Traditional Posters : Diffusion & Perfusion - Neuro
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Diffusion MR: Advanced Signal Models & Reconstruction

Monday May 9th
Exhibition Hall  14:00 - 16:00

1911.   A hierarchy of analytic models for the diffusion MRI signal in brain white matter  
Eleftheria Panagiotaki1, Torben Schneider1,2, Bernard Siow1,3, Mark F Lythgoe3, Matt G Hall1, and Daniel C Alexander1
1Centre for Medical Image Computing, Dept. of Computer Science, University College London, London, United Kingdom, 2Institute of Neurology, University College London, 3Centre for Advanced Biomedical Imaging, University College London

This study aims to identify the minimum requirements for an accurate model of the diffusion MR signal in white matter of the brain. We construct a hierarchy of multi-compartment models of white matter from combinations of simple models for the intra- and the extra-axonal spaces. We devise a new diffusion MRI protocol that provides measurements with a wide range of parameters for diffusion sensitization both parallel and perpendicular to white matter fibres. We use the protocol to acquire data from a fixed rat brain, which allows us to fit, study and compare the different models.

1912.   Statistical Analysis of Apparent Fibre Density: Supra-threshold clustering over space and orientation 
David Raffelt1,2, J-Donald Tournier3,4, Gerard Ridgway5, Stephen Rose6, Robert Henderson7, Stuart Crozier2, Alan Connelly3,4, and Olivier Salvado1
1The Australian E-Health Research Centre, CSIRO, Brisbane, QLD, Australia, 2Biomedical Engineering, School of ITEE, University of Queensland, Brisbane, QLD, Australia, 3Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, VIC, Australia, 4Department of Medicine, University of Melbourne, Melbourne, VIC, Australia, 5Institute of Neurology, University College London, London, United Kingdom, 6Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia, 7Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia

Apparent Fibre Density (AFD) is a new measure based on information provided by Fibre Orientation Distributions. AFD enables voxel-based analysis to be performed over space and orientation, and therefore population differences may be attributed to a single fibre within a voxel containing multiple fibres. Performing comparisons over many orientations within each voxel increases the number of multiple comparisons. We present a method for cluster-based inference of spatially extended differences in AFD by identifying clusters of contiguous supra-threshold directions using neighbours defined in space and orientation. The proposed method is demonstrated using a cohort of Motor Neurone Disease and healthy subjects.

1913.   Rapid Diffusion Spectrum Imaging with Partial q-Space Encoding 
Anh Tu Van1, Rafael O'Halloran1, Samantha Holdsworth1, and Roland Bammer1
1Radiology, Stanford University, Stanford, CA, United States

Despite its much richer information regarding the microstructure of neuronal architectures than other imaging techniques, such as diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), applications of diffusion spectrum imaging (DSI) in in vivo studies are limited due to its long total acquisition time. The current study proposes to significantly speed up DSI by using partially encoding in q-space, similar to partial Fourier encoding in traditional k-space domain. Both phantom and in vivo experiments are done to show the performance of the proposed method. For the experiments presented, the achieved acquisition speed-up was 44.4%.

1914.   Improved sampling patterns for accelerated diffusion spectrum imaging using compressed sensing 
Marion Irene Menzel1, Jonathan Immanuel Sperl1, Ek Tsoon Tan2, Kedar Khare2, Kevin F King3, Xiaodong Tao2, Christopher J Hardy2, and Luca Marinelli2
1GE Global Research, Garching bei München, Germany, 2GE Global Research, Niskayuna, NY, United States, 3GE Healthcare, Waukesha, WI, United States

The combination of undersampled acquisition and reconstruction using compressed sensing enables the acceleration of diffusion spectrum imaging, bringing this application closer to clinical practice. This work evaluates the performance of compressed sensing as a function of data reconstruction size, pattern pa-rameter and specific realization of the random pattern. Among the sampling pattern distributions we tested both in simulations and in vivo data from brains of healthy volunteers, our results demonstrate that Gaussian undersampling performed best. Especially for higher acceleration factors and small matrix sizes the appropriate realization of the sampling pattern from the random distribution has to be chosen carefully.

1915.   Sparsity Characterisation of the Diffusion Propagator 
Etienne Saint-Amant1, and Maxime Descoteaux1
1Computer Science Department, Université de Sherbrooke, Sherbrooke, Québec, Canada

In a Compressed Sensing (CS) framework, we focused on characterizing the sparsity of diffusion propagator from Diffusion Spectrum Imaging (DSI) data. We extensively analyzed the performance of the 3D orthogonal wavelet basis and biorthogonal wavelet basis. We answer important questions such as: What is the best basis? Is biorthogonality showing benefits over orthogonality? What is the best thresholding method? How does this apply in a real human brain dataset?

1916.   Towards Automated Modelling of Maxillofacial Musculature 
Greg Daniel Parker1,2, Nicholas Drage3,4, Paul L Rosin2, A David Marshall2, Stephen Richmond4, John Evans1, and Derek K Jones1
1CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, 2School of Computer Science, Cardiff University, Cardiff, United Kingdom, 3Cardiff Vale NHS Trust, United Kingdom,4School of Dentistry, Cardiff University, United Kingdom

Accurate in vivo estimates of muscle fibre trajectory are desirable for evaluation of subject-specific maxillofacial surgical treatment options. While diffusion tensor MRI provides adequatly reconstructs larger muscles (e.g. calf), fibre crossing inherent to maxillofacial musculature exposes well-known limitations; necessitating alternative analysis methodologies. Constrained spherical harmonic deconvolution demonstrates potential, however current data-driven calibration (optimized for white matter) produce spurious peaks in the fibre orientation density, adversely affecting tractography. With clinical application in mind, we demonstrate an automated tissue-specific calibration which, for the first time, successfully reconstructs complex muscle tissue in vivo and include preliminary results of unsupervised tract segmentation.

1917.   Interpolation of DWI prior to DTI reconstruction, and its validation 
Tim B. Dyrby1, Henrik M Lundell1, Matthew G Liptrot1, Mark W Burke2, Maurice Ptito1,3, and Hartwig R Siebner1
1Danish Research Centre for MR, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 2College of Medicine, Howard University, Washington DC, United States, 3School of Optometry, University of Montreal, Montreal, Canada

We hypothesise that super resolution (SR) of HARDI DWI data can extract anatomical details that are usually obscured by partial volume effects and thus are currently only visible if acquired at higher spatial resolutions. Here we validate a simple SR approach, where DWI data are interpolated prior to reconstruction. Using 8x SR interpolation of low resolution images, acquired from an ex-vivo monkey brain, new anatomical details matching those in a high resolution dataset, became apparent. Higher SR-factors introduced smoothing. Our preliminary results suggest that HARDI DWI data contain hidden anatomical detail that can be extracted with this simple SR approach.

1918.   Fiber Continuity: An Anisotropic Prior for ODF Estimation 
Marco Reisert1, and Valerij Kiselev1
1Medical Physics, University Medical Center Freiburg, Freiburg, Baden Württemberg, Germany

The accurate and reliable estimation of fiber orientation distributions based on diffusion-sensitized magnetic resonance images is a major prerequisite for tractography algorithms or any other derived statistical analysis. In this work we formulate the principle of fiber continuity (FC), which is based on the simple observation that the imaging of fibrous tissue implies certain expectations to the measured images. From this principle we derive a prior for the estimation of fiber orientation distributions based on high angular resolution diffusion imaging (HARDI). We demonstrate on simulated, phantom and in vivo data the superiority of the proposed approach.

1919.   Non-Cartesian Compressed Sensing for Diffusion Spectrum Imaging 
Eric Aboussouan1, Luca Marinelli2, and Ek Tsoon Tan2
1Barrow Neurological Institute, Phoenix, AZ, United States, 2GE Global Research, Niskayuna, NY, United States

Diffusion Spectrum Imaging (DSI) can be accelerated the application of compressed sensing (CS) in the three q-space dimensions. Rather than sampling a subset of a Cartesian q-space, we propose to further minimize coherent aliasing by undersampling q-space according to a non-Cartesian sampling pattern. Simulation and preliminary in vivo results are shown suggesting the validity of the approach.

1920.   Characterizing Complex White Matter Structure from Cube and Sphere Diffusion Imaging with a Multi-Fiber Model (CUSP-MFM) 
Benoit Scherrer1, and Simon K Warfield1
1Radiology, Harvard Medical School, Boston, Massachusetts, United States

Multi-tensor models are of great interest for clinical applications because they enable the assessment of the white matter microstructure in addition to the brain connectivity. We propose a novel acquisition scheme and a novel fitting procedure for multi-fiber assessment. Our acquisition scheme combines spherical and cubic sampling. It enables multiple b-values to be acquired with low geometric and intensity distortion. Our optimization algorithm ensures spatially smooth and consistent positive definite tensors. We evaluate our CUSP-MFM (CUbe+SPhere Multi-Fiber Model) on both synthetic and clinical data. We demonstrate the ability of CUSP-MFM to characterize complex fiber structures from short duration acquisitions.

1921.   Fibres at the Magic Angle Generated by Inappropriate Calibration (MAGIC) 
Greg Daniel Parker1,2, and Derek K Jones1
1CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, 2School of Computer Science, Cardiff University, Cardiff, United Kingdom

Constrained spherical-harmonic deconvolution (CSD) provides resolution of intra-voxel “crossing fibre” orientation through deconvolution of an idealised (calibration) response from spherical harmonics fit to the target diffusion-weighted signal. Given a single-fibre low anisotropy target,we observe that, with high calibration anisotropies, spurious peaks are observed in the resultant deconvolution at elevations (relative to fibre orientation) consistent with the zero crossing (magic angle) and minima of the 2nd order Legendre polynomial, adversely affecting tractography. Bootstrap analysis however indicates that azimuthal distribution of such peaks appears uniform, allowing true “crossing fibre” to be distinguished through measurement of uncertainty.

1922.   Robustness of diffusion scalar metrics when estimated with Generalized Q-Sampling Imaging acquisition schemes 
Marta Morgado Correia1, Guy B Williams2, Frank Yeh3, Ian Nimmo-Smith1, and Eleftherios Garyfallidis1
1MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom, 2Wolfson Brain Imaging Centre, Cambridge, United Kingdom, 3Carnegie Mellon University, Pittsburgh, United States

Generalized Q-Sampling Imaging (GQI) has recently been introduced by Yeh and colleagues and was shown to have comparable accuracy to other well established q-space methods when it comes to resolving crossing fibres. In this study we compared the estimated values of MD, FA and Quantitative Anisotropy (QA) obtained with grid and shell GQI sampling schemes, in terms of their precision and ability to differentiate between different brain fibre populations. Our results suggest that a grid sampling scheme produces more robust results than a single shell acquisition.

1923.   Optimizing the Metric for Brain White Matter Comparisons 
Natasha Lepore*1, Caroline Brun*2, Maxime Descoteaux3, Yi-Yu Chou4, Greig de Zubicaray5, Katie McMahon5, Margie Wright6, Nicholas Martin6, James Gee2, and Paul Thompson *equal contribution7
1Department of Radiology, Children's Hospital, Los Angeles, Los Angeles, CA, United States, 2Department of Radiology, Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States, 3Université de Sherbrooke, Canada, 4Laboratory of NeuroImaging, UCLA, United States, 5University of Queensland, Australia, 6Genetic Epidemiology Lab, QIMR, Australia, 7Laboratory of NeuroImaging, UCLA, Los Angeles, CA, United States

Diffusion MRI is a popular tool used to compare brain white matter structure between groups of subjects. When this technique is used to compare two populations, it is common practice to reduce the sometimes-large number of diffusion gradients to a univariate measure at each voxel, such as the fractional anisotropy. However, we and others have designed voxel-wise comparison methods for HARDI data and used multivariate measures for HARDI group comparisons. Here we compare statistical power for two scalar and two multivariate measures derived from the HARDI signal.

1924.   Compressive Sensing Ensemble Average Propagator Estimation via L1 Spherical Polar Fourier Imaging 
Jian Cheng1,2, Sylvain Merlet2, Aurobrata Ghosh2, Emmanuel Caruyer2, Tianzi Jiang1, and Rachid Deriche2
1Institute of Automation, Chinese Academy of Sciences, Beijing, Beijing, China, People's Republic of, 2INRIA Sophia Antipolis, Sophia Antipolis, Sophia Antipolis, France

Since Diffusion Tensor Imaging (DTI) cannot detect the fiber crossing, many new works beyond DTI has been proposed to explore the q-space. Most works, known as single shell High Angular Resolution Imaging (sHARDI), focus on single shell sampling and reconstruct the Orientation Distribution Function (ODF). The ODF, which has no radial information at all, is just one of features of Ensemble Average Propagator (EAP). Diffusion Spectrum Imaging (DSI) is a standard method to estimate EAP via numerical Fourier Transform (FT), which needs lots of samples and is impractical for clinical study. Spherical Polar Fourier Imaging (SPFI) [1,2] was proposed to represent the signal using SPF basis, then the EAP and the ODF have analytical closed forms. So the estimation of the coefficients is very important. In [1,2], the coefficients are estimated based on a standard Least Square (LS) with L2 norm regularization (L2-L2). In this paper, we propose to estimate A using LS with L1 norm regularization (L2-L1), also named as Least Absolute Selection and Shrinkage Operator (LASSO). And we prove that the L2-L1 estimation of the coefficients is actually the well known Compressive Sensing (CS) method to estimate EAP, which brings lots of Mathematical tools and possibility to improve the sampling scheme in q-space.

1925.   A Bayesian random effects model for enhancing resolution in diffusion MRI 
Martin David King1, Daniel C Alexander2, David G Gadian1, and Chris A Clark1
1Institute of Child Health, University College London, London, United Kingdom, 2Computer Science, University College London, London, United Kingdom

Poor spatial resolution is a limitation in various diffusion MRI applications, including tractography. A Bayesian latent variables random effects model has been developed for increasing effective spatial resolution, based on a Markov random field treatment in which intrinsic Gaussian autoregressive priors are assigned to the fibre spherical coordinates. The model is used to separate crossing-fibres at the junction between the cingulum and corpus callosum, using diffusion MRI data acquired with a moderate b-value and 20 directions. The analyses were performed using Markov chain Monte Carlo simulation. Results demonstrate that a satisfactory separation of the crossing components can be obtained.

1926.   A Riemannian Framework for Ensemble Average Propagator Computing 
Jian Cheng1,2, Aurobrata Ghosh1, Tianzi Jiang2, and Rachid Deriche1
1INRIA Sophia Antipolis, Sophia Antipolis, Sophia Antipolis, France, 2Institute of Automation, Chinese Academy of Sciences, Beijing, Beijing, China, People's Republic of

In Diffusion Tensor Imaging (DTI), Riemannian framework (RF) has been proposed for processing tensors, which is based on Information Geometry theory. Recently RF also has been proposed for Orientation Distribution Function (ODF) computing. In this paper, we propose the RF for EAPs and implement it via SPFI. We proved that the RF for EAPs is diffeomorphism invariant, which is the natural extension of affine invariant RF for tensors. It could avoid the so-called swelling effect for interpolating EAPs, just like the RF for tensors. We also propose the Log-Euclidean framework (LEF), Affine-Euclidean framework (AEF), for fast processing EAPs, and Geometric Anisotropy (GA) for measuring the anisotropy of EAPs, which are all the extensions of previous concepts in RM for tensors respectively.

1927.   Bessel Fourier Orientation Reconstruction: Using Heat Equation and Multiple Shell Acquisitions to Reconstruct Diffusion Propagator 
Ameer Pasha Hosseinbor1, Moo K. Chung2, Yu-Chien Wu3, and Andrew L. Alexander4
1Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, United States, 2Biostatistics, University of Wisconsin-Madison, 3Radiology, University of Wisconsin-Madison, 4Medical Physics, University of Wisconsin-Madison

We present a novel technique for analytical EAP reconstruction from multiple q-shell acquisitions. The solution is based on the heat equation estimation of signal for each shell acquisition.

1928.   A High Angular Resolution Diffusion Imaging (HARDI) Template of the Human Brain 
Anna Varentsova1, Shengwei Zhang2, and Konstantinos Arfanakis2
1Biological, Chemical and Physical Sciences, Illinois Institute of Technology, Chicago, IL, United States, 2Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States

The present work is devoted to the development of a high angular resolution diffusion imaging (HARDI) template from 67 coregistered, artifact-free datasets acquired with low angular resolution diffusion imaging. Preliminary results show that intravoxel fiber crossings can be resolved from combination of the 67 datasets, and that the information contained in the resulting template is in agreement with underlying fiber anatomy of the human brain.

1929.   A framework for modelling the regional variation of white matter microstructure 
Gemma L Morgan1, Hui Zhang1, Brandon Whitcher2, and Daniel C Alexander1
1Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom, 2Clinical Imaging Centre, GlaxoSmithKline, London, United Kingdom

We present a new framework for modelling the regional variation of tissue parameters estimated from diffusion MRI across white matter regions of interest. The method can be used to compare differences in parameter variation between groups and statistical tests allow the localisation of significant differences. We demonstrate the technique on the midsagittal corpus callosum and are able to detect significant differences in the genu of two distinct age groups

1930.   Real-time Rician noise correction applied to real-time HARDI and HYDI 
Véronique Brion1, Olivier Riff1, Irina Kezele1, Maxime Descoteaux2, Denis Le Bihan1, Jean-François Mangin1, Cyril Poupon1, and Fabrice Poupon1
1NeuroSpin, CEA/I²BM, Gif-sur-Yvette, France, 2Sherbrooke University, Sherbrooke, Canada

We adressed the problem of the correction of the Rician noise, corrupting diffusion-weighted images at high b-values, in real-time. We combined a Linear Minimum Mean Square Error Estimator (LMMSE) together with a Kalman framework in order to compute in real-time the noise-free diffusion data, as well as the diffusion maps stemming from any local high angular resolution diffusion (HARDI) or hybrid diffusion (HYDI) model. A feedback is retropropagated from the Kalman filter to the LMMSE, in order both to reinforce the influence of the local structure onto the noise correction, and to prevent smoothing effects. The technique vas validated on synthetic and real data acquired at low signal to noise ratio (SNR) to assess its efficiency and the full pipeline was tested on the computation of orientation distribution functions.

1931.   Multi-shelled q-ball imaging without assuming inversion symmetry 
Eizou Umezawa1, Masayuki Yamada1, Chiaki Tsunetomi1, and Hirofumi Anno1
1Graduate School of Health Sciences, Fujita Health University, Toyoake, Aichi, Japan

In diffusion MR analyses, the inversion symmetry of the water molecule diffusion is often assumed: the property of diffusion into a direction is identical to that into the opposite direction. Recently, a novel method, multi-shelled q-ball imaging (MS-QBI), has been proposed. In this study, we propose a method to detect the inversion asymmetry of diffusion with MS-QBI. We also perform the numerical simulation of detecting the asymmetry and examine the ability. MS-QBI will be able to detect the inversion asymmetry if the asymmetry is large enough. It is possible that MS-QBI can detect the inversion asymmetry in the case of the small voxel size realized by a high sensitivity coil system such as the cryoprobe.

1932.   Registration of high b value diffusion images 
Shani Ben Amitay1, Silvia De Santis2, Derek Jones2, and Yaniv Assaf3
1Tel Aviv University, Tel Aviv, Israel, 2CUBRIC, School of Psychology, Cardiff University, Wales, UK, United Kingdom, 3Tel Aviv University, Israel

High b-value diffusion imaging has been suggested to provide an enhanced contrast toward different cellular components. However, they suffer from low SNR, therefore, we suggest a framework based on both experimental data (DTI) and simulations (using CHARMED framework) to register the high b-value diffusion images. We inversely used the CHARMED model to generate template images that simulated the contrast seen in diffusion weighted images acquired at different b-values and gradient directions in the native image space of each subject. All high b-value images were registered to the matching templates. This approach makes motion correction feasible for the first time.

Traditional Posters : Diffusion & Perfusion - Neuro
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Diffusion: DTI & ADC

Tuesday May 10th
Exhibition Hall  13:30 - 15:30

1933.   Size and Shape Matter: Another Look at Tensor Statistics 
Nicholas Lange1,2, and Peter J Basser3
1Departments of Psychiatry and Biostatistics, Harvard University, Boston, MA, United States, 2Neurostatistics Laboratory, McLean Hospital, Belmont, MA, United States, 3PPITS, STBB, NICHD, National Institutes of Health, Bethesda, MD, United States

More biological information may already be contained in diffusion tensors measured typically by standard protocols run on clinical scanners in addition to that conveyed by their first-order size (e.g., mean, axial and radial diffusivity), second-order shape (e.g., FA) and third-order shape (skewness) coefficients. An enriched understanding of the “size” and “shape” of a tensor can be obtained by close inspection of its associated covariance tensor. This tensor takes on a variety of patterns whose complexity depends on the tissue’s unknown symmetry class, which can be determined by statistical methods, that may provide new insights in typical and disordered brain circuitry.

1934.   Robust and efficient white matter analysis using tract shape modelling and principal components analysis 
Jonathan D Clayden1
1Institute of Child Health, University College London, London, United Kingdom

Here we demonstrate how probabilistic neighbourhood tractography (PNT) and principal component analysis (PCA) may be used together to analyse properties of white matter tracts in a robust and data-efficient manner. PNT is a method for segmenting tracts in groups using a shape model, while PCA allows common factors across tracts to be identified. This approach can help reduce the multiple comparisons problems widely faced in the statistical analysis of magnetic resonance data.

1935.   Generalizing Diffusion Tensor Model using Probabilistic Inference in Markov Random Fields 
Cagatay Demiralp1, and David H. Laidlaw2
1Brown University, Providence, RI, United States, 2Brown University

We provide a proof of concept for modeling configuration distributions in DTI and their practical estimations. The power of the MAP-MRF framework comes from its mathematical convenience in modeling prior distributions and the fact that it results in a global optimization driven by local patches (context).

1936.   The Effect of Inflammation on DTI Derived Axial and Radial Diffusivity: A Monte Carlo Simulation Study 
Yong Wang1, and Sheng-Kwei Song2
1Radiology, Washington University, Saint Louis, MO, United States, 2Radiology, Washington University in St. Louis, Saint Louis, MO, United States

Diffusion tensor imaging (DTI) derived radial diffusivity and axial diffusivity have been used to detect myelin and axon integrity respectively in CNS injury. Although it has been well recognized that crossing fibers pose significant challenge in the application of DTI derived directional diffusivity. It is not clear how the inflammation caused vasogenic edema and cell infiltration impact DTI findings. In this study, Monte Carlo simulation is employed to demonstrate the possible false assessment of axonal injury and/or demyelination of a normal axon fiber bundle under the influence of inflammation.

1937.   The Relative Sensitvity of Different White Matter Indices to Partial Volume Artefacts 
Derek K Jones1
1CUBRIC, School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom

We characterise the relative sensitivity of different white matter indices to the effects of partial volume contamination by CSF. We show that mean diffusivity is far more sensitivity than fractional anisotropy. The sensitivity is also dependent on the b-value and the anisotropy of the tensor.

1938.   A New Robust Algorithm for Diffusion Tensor Evaluation 
Ivan I. Maximov1, Farida Grinberg1, and Nadim Jon Shah1,2
1Institute of Neuroscience and Medicine 4, Forschungszentrum Juelich, Juelich, Germany, 2Department of Neurology, Faculty of Medicine, JARA, RWTH Aachen University, Aachen, Germany

We propose a new algorithm for diffusion tensor reconstruction based on the robust least median squares estimator. The developed method allows one to determine the outliers that may appear due to physiological noise or other tissue-related singularities. This feature and the stability of the least median squares to noise level variation yield a new and very promising approach in research and in clinical practice.

1939.   Bias in Diffusion Tensor-Derived Quantities Depend on The Number of DWIs Composing The DT-MRI Dataset 
Firouzeh Tannazi1, Lindsay Walker1, Michael Curry1, and Carlo Pierpaoli1
1STBB/PPITS/NICHD/NIH, Bethesda, MD, United States

In this study we investigate the effects of the number of images comprising the DTI data set on the statistical properties of diffusion tensor eigenvalues and anisotropy indices derived from them. The results of Monte Carlo simulations along with the analysis of phantom DTI data indicate an overall underestimation of Eig3 and an overestimation of FA and Eig1 as the number of images in DTI estimation is reduced.

1940.   DTI Reconstruction: K-space Average, Image-space Average, or No Average 
Shu-Wei Sun1,2
1Biophysics and Bioengineering, Loma Linda University, Loma Linda, CA, United States, 2Radiation Medicine, Loma Linda University, Loma Linda, CA, United States

Diffusion Tensor Imaging (DTI) is achieved by collecting a series of Diffusion Weighted Images (DWI) with different diffusion weighted vectors. For each DWI, it is usually acquired with multiple repetitions to boost the signal to noise ratio. On may perform k-space average or image-space average to boost the signal to noise ratio for each DWI. In this study, we compared DTI maps of mouse brains in vivo using k-space average, image-space average, and no average approaches. K-space average provided the least contrast for presenting white matter on RA maps.

1941.   Diffusion Anisotropy Corrections for Vessel Size and Microvessel Density Imaging 
Jens H Jensen1
1Department of Radiology, New York University School of Medicine, New York, NY, United States

The standard theories for vessel size imaging (VSI) and microvessel density imaging (MDI) are based on an assumption of isotropic water diffusion. Therefore, the validity of applying these techniques to white matter may be questioned. Here the corrections to the basic VSI and MDI equations due to diffusion anisotropy are explicitly calculated in terms of the diffusion tensor. For the most anisotropic brain regions, the corrections are found to be significant, although not large. These results may relevant for application of VSI and MDI to the assessment of angiogenesis in white tumors.

1942.   Correcting the bias in the ADC value due to local perturbation fields: a physically informed model 
Siawoosh Mohammadi1, Zoltan Nagy1, Harald E Moeller2, David Carmichael3,4, Mark Symms3, Oliver Josephs1, and Nikolaus Weiskopf1
1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom, 2Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom, 4MRI unit, National Society for Epilepsy, Chalfont St. Peter, United Kingdom

Imaging artefacts, which perturb diffusion-weighted images, can bias the estimated diffusion tensor. Important sources of imaging artefacts in DTI are eddy current fields, gradient nonlinearities or mis-calibration of the gradient amplitude. They can be modelled by introducing the concept of a local perturbation field (LPF). In this study, we used first-order perturbation theory to introduce a physically-informed model that estimates and corrects for the effect of LPFs. Using phantom and human DTI measurements on two different scanners we were able to estimate the LPFs and improve the quality of FA maps without requiring vendor-specific information.

1943.   Model-Based Reconstruction of Undersampled DTI Data 
Christopher L Welsh1,2, Edward W Hsu1,2, and Edward VR DiBella1,2
1Bioengineering, University of Utah, Salt Lake City, Utah, United States, 2UCAIR, University of Utah, Salt Lake City, Utah, United States

Diffusion Tensor Imaging (DTI) is useful for characterizing tissue microstructure, but suffers from long scan time and low SNR. To allow faster acquisition, a model-based strategy is presented to directly estimate diffusion tensors from undersampled k-space data. Using an acceleration factor of 2, different sampling schemes were investigated and found to generally outperform acquiring equivalent number of full-resolution scans. Minor performance differences were also observed among the schemes for estimating different DTI parameters. These findings suggest the proposed strategy can be used to reduce DTI scan time by half while incurring little or no loss in the parameter estimation accuracy.

1944.   Registration based correction of DWI gradient orientations 
Ben Jeurissen1, Maarten Naeyaert1, Alexander Leemans2, and Jan Sijbers1
1Vision Lab, Dept. of Physics, University of Antwerp, Antwerp, Belgium, 2Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands

Misalignment between diffusion weighted (DW) images and the corresponding gradient orientations leads to misinterpretation of rotationally variant diffusion parameters and tractography results. We propose a method to automatically correct for rigid misalignment of the gradient orientations, using a registration metric based on the average fiber trajectory length. Using simulations we show that our method converges to the 'ground truth' orientations and that small 'angulation' errors can still be detected, that are easily overlooked by visual inspection. While the method uses diffusion tensor tractography to calculate trajectory lengths, the recovered gradient orientations can be applied in general DWI post-processing.

1945.   The anisotropic bias of fractional anisotropy in anisotropically acquired DTI data 
Sjoerd B Vos1, Max A Viergever1, and Alexander Leemans1
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands

In order to reduce DTI scan time, slice thickness is often increased while maintaining a high in-plane resolution. The resulting anisotropic voxel size means that the orientation-dependent diffusion information is sampled in a higher resolution in-plane than through-plane. In this work we show that the bias in fractional anisotropy, introduced by anisotropically acquired DTI data, is dependent on the orientation of the fiber bundle of interest. Furthermore, we demonstrate that the diffusion bias is not solely determined by the anisotropy of the voxel size, but strongly depends on the relation between the fiber bundle and the data grid as well.

1946.   Diffusion tensor imaging distortion correction with T1 
KI SUENG CHOI1,2, Alexandre R. Franco2, Paul E. Holtzheimer2, Helen S. Mayberg2, and Xiaoping P. Hu1
1Bioengineering, Georgia Institute of Technology / Emory University, Atlanta, GA, United States, 2Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States

DW-EPI is very sensitive to B0 inhomogeneities that produce geometric distortion, primarily along the phase-encoding direction. As a result, artifacts degrade the ability of using diffusion measures and diffusion tractography. Several different techniques were suggested for correcting susceptibility distortion. However, to apply these correction techniques, additional images (field map, T2) are required. In this work, we examine susceptibility distortion correction using image based non-linear registration along with inverting the intensity of the T1 image. This method exhibits better performance for geometrical distortion correction in frontal region and an ability to analyze clinical diffusion data without additional collection of images.

1947.   The effect of atlas selection on voxel based analyses of DTI data 
Wim Van Hecke1,2, Louise Emsell3,4, Alexander Leemans5, Caroline Sage6, Jelle Veraart7, Stefan Sunaert6, Jan Sijbers7, and Paul M Parizel7
1University of Antwerp, Antwerp, Antwerp, Belgium, 2University of Leuven, Leuven, Leuven, Belgium, 3The Murdoch Childrens Research Institute, Australia, 4NUI Galway, Ireland, 5Image Sciences Institute, Utrecht, Netherlands, 6University of Leuven, Belgium, 7University of Antwerp, Belgium

In this study, the effect of atlas selection on voxel based analyses of DTI data is examined. To this end, data sets of healthy subjects and multiple sclerosis patients were aligned to a population-specific atlas, a subject-based MNI template, and the ICBM-81 atlas.

1948.   What is the component that appears in diffusion-weighted imaging at low b values? 
Kimihiro Ogisu1, Hidetsugu Sakai2, and Toru Yamamoto2
1Graduate School of Medicine, Hokkaido University, Sapporo, Japan, 2Graduate School of Health Sciences, Hokkaido University

The signal from intravoxel incoherent motion (IVIM) appears in diffusion-weighted imaging at low b values. This low-b-value component is believed to reflect capillary blood flow in tissue. However, the quantity of the low-b-value component contradicts the data on capillary blood volume in the literature. To determine the origin of the low-b-value component, we investigated the proton density and T2 value of the component. We found that the low-b-value component has a larger T2 value than does blood and that this component exhibits IVIM. Because the hydrostatic pressure and osmotic pressure in capillaries drive interstitial fluid flow, which has a large T2 value, we suggest that the interstitial fluid mainly contributes to the low-b-value component.

1949.   Diffusion Tensor Imaging tracks repair of Retinal Pigment Epithelium (RPE) layer using Hematopoietic Stem Cells in mice 
Saurav Chandra1, Sergio Caballero2, Maria B Grant2, and John R Forder1,3
1Biomedical Engineering, University of Florida, Gainesville, FL, United States, 2Pharmacology, University of Florida, 3Radiology, University of Florida

The study aims to restore visual function in mice impaired by retinal degeneration by using hematopoietic stem cells (HSCs) to repair the retinal pigment epithelium (RPE) layer. HSCs expressing the gene RPE65 were successful in differentiating into RPE cells and proliferating to the specific site to restore the RPE layer. Diffusion tensor imaging successfully visualized differences between repaired and unrepaired RPE layers in mice. Fractional anisotropy (FA) was observed to markedly higher in repaired retinas (as is the case in any structured anatomy) compared to unrepaired retinas which had a depleted RPE layer.

1950.   High Angular Resolution Diffusion Microscopy (HARDM) detects Retinal Disruption in mice with Diabetic Retinopathy 
Saurav Chandra1, Angelos Barmpoutis2, Nicholas Simpson3, and John R Forder1,4
1Biomedical Engineering, University of Florida, Gainesville, FL, United States, 2Computer and Information Sciences Engineering, University of Florida, 3College of Medicine, University of Florida, Gainesville, FL, United States, 4Radiology, University of Florida, Gainesville, FL, United States

Diabetic retinopathy is the most common eye disease affecting diabetics and a leading cause of blindness. However, it cannot be diagnosed in its early stages. We used High Angular Resolution Diffusion Microscopy (HARDM) as a non-invasive tool to detect this disease at an early stage in mice. HARDM of control eyes showed water diffusion in the retina was restricted, reflecting an organized structure within the retinal layers. Comparison with control eyes showed the integrity of these layers is compromised in eyes from diabetic animals with elevated glucose levels. FA is also significantly decreased in the diabetic retinas compared to controls.

1951.   Accounting for Changes in Signal Variance in Diffusion Weighted Images Following Interpolation for Motion and Distortion Correction 
Mustafa Okan Irfanoglu1, Lindsay Walker2, Raghu Machiraju3, and Carlo Pierpaoli2
1Computer Sciences and Engineering, The Ohio State University, Columbus, OH, United States, 2NIH, 3The Ohio State University

In this work, we propose a novel technique to account for changes in signal variance in diffusion weighted images due to interpolation artifacts related to image registration based motion and distortion correction steps. Our technique can model signal variance changes due to sequential transformation applications and can cope with all types of interpolation kernels. We show our results as improvements in Chi-squared maps of tensor fitting.

Traditional Posters : Diffusion & Perfusion - Neuro
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Diffusion Acquisition & Pulse Sequences Methods

Wednesday May 11th
Exhibition Hall  13:30 - 15:30

1952.   High Resolution Multiple Slice Composite Inner Volume Excitation Echo Planar Diffusion Weighted imaging 
Hing-Chiu Chang1,2, Tzu-Cheng Chao3, Yi-Jui Liu4,5, Kuo-Fang Shao5, Cheng-Chieh Cheng2, Chao-Chun Lin2,6, and Hsiao-Wen Chung2,7
1Global Applied Science Laboratory, GE Healthcare, Taipei, Taiwan, 2Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, 3Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States, 4Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, 5Master's Program in Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan, 6Department of Radiology, China Medical University Hospital, Taichung, Taiwan,7Department of Radiology, Tri-Service General Hospital, Taipei, Taiwan

Reduced field of view (rFOV) technique has been known for its advance in shortening the read-out train in MR imaging. With this excitation scheme, high resolution Echo Planar Imaging (EPI) becomes available with less geometric distortion. In this work, a multiple slice rFOV sequence was proposed with multiple sequential volume acquisition to combine the rFOV images as a full FOV image with appropriate intensity correction to compensate the effect of RF profile imperfection during excitation. And a high resolution in vivo EP-DTI dataset with tractography result was demonstrated to confirm the feasibility of this proposed scheme on clinical research.

1953.   Reduced-FOV Single-Shot Diffusion-Weighted EPI: Extended Slice Coverage with Tailored RF Pulse Design 
Emine Ulku Saritas1, Ajit Shankaranarayanan2, Greg Zaharchuk3, and Dwight G Nishimura4
1Department of Bioengineering, University of California, Berkeley, CA, United States, 2Applied Science Laboratory, GE Healthcare, Menlo Park, CA, United States, 3Department of Radiology, Stanford University, Stanford, CA, United States, 4Department of Electrical Engineering, Stanford University, Stanford, CA, United States

The use of a 2D echo-planar RF excitation has recently been proposed for high-resolution diffusion-weighted imaging (DWI) of targeted regions. This method excites only the region of interest, while providing inherent fat suppression and contiguous multi-slice imaging. However, the number of slices that can be acquired in a single TR is limited due to the periodicity of the excitation profile. In this work, we propose significant improvements in RF pulse design to overcome this limitation, and specifically demonstrate that the coverage can be doubled without any SNR or scan time penalty. We validate the proposed method with in vivo high-resolution axial DWI of the spinal cord.

1954.   A 3D radial FSE-based SPLICE sequence for MR diffusion imaging 
Jiangsheng Yu1, Yiqun Xue1, Mark A Rosen1, and Hee Kwon Song1
1Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA, United States

Currently, the gold standard technique for in vivo diffusion imaging is single-shot diffusion-weighted EPI (DW-EPI). However, DW-EPI is sensitive to off-resonance effects, and artifacts are often observed, particularly near air-tissue boundaries. While FSE-based diffusion methods have also been proposed, CPMG conditions can become easily violated, particularly in the presence of motion during diffusion sensitization. The SPLICE technique was recently developed to overcome these artifacts. In this work, we present preliminary results of a hybrid 3D radial FSE SPLICE technique and demonstrate improved ADC maps in both phantom and in vivo experiments.

1955.   Reduction of Image Distortion in Non-Axial Diffusion-Weighted Imaging Using Steer-PROP 
Girish Srinivasan1,2, Novena Rangwala1,2, and Xiaohong Joe Zhou1,3
1Center for MR Research, University of Illinois Medical Center, Chicago, IL, United States, 2Department of Bioengineering, University of Illinois Chicago, Chicago, IL, United States, 3Departments of Bioengineering, Radiology, Neurosurgery, University of Illinois Medical Center, Chicago, IL, United States

Severe image distortion is often seen in diffusion-weighted single-shot EPI (SS-EPI) due to strong concomitant gradient and other off-resonance effects. A GRASE-based PROPELLER sequence, Steer-PROP, is developed to reduce the image distortion. Diffusion images were obtained from non-axial planes on the human brain using the Steer-PROP sequence, and showed substantially reduced distortion when compared with SS-EPI. The scan time of Steer-PROP was ~4-5 times longer than that of SS-EPI, but 3-5 times faster than conventional PROPELLER. With further improvement in time efficiency, Steer-PROP can be a strong contender for diffusion imaging in non-axial planes where SS-EPI is problematic.

1956.   A Sliding-Window Re-Acquisition Scheme for Multi-Shot, Diffusion-Weighted Imaging with 2D Navigator Correction 
David Andrew Porter1, Keith Heberlein1, and Robin Martin Heideman2
1Siemens Healthcare, Erlangen, Germany, 2Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

A number of sequences use a 2D navigator to correct phase error in multi-shot, diffusion-weighted imaging. The limited resolution of these 2D navigators means that it is not possible to correct high-spatial-frequency phase errors. Previous studies have shown that navigator-based re-acquisition can be used to re-measure these scans and avoid artifacts in the final image, but the techniques used were not suitable for acquiring large volumes of data. This study describes the use of a modified re-acquisition scheme with diffusion-weighted, readout-segmented EPI to acquire high resolution DTI with a 32 channel head coil.

1957.   k-space and q-space: Combining Ultra-High Spatial and Angular Resolution in Diffusion Imaging using ZOOPPA at 7T 
Robin Martin Heidemann1, Alfred Anwander1, Thorsten Feiweier2, John Grinstead3, Gabriele Lohmann1, Thomas R Knösche1, and Robert Turner1
1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Siemens Healthcare, Erlangen, Germany, 3Siemens Medical Solutions, Portland, United States

There is still a debate whether k-pace (high resolution) or q-space (high angular resolution) imaging is better to resolve crossing fibres. In the current study we use a recently introduced combination of zoomed imaging and parallel imaging to obtain diffusion-weighted images with isotropic high resolution and high angular resolution at ultra-high field strength. The acquired data with 1 mm isotropic resolution has sufficient SNR to resolve crossing fibres in the white matter.

1958.   Distortion Free High Resolution in vivo Whole Brain Diffusion Tensor Image on 7.0T MRI 
Se-Hong Oh1, Jun-Young Chung1, Sung-Yeon Park1, Joshua Haekyun Park1, Dae-Hoon Kang1, Myung-Ho In2, Maxim Zaitsev3, Oliver Speck2, Young-Bo Kim1, and Zang-Hee Cho1
1Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea, Republic of, 2Department of Biomedical Magnetic Resonance, Institute for Experimental Physics, Otto-von-Guericke University Magdeburg, Magdeburg, Germany, 33 Department of Radiologic Research, Medical Physics, University Hospital of Freiburg, Freiburg, Germany

Diffusion pulse sequences based on single-shot EPI inherit virtually all of the artifacts associated with EPI. For example, distortion caused by magnetic susceptibility variations and B0 field inhomogeneity is frequently observed in the frontal sinus. When high resolution at higher magnetic field imaging like 7.0T, diffusion weighted images severely suffer from distortions due to susceptibility artifacts. Therefore, to acquire high resolution DTI images at 7.0T UHF MRI, we should solve geometric distortion problem. To correct geometric distortion use distortion and non-distortion dimensional combined PSF correction method. Then we can correct the geometric distortion both compressed and stretched area more accurately. These results show the efficacy of distortion correction for the anatomical accuracy of fiber tractography. With 7.0T distortion free high-resolution DWI data, we are able to visualize anatomically accurate fiber tractography image as well as small fiber tractography image such as mammillo thalamic tract, which not achievable at low field MRI (i.e. 1.5T or 3.0T).

1959.   Single-Shot Diffusion-Weighted Spiral Imaging 
Bertram Jakob Wilm1, Christoph Barmet1, and Klaas Paul Pruessmann1
1Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Zurich, Switzerland

We present a comprehensive approach to diffusion weighted single-shot spiral imaging. On the basis of field monitored data images are obtained by higher-order reconstruction including static-B0correction and parallel imaging. The Images with an in-plane resolution of 1.4 mm do not show aliasing related artifacts and are virtually free from B0 off-resonance effects.

1960.   Motion-Induced Phase Error Correction in 3D Diffusion-Weighted Imaging 
Anh Tu Van1, Diego Hernando1, Joseph Holtrop2, and Bradley P Sutton2,3
1Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States,3Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States

A robust 3D motion-induced phase error estimation and correction algorithm is introduced in the present study to enable in vivo 3D diffusion-weighted imaging. Parameters of the phase error are estimated by nonlinear fitting of navigator images to a motion-induced phase error model and used to correct the k-space data. The phase error parameter estimation is unbiased with mean square errors approaching the Cramer-Rao lower bound. The correction is time efficient with performance independent of the 3D k-space trajectory used. Simulation and in vivo results were obtained to demonstrate the accuracy of the proposed method.

1961.   Isotropic High-Resolution 3D Diffusion Weighted SSFP Imaging with Spiral Projection Imaging 
Rafael Luis O'Halloran1, Murat Aksoy1, Eun Soo Choi1, and Roland Bammer1
1Radiology, Stanford University, Palo Alto, CA, United States

The Spiral projection readout is combined with DW-SSFP to acquire 3D diffusion weighted images at multiple diffusion directions in reasonable scan times for whole brain coverage in a healthy human volunteer. A retrospective cardiac gating technique and iterative-SENSE reconstruction is used to address reproducible phase errors caused by cardiac motion and compared to a standard gridding reconstruction. Images at multiple diffusion encoding strengths are presented.

1962.   Impact of the point-spread function on parameters derived from diffusion-weighted imaging: axial versus sagittal acquisition 
J-Donald Tournier1,2, Fernando Calamante1,2, and Alan Connelly1,2
1Brain Research Institute, Florey Neuroscience Institutes, Melbourne, Victoria, Australia, 2Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia

Diffusion-weighted imaging (DWI) data are typically acquired using single-shot multi-slice EPI. Images acquired with these sequences will inevitably have differences in the point-spread function along the different orientations (i.e. through-slice versus in-plane). These differences can introduce errors in the DW signal and derived parameters due to Gibbs ringing in the immediate vicinity of high signal areas (particularly CSF), which will depend on the direction of the imaging slice with respect to the direction of signal change. In this study, we demonstrate this effect by comparing images acquired using otherwise equivalent axial and sagittal DWI protocols.

1963.   The Deleterious Effect of Concomitant Gradient Fields on Diffusion Imaging 
Corey Allan Baron1, Robert Marc Lebel1, Alan H Wilman1, and Christian Beaulieu1
1Biomedical Engineering, University of Alberta, Edmonton, AB, Canada

Concomitant fields are small unavoidable magnetic field components that exist during the application of imaging gradients. They can usually be ignored for common pulse sequences. However, in diffusion tensor imaging, large gradients are required to sensitize the MR signal to water diffusion, and phase accrual from the concomitant fields can lead to image artefacts. This is of particular concern for eddy current cancelling diffusion preparations used in combination with systems having large gradients. We demonstrate that an erroneous increase in apparent diffusion coefficient can occur in phantom and human brain, and we propose and validate a prospective correction.

1964.   Crusher Gradient Reversal to Eliminate Stimulated Echo Artifacts in Dual Spin Echo Diffusion MRI 
Gaohong Wu1, Sangwoo Lee1, Xiaoli Zhao1, and Zhu Li1
1GE Healthcare, Waukesha, WI, United States

A crusher gradient reversal method is proposed to overcome the stimulated echo artifacts in dual spin echo diffusion MRI. The polarity of crusher gradients before and after the two refocusing pulses is reversed according to the polarity of diffusion gradients. The reversal allows the crusher gradients and diffusion gradients to be added up, so that there are always enough crushers to kill the stimulated echo signal. The removal of stimulated echo artifacts is not specific to certain b-values, and does not have impact on sequence performance.

1965.   Diffusion-limited diffusion MRI and a universal optimum b-value 
Van Wedeen1, and Guangping Dai1
1Radiology, Martinos Center/ MGH, Charlestown, MA, United States

If we model q-space MRI as an imaging micro-structure, its effective resolution is the sum of two terms: “camera resolution” proportional to q-1=(lower case Greek gammaGt)-1, and blurring by the diffusion kernel, which if Gaussian has width (2Dt)-1/2. Defining effective resolution as the root-mean-square, setting t=lower case Greek delta=∆ and minimizing, the best-possible diffusion-limited structural resolution is Rmin=√3(D/lower case Greek gammaG)1/3, achieved with encoding time topt=D-1/3(lower case Greek gammaG)-2/3 and bopt=(π2/6)D-1. In vivo, if observed max(D-1)≈5Dwater-1 then bopt≈20,000s/mm-2. Thus, an optimal b-value of q-space MRI depends only on diffusivity and is gradient-independent; stronger gradients improve structural resolution insofar as they reduce diffusion encoding time at optimal b.

1966.   Optimised Gradient Waveform Spin-Echo sequence for Diffusion Weighted MR in a Microstructure Phantom 
Bernard M Siow1,2, Ivana Drobnjak1, Mark F Lythgoe2, and Daniel C Alexander1
1Centre for Medical Image Computing, UCL, London, United Kingdom, 2Centre for Advanced Biomedical Imaging, UCL, London, United Kingdom

Diffusion MRI has been used for probing tissue microstructure and of particular interest is axon radius distribution estimates. Abnormal distributions are found in pathologies such as amyotrophic lateral sclerosis and schizophrenia. PGSE sequences have been traditionally used for diffusion weighting and optimised protocols that use these sequences have been used to provide reliable axon radius estimates >5µm. Recently, an in silico study optimised the shape of the gradient waveforms for particular axon radii and showed that protocols that used these optimised waveforms provided improved axon radii estimates <5µm. In this study, we implement these optimised gradient waveform protocols on a pre-clinical scanner. These protocols were used to study microcapillary phantoms that have pore radii of 1-10 µm. A good agreement between simulated and measured signal was found, giving a strong indication that these sequences can be practically implemented in vitro and in vivo. Potentially, these protocols can provide extra sensitivity to microstructural features <5µm.

1967.   On the Diffusion Sensitivity of 2D- and 3D-Turbo Spin Echo Sequences 
Matthias Weigel1, and Jürgen Hennig1
1Dept. of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany

The present work investigates the diffusion sensitivity of 2D- and 3D-TSE sequences; for variants with low constant or variable refocusing flip angles in particular. The performed simulations using realistic protocol settings are based on an extended phase graph (EPG) approach that was published recently. It is found that especially novel 3D-TSE sequences with extended echo trains and variable low flip angles – usually known as SPACE or CUBE – exhibit a notable diffusion weighting that should not be neglected.

1968.   Simulation of Diffusion Weighted SSFP: Time to Reach the Steady State and Effects on Anisotropic Diffusion 
Eun Soo Choi1, Rafael O'halloran2, Ernesto Staroswiecki2, and Roland Bammer2
1Stanford University, Stanford, California, United States, 2Department of Radiology, Stanford University, Stanford, California, United States

Diffusion-weighted SSFP imaging offers high diffusion contrast with low spin preparation time, but requires an initial period to reach steady state. It is important to know how long this initial period is so that data collection can begin after steady state is achieved. Here, the time to reach steady state is investigated in three simulated brain tissue types using the extended phase graph simulation. The dependence of the time to steady state on multiple parameters such as TR, flip angle, and diffusion coefficient is explored. Additionally the effect of switching the diffusion gradient direction on the steady state is investigated. The time to return to steady state after the switch has implications for diffusion tensor imaging of anisotropic diffusion

1969.   Analysis of Diffusion-Weighted SSFP Signal with Computer Simulation 
Eun Soo Choi1, Rafael O'halloran2, Ernesto Staroswiecki2, and Roland Bammer2
1Stanford University, Stanford, California, United States, 2Department of Radiology, Stanford University, Stanford, California, United States

Increasingly, diffusion weighted (DW) imaging is being performed with higher numbers of diffusion directions and is moving toward isotropic 3D acquisition. DW SSFP imaging has the potential to meet these challenges due to its increased scan time efficiency compared with conventional spin echo DWI. A major factor limiting widespread adoption of DW SSFP is that the signal depends not only on pulse timing and geometry but also upon the physical parameters, T1, T2, and diffusion coefficient. Here we present Bloch simulations of the pulsed gradient DW-SSFP sequence and compare it to the extended phase graph simulation as well as to the approximate analytical solution of Wu and Buxton.

Traditional Posters : Diffusion & Perfusion - Neuro
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Perfusion/Permeability: DSC Methods

Thursday May 12th
Exhibition Hall  13:30 - 15:30

1970.   Quantitative perfusion imaging by USPIO bolustracking: the Maximum Slope Model 
Peter Roland Seevinck1,2, Mark J Bouts1, Annette van der Toorn1, and Rick Martin Dijkhuizen1
1Biomedical MR Imaging and Spectroscopy, Image Sciences Institute, University Medical Center Utrecht, Utrecht, Utrecht, Netherlands, 2Physics of MRI, Image Sciences Institute, University Medical center Utrecht, Utrecht, Netherlands

Absolute quantification of perfusion parameters critically contributes to the accuracy of characterizing tissue status, predicting lesion outcome, as well as monitoring therapy in experimental and clinical stroke studies. In this work we investigated the use of USPIO for perfusion imaging, instead of Gd-DTPA, which would enable the simultaneous assessment of vascular architecture (e.g. angiogenesis) by ssCE-MRI. The signal time course typical for USPIO bolus tracking motivated us to apply an alternative method for absolute quantification of perfusion parameters, i.e. the maximum slope model. This model was demonstrated to provide realistic values for CBV and CBF in rats in vivo.

1971.   An improved quantification method to characterize cerebral hemodynamic changes after carotid endarterectomy surgery: a dynamic susceptibility contrast MRI study. 
David E Crane1, Bradley J MacIntosh1,2, Ediri Sideso3, James Kennedy3, Ashok Handa4, Manus J Donahue5, and Peter Jezzard5
1Heart and Stroke Foundation Centre for Stroke Recovery, Sunnybrook Research Institute, Toronto, ON, Canada, 2Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom, 4Nuffield Department of Surgery, University of Oxford, Oxford, United Kingdom, 5Clinical Neurology, FMRIB Centre, University of Oxford, Oxford, United Kingdom

A method of calculating quantitative DSC, thereby permitting longitudinal comparison, is demonstrated and applied to patients undergoing carotid endarterectomy surgery. Quantification was performed with the “bookend” technique, where T1-weighted steady-state measurement of CBV is used to scale DSC-derived absolute CBF values. Subcortical grey matter CBF results agreed with reported values and age trends. Comparison of pre vs. post surgery showed low inter-session variability and significant surgery effects. Thus, the DSC-bookend approach may be useful in characterizing the interaction between hemodynamics and CEA effects thereby helping to identify patients most likely to benefit from surgery.

1972.   Spin-echo and Gradient-echo PWI CBF vs. ASL CBF: An Initial Comparison. 
Matus Straka1, Heiko Schmiedeskamp1, Greg Zaharchuk1, Jalal B Andre1, Jean-Marc Olivot2, Nancy J Fischbein1, Maarten G Lansberg2, Michael E Moseley1, Gregory W Albers2, and Roland Bammer1
1Radiology, Stanford University, Stanford, CA, United States, 2Stanford Stroke Center, Stanford University, Stanford, CA, United States

Novel SAGE DSC-MRI sequence delivers both spin- and gradient-echo PWI CBF maps that provide information about both microcapillary and macrovascular brain perfusion. A comparison of the SAGE-derived CBF values with reference ASL CBF is presented. 10 initial SAGE cases were acquired, postprocessed by deconvolution to obtain CBF, and after coregistration with ASL CBF, voxel-wise comparison of CBF values was executed. A scaling factor of 4.8 was found between GRE and SE-based CBF values. It was observed that SE-based CBF maps correlate with ASL CBF better that those from GRE, but contrast in SE CBF and ASL CBF is not identical.

1973.   Low-Resolution Cartesian Compressed Sensing MRI: Application to Dynamic Susceptibility MRI 
David S Smith1,2, Thomas E Yankeelov1,2, and Christopher Chad Quarles1,2
1Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States, 2Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States

We show that using Compressed Sensing MRI to accelerate low-resolution, 2-D Cartesian Dynamic Susceptibility MRI by up to a factor of two has no significant influence on the derived hemodynamic parameters.

1974.   Flow Heterogeneity as a Potential Biomarker of Vascular Normalisation in Tumour Studies 
John David Dickson1, Richard E Ansorge1, and Stephen Price2
1Department of Physics, Cambridge University, Cambridge, Cambridgeshire, United Kingdom, 2Medical School, Cambridge University

Recent research has shown that the success of anti-angiogenic treatment can be due to a process known as vascular normalisation. The need to track the effectiveness of anti-angiogenic treatment has therefore created a demand for effective biomarkers of vascular normalisation. One proposed biomarker is the radii of vessels present, however vessel size imaging requires intravenous injection of Iron Oxide contrast agents. We propose that effective information on normalisation of vascular morphology may be attainable using only Gadolinium-based tracers by measuring intravoxel heterogeneity in flow rate.

1975.   Use of the relationship between phase and magnetic susceptibility for assessment of assumed contrast agent distributions in vivo: Application to Capital Greek DeltaR2* maps in dynamic susceptibility contrast MRI 
Emelie Lindgren1, Linda Knutsson1, Danielle van Westen2, Freddy Ståhlberg1,3, and Ronnie Wirestam1
1Dept. of Medical Radiation Physics, Lund University, Lund, Sweden, 2Radiology, Skane University Hospital, Lund, Sweden, 3Dept. of Diagnostic Radiology, Lund University, Lund, Sweden

Magnetic susceptibility quantification by deconvolution of measured phase maps is an interesting approach, although the method constitutes an ill-posed inverse problem to which an ideal solution is presently lacking. An interesting intermediate step is to compare measured phase maps (reflecting true local susceptibility) with artificial phase maps calculated by convolution of an assumed susceptibility distribution. Delta_R2* maps were assumed to represent contrast agent concentration (i.e., proportional to susceptibility), as is traditionally the case in DSC-MRI. Differences between measured and artificial phase maps were observed, not inconsistent with different T2* relaxivities in different compartments, as predicted by previously published simulation studies.

1976.   Improving CBF Image Contrast with Frequency Extrapolation for DSC-MRI during Acute Stroke 
Matthew Ethan MacDonald1,2, Micheal Richard Smith1,3, and Richard Frayne2,3
1Departments of Electrical and Biomedical Engineering, University of Calgary, Calgary, AB, Canada, 2Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, AB, Canada,3Departments of Radiology and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada

DSC-MRI is can provide estimates of the tissue perfusion in the early onset of stroke. CBF is a perfusion parameter that has been suggested for detecting regions of tissue that are affected by ischemia and may still be salvageable with treatment. The calculation of CBF from raw perfusion data requires deconvolution, which has been shown to have MTT-dependent bias. In this work, frequency domain extrapolation is introduced during the deconvolution process to correct for this bias. The algorithm is tested across ten ischemic stroke patient data sets, and compared with follow up imaging, ROC analysis is used to determine detection.

1977.   Determination of Collateral Supply Patterns Using Conventional Dynamic Susceptibility Contrast Perfusion Imaging 
Cihat Eldeniz1, Yueh Lee2, Jeffrey Keith Smith2, Tyler B. Jones2, Weili Lin2,3, Sten Solander2, James Faber4, and Hongyu An2
1Biomedical Engineering, University of North Carolina, Chapel Hill, NC, United States, 2Department of Radiology, University of North Carolina, Chapel Hill, NC, United States, 3Department of Neurology, University of North Carolina, Chapel Hill, NC, United States, 4Department of Cell and Molecular Physiology, University of North Carolina, Chapel Hill, NC, United States

In this study, we have shown that an integration of CBF, MTT and Tmax obtained from DSC data can be utilized in detecting collateral supply to ischemic tissue. Our findings are in agreement with the gold standard DSA assessment in human stroke patients.

1978.   A patient-specific global residue function improves reproducibility in longitudinal monitoring of perfusion changes in low-grade gliomas 
Atle Bjornerud1,2, Kim Mouridsen3, and Kyrre Eeg Emblem4,5
1Interventional Centre, Oslo Univeristy Hospital, Oslo, Norway, 2Dept. of Physics, Univ. of Oslo, Oslo, Norway, 3Center for Functionally Integrative Neuroscience, Aarhus University Hospital, Denmark, 4A. A. Martions Center for Biomedical Imaging, Massachusetts General Hospital, 5Oslo Univeristy Hospital, Norway

We present a method for improved reproducibility of DSC-MRI based perfusion measurements through the generation of a global patient specific tissue residue function obtained at a single time-point using an automatically generated AIF. The global scan-specific tissue response is then combined with the global residue function and the initial AIF to reconstruct a scan-specific AIF used to derive perfusion parameters at each time-point. The method was tested in the analysis of unaffected brain tissue in glioma patients undergoing multiple longitudinal scans and was found to significantly improve reproducibility of perfusion measurements compared to using scan-specific AIFs.

1979.   Prediction of clinical outcome in glioma patients using a combination of epidermal growth factor receptor (EGFR) and relative cerebral blood volume (rCBV) measured by dynamic susceptibility-weighted contrast-enhanced magnetic resonance imaging 
Marcel Oei1, Albert Idema1, Pieter Vos1, Sandra Boots-Sprenger1, Judith Jeuken1, and Mathias Prokop1
1Radboud University Nijmegen Medical Centre, Nijmegen, Gelderland, Netherlands

Problem: Good prediction of clinical outcome is important for determining therapy in glioma tumors. Aim: Evaluate the combination of rCBV and EGFR to predict clinical outcome in glioma patients. Methods: rCBV was measured from DSC-MR images in 44 patients. EGFR copy numbers of 18 tumor samples were derived using MLPA. Statistical analyses were used to determine correlation, ROC curves and Kaplan-Meier Survival curves. Results: A strong significant correlation was found between rCBV and EGFR. Patients with rCBV < 5.45 and normal EGFR had significant longer survival. Conclusion: The addition of EGFR improved the prediction of clinical outcome of rCBV.

1980.   Correlation of DSC parameters with histopathological complex microvasculature in GBM patients 
Emma Essock-Burns1,2, Joanna J Phillips3,4, Janine M Lupo2, Soonmee Cha2,5, Susan M Chang5, and Sarah J Nelson1,6
1UCSF/UCB Joint Graduate Group in Bioengineering, University of California San Francisco, San Francisco, California, United States, 2Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States, 3Department of Pathology, University of California San Francisco, 4Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, United States, 5Department of Neurological Surgery, University of California San Francisco, San Francisco, California, United States, 6Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California, United States

Glomeruloid vasculature, a hallmark of GBM tumors, is associated with breakdown of the blood-brain barrier. During DSC-imaging this results in extravasation of contrast, causing challenges for accurate perfusion assessment. 35° flip angle DSC acquisition is one strategy for mitigating this competing effect. This study correlated complex vasculature from 22 GBM biopsies to DSC-perfusion parameters acquired with either 35° or 60° flip angle. Percent signal recovery inversely correlated with presence of complex vasculature across the study population and for the subset of data acquired with 35° flip angle. This study supports that complex vasculature can be well studied with 35° DSC-imaging.

Moran Artzi1,2, Orna Aizenstein3, Talma Hendler1,2, Rinat Abramovitch4, and Dafna Ben Bashat1
1Functional Brain Center, Wohl institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel, 2Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel, 3Radiology Department, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel, 4The Goldyne Savad Institute for Gene Therapy, Hadassah Hebrew University Medical Center, Jerusalem, Israel

The aim of this study was to use unsupervised multimodal classification method on a combined data obtained from hyperoxia challenge and dynamic-susceptibility-weighted imaging, in order to characterize brain tissue vascularity in the healthy brain. Three brain clusters were defined and classified as white matter, gray matter and dura&blood vessels. Significant differences between the clusters and between brain lobes were detected with a trend of higher vascularity in the right versus the left hemisphere. This combination of methods provides comprehensive knowledge which may be used by future studies to improve characterization of the hemodynamic features of the healthy and pathological brain.

1982.   Dynamic susceptibility contrast imaging study of the healthy brain using multiparametric classification 
Moran Artzi1,2, Orna Aizenstein3, Talma Hendler1,2, and Dafna Ben Bashat1
1Functional Brain Center, Wohl institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel, 2Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel, 3Radiology Department, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel

The characterization and quantification of dynamic susceptibility contrast (DSC) imaging is important for clinical interpretation, though this calls for a reliable healthy reference. In this study, an unsupervised multiparametric method was used to classify brain tissue and a defined brain vascular territories template was used to study perfusion parameters in 25 healthy subjects. Three brain clusters were defined and classified as white matter, gray matter and major blood vessels. Perfusion parameters were significantly different between tissue types and between vascular territories. The unsupervised clustering method enabled tissue classification and may have a wide range of clinical applications.