Phillip Zhe Sun¹, Enfeng Wang¹, Xiaoan Zhang², and Jerry S Cheung^1
1Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ²Department of Radiology, 3rd Affiliated Hospital, Zhengzhou University, ZhengZhou, He Nan, China

Arterial spin labeling (ASL) MRI has been increasingly used for examining acute stroke as a research tool. However, CBF calculation requires acquisition of T1app map, which is significantly shorter than the intrinsic T1 map due to concomitant RF irradiation effects. As such, the conventional approach of normalizing with a single T1app value may not be sufficient to characterize regional CBF. We showed that parametric T1app /T1 map remained reasonably homogeneous so that T1app map can be estimated from T1 map, permitting quantitative CBF mapping. The proposed approach has been extended for multi-slice CBF measurement in vivo.

Wouter Koning¹, Johanneke H. Bluemink¹, Esben Petersen¹, Alexander Raaijmakers¹, Anke Henning², Cornelis A.T. van den Berg¹, Jaco Zwanenburg¹, Peter Luijten¹, and Dennis W.J. Klomp^1
1University Medical Center, Utrecht, Netherlands, ²ETH Zurich, Zurich, Switzerland

A setup is presented for the use of radiative antenna’s as external labeling coils for cASL at 7T. Four radiative antenna’s attached to a neck pillow filled with heavy water are used to create a B1 field in the neck. This neck pillow can be used in combination with a head coil for labeling during ASL experiments. SAR calculations show that using this setup labeling pulses for cASL can be used with a factor 5.5 longer duration than is allowed with the use of the head coil, while remaining within SAR safety guidelines.

Reiner Umathum¹, and Ann-Kathrin Homagk^1
1German Cancer Research Center, Heidelberg, Germany

A sequence controlled RF pulse switch at 7T for PASL with an external labeling coil R. Umathum, A-K. Homagk Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany Monitoring cerebral blood flow (CBF) using a separate labeling coil for pulsed arterial spin labeling (PASL) usually requires a fully equipped additional RF transmit channel comprising a synthesizer, pulse modulator, power amplifier and a special interface controller. Here we present a solution which is transparent for the scanner hardware, solely controlled by any pulse sequence at run time and which can produce any pulse shape and timing scheme which the ASL imaging sequence is capable of. First results using a water filled head phantom indicate reduced SAR at 300 MHz.

Xing Lv¹, Jing Wang², Yudong Zhang³, Jue Zhang¹, Xiaoying Wang³, Xiaoping Hu⁴, and Jing Fang^1
1College of Engineering, Peking University, Beijing, Beijing, China, ²Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China, ³Dept. of Radiology, Peking University First Hospital, Beijing, China, ⁴Biomedical Imaging Technology Center, Emory University, Atlanta, GA, United States

Among all kinds of arterial spin labeling (ASL) techniques for multi-slice perfusion imaging, Continuous ASL with a separate coil (or Dual-coil CASL) has been proven to have the best SNR with eliminated magnetic transfer interference. However, Most implementations of Dual-Coil CASL(DC-CASL) in previous reports require two independent sets of proton RF channel and amplifier, which are not currently available on most clinical MRI scanners. In this study, a portable RF transmitter, which is based on a single chip microcomputer (SCM)+ Direct Digital Synthesizer (DDS) structure, designed and tested for non-invasive perfusion imaging in clinic. The quantitative CBF measurement results testified the feasibility of this setup. With its high quality imaging, minimized size and low cost, the separated coil based CASL setup may be valuable for further clinical usage.

Sung-Hong Park¹, Jeffrey W. Barker^1,2, and Kyongtae Ty Bae^1
1Radiology, University of Pittsburgh, Pittsburgh, PA, United States, ²Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States

ALADDIN is a new imaging technique that enables us to perform interslice perfusion-weighted (PW) imaging with no separate preparation pulse. In this article, we investigated the feasibility of quantitative mapping of blood perfusion with ALADDIN at various flip angles. Sensitivity of PW signals kept increasing with flip angle. Centric phase-encode order provided twice higher sensitivity than linear phase-encode order. These experimental results agreed with the simulation results. Cerebral blood flow measured with ALADDIN was close to the values from pulsed arterial spin labeling. The current study helps us to optimize and quantitatively map ALADDIN PW signals.

Ze Wang¹, Anna Rose Childress¹, and John A Detre^2
1Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, United States, ²Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States

Arterial spin labeling (ASL) is not stable across time but no one has taken this into account during perfusion quantification. Due to the systematic labeling and control labeling, ASL CBF quantification is a natural two-class data classification process. Based on this phenomenon, we used a powerful machine learning algorithm, the support vector machine (SVM), to extract the spin labeling function from the ASL data and used it for CBF quantification. The method demonstrated significantly improved temporal SNR and spatial image quality for CBF quantification using normal healthy subjects’ data and data from patients with Alzheimer’s Disease.

Li Zhao¹, and Craig Meyer^1,2
1Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States, ²Radiology, University of Virginia, Charlottesville, Virginia, United States

By designing optimal observation times (TI) in dynamic PASL, we can achieve more accurate estimation of CBF. Here, we compare optimal designs for the high/low SNR case, White Gaussian/Rician noise model, and the results from L1/L2 norm estimation. The results show a) optimal sampling design gives accurate estimation, b) low SNR, Rician noise could result biased estimation.

Youngkyoo Jung^1,2, and Megan Johnston^2
1Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States, ²Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC, United States

3D ASL imaging provides high SNR benefit over 2D methods. Segmented 3D acquisition methods covering the entire k-space during multiple labeling periods are often preferred to reduce blurring in the slice encoding direction. However, applications of the segmented acquisition are limited to baseline perfusion imaging. We propose an interleaved 3D spiral FLASH imaging method that collects the entire k-space within a single labeling period which offers high temporal resolution, and reduces geometric distortions. We also investigated the trade-off between the number of interleaves and SNR benefit. The proposed method would be beneficial to various ASL applications.

Xiaowei Zou^1,2, and Truman R. Brown^2
1Columbia University, New York, NY, United States, ²Medical University of South Carolina, Charleston, SC, United States

PASL-like Pseudo Random Amplitude Modulation sequence using echo-planar imaging acquisition to measure CBF transit time distribution

Eidrees Ghariq¹, Michael A. Chappell^2,3, Sophie Schmid¹, Wouter M. Teeuwisse¹, Mark A. van Buchem¹, Andrew G. Webb¹, and Matthias J.P. van Osch^1
1C.J.Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands, ²Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom, ³FMRIB Centre, University of Oxford, Oxford, United Kingdom

Dual-echo arterial spin labeling (DE-ASL) facilitates simultaneous acquisition of BOLD and perfusion-weighted fMRI data. Background suppression (BGS) modules are designed to improve the low intrinsic ASL SNR, but are believed to be undesirable in DE-ASL, because they could decrease BOLD functional sensitivity. In this study, the effects of BGS-pulses on the sensitivity of DE-ASL for BOLD and CBF signal changes were studied. BGS levels of up to 90% were achieved, thereby increasing CBF sensitivity significantly, while loss in BOLD sensitivity remained small, suggesting the possibility of DE-ASL fMRI with BGS.

Xingxing ZHANG¹, Esben T. Petersen^2,3, Eidrees Ghariq¹, Jill de Vis², Andrew G. Webb¹, Wouter M. Teeuwisse¹, Jeroen Hendrikse², and Matthias J.P. van Osch^1
1The C.J.Gorter Center for High Field Magnetic Resonance, Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands, ²Department of Radiology, University Medical Center Utrecht, Utrecht, Utrecht, Netherlands, ³Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Utrecht, Netherlands

Blood T1 is a crucial parameter in the ASL technique, especially for the quantification of CBF. The increase in blood T1 at higher field strengths is one of the main presumed advantages of ASL at higher field MRIs. In this study the blood T1 was measured in the sagittal sinus at three different field strengths: 1.5T, 3T and 7T. The main findings were that the T1 increased linearly with field strength and that the T1 at 7T (2087ms) was lower than previously reported.

Thomas Kampf¹, Xavier Helluy², Christian Herbert Ziener³, Peter Michael Jakob², and Wolfgang Rudolf Bauer^4
1Experimental Physics 5, Universtity of Wuerzburg, Wuerzburg, Bavaria, Germany, ²Experimental Physics 5, University of Wuerzburg, Germany, ³Division of Radiology, German Cancer Research Center, Germany, ⁴Department of Internal Medicine I, Universitaetsklinikum Wuerzburg, Germany

The effect of the Look-Locker readout scheme on myocardial perfusion measurement applying ASL methods based on T₁ mapping is investigated. Furthermore, the effect of partially inverting the left ventricular blood during the slice selective inversion is considered. Significant influence of each issue on the obtained perfusion is found.

Matt N Gwilliam¹, David J Collins¹, Martin O Leach¹, and Matthew R Orton^1
1CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research, London, United Kingdom

The fitting of pharmacokinetic models to DCE-MRI gadolinium uptake curves is computationally expensive and complicated by several factors including a lack of arterial input function. This work presents a method for determining a simple projection vector, for various pharmacokinetic parameters, that can directly project an uptake curve into PK space. Projection vectors are optimised using a robust fitting algorithm and a training set of uptake curves. The projection vectors are then applied to a set of uptake curves to a test set from a different cohort and good correlation with model fitting techniques is found.

Patrik Brynolfsson¹, Anders Garpebring¹, Thomas Asklund², and Tufve Nyholm^1
1Dept. of Radiation Sciences, Umeå University, Umeå, Sweden, ²Division of Oncology, Dept. of Radiation Sciences, Umeå University, Umeå, Sweden

An alternative method for generation of parametric maps in dynamic contrast-enhanced MRI was investigated on in vivo data. The method is based on clustering of voxels with similar contrast agent kinetics. In this study, the clustering method was compared with a conventional voxel-by-voxel analysis. The results showed that the calculation time was reduced by a factor 8 for a single slice, and parametric maps looked visually similar. However, a correlation analysis revealed that improvements are needed for the cluster-based analysis to reach its full potential.

Yen-Peng Liao¹, Chi-Jen Chen^1,2, and Ho-Ling Liu^3
1Department of Medical Imaging, Taipei Medical University - Shuang Ho Hospital, New Taipei City, Taiwan, Taiwan, ²Department of Medicine, Taipei Medical University, Taipei City, Taiwan, Taiwan, ³Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan County, Taiwan, Taiwan

A modified reference region (mRR) model including vascular term for dynamic contrast-enhanced MR imaging (DCE-MRI) can quantify physiological parameters without the need of an arterial input function (AIF). However, inaccurate assumptions of the parameters of a reference region (RR) may induce large estimation error in the quantification of a tissue of interest (TOI). This study aimed to assess the uncertainty in the pharmacokinetic analysis with a mRR model using computer simulations. The results showed estimation errors of [+41.8 to -17.08], [+47.85 to -21.08], and [+37.67 to -24.33] for [-30% to +30%] variations on inaccurate K ^trans,RR, v_e,RR and v_p,RR , respectively.

Matt N Gwilliam¹, David J Collins¹, Martin O Leach¹, and Matthew R Orton^1
1CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research, London, United Kingdom

Analysing DCE-MRI Gadolinium uptake curves from a cohort of patients using principal component analysis can produce metrics that correlate with pharmacokinetic parameters and retain their meaning across datasets implying that treatment effects can be detected. This work demonstrates that these correlations can be improved further by taking into account onset time.

Hassan Bagher-Ebadian^1,2, Siamak P Nejad-Davarani^1,3, Rajan Jain⁴, Douglas Noll³, Quan Jiang^1,2, Ali Syed Arbab⁴, Tom Mikkelsen⁵, and James R Ewing^1,2
1Neurology, Henry Ford Hospital, Detroit, Michigan, United States, ²Physics, Oakland University, Rochester, Michigan, United States, ³Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, ⁴Radiology, Henry Ford Hospital, Detroit, Michigan, United States, ⁵Neurosurgery, Henry Ford Hospital, Detroit, Michigan, United States

In Dynamic Contrast Enhanced (DCE- MRI) studies, pharmacokinetic models rely on converting the time course of the signal intensity to changes in the longitudinal relaxation rate, ΔR1(t). However, many researchers employ the normalized Signal Intensity, for quantitative and semi-quantitative DCE analyses instead of ΔR1(t). In this study, one-dimensional error propagation is applied to the previously described analytical approach in order to investigate the difference between ΔR1(t) and normalized signal intensity profiles. A full analytical methodology is presented for quantifying and comparing the level of agreement in the profiles in both techniques for different levels of contrast enhancement ratios.

Nina Tunariu¹, David J Collins¹, Matthew Orton¹, James A d'Arcy¹, Christina Messiou¹, Veronica A Morgan¹, Sharon L Giles¹, Catherine J Simpkin², and Nandita M deSouza^1
1CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, Sutton, London, United Kingdom, ²CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, Sutton, United Kingdom

Dynamic contrast enhanced MRI (DCE-MRI) has been successfully used as biomarker of angiogenic activity in preclinical and clinical trials. The time of arrival of the bolus (onset time) definition has a great influence on DCE parameter estimates and an incorrect onset time can lead to a strong bias. In our experience the automated methods can fail to detect an accurate onset time in cases of tumors that show low contrast uptake, and manual adjustment is essential. This study compares the effect of the onset time as detected using four different methods, on the DCE parameters estimates and their reproducibility.

Martin Buechert¹, Henrik Gille², Jan Kuhlmann³, and Klaus Mross^4
1MRDAC Magnetic Resonance Development and Application Center, University Medical Center Freiburg, Freiburg, Germany, ²Pieris AG, Freising, Germany,³University Medical Center, Freiburg, Germany, ⁴Klinik für Tumorbiologie, Freiburg, Germany

For assessing treatment response DCE-MRI is a valuable tool. Parameters calculated using pharmacokinetic modeling may depend on the sampling duration which equals the number of sampled data points for equally distributed sampling. This was previously investigated by computer simulations but there is limited verification of these findings using real in vivo patient data. This dependency on sampling duration of the Ktrans, Ve and the fit accuracy were investigated using patient data with a long sampling duration in comparison to an artificial shortened sub set of these data. Results were in agreement with the published simulations.

Kumar Rajamani¹, Dattesh Shanbhag¹, Rakesh Mullick¹, and Sandeep N Gupta^2
1Medical Image Analysis, GE Global Research, Bangalore, Karnataka, India, ²Biomedical Image Processing Laboratory, GE Global Research, Niskayuna, NY, United States

We have demonstrated the precision of pharmacokinetic parameters and its effect due to duration of the time-intensity signal. Our results demonstrate that for the prostate case it is preferable to have scan duration of 5 minutes. Scan durations of more than 6 minutes do not generally contribute to any further improvement in the parameters.

Yi-Ying Wu¹, Chen-Hao Wu^1,2, Chih-Ming Chiang¹, Chi-Chang Chen¹, and Jyh-Wen Chai^1
1Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan, ²Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan

In DCE-MRI, the venous output function (VOF) from superior sagittal sinus (SSS) is commonly used to replace arterial input function (AIF) to measure permeability of brain lesions. However, there is a lack of comprehensive studies about how to sample the vessel voxels for VOF measurements to achieve a good consistency in quantification of permeability in DCE-MRI. The aim of this study is to investigate the consistency in permeability measurements of metastatic brain tumors using VOF and AIF to analyze DCE-MRI with the commercial-available automatic software.

Prativa Sahoo¹, Rishi Awasthi², Ram KS Rathore¹, and Rakesh Kumar Gupta^2
1Mathematics & Statistics, Indian Institute of Technology, Kanpur, Kanpur, Uttar Pradesh, India, ²Radiodiagnosis, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India

DCE-MRI was performed on 46 patients with 32 patients having Chronic Infective and 14 patients having Chronic Inflammatory Knee Arthritis. Discriminate function analysis was performed to discriminate tubercular and non-tubercular inflammation. For DCE-MRI quantification both local AIF and global AIF was used. Pharmacokinetic analysis was performed using two compartmental and three compartmental model. Our result suggest that Global AIF and Local AIF does not effects the discrimination of tuberculoma from non-tuberculoma however using three compartment model instead of two compartment model significantly improves the discrimination.

Greg O. Cron^1,2, Thanh B. Nguyen^1,2, Rebecca E. Thornhill^1,2, Jean-Francois Mercier¹, Claire Foottit¹, Carlos H. Torres^1,2, Santanu Chakraborty^1,2, John Woulfe^1,2, Jean-Michel Caudrelier^1,2, John Sinclair^1,2, Matthew J. Hogan^1,2, Ian Cameron^1,2, and Mark E. Schweitzer^1,2
1The Ottawa Hospital, Ottawa, ON, Canada, ²The University of Ottawa, Ottawa, ON, Canada

For DCE-MRI of cerebral gliomas, temporal resolution can be increased using 2D sequences with limited coverage. However, the resultant saturation and inflow effects distort the measured vascular input function (VIF). A relatively new way to solve this problem is phase-derived VIFs (VIF). The purpose of this study was to compare the reproducibility and diagnostic value of tracer kinetic parameters (TKPs) calculated with individually-measured VIF and a published population-averaged VIF (VIFpop), in a group of 31 patients. VIF was superior to VIFpop for TKP reproducibility. VIF- and VIFpop- derived TKPs were equally good at distinguishing low- from high- grade tumors.

Dominique L. Jennings¹, Daniel B. Chonde², Jayashree Kalpathy-Cramer¹, Kim Mouridsen³, Gregory Sorensen¹, Alexander Guimaraes⁴, Bruce Rosen¹, Tracy Batchelor⁵, Elizabeth R. Gerstner⁵, and Ciprian Catana^1
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, ²HST, Massachusetts Institute of Technology, Boston, MA, United States, ³Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, ⁴Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, ⁵Department of Neurology and Cancer Center, Massachusetts General Hospital, Boston, MA, United States

Phase-based DCE-MRI measurements of the vascular input function are insensitive to common imaging-related artifacts observed in magnitude-based vascular input functions. Here we propose the use of PET-based vascular input functions to evaluate the differences between the two MR-based measurements and relative effects of both on estimates of K^trans.

Michael A Chappell^1,2, Thomas W Okell², Bradley J MacIntosh³, Peter Jezzard², and Stephen J Payne^1
1Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom, ²FMRIB Centre, University of Oxford, Oxford, United Kingdom,³Department of Medical Biophysics, University of Toronto, Toronto, Canada

There a number of sources of signal in Arterial Spin Labelling perfusion measurements. The major components that have been addressed to date are label undergoing exchange in the capillaries from which blood flow measurements can be obtained and that remaining in large arteries. However, it has been proposed that signal in impermeable small arterial vessels before the capillary space may also need to be accounted for. In this work the effects of pre-capillary signal on flow and blood volume estimation using multi-inversion time data and a model-based analysis strategy are examined.

Qin Qin^1,2, Alan J Huang^2,3, Jun Hua^1,2, Robert Stevens⁴, John E Desmond⁵, and Peter C.M. van Zijl^1,2
1Department of Radiology, Johns Hopkins University, Baltimore, Maryland, United States, ²Kirby Center, Kennedy Krieger Institute, Baltimore, Maryland, United States, ³Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States, ⁴Department of Anesthesiology Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, United States, ⁵Department of Neurology, Johns Hopkins University, Baltimore, Maryland, United States

Typically, cerebral blood flow (CBF) measurements using Pseudo-Continuous ASL (PCASL) are acquired at a single post-labeling delay assuming minimum difference of arterial arrival times (AAT) across regions. We performed 3D high-resolution whole-brain PCASL at multiple post-labeling delays and analyzed the data using a general kinetic model. Both voxel-based and ROI-based fitting results displayed a heterogeneous distribution of AAT in various regions. The PCASL measurements over a series of delays can help estimate CBF and ATT simultaneously, which will improve the accuracy of CBF quantification. Implementation of this approach (15 min) is demonstrated to be feasible on a 3T clinical scanner.

Yoon Chung Kim¹, Yoon-Hee Cha¹, Shruthi Chakrapani¹, and Danny JJ Wang^1
1University of California, Los Angeles, CA, United States

Perfusion is normally coupled to metabolism and neural function, and correlations of those for each brain region would be useful in interpreting future studies for investigating normal brain function or a diseased state. However, existing studies comparing ASL and FDG-PET are limited by small sample size. Thus, we performed a systematic evaluation of resting pseudo-continuous ASL (pCASL) and 18FDG-PET on 19 healthy subjects to determine the correlation between perfusion and FDG-PET CMRglu measurements across different brain regions. Our study showed that there is generally a good correlation between ASL CBF and PET CMRglu across pixels in the group mean images whereas the correlation of mean CBF and CMRglu values across 19 subjects is intermediate. We also found that metabolism of caudate and putamen is significantly higher relative to perfusion rate, consistent with an earlier report. While susceptibility effects and ROI size differences may to a certain degree account for the observed regional variations, the biophysical mechanism underlying the coupling and uncoupling of glucose metabolism and perfusion across brain regions warrants further investigation.

Xiufeng Li¹, Jeffrey S. Spence^2,3, Subhendra N. Sarkar⁴, David E. Purdy⁵, Gregory J. Metzger¹, Robert W. Haley³, and Richard W. Briggs^3,6
1Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, ²Clinical Sciences, UT Southwestern Medical Center, Dallas, TX, United States, ³Internal Medicine, UT Southwestern Medical Center, Dallas, TX, United States, ⁴Radiology, Harvard Med. School, Beth Israel Deaconess Med. Ctr., Boston, MA, United States, ⁵Siemens Healthcare, Malvern, PA, United States, ⁶Radiology, UT Southwestern Medical Center, Dallas, TX, United States

Measuring hippocampal longitudinal sub-region perfusion has significant clinical relevance, with potential for better diagnosis and understanding of healthy and pathological hippocampal physiology. To evaluate the reliability of measuring hippocampal longitudinal sub-region perfusion using arterial spin labeling (ASL) imaging, measurement errors due to both random spatial noise and temporal physiological noise in OPTIMAL FAIR ASL studies of rCBF were evaluated. Results indicate that hippocampal longitudinal sub-region perfusion can be reliably measured using ASL imaging.

Rui Wang¹, Zhentao Zuo¹, Rong Xue¹, Yan Zhuo¹, and Danny JJ Wang^2
1State Key Lab of Brain and Congitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics,Chinese Academy of Sciences, Beijing, China, ²Neurology,UCLA, Los Angeles, CA, United States

The goal of this study was to estimate the labeling efficiency and longitudinal reliability of vessel encoding pseudo-continuous ASL (VE-PCASL) for the 3 main feeding arteries at 3T, utilizing phase-contrast (PC) MRI as the reference standard. We calculated the global labeling efficiency and those of the right internal carotid (R), left internal carotid (L), and basilar artery (B) of VE-PCASL. Our results demonstrated that the labeling efficiency of VE-PCASL is reproducible and is not sensitive to labeling locations. However, the labeling efficiency of B was lower than that of the carotid arteries.

Nolan S. Hartkamp¹, Michael Helle^2,3, Reinoud P.H. Bokkers¹, Jeroen Hendrikse¹, and Matthias J.P. van Osch^4
1Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands, ²Institute of Neuroradiology, Christian-Albrechts-Universität, Kiel, Germany, ³Philips Technologie GmbH, Innovative Technologies, Research Laboratories, Hamburg, Germany, ⁴C.J. Gorter Center, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands

The aim of this study was to compare the differences of perfusion territories determined by vessel-encoded and super-selective pseudo-continuous arterial spin labeling MRI. Cases are presented to illustrate the capability of either technique to determine correct perfusion territories in vascular variations and mixed perfusion areas. The results of this study show that perfusion territories of vessel-encoded and super-selective p-CASL RPI agree reasonably well. Vessel encoded ASL however fails to detect mixed perfusion areas, which leads to erroneous boundaries in these areas.

Thomas W Okell¹, Michael A Chappell², and Peter Jezzard^1
1FMRIB Centre, Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, United Kingdom, ²Institute of Biomedical Engineering, Department of Engineering, University of Oxford, Oxford, Oxfordshire, United Kingdom

Quantification of cerebral blood flow (CBF) may be confounded in brain regions fed by multiple arteries with different transit delays, as may be the case in patients with significant collateral flow. Vessel-encoded pseudocontinuous arterial spin labeling (VEPCASL) generates artery specific perfusion maps, allowing the fitting of a kinetic model to each arterial component separately. Here we compare CBF quantification and signal-to-noise ratio (SNR) using VEPCASL to conventional PCASL in healthy volunteers. Despite reduced SNR, the CBF estimates from VEPCASL were comparable to those from PCASL. Therefore VEPCASL may improve CBF quantification in cases of mixed blood supply.

Yi Dang¹, Bing Wu², Ying Sun³, Dapeng Mo⁴, Xiaoying Wang^1,2, Jue Zhang^1,3, and Jing Fang^1,3
1Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China, ²Dept. of Radiology, Peking University First Hospital, Beijing, China,³College of Engineering, Peking University, Beijing, China, ⁴Dept. of Neurosurgery, Peking University First Hospital, Beijing, China

The contribution of collaterals from internal carotid can be assessed by depicting of vascular perfusion territories using arterial spin labeling. But so far there is no method available to evaluate the collateral perfusion territory from external carotid in MR. In this study, we present a new labeling scheme on the basis of the vessel-encoded arterial spin labeling to quantitatively assess collaterals from external carotid. The results demonstrate that the proposed method is able to visualize the perfusion territory of ECA to depict the status of collateral circulation and can be used as a promising tool to assess cerebrovascular surgery.

Rajesh Kumar¹, Mary A Woo², Danny JJ Wang³, Paul M Macey², Jennifer A Ogren², Gregg C Fonarow⁴, and Ronald M Harper^1
1Neurobiology, University of California at Los Angeles, Los Angeles, CA, United States, ²UCLA School of Nursing, University of California at Los Angeles, Los Angeles, CA, United States, ³Neurology, University of California at Los Angeles, Los Angeles, CA, United States, ⁴Cardiology, University of California at Los Angeles, Los Angeles, CA, United States

Heart failure (HF) patients show brain injury in autonomic, neuropsychological, and cognitive regulatory sites, possibly resulting from localized hemodynamic alterations; however, regional cerebral blood flow (CBF) activity in those areas is unknown. We used non-invasive arterial spin labeling (ASL) procedures to assess regional CBF changes in HF subjects over controls. Multiple localized brain sites in HF, including frontal, parietal, and temporal regions, basal-ganglia, limbic, brainstem, and cerebellar areas showed reduced CBF, compared to controls. Regionally reduced CBF may stem from initial injury to midline medullary raphe regulatory sites, which cascades to modify vascular supply to more-rostral and cerebellar areas.

Bradley J MacIntosh^1,2, Manus J Donahue³, Michael A Chappell⁴, David E Crane¹, and Peter Jezzard^5
1Imaging Research, Sunnybrook Research Institute, Toronto, ONTARIO, Canada, ²Medical Biophysics, University of Toronto, Toronto, ON, Canada,³Radiology, Vanderbilt University School of Medicine, ⁴Institute of Biomedical Engineering, University of Oxford, ⁵Clinical Neurology, University of Oxford

Arterial spin labeling can be used to study stroke and other cerebrovascular diseases. Using mutiple inflow ASL (i.e. post-label delays), it is possible to estimate cerebral blood flow (CBF) and other relevant parameters like arterial transit time (ATT). We develop a metric to determine the proportion of voxels whose ASL model fit produces significant estimates of CBF and ATT. Participants had a range of carotid artery disease of which case some went on to have a carotid endarterectomy (CEA). Fewer significant CBF voxels were detected in the hemisphere with greater stenosis and among individuals went for CEA surgery.

Henri JMM Mutsaerts¹, Dennis FR Heijtel¹, Charles BLM Majoie¹, Edo Richard², and Aart J Nederveen^1
1Radiology, Academic Medical Center, Amsterdam, North-Holland, Netherlands, ²Neurology, Academic Medical Center, Amsterdam, North-Holland, Netherlands

The present data of 34 patients with varying degrees of dementia suggest that total WM perfusion can be obtained from relatively short scantimes (2 min.) using p-CASL with background suppression. Rather than disregarding WM perfusion data because of too low SNR for voxel-wise analyses, this data encourages to analyze the whole WM perfusion as potential extra marker. This could be a clinically relevant marker as WM degradation is involved in, and may even be the onset of, many neurological disorders.

Iris Asllani¹, Christian Habeck², Ronald Lazar², and Randolph Marshall^2
1Columbia Universtiy, New York, NY, United States, ²Columbia Universtiy

One of the most significant challenges in stroke neurology is predicting outcomes. While fMRI has played a key role in our understanding of how stroke affects brain function and cognition, translation of imaging data into clinically useful outcomes has been largely ineffectual. This is mainly due to inherent limitations of task-based BOLD fMRI and to a lack of integration of imaging data with other physiological variables. In this study we address these shortcomings by: 1) Acquiring resting functional connectivity networks of cerebral blood flow (CBF) using arterial spin labeling (ASL) perfusion fMRI. 2) Assessing how focal injury affects the integrity of these networks. 3) Investigating the relationship between these networks and other physiological correlates of disease. We focus on carotid occlusive disease as an ideal model for testing perfusion based functional networks. We plan to use tissue specific ASL fMRI to identify perfusion resting state functional networks (pRFNs) in patients with carotid occlusive disease and healthy controls. Our primary goal is to assess how pRFNs are affected by infarction, hypoperfusion, functional state, and collateral flow.

Dattesh D Shanbhag¹, Sandeep N Gupta², Kumar T Rajamani¹, Yingxuan Zhu³, and Rakesh Mullick^4
1Medical Image Analysis Laboratory, GE Global Research, Bangalore, Karnataka, India, ²Biomedical Image Processing Laboratory, GE Global Research, Niskayuna, NY, United States, ³Image Analytics Laboratory, GE Global Research, Niskayuna, NY, United States, ⁴GE Global Research, Biosignatures & Signal Processing, Bangalore, Karnataka, India

A completely automated and generalized methodology for detection of vascular input functions with dynamic contrast enhancement data is presented. The technique is demonstrated for brain and prostate DCE data with excellent correlation (~0.97) between manually defined VIF and that detected using automated method. The method provides consistent and reliable VIF well suited to anatomy being studied: in brain (sagittal sinus) and in prostate (femoral artery

Robert Merwa¹, and Gernot Reishofer^2
1Medical Engineering, Upper Austria University of Applied Sciences, Linz, Austria, ²Department of Radiology, Medical University of Graz, Graz, Austria

DCE T1-weighted MRI provides a technique for the determination of human tissue parameters. For field strength above 1.5 T B1-inhomogeneities occur which produce considerable intensity variations and the estimation of these tissue parameters fails. In order to tackle this challenge a huge amount of images and complex mathematical calculations are used hence the manual handling is pretty difficult and not fail-save. The aim of this work was to develop a software package for the automatic calculation of the (a) T1-relaxation time, (b) concentration of the contrast agent, (c) AIF in a major artery and (d) tissue parameters for defined regions.

Tian Liu¹, Yinghua Ma², Min Lou³, Timothy Vartanian², and Yi Wang^4
1MedImageMetric LLC, New York, NY, United States, ²Neuroscience and Neurology, Weill Cornell Medical College, New York, New York, United States,³Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hang Zhou, Zhe Jiang, China, ⁴Radiology, Weill Cornell Medical College, New York, New York, United States

In vivo quantification of contrast agent using T1/T2* based methods are subject to large errors due to quenching effects. On the other hand, superparamagnetic iron oxide or gadolinium based contrast agents are highly paramagnetic, making them ideal candidates for quantitative susceptibility mapping. In this study, we demonstrated the feasibility of using QSM for the investigation of vasculature in the human brain tumor.

Su-Chin Chiu¹, Chun-Jung Juan², Hsiao-Wen Chung¹, Cheng-Chieh Cheng¹, Hing-Chiu Chang³, Cheng-Yu Chen², and Guo-Shu Huang^2
1Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, ²Radiology, Tri-Service General Hospital, Taiwan, ³GE Healthcare, Taiwan

The effects of fat saturation on quantitative perfusion measurements using dynamic contrast-enhanced (DCE) in parotid glands have been proved. In this study, it is proposed to select a pre-contrast baseline of low-fat tissue to reduce the effect, which is effective in reducing bias from fat content in DCE-MRI of the parotid gland. The disagreements between perfusion measurements with and without fat saturation scan are reduced to the level without statistical significance (p>0.05) both in phantom and in vivo experiments.

Federico Pineda¹, Marko Ivancevic², Gillian Newstead¹, Hiroyuki Abe¹, Johannes Buurman², and Gregory Karczmar^1
1University of Chicago, Chicago, IL, United States, ²Philips Healthcare, Best, Netherlands

Calibration phantoms that can be inserted in a breast coil during a routine DCE-MRI of the breast were developed. These phantoms provide reference signals that can be used to generate quantitative concentration of contrast media and MRI-detectable proton density maps. To date 23 patients have been scanned with these phantoms, peak concentration values suggest a correlation between malignancy and concentration. MRI-detectable proton density may be a novel source of diagnostically useful information. These quantitative images have the potential to provide standardized, quantitative information that is independent of acquisition parameters, which could facilitate comparisons across different scanners and/or institutions.

Jing Yuan¹, Steven Kwok Keung Chow¹, David Ka Kwai Yeung¹, Anil T Ahuja¹, and Ann D King^1
1Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong

This study is to quantitatively evaluate the kinetic parameter estimation deviation with dual-flip-angle (DFA) T1 mapping in head and neck (HN). 23 patients with HN tumors received DCE-MRI. T1 maps were generated based on multiple-flip-angle (MFA) method and DFA combinations. kep, Ktrans and vp maps based on MFA and DFAs were calculated and compared in primary tumor, salivary gland and muscle. The results showed that DFA-induced T1 deviations could result in significant errors in kinetic parameter estimation, particularly Ktrans and vp, even with the optimized DFAs. MFA is suggested for accurate pharmacokinetic analysis in HN if scan time permitted.

Philippe Gauderon^1,2, Marina Salluzzi^2,3, Michel Louis Lauzon^2,3, Michael Richard Smith^1,4, and Richard Frayne^2,3
1Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada, ²Seaman Family MR Research Centre, Calgary, Alberta, Canada, ³Radiology, University of Calgary, Calgary, Alberta, Canada, ⁴Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada

A fast 3D SPGR sequence is suitable for dynamic contrast enhanced (DCE) cerebral perfusion imaging is demonstrated. As a proof of concept, the investigation validated the suitability of the imaging sequence for quantitative perfusion imaging using a static phantom. Perfusion maps generated from initial in vivo acquisitions were in agreement with literature values. The main shortcoming of the sequence was the low contrast-to-noise ratio (CNR) in cerebral tissue, though this concern was somewhat mitigated by increasing TR and using other approaches to preserve temporal resolution.

Renate Gruner^1,2, Ingfrid Salvesen Haldorsen¹, Torfinn Taxt^1,2, and Helga Salvesen^2,3
1Dept of Radiology, Haukeland University Hospital, Bergen, Bergen, Norway, ²University of Bergen, Bergen, Bergen, Norway, ³Dept of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Bergen, Norway

The purpose was to explore the feasibility of dynamic contrast enhanced MRI (DCE-MRI) in endometrial carcinomas and investigate possible correlation between perfusion derived parameters and the apparent diffusion coefficient (ADC) estimated from diffusion weighted imaging. Endometrial carcinoma is the most common gynecological malignancy in industrialized countries, and the incidence is increasing. Tracer kinetic modeling was performed using the adiabatic approximation model of Johnson and Wilson (aaJW). The endometrial carcinomas displayed lower post contrast enhancement and faster contrast was-out compared to normal myometrium. These first results in ten patients show that DCE-MRI acquisition and modeling in highly feasible in endometrial carcinomas.

Andrea Kassner^1,2, Meah Gao², Jackie Leung¹, Madison McGregor², Neil Sokol², and David Mikulis^2,3
1Diagnostic Imaging, The Hospital for Sick Children, Toronto, Ontario, Canada, ²Medical Imaging, University of Toronto, Toronto, Ontario, Canada,³Medical Imaging, Toronto Western Hospital, Toronto, Ontario, Canada

Loss of blood-brain barrier (BBB) integrity in acute ischemic stroke is a precursor to hemorrhagic transformation. Dynamic contrast enhanced (DCE) CT and MR imaging can quantify the integrity of the BBB when used with a suitable pharmacokinetic model. We compared DCE-CT and DCE-MRI permeability ratios in a rodent stroke model using the same pharmacokinetic model and determined a statistically significant correlation between the two modalities. The results of this study open up the possibility for multi-modal DCE studies.

HyunJin Park¹, Jin Seo², Young Han Lee², Ho-Taek Song*², Chang Hoon Moon³, Hee-Soon Lee³, Ho Yong Lee³, Hee-Jung Cha⁴, and Young Joo Min^3
1Brain Korea 21 Project for Medical Science, Yonsei University, Seoul, Korea, ²College of Medicine, Yonsei University, Seoul, Korea, ³Biomedical Research Center, Ulsan University Hospital, Korea, ⁴Department of Pathology, Ulsan University Hospital, Korea

Dynamic contrast enhanced MRI (DCE-MRI) technique can provides quantitative information about the tumor vasculature and it has been widely used to evaluate the biological activity of targeted therapy in clinical trials. However, there has been little known about the quantitative imaging validation of proteasome activity driven by vascular disrupting agent (VDA) in a cancer model by MRI. Therefore, we investigated antivascular effects of VDA in CT26 colon cancer xenograft mouse model following treatment with the KML001 by DCE-MRI. Significant decrease (p<0.05) of Kep was observed in post treatment of KML001.

Shigeyoshi Saito¹, Yuto Kashiwagi², Ryota Ogihara¹, Akie Sugiura¹, Takashi Konishi¹, Shin Takamatsu¹, Yuuki Takeuchi¹, Mana Tsugeno¹, Kohji Abe², and Kenya Murase^1
1Department of Medical Physics and Engineering, Osaka University, Suita, Osaka, Japan, ²Innovative Drug Discovery Research Laboratories, Shionogi & Co., Ltd, Toyonaka, Osaka, Japan

Hyperglycemia causes damage in the blood vessels and nerves of the body, which in turn develop into the major complications of diabetes. Peripheral neuropathy and peripheral circulatory disorder may induce diabetic foot lesions Our purpose of this study was to assess peripheral micro-vessel damage in streptozotocin (STZ)-induced diabetic rats by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and histological experiment.

Teodora-Adriana Perles-Barbacaru¹, Francois Berger¹, and Hana Lahrech^1
1Grenoble Institute of Neurosciences, INSERM U836, Grenoble, France

The Rapid Steady State T₁ (RSST₁) MRI technique, previously used with intravenous injections, can be used with intraperitoneal (i.p.) injections of Gd-DOTA to acquire cerebral blood volume fraction (BVf) maps in mice. The longer time window after i.p. administration of Gd-DOTA is used to study the sensitivity of the RSST₁-technique to BVf changes induced by the vasodilator Acetazolamide. A 20% BVf increase was observed within 10 minutes after Acetazolamide injection confirming the vascular biodistribution of Gd-DOTA and validating the technique. The RSST₁-technique with i.p. administration of Gd-DOTA can therefore be used for pharmacological MRI experiments in mice.

Gregory S. Duane¹, Yanwei W. Wang², Blake R. Walters², and Jae K. Kim^2
1Thunder Bay Regional Research Institute, Thunder Bay, ON, Canada, ²Thunder Bay Regional Research Institute

The impulse-propagator (matrix) method is extended to a three-dimensional idealized cell geometry describing nucleus, cytoplasm, and extracellular fluid. A basis is constructed, appropriate for the boundary conditions specified on spheres, consisting of spherical Bessel functions of radius multiplied by spherical harmonics in the angular variables. For a PGSE sequence, clear diffraction patterns are obtained for both nucleus and cytoplasm, with cytoplasm dominating the total signal. Results compare favorably with Monte Carlo simulation results. With OGSE, the nuclear diffraction pattern dominates. In either case, vestiges of the diffraction pattern in the total signal could potentially be used to assess nucleus size.

Carl-Fredrik Westin¹, Ofer Pasternak¹, and Hans Knutsson^2
1Department of Radiology, BWH, Harvard Medical School, Boston, MA, United States, ²Department of Biomedical Engineering, Medical Informatics, Linköping University, Linköping, Sweden

Minimizing the error propagation that a diffusion MRI gradient scheme introduces is an important task in the design of robust and un-biased experiments. We propose two schemes for the construction of rotationally invariant multiple-shells. The first is a dual frame method that optimizes the rotation invariance of any set of samples. The second uses a subset of the icosahedral set that can intuitively be used for nested rotationally invariant schemes with pre-defined number of samples. Rotationally invariance produces orientationally unbiased estimates and reduces the correlation of the samples, which is an important feature for reconstruction methods such as multiple shells and compressed sensing.

Christophe Lenglet¹, Stamatios Sotiropoulos², Steen Moeller¹, Junqian Xu¹, Edward J Auerbach¹, Essa Yacoub¹, David Feinberg³, Kawin Setsompop⁴, Lawrence Wald⁴, Tim E Behrens², and Kamil Ugurbil^1
1Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, ²Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom, ³Advanced MRI Technologies, Sebastopol, CA, United States, ⁴Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States

Signal intensity in magnitude MR images follows a Rician distribution when single-channel receiver coils are employed. For multi-channel coil acquisitions, noise properties change, and the observed noise levels depend on the image reconstruction method used to combine information from different coils. This is problematic for diffusion-weighted MRI, where any artificial elevation of the noise floor limits the ability to properly quantify the signal attenuation and, ultimately, estimate fiber orientation for tractography. We propose to use a multi-channel SENSE1 reconstruction of GRAPPA un-aliased data, which exhibits Rician noise properties, and demonstrate its advantage over the RSoS reconstruction for fiber orientation estimation.

Michal E Komlosh^1,2, Evren Ozarslan^1,2, Martin J Lizak³, and Peter J Basser^1
1STBB,PPITS,NICHD,NIH, Bethesda, MD, United States, ²CNRM,USUHS, Bethesda, MD, United States, ³NMRF,NINDS,NIH, Bethesda, MD, United States

A novel 3D acquisition scheme was used to map the average axon diameter of a complex white matter structure with double-PFG filtered MRI. The method was tested on a coronal slice of a rat brain where the orientation of white matter within the corpus callosum is known to vary.

April M Chow¹, Victor Ai², Polly SY Cheung³, Siu Ki Yu¹, and Gladys G Lo^2
1Medical Physics & Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China, ²Department of Diagnostic and Interventional Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China, ³Breast Care Center, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China

Diffusion-weighted imaging (DWI) characterizes the random microscopic motion of molecules and enables assessment of tissue microstructure. This technique has been widely used to characterize malignant and benign breast lesions. A number of studies have been reported to optimize b-value for improving the detection of changes in pathologies in various organs. However, study on effect of b-value on DWI quantitation in detecting malignant breast lesion has been limited. In this study, the effect of b-value on the absolute quantitation of ADC and their diagnostic performance in detecting malignant breast lesions was investigated at 3 T. The results showed that the apparent diffusivities generally decreased with b-value in both malignant breast lesions and normal fibroglandular tissue. The diagnostic accuracy of ADC in detecting malignant breast lesions increased with b-value.

Jun-Cheng Weng^1,2, Fatima Ali Nasrallah³, and Kai-Hsiang Chuang^3
1School of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan, ²Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan, ³MRI Group, Singapore Bioimaging Consortium, A*STAR, Singapore, Singapore

Diffusion MRI is a technique for studying various aspects of microscopic tissue composition and organization in the central nervous system (CNS). The diffusion time is a key parameter to determine restricted diffusion in microstructures and hence the sensitivity of diffusion MRI to different spatial dimensions. However, it is not straightforward to implement pulsed gradient spin echo (PGSE) diffusion experiments with short diffusion times that are needed to highlight structures at microscopic scales. One alternative is to use oscillating gradient spin echo (OGSE) or the so-called temporal diffusion spectroscopy, which allows short diffusion time better than PGSE sequence, to provide a unique way to measure water diffusion. Diffusion spectrum imaging (DSI) is one of the diffusion MRI techniques that can map complex fiber architecture in the brain. We sought to apply OGSE DSI to identify minuscule neuroarchitecture in the brain. By applying oscillating diffusion-sensitive magnetic gradients to tag translational motion of water molecules, 3D probability density function (PDF) of molecular displacement can be reconstructed from the measured OGSE DSI data. For comparison, diffusion tensor images (DTI) of the rat brain were acquired using the OGSE and PGSE sequences. We demonstrate DSI maps with oscillating gradient revealed novel tissue contrast in the rat hippocampus.

Yong Wang¹, and Sheng-Kwei Song^1
1Radiology, Washington University in St. Louis, Saint Louis, MO, United States

Diffusion basis spectrum imaging has recently been developed to resolve the crossing fiber and partial volume effects of inflammation or CSF. However, prototype DBSI diffusion scheme has not been optimized. This study employed Cramer-Rao lower bound analysis to compare the precision of DBSI using a multiple-shell scheme vs. the grid scheme. Monte Carlo simulation was employed to examine the effect of signal quality, diffusion weighting strength, and diffusion gradient distribution on the accuracy and precision of DBSI. We found that grid scheme with higher SNR, stronger diffusion weighting, and optimized diffusion gradient distribution can significantly improve the quality of DBSI solution.

Othman I Alomair¹, Graham J Galloway¹, Ian M Brereton¹, Maree Smith², and Nyoman D Kurniawan^1
1Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia, ²Pharmacy School, University of Queensland, Brisbane, Queensland, Australia

Segmented echo planar imaging diffusion weighted imaging has been robust in acquiring data at 16.4 Tesla magnetic field with HARDI reconstruction within experimental time frame.

Giulia Di Pietro^1,2, Marco Palombo^2,3, and Silvia Capuani^2,3
1IIT@Sapienza, Physics Department, Rome, Italy, Italy, ²“Sapienza” University of Rome, Physics Department, Rome, Italy, ³CNR IPCF UOS Roma, Physics Department, “Sapienza” University of Rome, Rome, Italy

Effective Gi measured by using Spin-Echo (SE), Diffusion Decay Internal Field (DDIF) and Modified Diffusion Decay Internal Field (DDIF(M)) method for discriminating porous systems characterized by different pores size were compared. The behaviors of Gi extracted from SE, DDIF and DDIF(M) as a function of beads sizes, show similar trends. However, Gi values extracted from SE decay better discriminates between different porous systems when compared to Gi extracted from DDIF and DDIF(M) decays. Finally SE method, unlike DDIF method, can be easily implemented on clinical scanners and requires less time for data acquisition and data processing than DDIF one.

Matthias Weigel¹, and Jürgen Hennig^1
1Dept. of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany

Recent work showed that ‘modern’ types of turbo spin echo sequences (TSE) using low and varying refocusing flip angles and high resolution such as SPACE, VISTA, and CUBE have an inherent diffusion sensitivity b_eff, which can generate participating diffusion contrast in the image. The current work demonstrates that these b_eff are not sequence-specific constants, on the contrary, they notably depend on the relaxation times and T2 in particular, as well as on the diffusion coefficient. Thus, TSE inherent diffusion sensitivity significantly depends on the tissue, which is also valid for TSE based preparation schemes such as the superstimulated echo mechanism.

Dan Xu¹, Gaohong Wu², Kenichi Kanda², Joe K. Maier², and Kevin F. King^1
1Applied Science Lab, GE Healthcare, Waukesha, WI, United States, ²MR Engineering, GE Healthcare, Waukesha, WI, United States

High order eddy currents (HOEC) can cause significant, direction-dependent image distortions and image shape/intensity discontinuities between station boundaries in whole body diffusion weighted imaging (WB-DWI). In this paper, we use a combined prospective and retrospective compensation method to correct HOEC induced distortions. WB-DWI volunteer results show that the method can effectively reduce in-plane distortion, misregistration, and station boundary discontinuities, thus significantly improving WB-DWI image quality.

A. Alhamud¹, M Dylan Tisdall^2,3, Khader M Hasan ⁴, André J.W. van der Kouwe^2,3, and Ernesta M Meintjes^1
1University of Cape Town, Cape Town, WC, South Africa, ²Athinoula A. Martinos Center for Biomedical Imaging, ³Department of Radiology, Harvard Medical School, ⁴University of Texas Health Science Center, Houston, United States

Previously, we introduced volumetric navigators (3D-EPI) to perform prospective motion correction in diffusion tensor imaging (DTI) that allows real-time tracking of head pose. The navigated diffusion sequence has been further modified to reacquire motion corrupted diffusion volumes during which the motion exceeded a pre-defined threshold. The purpose of this work is to highlight the effect of subject head motion and the effects of retrospective and prospective motion correction with the reacquisition on the diffusion data, in particular, the fractional anisotropy (FA) of the whole brain-white matter (WM).

Klaus H. Fritzsche^1,2, Bram Stieltjes², Thomas van Bruggen², Hans-Peter Meinzer², Carl-Fredrik Westin¹, and Ofer Pasternak^1
1Laboratory of Mathematics in Imaging, Harvard Medical School, Boston, Massachusetts, United States, ²German Cancer Research Center, Heidelberg, Germany

Partial volume is a major confounding factor in the analysis of diffusion tensor imaging datasets. The mixing effects of different compartments within each voxel are non-linear, acquisition dependent, and likely to exceed microstructural effects of interest. In this work, we combine two approaches to ameliorate these problems: Free-water elimination that eliminates intra-voxel CSF contamination and partial volume clustering that classifies and probabilistically selects all non-contaminated voxels. We demonstrate the increased sensitivity of this method in a tract specific analysis of the corpus callosum, recognizing abnormalities on a clinical dataset of Alzheimer’s disease, compared with matched controls.

Corey Allan Baron¹, and Christian Beaulieu^1
1Biomedical Engineering, University of Alberta, Edmonton, AB, Canada

Conventional DTI can be impaired by partial volume effects, particularly for brain structures adjacent to cerebrospinal fluid (CSF). We describe two methods of CSF signal reduction that do not increase SAR nor affect scan time: 1) a reduction of repetition time by acquiring DTI data in smaller sets of slices to reduce the signal contributions from long T1 CSF; 2) the application of a small degree of diffusion weighting on the minimal b values to attenuate CSF (i.e. do not acquire b=0 images). The techniques are evaluated using deterministic tractography of the fornix in five individuals.

Dariya I. Malyarenko¹, Brian D. Ross¹, and Thomas L. Chenevert^1
1Radiology - MRI, University of Michigan, Ann Arbor, Michigan, United States

Gradient non-linearity leads to spatially-dependent b-values and consequently significant non-uniformity error (~10-20%) in ADC measurements over clinically-relevant FOVs. For quantitative analysis of ADC errors, a gradient correction tensor model of spatially-dependent gradient fields was used. The model included the effect of imaging gradients, gradient cross-terms and their influence in presence of media anisotropy. All-inclusive error analysis allowed finding minimal number of spatial correction terms to achieve sufficient ADC error reduction (by 75-95%) for tissue-like diffusion anisotropy. Simplified ADC correction algorithm is suggested for implementation on MR systems based on known gradient hardware properties

Joelle E Sarlls¹, Philip Shaw^2,3, Nancy E Adleman⁴, and Vinai Rooopchansingh^5
1NINDS/NIH MRI Research Facility, National Institutes of Health, Bethesda, MD, United States, ²NIMH, National Institutes of Health, ³NHGRI, National Institutes of Health, ⁴NIMH/Emotion and Development Branch, National Institutes of Health, ⁵NIMH/Functional MRI Facility, National Institutes of Health

A retrospective study of pediatric imaging data revealed widespread corruption of diffusion images due to large head motion. Using an automated real-time software framework, and straightforward calculations in AFNI, diffusion-weighted imaging volumes that have been corrupted by large motions can be detected and reacquired within a scan session. This rapid diffusion QA method provides an efficient way for consistent diffusion data sets to be acquired, with minimal scan time. Reacquiring the corrupted diffusion data avoids potential bias due to removal of variable numbers of corrupted volumes and potentially increases sensitivity to detect change in diffusion properties in populations that tend to move.

Mustafa Okan Irfanoglu^1,2, Lindsay Walker^1,2, Raghu Machiraju³, and Carlo Pierpaoli^1
1NIH, NICHD, Bethesda, MD, United States, ²Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States, ³Computer Sciences & Engineering, The Ohio State University, Columbus, OH, United States

Diffusion imaging data generally requires additional postprocessing in order to correct for artifacts and distortions. Typical correction methodologies involve the use of image registration techniques, which employ some form of interpolation to generate the final corrected images. The effects of these interpolation steps have generally been disregarded in the community. In this work, we show that even with the same data and fixed registration correction parameters, the choice of interpolation technique can have a profound effect on the distribution of tensor derived scalar quantities, hence can affect the outcomes of histogram based analysis.

Danilo Scelfo¹, Laura Biagi¹, Mauro Costagli^1,2, and Michela Tosetti^1,2
1IRCCS "Stella Maris" Scientific Institute, Pisa, Italy, Italy, ²IMAGO7, Pisa, Italy

We proposed algorithm for the automatic detection and removal of diffusion-related artifacts which seems to be a useful tool to be exploited in the normal DW images pre-processing. It allows the user to detect and evaluate potential artifacts and, if required, to remove the volume corresponding to the detected artifact and rearrange the coordinate table of the applied diffusion gradients.

Daniel Güllmar¹, Catharina Lange^1,2, Christian Ros¹, Andreas Deistung¹, and Jürgen R Reichenbach^1
1Medical Physics Group / IDIR I, Jena University Hopital, Jena, Thuringia, Germany, ²University of Applied Sciences, Jena, Thuringia, Germany

We have used DTI wild bootstrapping method to evaluate different diffusion protocol settings in order to optimize spatial resolution in terms of standard deviation of typical diffusion tensor properties like fractional anisotropy and cone of uncertainty.

David Raffelt^1,2, J-Donald Tournier^1,3, Olivier Salvado², and Alan Connelly^1,3
1Brain Research Institute, Florey Neuroscience Institutes, Melbourne, VIC, Australia, ²The Australian E-Health Research Centre, CSIRO, Brisbane, QLD, Australia, ³Department of Medicine, University of Melbourne, Melbourne, VIC, Australia

Tractography and voxel-based analysis of diffusion-weighted images (DWI) benefit from higher-order models that require the acquisition of a large number of diffusion orientations at high b-values. The associated long scan times increase the likelihood of subject motion. Furthermore, high b-value DWI is also more prone to eddy-current induced distortions. Existing methods to correct motion and eddy-current artefacts are inadequate due to the poor SNR associated with high b-values. We present a robust method to correct motion and eddy-current artefacts in high b-value data. Validation experiments demonstrate that the proposed method can accurately correct b=3000s/mm ² data with typical noise levels.

Kurt Hermann Bockhorst¹, Priya Goel¹, and Ponnada A Narayana^1
1DII, University of Texas, Houston, Texas, United States

Registration is commonly used during the post processing of medical imaging data. However, the effect of registration on the quantification of imaging metrics as DTI has not been reported recently. The submitted abstract documents a significant decrease of FA values (up to 20%) in the white matter (splenium and genu) of rat brains after registration. We studied this phenomenon with four different types of registration: AIR, FSL, DTI-TK (tensor based) and ANTS. All of these methods caused a significant decrease in FA.

Mustafa Okan Irfanoglu^1,2, Michael Curry¹, Evren Özarslan^1,2, Cheng Guan Koay¹, Sinisa Pajevic¹, and Peter J. Basser^1
1NIH, NICHD, Bethesda, MD, United States, ²Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States

The uncertainty inherent in the estimated diffusion tensors can have profound effects on the analysis outcomes. In this word, we propose a novel method to visualize DTI uncertainty along with similarity metrics that incorporate this information. These metrics can be employed in a variety of applications including tensor field image registration or tensor image segmentation.

Elodie André¹, Evelyne Balteau¹, Christophe Phillips¹, Ezequiel Farrher², Ivan Maximov², Farida Grinberg², and N. Jon Shah^2,3
1Cyclotron Research Centre, University of Liège, Liège, Belgium, ²Institute of Neuroscience and Medicine - 4, Forschungszentrum Jülich GmbH, Jülich, Germany, ³JARA - Faculty of Medicine, RWTH Aachen University, Aachen, Germany

Low SNR is a critical issue in diffusion kurtosis imaging because of the use of high b-values (up to 3000 s mm-2). We tested different noise correction methods prior to kurtosis fitting and show that noise correction is a necessary step in kurtosis processing, providing higher tissue contrast and better parameter estimates.

Gernot Reishofer¹, Karl Koschutnig², Christian Langkammer³, Stefan Ropele³, Stephen Keeling⁴, Robert Merwa⁵, and Franz Ebner^6
1Radiology, Medical University of Graz, Graz, Styria, Austria, ²Psychology, University of Graz, ³Neurology, Medical University of Graz, ⁴Mathematics and Scientific Computing, University of Graz, ⁵Medical Engeneering, Upper Austria University of Applied Sciences, ⁶Radiology, Medical University of Graz

Advanced scan techniques in diffusion tensor imaging (DTI), such as readout segmented EPI enable high resolution DTI, but suffer from low signal to noise ratio. In this work we present a novel method for the spatially dependent regularization of the diffusion tensor based on independent component analysis and total variation regularization. We demonstrate that the diffusion tensor evaluated from noisy DWI data is successfully denoised, while fine structural details are preserved. This allows for the application of high resolution DTI in a clinically acceptable time.

Ezequiel Farrher¹, Farida Grinberg¹, and N. Jon Shah^1,2
1Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich, Juelich, Germany, ²JARA - Faculty of Medicine, RWTH Aachen University, Aachen, Germany

In the recent years, diffusion kurtosis imaging has become an important method for the quantification of the non-Gaussian diffusion in brain tissue by means of magnetic resonance imaging. In this work we carry out an experimental investigation of the optimal allowed range of b-values according to the type of tissue under examination and an applied set of gradient directions. We examine how the mean-diffusivity and mean-kurtosis maps are influenced by the chosen range of b-values and propose an optimization scheme.

Andrada Ianus¹, Bernard Siow¹, Hui Zhang¹, and Daniel C. Alexander^1
1University College London, London, United Kingdom

This work presents analytical formulae for both free and restricted diffusion NMR signal from a square wave oscillating gradient spin-echo (SWOGSE) sequence. The expressions are computed using the Gaussian Phase Distribution approximation and we demonstrate for cylindrical geometry. The results for different radii, frequencies, and gradient strengths are compared with the values obtained from Monte Carlo diffusion simulation. In all cases the error was less than 3% of the signal and the total computation time was reduced by several orders of magnitude, which enables model fitting applications, e.g. to generate whole brain parameter maps.

Shiyang Wang^1,2, Michael Chopp^1,2, Siamak Pourabdollah Nejad D.¹, JiaNi Hu³, and Quan Jiang^1,2
1Neurology, Henry Ford Hospital, Detroit, MI, United States, ²Physics, Oakland University, Rochester, MI, United States, ³Radiology, Wayne State University, Detroit, MI, United States

Neurite density measured in healthy volunteers using hybrid diffusion. Neurite density measured in TBI patient using simultaneous image refocusing sequence combined with hybrid gradient encoding scheme.

Jennifer A. McNab¹, Thomas Witzel¹, Himanshu Bhat², Keith Heberlein², Boris Keil¹, Julien Cohen-Adad¹, M. Dylan Tisdall¹, and Lawrence L. Wald^1,3
1A.A. Martinos Center for Biomedical Imaging, Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States,²Erlangen USA Inc., Siemens Medical Solutions, Charlestown, MA, United States, ³Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

In this work we use a novel gradient coil AS302 which is part of a new 3T system (MAGNETOM Skyra CONNECTOM, Siemens Healthcare) capable of up to 300 mT/m to measure, in the in vivo human brain, the full axon diameter distribution in the corpus callosum as determined by the AxCaliber method.

Martin A. Koch^1,2, and Jürgen Finsterbusch^1
1Systems Neuroscience, Neuroimage Nord, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ²Institute of Medical Engineering, University of Lübeck, Lübeck, Germany

Double wave vector diffusion weighting is a new approach for assessing tissue characteristics such as mean pore size and shape: for restricted diffusion the MR signal acquired with two successive diffusion weighting periods may depend on the angle between the two applied gradient directions. At short mixing times, the signal difference between parallel and antiparallel gradient orientations can be related to the mean pore size. It is investigated whether the size estimate derived from this signal difference is sensitive to pathological changes in the tissue microstructure of the corticospinal tracts.

Marco Palombo^1,2, Cesare Cametti¹, Mariella Dentini³, and Silvia Capuani^1,2
1“Sapienza” University of Rome, Physics Department, Rome, Rome, Italy, ²CNR IPCF UOS Roma, Physics Department “Sapienza” University of Rome, Rome, Italy, ³“Sapienza” University of Rome, Department of Chemistry, Rome, Italy

We introduce a novel imaging method to characterize and to map anomalous diffusion processes of water in heterogeneous systems by means of diffusion weighted NMR techniques at varying of the diffusion time. The approach is based on the theory of the Continuous-Time-Random-Walk and introduces the á index, which quantify sub-diffusion processes. We present the first á-map obtained in two controlled porous phantoms characterized by the same void and interconnect size distribution but by different type of porous matrix walls (smooth or rough). Our results show that á-maps, unlike the conventional MD-maps, are able to discriminate between these two samples.

Silvia De Santis¹, Tim Vivian-Griffiths¹, Sonya Bells¹, Yaniv Assaf², Sean Deoni³, and Derek K Jones^1
1CUBRIC, Cardiff University, Cardiff, United Kingdom, ²Tel Aviv University, Tel Aviv, Israel, ³Brown University, United States

In this work, we develop an efficient and clinically-applicable protocol that provides comprehensive assessment of WM microstructure, providing not only estimates of FA, but also of the attributes of WM that drive differences in FA. Combining relaxometric and diffusion acquisition maps, the axonal diameter distribution can be obtained with a clinical setup. The resulting protocol comprehensively characterizes WM features (AD, myelination, axon density), overcoming the lack of specificity of DTI measures and thus allowing specific conclusions to be drawn when looking at group differences.

Markus Nilsson¹, and Daniel Alexander^2
1Department of Medical Radiation Physics, Lund University, Lund, Sweden, ²Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom

The resolution limit in diffusion MRI determines the minimal structural size, e.g. axon diameter, that is possible to estimate accurately. In q-space analysis, this limit scales according to the inverse cube root of the maximal gradient strength (Gmax). In this study, we show by theoretical analysis and simulations that the resolution limit scales as the inverse square root of Gmax for model-based diffusion MRI.

Lauriane Jugé¹, Simon Auguste Lambert¹, Simon Chatelin¹, Leon ter BEEK², Valérie Vilgrain¹, Bernard E Van BEERS¹, Lynne E Bilston³, Bojan Guzina⁴, Sverre Holm⁵, and Ralph Sinkus^1
1U773-CRB3, INSERM, Paris, France, ²Philips Medical Systems, Best, Netherlands, ³University of New South Wales, Neuroscience Research Australia, New South Wales, Australia, ⁴Dept. of Civil Engineering, University of Minnesota, Minneapolis, MN, United States, ⁵Informatics, University of Oslo, Oslo, Norway

In diffusion-weighted imaging, micro-structural information is lost due to the massive averaging that occurs within the imaging voxel and can only be revealed when exploring the tissue using different b-values. Similarly, for the first time we demonstrated using magnetic resonance elastography (MRE) that the frequency-dependence of mechanical shear wave diffusion can allow probing sub-voxel distributions of scattering structures and as a consequence overcome the spatial resolution limitation relying intrinsically on the MR imaging sensitivity. This technique opens perspective of detecting small metastases or neo-vascularisation which could really justify the use of MRE as a powerful clinical diagnosis tool.

Sharon Peled¹, Saadallah Ramadan², and Carl-Fredrik Westin^1
1Radiology, Brigham and Women's Hospital, Boston, MA, United States, ²School of Health Sciences, University of Newcastle, Callaghan, NSW, Australia

A comparison of the spin echo and stimulated echo DWI signals may yield an in vivo biomarker reflecting the permeability and/or thickness of the myelin sheath. The spin echo and stimulated echo DW-EPI signals can both be measured after a single excitation.

Wilfred W Lam¹, Saad Jbabdi¹, and Karla L Miller^1
1FMRIB Centre, University of Oxford, Oxford, Oxon, United Kingdom

A model that fits the extracellular diffusivity spectrum of square-packed, non-abuttting cylinders was developed and validated with simulation. A combination of sine- and cosine-modulated oscillating gradients provided sensitivity to the intracellular and extracellular compartments. Values for intracellular volume fraction, effective intracellular and extracellular radii, and diffusivity spectra of the splenium of a post-mortem macaque brain were acquired using a clinical MR scanner.

Michal E Komlosh^1,2, Evren Ozarslan^1,3, Martin J Lizak⁴, Iren Horkayne-Szakaly⁵, Raisa Z Freidlin⁶, and Peter J Basser^1
1STBB,PPITS,NICHD,NIH, Bethesda, MD, United States, ²CNRM,USUHS, Bethesda, MD, United States, ³CNRM,USUHS, United States, ⁴NMRF,NINDS,NIH, Bethesda, MD, United States, ⁵Neuropathology and Ophthalmic Pathology, Armed Forces Institute of Pathology, United States, ⁶CIT,NIH, Bethesda, MD, United States

Double-PFG filtered MRI was used with a theoretical model to obtain an average fiber diameter map of fixed pig spinal cord. K-means segmentation and histological analysis were performed to verify the result. This study demonstrates that d-PFG filtered MRI is a powerful tool for mapping axon diameter, and potentially other microstructural features of tissues.

Jelle Veraart¹, and Jan Sijbers^1
1Vision Lab, University of Antwerp, Antwerp, Belgium

Many diffusion models require highly diffusion-weighted MR images, which suffer from low signal-to-noise ratio (SNR). Not only the precision of the diffusion model parameter estimators depends on the SNR, the estimator’s accuracy will also be affected if the Rice distribution of magnitude MR data is not accounted for. We will give a technical overview of –on the one hand - the effect of the so-called Rician bias on diffusion model parameters - on the other hand – some techniques, which were proposed to reduce/remove the Rician bias.

Fan Lam^1,2, S. Derin Babacan², Norbert Schuff³, and Zhi-Pei Liang^1,2
1Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ²Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ³Center for Imaging of Neurodegenerative Diseases, VA Medical Center, San Francisco, CA, United States

A novel method is proposed to denoise diffusion weighted image sequences. The proposed method uses a penalized maximum likelihood formulation that handles Rician noise and incorporates low rank structure and prior edge information. The proposed method has been evaluated using experimental DTI data, and provides superior performance on recovering image features, anisotropy and orientation information of diffusion tensors originally corrupted by noise. We expect the proposed method to prove useful for achieving higher measurement precision and/or reducing data acquisition time for diffusion MRI.

Tokunori Kimura¹, and Yuataka Machii^1
1MRI development department, Toshiba Medical Systems Corp., Otawara, Tochigi, Japan

A technique of computed diffusion weighted imaging (cDWI) allowing to generate high b-value equivalent DWI images from low b-value images was assessed. In this study, simulation, phantom and volunteer study were performed to optimize b-values for the range of biologic tissue ADC under Rician noise. cDWI could provide better SNR images than the mDWI when original data SNRs were kept >3, by reducing background signals below noise bias which is problematic on standard mDWI. In conclusion, cDWI at optimum conditions can provide high CNR body diffusion imaging especially for higher ADC and shorter T2 tissues under Rician noise.

Jelle Veraart¹, Sofie Van Cauter², Stefan Sunaert², and Jan Sijbers^1
1University of Antwerp, Antwerp, Antwerp, Belgium, ²Department of Radiology, University Hospitals of Leuven, Leuven, Belgium

Many diffusion models require highly diffusion-weighted images, which suffer from low signal-to-noise ratio, eddy current distortions, and subject motion. Prior to diffusion model fitting, those distortions should be corrected; That data correction alters the underlying Rician data distribution. Therefore, previously proposed methods remove the Rician bias might be suboptimal. We propose a conditional least squares estimator (CLS), which is from theoretically an equivalent to the maximum likelihood estimator (MLE). However, the CLS remains, unlike the MLE, in well-defined cases unbiased after data correction as it can rely on the linearity of the expectation operator in high SNR and homogeneous regions.

Veronique Brion¹, Olivier Riff¹, Maxime Descoteaux², Jean-François Mangin¹, Denis Le Bihan¹, Cyril Poupon¹, and Fabrice Poupon^1
1NeuroSpin, CEA/I²BM, Gif-sur-Yvette, France, ²Sherbrooke University, Sherbrooke, Canada

This abstract proposes a novel real-time non central χ noise correction method for diffusion-weighted MR data that are known to be particularly sensitive to noise, as the diffusion indicator in the tissues corresponds to a signal loss. The technique is based on a Parallel Kalman Filter which is well adapted for non-Gaussian noise distributions, and which is as suitable for real time purposes as the standard Kalman filter. The results on simulated and real HARDI data show that it outperforms the standard Kalman Filter approach since non-Gaussian noise distributions are directly embedded in the process through their Gaussian mixture approximation.

Lin-Ching Chang¹, and Carlo Pierpaoli^2
1Department of Electrical Engineering and Computer Science, The Catholic University of America, Washington, DC, United States, ²National Institutes of Health, Bethesda, MD, United States

Correctly estimating the expected signal standard deviation (SD) due to thermal noise in diffusion weighted images (DWIs) is important for controlling image quality, correctly computing the chi-squares value, image registration and outlier detection. For single channel acquisitions, signal SD could be estimated from a ghost-free region of the image background. However, the signal in the background of DWIs acquired on modern clinical scanners cannot be used for this purpose. This paper proposes an object-based method taking advantage of robust regression and residual analysis to estimate signal SD. Results from simulation indicate that the proposed method performs very well even in the presence of DWI volumes which are completely corrupted.

Zhenyu Zhou^1,2, Yijun Liu³, Guang Cao¹, Karen M. von Deneen³, and Dongrong Xu^2
1Global Applied Science Laboratory, GE Healthcare, Beijing, Beijing, China, ²MRI Unit, Columbia University, New York, NY, United States, ³McKnight Brain Institute, University of Florida, Gainesville, FL, United States

Diffusion weighted imaging is always influenced by both thermal noise and spatially and/or temporally varying artifacts such as subject motion and cardiac pulsation. Motion artifacts are particularly prevalent, especially when scanning an uncooperative population with several disorders. In this study, we proposed a classifier work frame which can classify DWIs as normal images or motion artifacts. It achieves better performance in tensor estimation by automatic unvoxel-wise outlier rejection compared with manual and visual inspection, and previous voxel-wise outlier rejection methods. The proposed method could potentially remove the influence of unexpected motion artifacts in DWI acquisitions.

Nikolaos Dikaios¹, Shonit Punwani², Valentin Hamy¹, Pierpaolo Purpura², Heather Fitzke³, Scott Rice², Stuart Taylor³, and David Atkinson^3
1Department of Medical Physics and Bioengineering, University College London, London, Greater London, United Kingdom, ²Department of Radiology, University College London Hospital, ³Centre for Medical Imaging, University College London

The aim of this work was to determine whether classification of benign and metastatic cervical nodes based on diffusion weighted imaging (DWI) could be improved by use of a maximum likelihood algorithm for derivation of ADC parameters. A non linear least squares (LSQ) algorithm is usually used to fit parameters to the measured MR signal intensities as a function of b-value. LSQ assumes that the noise in high b-values is normally distributed whereas in reality it follows a Rice distribution. To account for the Rician noise, maximum likelihood (ML) algorithms have been proposed that provide unbiased ADC estimates. In this work the monoexponential, stretched exponential and biexponential models were examined, with their involved parameters calculated using the LSQ and the ML algorithms.

Jose V Manjon¹, Pierrick Coupe², Luis Concha³, Antoni Buades⁴, Louis Collins⁵, and Montserrat Robles^6
1IBIME, UPV, valencia, Spain, ²LaBRI, Bourdeaux, France, ³UNAM, Mexico, ⁴Universite Paris Descartes, France, ⁵MNI, Canada, ⁶IBIME, UPV, Valencia, Spain

Diffusion Weighted Images normally show a low SNR due to the presence of noise from the measurement process which complicates and potentially bias the estimation of the diffusion parameters. In this paper, a new denosing method is proposed which takes into consideration the multicomponent nature of DW images. This new filter reduces random noise in multicomponent Diffusion MR images by locally shrinking less significant Principal Components using an overcomplete approach. The proposed method is compared with similar state of art methods using synthetic and real clinical MR images showing an improved performance in all cases analyzed.

Kerstin Pannek¹, David Raffelt², Christopher Bell¹, Jane Mathias³, and Stephen Rose^1
1The University of Queensland, Brisbane, Queensland, Australia, ²Brain Research Institute, Australia, ³University of Adelaide, Australia

Diffusion weighted images are prone to artefacts caused by physiological noise. Existing model based approaches for voxel-wise identification of such artefacts rely on the diffusion tensor model, which is problematic in crossing fibre areas and at higher b-values required for high angular resolution diffusion imaging. We developed a voxel-wise identification method based on a higher order model of diffusion, and compared outlier probability maps obtained using the tensor model with those obtained using a higher order model in a cohort of 103 healthy participants.

Tokunori Kimura¹, and Takashi Shigeta^1
1MRI development department, Toshiba Medical Systems Corp., Otawara, Tochigi, Japan

The purpose of this study was to assess a technique named INCUS (inhomogeneous noise correction combined with uniform filter and sensitivity map) for correcting spatially inhomogeneous noise on parallel imaging (PI) adaptively by combing with the Wiener filter (WF). Three types of WF were compared between INCUS and uniform type to DWI images. The INCUS could naturally reduce such noises while minimizing blur, and the minimum RMSE was smaller in the INCUS-WF than in the uniform-WF. We concluded that INCUS-WF is simple but very effective to optimally and automatically improve the spatially inhomogeneous noise on PI.

Koichi Oshio^1
1Department of Diagnostic Radiology, Keio University School of Medicine, Shinjuku-ku, Tokyo, Japan

The shape of bi-exponential fitting errors in the parameter space was calculated and visualized. From these plots, it is suggested that parameter estimation with bi-exponential curve fitting is not reliable, even though the fitting itself is good, especially for small range of b-value. Using a new set of parameters, D and d, it is possible to estimate the parameters more reliably, and the parameter interpretation becomes more straightforward.

Ben Jeurissen¹, Alexander Leemans², Jacques-Donald Tournier^3,4, and Jan Sijbers^1
1Vision Lab, University of Antwerp, Antwerp, Belgium, ²Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ³Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australia, ⁴Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia

In voxels containing multiple fiber orientations, diffusion tensor imaging (DTI) has been shown to provide misleading white matter orientation ‘integrity’ information. Several methods have been proposed to extract fiber orientation information from the diffusion-weighted signal, many of them relying on the high angular resolution diffusion imaging (HARDI) protocol. The purpose of this presentation is to review the most widely-used methods for extracting fiber orientation information from single-shell HARDI data. From this overview, the need for multi-fiber reconstruction algorithms should be clear as well as the advantages and limitations of the different multi-fiber reconstruction methods.

Ben Jeurissen¹, Alexander Leemans², Jacques-Donald Tournier^3,4, Derek K Jones⁵, and Jan Sijbers^1
1Vision Lab, University of Antwerp, Antwerp, Belgium, ²Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ³Brain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australia, ⁴Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia, ⁵CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom

A recent study, using high quality diffusion weighted data and CSD, has shown that multiple fiber orientations can be detected consistently in approximately 90% of all WM voxels. In this work, we assess the impact on DTI fiber tractography and WM ‘integrity’ metrics by measuring: 1) the angle between the primary DTI eigenvector and the nearest CSD orientation; 2) the volume fraction of the non-dominant CSD fiber orientations. We show that errors in the DTI fiber orientations are widespread throughout the WM and that many voxels contain contributions from non-dominant orientations that would be sufficiently large to affect tensor-derived measures.

Sjoerd B Vos¹, Max A Viergever¹, and Alexander Leemans^1
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands

Complementary to track-density imaging (TDI), we have proposed tract coherence imaging, TCI, as a new MRI contrast to investigate the local architectural configuration of tract pathways. TCI quantifies the local consistency of fiber tract orientations for a given voxel resolution, limited between ‘0’ (random orientations) and ‘1’ (perfectly aligned fibers), providing an elegant framework for quantitative evaluations that can be used in a super-resolution framework. TCI does not depend on voxel size in homogenous tract configurations, facilitating quantitative analyses. Furthermore, the peak fiber orientations can be extracted from the tract pathways in each voxel to further understand the architectural complexity.

Nicole Murphy¹, Ching-Po Lin², and Chunlei Liu^3
1Brain Imaging Analysis Center, Duke University, Durham, North Carolina, United States, ²Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, N/A, Taiwan, ³Department of Radiology, Duke University, Durham, NC_3129, United States

 

Greg D Parker¹, and Derek K Jones^1
1CUBRIC, School of Psychology, Cardiff University, Cardiff, South Glamorgan, United Kingdom

We report a previously overlooked pitfall in spherical deconvolution approaches for reconstructing fibre orientation distribution functions (fODFs) through a spherical-harmonic (SH) basis. By examining single-fibre population (fibres along the same axis) cases, we are able to uncover descriptive deficiencies in the SH representation that result in spurious fODF peaks once the assumed and actual diffusive properties of the target fibrous tissue no longer agree (e.g. local degradation through disease). Through comparison with an alternative that does not rely on spherical harmonics, we are also able to suggest a viable alternative for cases where a 'one-size-fits-all' single-fibre diffusivity assumption is inappropriate.

Ek T Tan¹, Luca Marinelli¹, Christopher J Hardy¹, Kevin F King², Jonathan I Sperl³, and Marion I Menzel^3
1GE Global Research, Niskayuna, NY, United States, ²GE Healthcare, Waukesha, WI, United States, ³GE Global Research, Garching, Germany

Diffusional anisotropy is an important indicator for axonal integrity, but conventional DTI-based fractional anisotropy (FA) is not well-suited to describing anisotropy of multi-directional diffusivities. A multi-directional anisotropy (MDA) metric was proposed, which is analytically and experimentally shown to be equivalent to FA in single-fibers. In double-fibers, the mean MDA was higher than FA, while the variation of MDA was smaller than FA. In addition, fiber counts can be inferred from the diffusion propagator. The availability of both MDA and fiber counting can be useful for multi-parametric analysis of anisotropy in crossing-fiber and gray matter regions.

Antonio Tristán-Vega¹, and Carl-Fredrik Westin^1
1Laboratory of Mathematics in Imaging, Brigham and Women's Hospital, Boston, Massachusetts, United States

Compressed Sensing grants the possibility of reducing the number of samples required to describe a signal below its Nyquist rate. When applied to the estimation of the diffusion propagator in diffusion spectrum imaging, it arises the need to find a basis for which the propagator is sparse, which is not trivial. We address this problem by two means: 1) mapping the propagator to a space where it is sparse, and 2) using a model that explicitly isolates a non-sparse residual. We provide two reconstruction algorithms for such model, notably improving the estimation accuracy and sparsity compared to previous approaches.

Ezequiel Farrher¹, Tony Stöcker¹, Farida Grinberg¹, and N. Jon Shah^1,2
1Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich, Juelich, Germany, ²JARA - Faculty of Medicine, RWTH Aachen University, Aachen, Germany

Diffusion-weighted magnetic resonance imaging provides a unique, non-invasive tool to characterize tissue microstructure and orientation. In order to enable a quantitative validation of the proposed physical models to elucidate tissue orientation, it is necessary to have artificial systems with well-known structure and physical properties. In this work, we demonstrate the application of a multi-section diffusion phantom used for comparison of the performance of two models for high angular resolution diffusion imaging (HARDI) data analysis, i.e. the so-called Q-ball Imaging (QBI) and the constrained spherical deconvolution (CSD) methods.

Till Riffert¹, Thomas Knösche¹, and Alfred Anwander^1
1Cortical Networks and Cognitive Functions, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

 

Jennifer A. McNab¹, Jonathan R Polimeni¹, Ruopeng Wang¹, Jean C. Augustinack¹, Kyoko Fujimoto¹, Allison Player¹, Christina Triantafyllou^1,2, Thomas Janssens³, Reza Farivar¹, Wim Vanduffel^1,3, and Lawrence L Wald^1,4
1A.A. Martinos Center for Biomedical Imaging, Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, ²A.A. Martinos Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States, ³Laboratory for Neuro- and Psychophysiology, K.U. Leuven Medical School, Campus Gasthuisberg, Leuven, Belgium, ⁴Harvard-MIT Health Sciences and Technology Division, Massachusetts Institute of Technology, Cambridge, MA, United States

We compare cortical diffusion anisotropy in in vivo human (1 mm iso), in vivo macaque (0.7 mm iso) and in ex vivo human tissue (0.5 mm iso). All data sets show radial diffusion in M1 and tangential diffusion in S1, although the ex vivo human data also shows some regions of radial diffusion in S1.

Christoph Wolfram Ulrich Leuze¹, Alfred Anwander¹, Stefan Geyer¹, Pierre-Louis Bazin¹, and Robert Turner^1
1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Sachsen, Germany

Diffusion-weighted imaging (DWI) at high spatial and angular resolution was performed at 9.4 T on a block of fixed human cadaver brain tissue containing part of the motor-(M1) and somatosensory (S1) cortex. Analysis of the radiality of the diffusion showed that, unlike stated in earlier studies, the prevalent diffusion direction in S1 is not entirely tangential but rather that neighbouring layers with alternating tangential and radial diffusion properties in both M1 and S1 exist. High DWI spatial resolution is therefore clearly of great importance for correct conclusions regarding cortical orientational structure in the cortex.

Luke Bloy¹, Alex R Smith², Madhura Ingalhalikar², Robert T Schultz³, Timothy P.L. Roberts⁴, and Ragini Verma^2
1Section of Biomedical Imaging, University of Pennsylvania, Philadelphia, PA, United States, ²Section of Biomedical Imaging, Univeristy of Pennsylvania, Philadelphia, PA, United States, ³Center for Autism Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States, ⁴Lurie Family Foundation's MEG Imaging Center, Children's Hospital of Philadelphia, Philadelphia, PA, United States

This study compares the results of using DTI and HARDI based diffusion models as the driving force behind spatial normalization algorithms. Each modality underwent separate state of the art registration pipelines designed to optimally take advantage of each contrast. The deformations resulting from each pipeline were applied to the images of the other modality, allowing for three means of comparison. Both registration pipelines perform similarly when FA variance was used as a means of comparison, however using either FOD or normalized FOD variance HARDI registration performed better. This demonstrates the importance of using HARDI when accurate registration is required.

Yoshitaka Bito¹, Yuko Kawai², Koji Hirata¹, Toshihiko Ebisu³, Yosuke Otake¹, Satoshi Hirata¹, Toru Shirai¹, Yoshihisa Soutome¹, Hisaaki Ochi¹, Masahiro Umeda², Toshihiro Higuchi⁴, and Chuzo Tanaka^4
1Central Research Laboratory, Hitachi, Ltd., Kokubunji-shi, Tokyo, Japan, ²Medical Informatics, Meiji University of Integrative Medicine, Kyoto, Japan,³Neurosurgery, Nantan General Hospital, Kyoto, Japan, ⁴Neurosurgery, Meiji University of Integrative Medicine, Kyoto, Japan

Diffusion-weighted echo-planar spectroscopic imaging with a pair of bipolar diffusion gradients (DW-EPSI with BPGs) was used to acquire changes in apparent diffusion coefficient (ADC) for multiple metabolites, namely, N-acetylaspartate (NAA), creatine (Cr) and choline (Cho), in rat brains after a right middle cerebral artery occlusion (MCAO). The acquired changes in ADC maps of the metabolites and water were analyzed by using Gaussian mixture distribution, which takes advantage of the multiple spatial pixels acquired simultaneously by diffusion-weighted spectroscopic imaging. It is shown that DW-EPSI with BPGs is effective for investigating spatially varying ADC changes for metabolites and that this technique may be useful for understanding intra-cellular dynamics by using multiple metabolites as probes.

Xiaojie Wang¹, Yong Wang², Cheryl Nutter³, and Sheng-Kwei Song^2
1Chemistry, Washington University, Saint Louis, Missouri, United States, ²Radiology, Washington University, Saint louis, United States, ³Pfizer Inc., United States

Multiple sclerosis (MS) is an inflammatory demyelinating disease with axonal injury causing permanent neurological disabilities. Axonal preservation remains a significant challenge in current anti-inflammatory therapies of MS. In the present study, we demonstrate the efficacy of anti-inflammation and axonal preservation of FTY720 on experimental autoimmune encephalomyelitis (EAE) mice examined using diffusion MRI. The effect of increased cellularity and vasogenic edema associated with inflammation on diffusion tensor imaging parameters was also examined.

Tsang-Wei Tu¹, Yong Wang², Chia-Wen Chiang³, Tsen-Hsuen Lin⁴, Ying-Jr Chen³, Anne Cross⁵, and Sheng-Kwei Song^2
1Radiology, Washington University, Saint Louis, Missouri, United States, ²Radiology, Washington University, ³Chemistry, Washington University,⁴Physics, Washington University, ⁵Neurology, Washington University

A novel diffusion basis spectrum imaging (DBSI) was recently introduced to resolve inflammation in presence of axon and myelin damage in a mouse model of multiple sclerosis. Besides the anisotropic indices provided by DTI, the isotropic diffusion reflects inflammation, through the estimation of cellularity and water fraction. In current study, in vivo DBSI of the lumbar spinal cord from EAE mice was performed, followed by histological validation. DBSI parameters revealed evolving multiple neuropathologies in the EAE course. Histological findings substantiated in vivo DBSI results. The quantification of cell and water fractions successfully identified the spatial and temporal evolution of inflammation.

Dmitry S. Novikov¹, Jens H. Jensen², and Joseph A. Helpern^2
1Radiology, NYU School of Medicine, New York, NY, United States, ²Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States

The types of microstructural architecture in any media (including living tissues) are classified in terms of the long-time tail exponent in the molecular velocity autocorrelation function. The specific value of the power-law exponent obtained from the oscillating gradient spin echo measurement in rat cerebral gray matter characterizes the relevant tissue anatomy that restricts water diffusion. It is argued that short-range disorder, likely due to spines and varicosities, provides the chief hindrance to diffusion along dendrites and axons and that the increase in this structural disorder is a primary cause of the diffusivity drop in ischemic stroke.

Els Fieremans¹, Jens H. Jensen², Edward S. Hui², Dmitry S. Novikov¹, Ali Tabesh², Leonardo Bonilha², and Joseph A. Helpern^2
1Center for Biomedical Imaging, Radiology, New York University School of Medicine, New York, NY, United States, ²Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States

The decrease of the water diffusion coefficient in ischemic stroke provides a sensitive and reliable diagnostic tool. However, the underlying biophysical mechanisms for the diffusion drop are still not fully understood. In this study, we characterize changes in the white matter microstructure in human subacute stroke by applying a recently developed white matter model for diffusional kurtosis imaging, which yields estimates for the intra-axonal and extra-axonal diffusivities and for the axonal water fraction. A large change of 55% is observed in the intra-axonal diffusivity, consistent with axonal beading as a primary mechanism underlying the diffusion drop associated with ischemia.

Maria F Falangola¹, David Guilfoyle², Edward S Hui¹, Caixia Hu², Scott Gerum², John LaFrancois³, Xingju Nie¹, Jens Jensen¹, Ali Tabesh¹, and Joseph A Helpern,^1
1Radiology, Medical University of South Carolina (MUSC), Charleston, SC, United States, ²Medical Physics, Nathan Kline Institute, Orangeburg, New York, NY, United States, ³Dementia Research, Nathan Kline Institute, Orangeburg, New York, NY, United States

Since the transition from young to aged adult during the normal aging process leads to changes in grey matter morphology, characterizing the age-related diffusion patterns in the rodent brain is important for interpreting and differentiating the changes associated with pathological process in rodents’ models of neurodegenerative diseases. Diffusional Kurtosis Imaging (DKI) quantifies the non-Gaussian behavior of water diffusion, contributing additional information beyond that provided by diffusion tensor imaging. Here we report that the DKI can characterize the age-related microstructural changes in the cortex and sub-cortical regions in the normal mouse brain.

Umesh Rudrapatna¹, Pavel Yanev¹, Karsten Ruscher², Annette van der Toorn¹, Tadeusz Wieloch², and Rick Dijkhuizen^1
1Biomedical MR Imaging and Spectroscopy Group, Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ²Laboratory for Experimental Brain Research, Department of Clinical Sciences Lund, Lund University, Lund, Sweden

Elucidation of structural plasticity in lesion borderzones after stroke may lead to development of recovery-enhancing strategies. While diffusion tensor imaging (DTI) allows assessment of white matter reorganization, there is no established MR contrast for measurement of structural remodeling in grey matter. In this study we analyzed to what degree diffusion kurtosis imaging (DKI) allows detection of microstructural changes in perilesional grey matter. Our high resolution ex vivo study in a rat stroke model shows that at chronic time points, DKI parameters were significantly altered in perilesional cortex and striatum, and to a larger extent than DTI parameters. We speculate that DKI may significantly help to unravel the complex, heterogeneous microstructural changes associated with post-stroke tissue plasticity.

Nanjie Gong¹, Chun Sing Wong¹, Chun Chung Chan², Lam Ming Leung², Yiu Ching Chu³, and Queenie Chan^4
1Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, ²United Christian Hospital, Hong Kong, ³Kwong Wah Hospital, Hong Kong, ⁴Philips Healthcare, Hong Kong

To investigate the sensitivity of the measurements from DKI for differentiating between patients with MCI and patients with AD and detecting microstructural changes in both white matter and grey matter, we used region of interest (ROI) analysis focusing on the ROIs that have been previous investigated using DTI model in other studies. We hypothesize that with more precise model and additional information provided by DKI matrix, we could not only better differentiate between MCI and AD, but also better characterize the microtructural alternations. This study was approved by Institutional Review Board in Hong Kong. From 2011/03-2011/09, totally 24 patients (13 male, 11 female) were recruited from a local tertiary referring center. While none previous studies, in which DTI model were used, of Alzheimer�fs disease and MCI found any significant difference between these two groups in regions like whole brain grey matter, temporal lobe white matter or grey matter, our study, with a more precise diffusion model of DKI, found promising difference in these regions which may characterize brain tissue microstructural changes during the disease deteriorating. In addition, the extra measurement of Kaxial bears possibility of providing information in new aspects which will help improve the understanding and delineation of this disease. Further, only a few studies had demonstrated the correlation between MD or FA and MMSE score, and the results were controversial. It is worth nothing that in our study, in addition to MD and FA, Daxial and Dradial along with the new measurements of Kaxial, Kradial, and MK also significantly correlated with MMSE score. It suggests that DKI model�fs measurements may be more sensitive indicators for reflecting Alzheimer�fs disease progression.

Edward S. Hui¹, Chu-Yu Lee², Josef P. Debbins², Timothy Q. Duong³, and Joseph A. Helpern^1
1Dept of Radiology, Medical University of South Carolina, Charleston, South Carolina, United States, ²Dept of Electrical Engineering, Arizona State University, Tempe, Arizona, United States, ³Research Imaging Institute, UTHSCSA, San Antonio, Texas, United States

The diagnostic value of ADC obtained from DWI is often dwarfed by its pseudonormalization during subacute stroke. It is therefore necessary to find an alternative that is more sensitive and specific to the underlying structural changes along the course of ischemic infarction. One potential technique is diffusion kurtosis imaging (DKI) which measures non-Gaussianity of water diffusion. The current study showed that MK is a sensitive biomarker for ischemic injury, especially subacute stroke where MD and T2W pseudonormalize as a result of vasogenic edema. DKI could potentially complement conventional DWI for improving stroke diagnosis, particularly during the subacute phase.

Issei Fukunaga^1,2, Masaaki Hori², Yoshitaka Masutani³, Nozomi Hamasaki², Shuuji Sato², Takaaki Hattori⁴, Koji Kamagata², Masakazu Miyajima⁵, Madoka Nakajima⁵, Atsushi Nakanishi², Shigeki Aoki², and Atsushi Senoo^1
1Graduate School of Health Promotion Science, Tokyo Metropolitan University, Nerima ward, Tokyo, Japan, ²Department of Radiology, Juntendo University, Bunkyo ward, Tokyo, Japan, ³Department of Radiology, Graduate School of Medicine, The University of Tokyo, Bunkyo ward, Tokyo, Japan,⁴Department of Neurology, Kanto Central Hospital, Setagawa ward, Tokyo, Japan, ⁵Department of Neurosurgery, Juntendo University, Bunkyo ward, Tokyo, Japan

We studied the diffusion characteristics of the brain in patients with idiopathic normal pressure hydrocephalus and in age-matched controls by using tract-specific analysis.

Renaud NICOLAS¹, Gérard RAFFARD², Stéphane SANCHEZ², Eric PETERSON², Florent AUBRY¹, Isabelle BERRY¹, Pierre CELSIS¹, and Bassem HIBA^2
1Imagerie cérébrale et handicaps neurologiques; UMR 825, INSERM, F-31059 Toulouse, France, ²Centre de Résonance Magnétique des Systèmes Biologiques,UMR 5536, CNRS, F-33076 Bordeaux, France

DWI images of 7 juvenile rats following MCAO were acquired with b-factors up to 2500 s/mm² and with three diffusion times (10,30,50 ms)and analysed with the Statistical Model of Diffusion Imaging that provide a way to estimate Diffusional Kurtosis of ischemic brain regions. A statistically significant change for Dapp (40 % reduction) and Kapp (55 % rise) were observed in ischemic versus healthy cortex. No significant effects of diffusion times were observed in this preliminary study.

Jerry S Cheung¹, Enfeng Wang^1,2, and Phillip Zhe Sun^1
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH and Harvard Medical School, Charleston, MA 02129, United States, ²Department of Radiology, 3rd Affiliated Hospital, Zhengzhou University, China

By providing detailed properties on water diffusion and therefore more specific information on microstructural environment, diffusional kurtosis imaging (DKI) may allow better characterization on heterogeneous ischemic cerebral tissue. In this study, we examined and compared mean diffusion (MD) and mean kurtosis (MK) lesions in a transient middle cerebral artery occlusion (MCAO) ischemia rat model. Our results demonstrated that substantial mismatch between MD and MK lesions existed during MCAO, yet largely vanished following reperfusion. These initial findings suggest that diffusional kurtosis in addition to water diffusivity may improve understanding of the diffusion changes related to microstructural disturbances following acute cerebral ischemic injury.

Sarah Mang^1
1German Cancer Research Center DKFZ, Heidelberg, DE, Germany

Presentation and comparison of different DTI based methods for the segmentation of substructures in the Thalamus. Advantages and disadvantages of the different method types are discussed.

Bagrat Amirbekian^1,2, and Roland Henry^1
1University of California San Francisco, San Francisco, California, United States, ²UC Berkeley & UCSF Graduate Program in Bioengineering, San Francisco, California, United States

Fiber tracking is a powerful method to explore structural connectivity of white matter. However, without statistical methods to estimate the uncertainties associated with quantitative connectivity measures it is very hard to compare fiber tracking results. This study looks at the possibility of using the residual bootstrap with fiber tracking to establish confidence intervals on connectivity measures.

Yurui Gao^1,2, Ann S. Choe^1,2, Xia Li¹, Iwona Stepniewska³, and Adam W. Anderson^1,4
1VUIIS, Vanderbilt University, Nashville, TN, United States, ²BME, Vanderbilt University, Nashville, TN, United States, ³Psychology, Vanderbilt University, Nashville, TN, United States, ⁴BME, Radiology and Radiological Science, Vanderbilt University, Nashville, TN, United States

In our previous study, we validated DTI-tractography-based measures of primary motor area (M1) cortical-cortical connectivity. To further understand our previous result of validation, in this study we investigated the agreement between DTI-tractography-derived white matter pathways and histological pathways. We reconstructed the 3D pathway of histological fibers as well as DTI fibers originating from the M1 forelimb subarea in the squirrel monkey and then quantitatively measured the agreement between the DTI-derived pathway and the histology. We also describe potential reasons for the failure of DTI tractography to align perfectly with histological tracts.

Christian Ros¹, Daniel Güllmar¹, Martin Stenzel², Hans-Joachim Mentzel², and Jürgen Rainer Reichenbach^1
1Medical Physics Group, Department for Diagnostic and Interventional Radiology I, Jena University Hospital, Jena, Thuringia, Germany, ²Pediatric Radiology, Department for Diagnostic and Interventional Radiology I, Jena University Hospital, Jena, Thuringia, Germany

With this contribution we present a new method for the semi-automatic, consistent extraction of fiber bundles from multiple tractography data sets. For every fiber bundle, reliability maps were computed to assess the contribution of every voxel to the bundle. The reliability maps were then used to classify the fiber tracts of each data set. Due to the use of multiple tractography data sets, we were able to correct erroneous or wrongly labeled tracts that usually occur in individual data sets. Resulting fiber bundles are more consistent across subjects compared to bundles that are extracted with the ROI based methods.

Angela Downing¹, Serena J Counsell¹, Daniel Rueckert², A David Edwards¹, and Jo V Hajnal^1
1Robert Steiner MRI Unit, Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College, London, London, United Kingdom, ²Department of Computing, Imperial College, London, London, United Kingdom

The development of thalamo-cortical projections is a key process in neonatal brain development. Parcellation of the thalamus according to thalamo-cortical connections found from DTI is becoming well established in adults but is currently uncertain in neonates. We have tested three methods, partial volume, constrained spherical deconvolution and global fibre reconstruction, using 32-direction HARDI data in term infants. Each method provided a parcellation in all cases and these were consistent to >63%. Whole brain seeding approaches were found to be the most consistent with each other and across subjects, as opposed to just considering paths seeded in the thalamus.

Manbir Singh¹, and Bryce Wilkins^1
1Radiology and Biomedical Engineering, University of Southern California, Los Angeles, CA, United States

Hippocampal connectivity is a key objective of many clinical studies particularly of elderly subjects. Using a recently reported multi-fiber per voxel streamline tractography approach that can construct up to 3 fiber orientations per voxel in DTI data acquired with as few as 25 gradient directions, and hippocampal subfield demarcation by FreeSurfer, we show tracts connecting individual hippocampal subfields to the entire brain. Despite partial volume effects of the 2x2x2 mm-3 DTI acquisition, which would lead to overlapping tracts, differences in the subfield connections consistent with biologically known hippocampal connectivity are apparent in these results.

Radu Jianu¹, Wenjin Zhou¹, Ryan Cabeen¹, Daniel Dickstein^2,3, and David H. Laidlaw^1
1Computer Science, Brown University, Providence, RI, United States, ²Psychiatry & Human Behavior, Brown University, Providence, RI, United States,³Bradley Hospital, Providence, RI, United States

We present a circular visualization interface of the tractography metrics for assessing cortical-connectivity integrity. We subdivided the gray matter into 80 regions-of-interest (ROIs) and calculated two metrics for each region-pair from the whole-brain tractography model produced from high angular resolution diffusion imaging. Three healthy control (HC) and three bipolar patients (BP) were examined in the visualization for their difference and location-specific changes in tractography metrics were identified.

Hu Cheng¹, Ruopeng Wang², and Aina Puce^1
1Indiana University, Bloomington, IN, United States, ²Harvard University, Boston, MA, United States

We investigated the effect of different fiber tracking schemes on the construction of structural brain networks. Our results show that HARDI and DTI, FACT and Tensorline, both result in similar networks with correlation coefficients greater than 0.9. HARDI is superior to DTI in terms of tracking efficiency and test-retest reliability. Tensorline algorithm is able to track longer fibers than FACT but also produces more variances. The use of white matter mask can effectively remove spurious fibers that normally cannot survive over long range tracking. The networks constructed with and without white matter mask are very different.

Emil Harald Jeroen Nijhuis^1,2, Douwe P Bergsma^3,4, Albert V van den Berg^5,6, Anne-Marie van Cappellen van Walsum^2,7, and David G Norris^1,8
1Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Gelderland, Netherlands, ²MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Overijssel, Netherlands, ³Department of Functional Neurobiology, Utrecht University, Helmholtz Research School, Netherlands, ⁴Department of Cognitive Neuroscience, University Medical Centre St Radboud, Netherlands, ⁵Department of Cognitive Neuroscience, Utrecht University, Helmholtz Research School, Netherlands, ⁶Department of Cognitive Neuroscience, University Medical Centre St Radboud, Nijmegen, Netherlands, ⁷Department of Anatomy, University Medical Centre St Radboud, Nijmegen, Netherlands, ⁸Erwin L Hahn Institute for MRI, Universität Duisburg-Essen, Germany

To determine the impact of a cerebral lesion on the neocortical network it is necessary to know its state in unharmed condition. We circumvent this problem by homotopically mapping a lesion to a healthy sample population and simulating its impact using a reachability and distance based measure.

Anand Pandit¹, Emma Robinson², Paul Aljabar³, Ioannis S Gousias¹, Daniel Rueckert³, Serena J Counsell¹, and David Edwards^1
1Centre for the Developing Brain, MRC/Imperial College, London, London, United Kingdom, ²FMRIB, University of Oxford, Oxford, United Kingdom,³Department of Computing, Imperial College, London, London, United Kingdom

In this study we combine a novel probabilistic tractography framework with Elastic Net LASSO regression in order to identify the structural connectivity patterns which are most predictive of neurodevelopmental outcome in prematurely born two-year old infants. Specific connections are shown to be responsible for effective neurological function. This work represents the first combined application of the tractography framework and regression method to this type of imaging data.

Nagesh Adluru¹, Do P. M. Tromp¹, Hui Zhang², and Andrew L. Alexander^1
1University of Wisconsin-Madison, Madison, WI, United States, ²University College London, United Kingdom

Tract specific analyses allow for statistical mapping of individual differences in specific white matter (WM) pathways. A crucial step involved in such advanced analyses is performing tractography in spatially normalized diffusion tensor imaging (DTI) data. Spatial normalization of DTI data often involves highly non-linear transformations of the acquired data with embedded interpolations of the data. Our study aims at investigating the effects of such transformations on the anatomical consistency of the normalized space tractography compared to the acquired space tractography. Our results demonstrate that DTI spatial normalization does preserve properties of WM tractography with a high degree of consistency.

Assaf Horowitz¹, Daniel Barazany², Galit Yovel², and Yaniv Assaf^2
1Tel Aviv University, Tel Aviv, Israel, Israel, ²Tel Aviv University

The corpus callosum (CC) is one of the largest fiber systems in the brain connecting and transferring information between the two hemispheres. Axcaliber is a diffusion MRI methodology the thorough analysis of multi-diffusion time, high b value DWI acquisition, allows the estimation of the axon diameter distribution (ADD). In this study we aimed to examine the inter-hemispheric transfer time (IHTT) and its relation to different axonal properties of the CC. We found that the ADD micro-structural differences at different parts of the CC are the base for the behavioral reaction time (IHTT) differences.

Yong Wang¹, Els Fieremans², Peng Sun¹, and Sheng-Kwei Song^1
1Radiology, Washington University in St. Louis, Saint Louis, MO, United States, ²Radiology, New York University, New York, NY, United States

Diffusion kurtosis imaging (DKI) has been proposed as a clinically feasible method to estimate the intra- and extra-axonal diffusivities, and the intra-axonal water fraction. Diffusion basis spectrum imaging (DBSI) has been recently introduced to model multiple diffusion compartments of crossing fibers and inflammatory response in white matter injury. We hypothesize that by incorporating restricted intra-axonal water diffusion component, DBSI can also quantify the intra-axonal water fraction. In this study, DBSI and DKI are applied to mouse trigeminal nerves. Preliminary results have demonstrated that DBSI obtained similar estimation on both intra-axonal water fraction and other associated indices as DKI counterparts.

Matthew M. Cheung^1,2, Leon C. Ho^1,2, Abby Y. Ding^1,2, Condon Lau^1,2, and Ed X. Wu^1,2
1Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China, ²Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China

It has been known that kurtosis measurements are dependent on the diffusion time (Δ), due to restricted diffusion, heterogeneity of diffusion compartments or water exchange over different compartments. In this study, we applied oscillating diffusion gradient to investigate the diffusion time effect to DKI measurements in rat brain tissues in vivo. Mean diffusivity and kurtosis were found to increase and decrease respectively with Δ, indicating increased restriction and microstructure heterogeneity. The Δ dependency may provide insights into the complex cellular properties in normal and diseased neural tissues.

Yoshitaka Masutani¹, and Shigeki Aoki^2
1Radiology, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan, ²Radiology, Juntendo Hospital, Bunkyo-ku, Tokyo, Japan

Non-Gaussianity quantification of water diffusion through diffusional kurtosis imaging (DKI) is expected in clinical applications such as classification of abnormal tissues. For faster computation of DKI parameters; K, D, and S0, we show that it is possible to obtain general closed-form expressions also for data sets by more than three b-values. In addition, we propose a fast and robust computation technique based on greedy removal of outlier sample pair of b-value and DWI signal. By using six data sets of brain from clinical MR scanner, the technique was proved to be fast, robust and effective for clinical DKI.

Marco Palombo^1,2, Silvia Gentili¹, Silvia De Santis^1,3, Marco Bozzali⁴, and Silvia Capuani^1,2
1“Sapienza” University of Rome, Physics Department, Rome, Rome, Italy, ²CNR-IPCF UOS Roma, "Sapienza" University of Rome, Rome, Rome, Italy,³CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, ⁴ISC - CNR Rome, Neuroimaging Laboratory Santa Lucia Foundation, Rome, Rome, Italy

The goal of this work was to investigate the influence of magnetic susceptibility () variations (quantified by the T2* parameter) on non-Gaussian water diffusion, evaluated by means of Diffusional Kurtosis Imaging method. To make our investigation more significant, the dependence of kurtosis indices were studied in both controlled phantom (characterized by pore size from 4 to 10 m and 10^-6 in SI) and human brain.Experimental results reported here show that  variations are correlated with the amount of deviation from Gaussian behavior observed in diffusive decay of water in both controlled phantoms and human brains using Kurtosis approach.

Bibek Dhital¹, and Robert Turner^1
1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

B-factors greater than 2000 s.mm^-2 are rarely used in diffusion-weighted imaging, due to the consequent loss of adequate SNR. Early studies at high b-factor used biexponential fitting, but recently its appropriateness for human brain imaging has been questioned, and kurtosis analysis has been proposed as an alternative with fewer fit parameters. Benefitting from the high SNR of diffusion-weighted STEAM-EPI at 7T, we acquired diffusion-weighted images with a resolution of 2 mm isotropic and maximum b-value of 8000 s.mm^-2 . Comparing biexponential fits to kurtosis fits for each voxel, we found that biexponential fits showed much superior goodness-of-fit throughout the brain.

Silvia De Santis¹, Yaniv Assaf², and Derek K Jones^1
1CUBRIC, Cardiff University, Cardiff, United Kingdom, ²Tel Aviv University, Tel Aviv, Israel

The CHARMED model was used to understand whether and where DKI contrast could be explained in terms of the underlying axonal geometry, calculating K directly from the propagator used in the CHARMED model and verifying the correlation between K and the CHARMED parameters in vivo. This work demonstrates that the information contained in DKI overlaps with the information extracted by CHARMED in areas of higher intra-voxel directional coherence, while a different information content in areas of non-negligible fibre dispersion.

Alexandru Avram¹, Arnaud Guidon², Chunlei Liu³, and Allen W Song^3
1Section on Tissue Biophysics and Biomimetics, NICHD, National Institutes of Health, Bethesda, Maryland, United States, ²Biomedical Engineering Department, Duke University, Durham, NC, United States, ³Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States

In this report we compare in vivo diffusion kurtosis measurements acquired with short and long echo times (TE) and discuss their potential for deriving a diffusional kurtosis measures for myelin water in vivo. Our findings provide initial evidence that the apparent kurtosis coefficient vary significantly with TE indicating differences between diffusional characteristics of T2 water pools in white matter.

Ali Tabesh¹, Jens H. Jensen¹, and Joseph A. Helpern^1,2
1Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, United States, ²Neurosciences, Medical University of South Carolina, Charleston, South Carolina, United States

The accuracy of diffusional kurtosis imaging (DKI) in resolving crossing fiber bundles was compared via simulations to those of diffusion spectrum imaging (DSI) and Q-ball imaging (QBI). The accuracies of these techniques and DTI were also investigated when a dominant fiber bundle intersects with an admixture of a subdominant bundle. The simulations utilized the analytical orientation distribution function representation for each technique. DSI provided the most accurate estimates in both comparisons, whereas QBI with b = 4000 s/mm2 and DKI with b = 2000-2500 s/mm2 offered similar accuracies. Finally, DKI was superior to DTI in estimating the dominant fiber bundle direction.

Filip Szczepankiewicz^1,2, Alexander Leemans³, Pia Sundgren^1,4, Ronnie Wirestam², Freddy Ståhlberg^1,2, Danielle van Westen^1,4, Jimmy Lätt⁴, and Markus Nilsson^2
1Department of Diagnostic Radiology, Lund University, Lund, Sweden, ²Department of Medical Radiation Physics, Lund University, Lund, Sweden,³University Medical Center Utrecht, Image Sciences Institute, Utrecht, Netherlands, ⁴Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden

Statistical power and variability analysis was performed using 20 sets of DKI data. The mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and radial kurtosis (RK) were determined in the cingulum, corpus callosum and corticospinal tract. Sample sizes required to detect a 10% difference with a power of 0.9 were calculated. Variability was divided into inter-subject biological differences and that arising from measurement noise. Minimum sample sizes varied across structures and metrics, but were approximately 15 for MD, FA and MK, and approximately 30 for RK. The inter-subject biological variability was the main contributor to total variability.

Chantal M.W. Tax¹, Sjoerd B. Vos¹, Jelle Veraart², Jan Sijbers², Max A. Viergever¹, and Alexander Leemans^1
1Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ²Visionlab, Department of Physics, University of Antwerp, Antwerp, Belgium

In addition to DTI, DKI quantifies the degree to which the diffusion is non-Gaussian and it can be used to estimate typical DTI measures more accurately but with lower precision. In this work, the difference in orientation information of the diffusion tensor was compared between DTI and DKI. There is a systematic deviation in orientation of the principle eigenvector, showing the difference in accuracy. In addition, deterministic and probabilistic fiber tracking on real diffusion MRI data confirms this difference in orientation information. In conclusion, the architectural configuration of the DKI based fiber pathways is more accurate than that of DTI.

Danielle Van Westen^1,2, Markus Nilsson³, Nils Karlsson², Mikael Johansson⁴, Freddy Ståhlberg^2,3, Pia C Sundgren^1,2, and Jimmy Lätt^1
1Center for Medical Imaging and Physiology, Skane University Hospital, Lund, Sweden, ²Diagnostic Radiology, Lund University, Lund, Sweden, ³Department of Medical Radiation Physics, Lund University, Lund, Sweden, ⁴Institute for Psychology, Lund University, Lund, Sweden

Regional values of the diffusional kurtosis, previously reported in a very limited number of structures, were determined in thirty-six healthy individuals in a large number of anatomically defined areas. Mean kurtosis varied from 1.38 in the splenium of the corpus callosum to 0.66 in the caudate head. Estimates in previously studied areas were well in line with those. Linear age-dependency for mean kurtosis was found in some regions, but no quadratic relationship with age, which may be due to the limited number of individuals studied.

Jiachen Zhuo¹, Jonathan Z. Simon², and Rao P Gullapalli^1
1Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States, ²Electrical & Computer Engineering, Biology, University of Maryland College Park, College Park, MD, United States

Diffusion kurtosis imaging (DKI) has gained much interest lately as a tool that can reveal subtle tissue microstructure changes over and beyond available from diffusion tensor imaging (DTI). The main challenge for clinical applications of DKI is the long imaging acquisition time due to the increased measurements needed to fit a more complex model (21 model parameters). Here we study the effect of diffusion weightings and diffusion directions in estimated DKI parameters to determine the optimal DKI imaging schemes within a clinically feasible image acquisition time (< 10min), and to understand the estimation variability in using these optimal DKI schemes.