rank component. The proposed approach can be applied even for static images, because the k-space low rank component comes from the intrinsic image properties. We demonstrate that the proposed algorithm clearly removes several types of artifacts such as impulse noises, motion artifacts, and herringbone artifacts.


34 Gradient Nonlinearity and B0-induced Distortion Corrections of Prospective Motion Correction Data at 7T MRI
Uten Yarach1, Daniel Stucht1, Hendrik Mattern1, Frank Godenschweger1, and Oliver Speck1
1Department of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Magderburg, Germany
Patient motion during an MRI of the brain can result in non-diagnostic image quality. Even with perfect prospective motion (PMC) tracking and correction, the varying coil sensitivity, gradient non-linearity, and B0 field shift can cause significant artifacts that cannot be corrected prospectively. Recently, a model-based MR image reconstruction via iterative solver was employed to minimize the sensitivity misalignment due to physiological movement. In this study, we extended the mentioned model by gradient-warped and B0-induced distortion corrections to reconstruct the PMC MR data. The result shows the improvement that is remarkably reduced artifacts after a few iterations of the proposed technique.


35 Referenceless high order EPI calibration based on multiplexed SENSE - Permission Withheld
Jiazheng Wang1, Bing Wu2, and Yongchuan Lai3
1Radiology Department, University of Cambridge, Cambridge, United Kingdom, 2GE healthcare MR Research China, Beijing, China, People's Republic of, 3GE heathcare China, Beijing, China, People's Republic of
Usually aper-volume or even per-slice basis reference scan is usually needed for correcting the phase inconsistency between odd and even shots attributed to eddy current in EPI. The phase correction is usually first order. In this work, the concept of multiplxed SENSE (MUSE) is extended for EPI N/2 ghost calibration. 


36 Improving functional imaging of the fetal brain using constrained image-based shimming to suppress maternal fat
Andreia S Gaspar1,2, Giulio Ferrazzi1, Rita G Nunes1,2, Emer J Hughes3,4, Shaihan J Malik1, Laura McCabe3,4, Kelly Pegoretti3,4, Mary A Rutherford3,4, Joseph V Hajnal1,4, and Anthony N Price1,4
1Biomedical Engineering, King's College London, London, United Kingdom, 2Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal, 3Perinatal Imaging and Health, King's College London, London, United Kingdom, 4Centre for the Developing Brain, King's College London, London, United Kingdom
Effective suppression of maternal fat is critical for functional imaging of the fetal brain with echo planar imaging (EPI). Localized image-based shimming (IBS) for the fetal brain is required but can provoke high field variation in maternal adipose regions causing fat suppression to fail.  We have addressed this issue by using IBS of the fetal brain with linear constraints across maternal fat regions and optimization of saturation pulse frequency offset. The results showed that is possible to obtain more complete fat supression when combining an optimized pulse offset with a constrained shimming approach without compromising fetal brain shim.


37 Sparse Parameter Global Signal Correction for Resting State fMRI Analysis
Xueqing Liu1, Zhihao Li2, Shiyang Chen2, and Xiaoping Hu2
1Department of Biomedical Engineering, Columbia University, New York, NY, United States, 2Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, Georgia
We describe a novel global signal removal method, sparse parameter global signal regression (SP-GSR), for fMRI data preprocessing. We assume the global signal to be low-rank and the remaining signal can be decomposed into orthogonal regressors with spatially sparse parameters. We demonstrated by simulation that SP-GSR can remove global signal and recovery true correlations without introducing anti-correlations. Application of this method to experimental data led to a more prominent and focused default mode network with isolated negative correlations.


38 Data Acquisition Strategies for Reducing Eddy-Current and Transient Oscillation Artifacts in Balanced Steady-State Free Precession
Hyun-Soo Lee1, Seung Hong Choi2, and Sung-Hong Park1
1Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea, Republic of, 2Department of Radiology, Seoul National University College of Medicine, Seoul, Korea, Republic of
The quality of balanced steady-state free precession is vulnerable to eddy-currents and transient oscillations. However, the conventional centric phase-encoding (PE) scheme makes these artifacts severe, thus needs additional compensation strategies. In this study, we propose an improved PE scheme where k-space is encoded from center to periphery in a group-wise manner (PE-grouping). This reduces related artifacts by preventing big jumps in k-space along PE direction. Also proposed were various averaging strategies that could further eliminate the residual artifacts by averaging two full images acquired not only with the PE-grouping, but also with the conventional centric and pairing schemes.


39 An effective way of overcoming TE variation in single-refocusing spatiotemporal-encoding imaging.
JaeKyun Ryu1,2, Joonsung Lee1,2, Seong-gi Kim1,2, and Jang-Yeon Park1,2
1Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Korea, Republic of, 2Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of
RASER(Rapid Acquisition by Sequential Excitation and Refocusing) sequence acquires all the echoes with same TE by using two refocusing pulses [1], whereas other spatiotemporal-encoding(SPEN) techniques using a single-refocusing pulse offers a shorter effective TE than RASER but with varying TE, thereby causing signal variation in the SPEN dimension [2]. Here, we propose an effective way of overcoming this problem of TE variation in single-refocusing SPEN imaging.


40 Improved gradient warping correction for large field-of-view imaging and application to radiation therapy planning
Paul T. Weavers1, Shengzhen Tao1, Kiaran McGee1, Joshua Trzasko1, Yunhong Shu1, Erik Tryggestad2, Ken-Pin Hwang3, Seung-Kyun Lee4, Thomas KF Foo4, and Matt Bernstein1
1Mayo Clinic, Rochester, MN, United States, 2Radiation Oncology, Mayo Clinic, Rochester, MN, United States, 3MD Anderson, Houston, TX, United States, 4GE Global Research, Niskayuna, NY, United States
Radiation therapy, especially proton beam therapy requires exacting spatial accuracy to deliver a sterilizing dose of ionizing radiation to the target volume with confidence.  The superior soft tissue contrast afforded by MRI vs. CT has increased interest in using MRI for treatment planning.  However, gradient non-linearities reduce the spatial accuracy of MRI.  We have developed a fiducial phantom based calibration procedure to map these gradient nonlinearities on a system-specific basis and generate up to 9th order spherical harmonic coefficients for correction.  These coefficients show improved spatial accuracy vs. standard 5th order, especially at distances >400mm from magnet and gradient isocenter.


41 Calibration-free EPI trajectory error correction by k-space data consistency
Julianna D. Ianni1,2 and William A. Grissom1,2,3,4
1Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 2Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States,3Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States, 4Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States
A method for automatic correction of EPI trajectory errors is presented.  The method is an iterative parallel imaging reconstruction which uses k-space data consistency to correct image artifacts. An advantage of the method is that it requires no calibration data and allows correction of non-static errors such as those due to gradient coil heating.


42 Measurement of magnetic susceptibility of commonly implanted metals from commercial prostheses
Matthew Robert Smith1, Jin Jung Kweon2, Eun Sang Choi2, Curtis Wiens1, Nathan Artz3, and Scott B Reeder1,4
1Radiology, University of Wisconsin, Madison, WI, United States, 2Florida State University, Tallahassee, FL, United States, 3St. Jude's Children's Hospital, Memphis, TN, United States, 4Medical Physics, University of Wisconsin, Madison, WI, United States
Despite important recent development, further progress of MR imaging around metallic prostheses is dependent on the ability to model the field perturbations surrounding the prostheses. These calculations require knowledge of the magnetic susceptibility of the metal which is not reported by the manufacturers. The purpose of this work was to estimate the magnetic susceptibility of commonly implanted metal alloys by measuring the magnetic moment across a range of clinical field strengths (0-5 Tesla) using a SQUID (Superconducting QUantum Interference Device) magnetometer. Linearity of the susceptibility across field strengths was also assessed.


43 Phase drift effect correction for MR Thermometry using magnetic field monitoring
Daniel Daniel Hernandez1, Eric Michel1, Ki Soo Kim1, and Soo Yeol Lee1
1Bio-medical engineering, Kyung Hee University, Yogin, Korea, Republic of
We propose a method to correct phase drift artifact from MR thermometry measurements with the use of Magnetic field monitoring (MFM). Field variations are measured with an array of MFM probes and correction maps are computed from the frequency shifts of FID signals. This method allows to have better resolution and can be used with any MR thermometry pulse sequence.


44 Reference-free Nyquist ghost removal in single-shot SPEN MRI using phase-corrected partial Fourier reconstruction
Ying Chen1, Song Chen1, Hui Liu2, Zhong Chen3, and Jianhui Zhong1,4
1Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, China, People's Republic of, 2MR Collaboration Northeast Asia, Siemens Healthcare, Shanghai, China, People's Republic of, 3Department of Electronic Science, Xiamen University, Xiamen, China, People's Republic of, 4Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, China, People's Republic of
Single-shot SPEN MRI is a technique capable of retaining the time efficiency of single-shot EPI but with significantly reduced geometric distortions. Akin to EPI, the phase inconsistency between even and odd echoes also result in Nyquist ghosts in SPEN images. This work is to present a scheme with more reliable performance than the previously reported Nyquist ghost correction method. Experimental results of human brains and in vivo rats show that the proposed method can remove ghosts without introducing blurring, and unwarping procedures can be conducted on the ghost-corrected data for further distortion correction.


45 Comparison of methods for choosing radial spoke directions in 3D UTE
Mark BYDDER1, Wafaa Zaaraoui1, and Jean-Philippe Ranjeva1
1Aix Marseille Université, MARSEILLE, France
Several algorithms for choosing the radial spoke directions were evaluated for use in 3D UTE imaging. It was observed that methods that produce a highly regular set of directions result in higher aliasing than those that are more irregular.


46 Flow-induced artifacts in two-point Dixon MRI: Incidence, severity and potential diagnostic pitfalls.
Tilman Schubert1, Peter Bannas2, Samir Sharma3, Sonja Kinner1, Mahdi Rahimi3, Frank Korosec3, and Scott Reeder1
1Radiology, University of Wisconsin Madison, Madison, WI, United States, 2Radiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 3Medical Physics, University of Wisconsin Madison, Madison, WI, United States
Chemical shift based two-point “Dixon” MRI with bipolar readout gradients may produce flow induced fat-water misallocation artifacts. These artifacts have the potential to mimic intravascular thrombus. We reviewed 100 cases of two-point body MRI exams to characterize the incidence, location and severity of these artifacts. Artifacts appeared in 46% of the cases, with  severe artifacts in 20% and mild artifacts in 26% of the patients. Given this high number of potentially thrombus-mimicking, flow-induced artifacts, radiologists should be aware of this potential pitfall when using two-point fat-water separation methods.


47 Two-Step Generic Referenceless Phase Combination (GRPC) for accurate phase image reconstruction from multiple receiver coils
Francesco Santini1,2, Mathieu D Santin3, Paulo Loureiro de Sousa4, and Oliver Bieri1,2
1Radiological Physics, University of Basel Hospital, Basel, Switzerland, 2Department of Biomedical Engineering, University of Basel, Basel, Switzerland, 3Institut du Cerveau et de la Moelle épinière, Hôpital Pitié-Salpêtrière, Paris, France, 4CNRS, ICube Laboratory, FMTS, Université de Strasbourg, Strasbourg, France
This work presents a method to combine the signal from multiple coils in order to obtain a coherent phase image. The methods is agnostic to the acquisition protocol and the coil geometry, and does not require operator interaction.


48 Image-based phase correction for dual-band EPI with slice-GRAPPA using point-by-point procedures in k-space
Hiroshi Toyoda1, Sosuke Yoshinaga2, Naoya Yuzuriha2, and Hiroaki Terasawa2
1CiNet, NICT, Suita, Japan, 2Department of Structural BioImaging, Kumamoto University, Kumamoto, Japan
We proposed an Image-based phase correction for dual-band EPI with slice-GRAPPA using point-by-point procedures in k-space. The results showed the usefulness and robustness of the proposed method compared with the conventional approach.
Exhibition Hall 

11:30 - 12:30

    Computer #

49 A combinatorial model approach for feature selection from multimodal MRI data
Xiaowei Zhuang1, Virendra Mishra1, Karthik Sreenivasan1, Charles Bernick1, Sarah Banks1, and Dietmar Cordes1,2
1Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States, 2Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States
Clinical applications of brain abnormality detection with supervised machine learning techniques are limited due to less and unbalanced sample sizes as compared to rich feature sets in patient population. We proposed a new combinatorial model approach, fs-RBFN, involving sampling from multivariate joint distribution, LASSO feature selection, RBFN cross validation, and inverse probability weighting to solve this problem. The proposed approach was validated against a ground truth phantom and further tested on a multimodal MRI dataset for cognitively impaired and non-impaired professional fighters. Our results suggest superior performance of this technique over several other out-of-the-bag feature selection algorithms.


50 Three-dimensional lung tumour motion tracking using an advanced template matching technique: Texture Reformatted Angle Correlation (TRAC)
Kevin K. Zhang1,2, Shivani Kumar2,3, Robba Rai3, Armia George3, Bin Dong1,4, and Gary P. Liney1,2,3,4
1Ingham Institute for Applied Medical Research, Sydney, Australia, 2South Western Sydney Clinical School, University of New South Wales, Sydney, Australia, 3Department of Medical Physics, Cancer Therapy Centre, Liverpool Hospital, Sydney, Australia, 4Centre for Medical Radiation Physics (CMPR), University of Wollongong, Sydney, Australia
Real-time lung tumour tracking and motion analysis is important in MRI-based radiotherapy planning to inform treatment margins and to permit accurate delivery for developing MR-Linac technology. This work describes a template matching approach to provide 3D motion assessment of lung tumours from real-time 2D images. Compared to previous work the TRAC technique utilises a multi-angled correlation analysis of the target region to correctly identify the tumour position. Results in both a moving phantom and in lung cancer patients show that the technique is feasible, accurate and can be easily adopted in widely used single plane cine imaging.


51 Renal segmentation from non-contrast T1-weighted MR images
Nicole Wake1, Jeremy C Lim2, Artem Mikheev1, Jas-mine Seah3, Elissa Botterill2, Shawna Farquharson4, Henry Rusinek1, and Ruth P Lim2,5
1Bernard and Irene Schwartz Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University School of Medicine, New York, NY, United States, 2Department of Radiology, Austin Health, Melbourne, Australia, 3Department of Endocrinology, Austin Health, Melbourne, Australia, 4Florey Neuroscience Institute, Melbourne, Australia,5The University of Melbourne, Melbourne, Australia
A semi-automatic renal segmentation technique for non-contrast T1-weighted MR images was developed.  Renal segmentation and volumetric analysis was tested in ten healthy volunteers and ten Type I diabetic patients. We found that this segmentation tool is fast, reliable, and requires minimal user interaction. Upon further validation, this method has clinical potential for monitoring renal status in appropriate patient populations.


52 Exploring abnormal arch shape patterns using CMR-based hierarchical 3D shape clustering: Application to a generic imaging population of repaired coarctation of the aorta
Jan L Bruse1, Abbas Khushnood1, Tain-Yen Hsia1, Andrew M Taylor1, Vivek Muthurangu1, and Silvia Schievano1
1Centre for Cardiovascular Imaging, UCL Institute of Cardiovascular Science & Great Ormond Street Hospital for Children, London, United Kingdom
We present a novel method for hierarchical 3D shape clustering of aortic arch shape models segmented and reconstructed from CMR imaging data. We apply the method to a cohort of 45 patients post aortic coarctation repair in order to explore previously unknown arch shape patterns that may relate to clinical outcome. Exploring a pathologic shape population using data mining and statistical shape modeling techniques can provide novel insight for improved diagnosis and treatment strategies and can thereby assisst in clinical decision making when analysing complex cases.


53 Direct CT conversion from a single ultra-short echo sequence
Soumya Ghose1, Jason Dowling1, Robba Rai2, Benjamin Schmitt3, and Gary Liney2,4,5,6
1eHealth, CSIRO, Brisbane, Australia, 2Liverpool Cancer Therapy Centre, Liverpool, Australia, 3Siemens Healthcare Pty Ltd, Macquarie Park, Australia, 4Medical Physics, Ingham Institute, Liverpool, Australia, 5UNSW Australia, Liverpool, Australia, 6University of Wollongong, Wollongong, Australia
Accurate conversion of MRI into attenuation correction maps is of current interest in PET-MR and MR-only radiotherapy planning in particular, where electron density calculation is particularly demanding and usually derived from CT. MRI methods to date have usually involved building a patient atlas and/or use of multiple imaging sequences and are time intensive. We propose a new single sequence approach based on ultra-short echo time to identify tissue classes of air, bone and soft-tissue in combination with a dynamic clustering regression based model that provides a direct CT conversion which is both efficient and accurate. 


54 Non-invasive estimation of arterial input function for imaging of cerebral blood flow on a PET/MR scanner
Mohammad Mehdi Khalighi1, Audrey Peiwen Fan2, Gaspar Delso3, Praveen K. Gulaka2, Bin Shen4, Aileen Hoehne4, Prachi Singh2, Jun-Hyung Park4, Dawn Holley2, Frederick T. Chin2,4, and Greg Zaharchuk2,4
1Applied Science Lab, GE Healthcare, Menlo Park, CA, United States, 2Radiology Department, Stanford University, Stanford, CA, United States, 3Applied Science Lab, GE Healthcare, Zurich, Switzerland,4Molecular Imaging Program, Stanford University, Stanford, CA, United States
Accurate measurement of Arterial Input Function (AIF) is essential in quantitative analysis of cerebral blood flow (CBF) using 15O-H2O PET imaging. The time-of-flight enabled Signa PET/MR scanner (GE Healthcare, Waukesha, WI, USA) provides quality PET images during the arrival of 15O-H2O tracer to the brain arteries, which can be used for carotid artery segmentation. The optimal time frame to segment these brain arteries for image-based AIF, is found by binning the PET list file every second and plotting the total number of true and scatter coincident events over time.


55 Partial volume correction of quantitative susceptibility maps for oxygen extraction fraction measurements.
Phillip G. D. Ward1,2, Audrey P. Fan3, Parnesh Raniga1, David G. Barnes2,4, David L. Dowe2, and Gary F. Egan1,5
1Monash Biomedical Imaging, Monash University, Clayton, Australia, 2Faculty of Information Technology, Monash University, Clayton, Australia, 3Lucas Center for Imaging, Department of Radiology, Stanford University, Stanford, CA, United States, 4Monash eResearch Centre, Monash University, Clayton, Australia, 5ARC Centre of Excellence for Integrative Brain Function, Melbourne, Australia
Partial volume effects impede the use of quantitative susceptibility maps for assessing small veins. Oxygen extraction fraction measures are particularly sensitive to these effects. We propose a geometric technique for calculating partial volume from binary venograms. The technique is able to calculate accurate partial volume maps, and vessel geometry, on simulated veins of sub-voxel radius. These partial volume maps are used to adjust for partial volume effects in estimating venous magnetic susceptibility.


56 Improving Tissue Segmentation of Brain MRI through Sparsity-guided Super-resolution Imaging
Jean-Christophe Brisset1, Louise E Pape1, Ricardo Otazo1, and Yulin Ge1
1Radiology, New York University School of Medicine, New York, NY, United States
Since human gray matter cortex is a relatively thin structure and has a complex folding pattern blended with white matter and cerebrospinal fluid (CSF), partial volume effect is always considered a challenging issue for precise tissue segmentation. Super-resolution (SR) is a common method that is often used in the picture world to recover a high-resolution image from low-resolution images. This study was performed to test whether a newly developed sparsity-guided SR algorithm can be adapted on standard clinical MRI images to improve brain tissue segmentation by decreasing partial volume effect.


57 Data and cluster-extent based thresholding to analyze statistical parametric maps in the study of knee articular cartilage biochemical composition.
Allison B Randolph V1, Valentina Pedoia1, Lorenzo Nardo1, and Sharmila Majumdar1
1Radiology & Biomedical Imaging, UCSF, San Francisco, CA, United States
Voxel-based relaxometry (VBR) allows for MR relaxtion time analysis without the sometimes deletorious assumtions of traditional ROIs. However, VBR introduces potentially new analysis issues, such as noise and map heterogeneity. In this study we propose to use VBR significance thresholding in conjunction with cluster-extent based thresholding to define data-driven  regions of interest (ROIs) that include the most critical information in Statistical Parametric Maps (SPM), controlling the aforesaid issues. The results suggests that the data driven voxel cluster ROIs and predefined traditional ROIs have unique, separate anatomical locations, and that the data-driven clusters perform better when correlated to osteoarthritis (OA) disease markers. 


58 Automatic organ-specific localization and quantification of fat in abdominal chemical shift encoding-based water-fat MRI: application to weight-loss in obesity
Jun Shen1, Thomas Baum2, Christian Cordes2, Beate Ott3, Claudia Eichhorn3, Thomas Skurk3,4, Hendrik Kooijman5, Ernst J Rummeny2, Hans Hauner3,4, Bjoern H Menze1, and Dimitrios C Karampinos2
1Department of Computer Science, TU Munich, Munich, Germany, 2Department of Radiology, TU Munich, Munich, Germany, 3Else Kröner Fresenius Center for Nutritional Medicine, TU Munich, Munich, Germany, 4ZIEL Research Center for Nutrition and Food Sciences, TU Munich, Munich, Germany, 5Philips Healthcare, Hamburg, Germany
The accumulation and regional distribution of abdominal adipose tissue and organ fat plays an important role in several diseases including obesity, metabolic syndrome and diabetes. The present work proposes a fully automatic method for abdominal organ segmentation and adipose tissue classification and measurement based on chemical shift encoding-based water-fat MR images. The results from the automatic method showed very good agreement with the manually created references. The developed automatic algorithm allowed the detection of regional differences in changes of adipose tissue depots in a study of 20 obese women undergoing a calorie restriction intervention.


59 Semi-Automatic Comparison of Myocardial Tissue Injury using a Non-Rigid Registration Method in patients with non-ischemic disease
Leili Riazy1, Simone Fritzschi2,3, Arthur Stötzner2,3, Fabian Mühlberg2,3, Luisa Schmacht2,3, Matthias Dieringer1,2,4, Florian von Knobelsdorff-Brenkenhoff2,3, Thoralf Niendorf1,2, and Jeanette Schulz-Menger2,3
1Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck Center for Molecular Medicine, Berlin, Germany, 2Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center (ECRC), Berlin, Germany, 3Department of Cardiology and Nephrology, HELIOS Klinikum Berlin Buch, Berlin, Germany, 4Siemens Healthcare GmbH, Erlangen, Germany
Late Gadolinium Enhancement (LGE) is the noninvasive gold standard for focal fibrosis, parametric mapping with and without contrast-media enable detection of diffuse fibrosis. We developed a non-rigid registration method to superimpose LGE images and T1-Maps allowing for pixel-wise comparison of LGE extent and abnormal T1 times. We observed significantly larger regions of ECV, T1 native and post-contrast abnormalities than LGE positive areas. However, LGE was not always completely covered by abnormalities of any of the mentioned parameters.


60 MRI-guided PET image denoising using a non-local means filter
Marie Anne Richard1, Réjean Lebel1, Jérémie P. Fouquet1, and Martin Lepage1
1Centre d'imagerie moléculaire de Sherbrooke, Université de Shebrooke, Sherbrooke, QC, Canada
Positron emission tomography (PET) images suffer from statistical noise, especially in short time frames. For applications requiring high temporal resolution, such as dynamic studies, efficient edge-preserving denoising algorithms such as the non-local means filter (NLMF) are needed. Because this filter relies on structural data, coregistered MR images were used to guide the NLMF. This novel method was compared to conventional PET-guided NLMF and proved superior in terms of increased contrast-to-background ratio and signal-to-noise ratio in a phantom model. It also increased small structure resolution in a rat model.


61 THOMAS: Thalamus Optimized Multi-Atlas Segmentation at 3T
Jason Su1, Thomas Tourdias2, Manojkumar Saranathan3, Pejman Ghanouni4, and Brian Rutt4
1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Neuroradiology, Bordeaux University Hospital, Bordeaux, France, 3Radiology, University of Arizona, Tucson, AZ, United States,4Radiology, Stanford University, Stanford, CA, United States
The efficacy of the Thalamus Optimized Multi-Atlas Segmentation (THOMAS) algorithm for segmentation of thalamic nuclei with white-matter-nulled MP-RAGE images is studied in 3T and 7T variants of the image contrast. 5 subjects are evaluated at both field strengths and ground truth manual delineations of nuclei are performed on the 7T images. We demonstrate that the algorithm performs as well on 3T images as on 7T within a dice coefficient of ±0.1 as evaluated against the ground truth. This indicates that THOMAS can now reach a much wider audience of interested groups.


62 Evaluation of feature-driven clustering of dynamic contrast enhanced and oxygen enhanced MRI data to assess tumour microenvironment heterogeneity
Adam K Featherstone1,2, James P B O'Connor2,3, Ross A Little1, Yvonne Watson1, Sue Cheung1, Kaye J Williams2,4, Julian C Matthews1,2, and Geoff J M Parker1,2,5
1Centre for Imaging Sciences, The University of Manchester, Manchester, United Kingdom, 2CRUK & EPSRC Cancer Imaging Centre in Cambridge and Manchester, Cambridge and Manchester, United Kingdom, 3Institute of Cancer Sciences, The University of Manchester, Manchester, United Kingdom, 4School of Pharmacy, The University of Manchester, Manchester, United Kingdom, 5Bioxydyn Ltd., Manchester, United Kingdom
DCE-MRI and OE-MRI scans were performed on 8 preclinical U87 tumour xenografts. Heuristic features (area-under-curve and rate-of-enhancement) were calculated from tumour voxel enhancement curves for each imaging modality. Clustering algorithms (k-means clustering and Gaussian mixture modelling) were applied to these features and native tissue T1 to investigate their utility in characterising physiological heterogeneity in tumours. Efficacy in identifying large regions where there is agreement between features is shown. Further optimisation is needed to optimise the approach to characterise smaller, and potentially important, regions where there is a lack of concordance between features.



63 Automatic sodium maps reconstruction using PatchMatch algorithm for phantom detection
Ferran Prados1,2, Bhavana S Solanky2, Patricia Alves Da Mota2, Manuel Jorge Cardoso1, Wallace J Brownlee2, Niamh Cawley2, David H Miller2, Xavier Golay3, Sebastien Ourselin1, and Claudia Angela Michela Gandini Wheeler-Kingshott2,4
1Translational Imaging Group, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom, 3Brain Repair & Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom, 4Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy
Quantitative sodium magnetic resonance imaging (23Na-MRI) enables the non-invasive measurement of in vivo total 23Na concentration (TSC) in the human brain. This involves a complex process of reconstructing datasets acquired to calculate a TSC map. Quantitative TSC map calibration relies on external reference phantoms with known concentration for linear calibration. This commonly involves manually segmenting the phantoms by trained raters, hindering automatic image analysis, and presenting a bottleneck in the TSC computation. We propose to substitute the manual segmentation by OPAL, a novel, fast, robust and reliable technique for segmenting sodium phantoms that allows fully-automatic reconstruction of TSC maps.


64 Dynamic Whole-Brain Connectivity underlying Abnormal Brain States in Late-onset Depression
Mingze Xu1,2, Shiyang Chen2, Bing Ji2,3, Jiuquan Zhang4, Huaiqiu Zhu1, Yi Zhang5, Yonggui Yuan6, Jiahong Gao1, Yijun Liu1, and Xiaoping Hu2
1Biomedical Engineering, Peking University, Beijing, China, People's Republic of, 2Biomedical Engineering, Emory University & Georgia Institute of Technology, Atlanta, GA, United States, 3University of Shanghai for Science & Technology, Shanghai, China, People's Republic of, 4Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, China, People's Republic of,5School of Life Science and Technology, Xidian University, Shaanxi, China, People's Republic of, 6Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China, People's Republic of
We conducted dynamic whole-brain connectivity analysis in Late-onset depression (LOD) to investigate alterations in brain networks. All subjects’ ROI-to-ROI dynamic FC were explored using a data-driven method to obtain the most explanatory states. Each state indicate a particular ROI-to-ROI FC pattern. The property of each state were determined based on its scores across time. Besides decreased FC in normal state, we found LOD patients switch between brain states more frequently and tend to enter LOD-risk states, due to and its high states variance and dominating increased FC in LOD-risk states. These results suggest neural mechanisms of disorder from dynamic perspective.


65 Application of Partial Least Squares regression for Fast and Robust Dictionary Matching for Magnetic Resonance Fingerprinting
Shivaprasad Ashok Chikop1, Vimal Chandran2, Imam Shaik1, Rashmi Rao1, Mauricio Antonio Reyes Aguirre2, and Sairam Geethanath1
1Medical Imaging Research Center, Dayananda Sagar Institutions, Bangalore, India, 2Institute of Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
The step size of the parameters used for simulation of dictionary determines the parameters being determined. Partial Least squares (PLS) can be used as a general frame work for fast and robust dictionary matching. Regression co-efficient matrix obtained from PLS can be used for localizing the different brain tissue types thus avoiding iterative searching.  The increase in contrast between the grey matter and white matter can be attributed to the intermediate values generated by PLS based matching. PLS matches comparatively better at low SNR images compared to the straight forward dot product method.


66 Cluster Analysis of Dynamic Contrast-Enhanced MRI Pharmacokinetic Parameters for Prostate Cancer Risk Stratification: a Step towards Practical Translation
Saba N Elias1, Guang Jia2, Firas G Petros3, Huyen Nguyen1, Debra L Zynger4, Zarine K Shah5, Ronney Abaza6, and Michael V Knopp1
1Radiology/Wright Center of Innovation, The Ohio State University, Columbus, OH, United States, 2Department of Physics & Astronomy, Louisiana State University, Baton Rouge, LA, United States,3Urology, The Ohio State University, Columbus, OH, United States, 4Pathology, The Ohio State University, Columbus, OH, United States, 5Radiology, The Ohio State University, Columbus, OH, United States, 6Robotic Urologic Surgery, OhioHealth Dublin Methodist Hospital, Dublin, OH, United States
Feasibility of classifying PCa into clusters based on microcirculatory features has the potential to predict outcome and assist in therapeutic treatment of PCa.


67 Pulmonary Imaging Biomarkers of COPD for Personalized Treatment and Better Outcomes
Dante PI Capaldi1, Anthony Lausch2, Khadija Sheikh1, Fumin Guo1, David G McCormack3, and Grace Parraga1
1Robarts Research Institute, The University of Western Ontario, London, ON, Canada, 2Credit Valley Hospital, Mississauga, ON, Canada, 3Department of Medicine, The University of Western Ontario, London, ON, Canada
In this proof-of-concept demonstration, we developed and generated multimodal-parametric-response-mapping (mPRM) from CT and MRI pulmonary measurements to phenotype chronic obstructive pulmonary disease (COPD).  We performed principal component analysis of the voxel distribution generated from co-registered inspiration or expiratory CT with  3He MRI SV cluster maps and 3He MRI ADC maps for ex-smokers with and without COPD.  Further work is necessary to determine the appropriate combination of imaging biomarkers generated from MRI and CT to provide useful information in deeply phenotyping COPD.


68 Brain Connectivity Analysis of Parkinson's Disease and “Scans Without Evidence for Dopaminergic Deficit" Patients
Tiago Constantino1,2,3, André Santos Ribeiro4, Ricardo Maximiano3, John Mcgonigle4, David Nutt4, and Hugo Alexandre Ferreira3
1Lisbon School of Health Technology-ESTeSL, Lisbon, Portugal, 2Spitalzentrum Biel, Biel, Switzerland, 3Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal, 4Centre for Neuropsychopharmacology, Imperial College London, London, United Kingdom
In this work we propose a comparison study between “Scans Without Evidence for Dopaminergic Deficit" (SWEDD) and Parkinson’s Disease (PD) patients against healthy subjects using the MIBCA toolbox. Here, we studied the difference in imaging and connectivity metrics obtained from anatomical (T1-weighted) and structural (Diffusion Tensor Imaging) data between the three groups. Results showed increased mean diffusivity in the frontal pole, rostral middle frontal gyrus and superior frontal gyrus between SWEDD and PD patients,  which can be related with the dopaminergic mesocortical pathway degeneration in PD. These preliminary results help clarify the differences between SWEDD and PD patients.


69 Resolving ambiguity in T1 mapping using complex MRI data
Kees M. van Hespen1, Dirk H.J. Poot1,2, Harm A. Nieuwstadt1, and Stefan Klein1
1Departments of Medical Informatics and Radiology, Erasmus MC, Rotterdam, Netherlands, 2Imaging Science and Technology, Delft University of Technology, Delft, Netherlands
We have recently developed an optimized T1 mapping protocol for carotid atherosclerotic plaque imaging, using a combination of inversion and recovery prepared acquisitions. This protocol requires less images to be taken (and thus shorter acquisition time) for precise T1 estimation than conventional inversion-prepared or saturation-prepared acquisition schemes. However, estimating T1 from magnitude data, acquired with the optimized settings, causes bimodality of T1 estimates, due to the ambiguity in sign of the inversion prepared magnitude images. Simulations and experiments on a hardware phantom and a volunteer show that the ambiguity resolves when we fit a complex-valued model to the complex data.


70 Comparing MRI texture heterogeneity with MTR and myelin water fraction as measures of myelin integrity
Tim Luo1, Shrushrita Sharma2, Mark Polivchuk3, Peng Zhai4, and Yunyan Zhang4
1Bachelor of Health Sciences, University of Calgary, Calgary, AB, Canada, 2Biomedical Engineering Program, University of Calgary, Calgary, AB, Canada, 3Computer Science, University of Calgary, Calgary, AB, Canada, 4Radiology and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
Changes in myelin integrity are associated with many neurological diseases. We acquired 9.4T MRI from healthy mouse brain to evaluate the utility of texture heterogeneity in T2-weighted MRI for assessing myelin integrity, in comparing with proposed measures including magnetic transfer ratio and myelin water fraction. Measurements were focused on the corpus callosum, with both anatomical (genu, body, splenium) and hemispheric (left, center, right) locations evaluated. All 3 methods showed the uniformity of myelin in corpus callosum between hemispheres, and no significant differences between anatomical locations were detected. Texture heterogeneity showed the best consistency between animals and deserves further verification.


71 Color mapping in medical imaging - you're (probably) doing it wrong
Jan-Gerd Tenberge1
1University of Münster, Münster, Germany
Some imaging software packages do not accurately display datasets due to difficulties in color mapping. We  show some of the shortcomings an three of the most widely used tools (FSL, SPM, FreeSurfer) and provide an easy fix that can be applied to correct the images output by these tools.


72 T1 Mapping through Bayesian Analysis with Spatial Information Collaboration (BASIC) using Steady-State-Based Imaging Data - Permission Withheld
Mustapha Bouhrara1 and Richard G. Spencer1
1NIA, NIH, Baltimore, MD, United States
We introduce two Bayesian-based analyses that use spatial information as a prior to improve the quality of voxel-by-voxel T1-mapping from spoiled gradient recalled echo (SPGR) imaging data. These approaches, called BASIC, combine voxel-by-voxel fitting with region-of-interest (ROI) parameter estimation. ROI parameters act as a constraint, while voxel fitting mitigates blurring and detail loss. The results were compared with those derived using a conventional nonlinear least-squares-based algorithm. Estimation of T1 from SPGR imaging data was markedly improved through use of the BASIC methods.

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