ISMRM 25th Annual Meeting & Exhibition • 22-27 April 2017 • Honolulu, HI, USA

Traditional Poster Session: Diffusion
1730 -1776 Diffusion: Biophysical Modeling & Microstructure
1777 -1814 Diffusion: Processing, Analysis, & Visualization
1815 -1876 Other
Diffusion: Biophysical Modeling & Microstructure
Traditional Poster

Tuesday, 25 April 2017
Exhibition Hall  13:45 - 15:45



Hybrid Modeling for Perfusion Quantification Using Intravoxel Incoherent Motion MRI
Yen-Peng Liao, Shin-ichi Urayama, Hidenao Fukuyama, Denis Le Bihan
IVIM-MRI has been used to estimate perfusion-relative parameters. To increase signal fitting robustness in case of limited SNR, an asymptotic method was recommended. Hence, with the asymptotic method, a threshold b-value should be determined above which flow contamination is deemed negligible. Various diffusion models and a wide range of values for this threshold can be found in the literature. These two effects on quantification were investigated using both computer simulations and human brain data. The results showed that the choice of the model and the threshold critically influenced the quantitative parameters.  We proposed a hybrid-modeling method to minimize systematic errors. 


Optimizing the Signal Model for Diffusional Kurtosis Imaging
Jens Jensen, Vaibhav Mohanty, Emilie McKinnon, Joseph Helpern
A generalized signal model for diffusional kurtosis imaging (DKI) is proposed containing an adjustable parameter that can be optimized to reduced systematic errors in kurtosis estimates. This is illustrated by applying an established tissue model for diffusion in brain to fix the parameter, and numerical simulations are employed to demonstrate the improvement in accuracy relative to kurtosis estimates obtained with the standard DKI signal model. Finally, in vivo brain data is used to compare mean kurtosis estimates obtained with the standard and optimized DKI signal models.


Determining surface to volume ratios in capillary tube samples using oscillating gradient spin echo sequences
Morgan Mercredi, Sheryl Herrera, Richard Buist, Melanie Martin
There is an increasing drive to use diffusion spectroscopy to infer the sizes of structures in samples. Most methods use pulsed gradient spin echo sequences which cannot provide short enough diffusion times to probe very small structures. Instead, we use oscillating gradient spin echo sequences (OGSE) to probe the short-time regime allowing for small structures to be measured. Here we use the apodised cosine OGSE to infer the surface to volume ratio of a collection of packed capillary tubes, and use it approximate the tube diameters.


Diffusion-weighted MR imaging of kidney after administration of 2 types of iodinated contrast medium: a time course study in CIN animal model
Kai Zhao, Xueqing Sui, Rui Wang, Zhiyong Lin, Xiaodong Zhang, Jian Luo, Xiaoying Wang
DWI is a preeminent noninvasive method to quantify renal function, which may be helpful to understand the pathogenesis of CIN. Our time course study indicates that the iodinated contrast medium can induce some affect to the different zone of kidney. And some differences do exist on the renal transport function after the two kinds of iodinated CM administration.


Monte-Carlo Analysis of Quantitative Diffusion Measurements Using Motion-Compensated Diffusion Weighting Waveforms
Yuxin Zhang, Óscar Peña-Nogales, James Holmes, Diego Hernando
Advanced diffusion MRI acquisition strategies based on motion-compensated diffusion-encoding waveforms have been proposed to reduce the signal voids caused by tissue motion. However, quantitative diffusion measurements obtained from these motion-compensated waveforms may be biased relative to standard monopolar gradient waveforms. This study evaluated the effect of different diffusion encoding gradient waveforms on the signal decay and diffusion measurements, using Monte-Carlo simulations with different microstructures and several reconstruction signal models. The results show substantial bias in observed signal decay and quantitative diffusion measurements in the same microstructure across different gradient waveforms, in the presence of restricted diffusion.


White Matter Structural Differences among Subjects with Obstructive Sleep Apnea after Persistent CPAP-Treatment: A Non-Gaussian Diffusion MR Study with TBSS
Jiaxuan Zhang, Terri E. Weaver, Zheng Zhong, Robyn A. Nisi, Kelly R. Martin, M. Muge Karaman, Xiaohong Joe Zhou
Obstructive sleep apnea (OSA) can result in brain white matter (WM) injuries due to the hypoxic exposure. Continuous positive airway pressure (CPAP) is a common method for treating OSA patients. However, it is unclear why some patients respond to the treatment whereas others do not. In this study, we employ a non-Gaussian diffusion MRI method using a continuous-time random-walk (CTRW) model with TBSS analysis to investigate the WM microstructural variations among OSA patients who responded differently to identical CPAP-treatment. Our results have shown that CTRW-related parameters in some WM tracts exhibited significant difference between the responders and non-responders.


A modified tri-exponential model for multi-b-value diffusion-weighted imaging to detect the strictly diffusion-limited compartment and its initial application in grading and differential diagnosis of gliomas
Qiang Zeng, Biao Jiang, Jianmin Zhang, Feina Shi, Fei Dong, Chenhan Ling
In this study, we focused on the strictly diffusion-limited compartment with extremely low ADC. Because of the negligible signal attenuation of this compartment, the ADC of this compartment was set as zero. By adding this compartment to the two-compartment model, we presented a modified tri-exponential model.  The AICcs of this model were  found to be lower than the bi-exponential model and the conventional tri-exponential model, indicating this model is the best. Additionally, the parameters derived from this model, especially the fraction of the strictly diffusion-limited compartment (f0), showed potential clinical value in distinguishing the grade of malignancy of tumors.


A Fractional Motion Diffusion Model for a Twice-Refocused Spin Echo Pulse Sequence: Analytical Expression and in vivo Demonstration
Muge Karaman, Xiaohong Zhou
The anomalous diffusion behavior of biological tissue has been investigated by several studies using non-Gaussian diffusion models. Among these, the fractional motion (FM) model has attracted an intense interest by the biophysics community and was recently been introduced to the MR community. The current diffusion signal formulism based on the FM model is limited to a simple Stejskal-Tanner gradient despite the widespread use of the eddy-current-resistant gradient waveform with the twice-refocused spin echo (TRSE) technique. In this study, we theoretically derive a formulism based on the FM diffusion model to characterize anomalous diffusion using a TRSE sequence, and experimentally validate it on healthy human brain in vivo.


Substantial Error in MD Estimation Introduced by Trace Imaging
Mohammad Alipoor, Göran Starck, Stephan Maier
Since the single compartment diffusion tensor model does not reflect all contributions in diffusion signal, subsequent implications also may not hold in practice. One of the implications proven wrong here, is that mean diffusivity (MD) maps, which result from diffusion measurements along three orthogonal directions (trace imaging), are independent of the direction of the applied orthogonal gradient triplet. Simulation results with anisotropic multi-compartment diffusion models and human nerve fiber data confirm that the MD measured by trace imaging, which is typically used for rapid stroke delineation, is substantially dependent on the direction of the applied orthogonal gradient triplet and b-value.


Translocation of Water Molecules in Tissue
Gregory Wilson, Charles Springer, Jeffrey Maki
Numerical simulations of water molecule translocation are presented.  The molecules execute random walks in a 3D ensemble of digital cells with density and size pertinent for biological tissue.  The mean net displacements reflect “hindered” or “restricted” translocations for both extra- and intracellular water, characterized by an infinite number of exponentials.  The hindrance is very sensitive to the cell membrane permeability, in the range for tissue – and controlled by active cell metabolism.  


The Maastricht Diffusion Toolbox (MDT): Modular, GPU accelerated, dMRI microstructure modeling
Robbert Harms, Alard Roebroeck
MDT's object oriented modular design allows arbitrary user specification and combinations of dMRI compartment models, diffusion microstructure models, likelihood functions and optimization algorithms. Many diffusion microstructure models are included, and new models can be added simply by adding Python script files. GPU based computations allow for ~60x faster model fitting; e.g. the 81 volume example NODDI dataset can be fitted whole brain in about 40 seconds, which makes MDT ideal for population studies. MDT can be extended to other modalities and models such as quantitative MRI. The software is open source and freely available at


Simulating measurements of diffusion across the cell membrane with DEXSY and FEXSY
James Breen-Norris, Bernard Siow, Ben Hipwell, Ioana Oprea, Thomas Roberts , Mark Lythgoe, Andrada Ianus, Daniel Alexander, Simon Walker-Samuel
Here, we use numerical simulations to demonstrate the feasibility of measuring diffusion exchange across the cell membrane using DEXSY (Diffusion Exchange spectroscopy) and compare it with FEXSY (Filter Exchange Spectroscopy). Simulations were carried out using the CAMINO platform, for a range of permeabilities, in a substrate chosen to model nerve tissue. The results of these simulations suggest that both DEXSY and FEXSY are capable of measuring diffusion exchange, over a physiologically meaningful range of permeabilities, and an extended range of permeabilities (0.365 to 2.008 µm/s). These results demonstrate the potential for these techniques to be used to differentiate pathology from normal tissue.


Deconvolution based approaches for the simultaneous quantification of IVIM, Free Water and non-Gaussian behavior in Diffusion MRI.
Alberto De Luca, Filippo Arrigoni, Alessandra Bertoldo, Martijn Froeling
The in-vivo Diffusion MRI (dMRI) signal does not generally arise from a single diffusion process but from the sum of multiples. In this study we investigated a deconvolution approach to simultaneously estimate non-Gaussian diffusion, free water (FW), IVIM and tissue fractions. We analyzed the brain data of a subject acquired with 60 different b-values with four deconvolution based approaches, and compared their results in terms of identified components. The four approaches provided consistent results, with the IVIM compartment being the most similar component across the four methods. Reliable quantification of multiple compartments, including membrane restrictions, is feasible with regularized approaches.


White matter biomarkers from fast protocols using axially symmetric diffusion kurtosis imaging
Brian Hansen, Ahmad Khan, Noam Shemesh, Torben Lund, Ryan Sangill, Leif Østergaard, Sune Jespersen
White matter tract integrity (WMTI) can be used to characterize tissue microstructure in areas with strongly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development, aging, and brain disorders. In clinical settings, however, the diffusion kurtosis imaging (DKI) protocol utilized as part of WMTI imaging may be prohibitively long. Consequently, the diagnostic value of the WMTI parameters is mostly explored in dedicated animal studies and clinical studies of slowly progressing diseases. Here, we evaluate WMTI based on recently introduced axisymmetric DKI which has lower data demand than conventional DKI.


Inferring cell morphology in the heart with a compartment model of diffusion MRI
Darryl McClymont, Irvin Teh, Hannah Whittington, Craig Lygate, Jürgen Schneider
We propose a three-compartment model to perform cytometry in cardiac diffusion MRI. Our approach adapts the VERDICT model to account for the anisotropic geometry of cardiomyocytes. The model was fit to data from ex-vivo mouse heart imaged with multiple diffusion times, diffusion directions, and q-shells. The model yields realistic volume fractions (intracellular/extracellular/vascular = 68/16/16%) and cell radii (7-9.5 μm). The parameters derived could aid quantitative characterisation of cardiomyopathies including hypertrophy and fibrosis.


A novel diffusion compartment imaging (DCI) model that captures the asymmetry of WM microstructure heterogeneity
Benoit Scherrer, Maxime Taquet, Etienne Saint-Onge, Gaetan Rensonnet, Simon Warfield
The DIAMOND diffusion compartment imaging (DCI) model has been recently proposed to model the 3-D diffusivity of each compartment with a statistical distribution of diffusion tensors. This enabled the assessment of compartment-specific diffusion characteristics while also capturing the intra-compartment heterogeneity. The approach, however, could only describe symmetric heterogeneity, while tissue heterogeneity likely differs along and perpendicular to the fascicles' orientation. In this work we propose a new statistical distribution model able to capture the asymmetric nature of tissue heterogeneity. We demonstrate that it captures different axial and radial heterogeneities in presence of dispersion and investigate results with in vivo data.


The Impact of Edema and Crossing Fibers on Diffusion MRI: ODF vs. DBSI
Ze-Zhong Ye, Sam Gary, Sourajit Mustafi, G. Glenn, Fang-Cheng Yeh, Chunyu Song, Peng Sun, Yu-Chien Wu, Jens Jensen, Sheng-Kwei Song
We quantitatively examined the effect of fiber crossing and edema on DTI metrics employing phantoms made of mouse trigeminal nerves and agarose gel. Edema mimicked by gel coating significantly impaired the accuracy of estimated crossing angles using the diffusion orientation distribution function. Diffusion basis spectrum imaging (DBSI) was able to estimate crossing angles in the presence of edema and recover individual nerve baseline diffusivity. 


Empirical reproducibility of clinically feasible ensemble average propagator imaging
Kurt Schilling, Vishwesh Nath, Justin Blaber, Prasanna Parvathaneni, Adam Anderson, Bennett Landman
In this study, we measure the reproducibility of metrics derived from the ensemble averaged propagator (EAP) estimated using the 3D-SHORE technique using a clinically feasible high angular resolution diffusion dataset repeated 11 times on a single subject. We find very low reproducibility in measures of microstructural restriction (including the mean-squared displacement and return to origin probability) as well as measures of the orientation distribution function (including peaks of the ODF). This study highlights the limitations of using advanced models with empirical data, particularly in the low-SNR regime. 


Reconstruction of fetal diffusion MRI using a spherical harmonic model
Maria Kuklisova Murgasova, Alessandro Daducci, Georgia Lockwood-Estrin, Daan Christiaens, Mary Rutherford, J Donald Tournier, Joseph Hajnal, Meritxell Bach Cuadra
We present a novel method for reconstruction of fetal dMRI based on spherical harmonic model that includes motion correction, distortion correction and super-resolution reconstruction. We show that all these steps are important for producing good quality results. Our method will facilitate investigations into brain white-matter development in utero.


Monoexponential, Biexponential, and Stretched exponential Diffusion-weighted Imaging Models: Quantitative Biomarkers for Differentiating Renal Clear Cell Carcinoma and Minimal Fat Angiomyolipoma
Haojie Li, Yao Hu, Daoyu Hu, Zhen Li
Compared to monoexponential DWI model, biexponential and stretched exponential DWI models are feasible and useful in the noninvasive tissue characterization of renal tumors. Water molecular diffusion heterogeneity index (α) and Dt may provide additional information and could lead to improved differentiation with better sensitivity and specificity in differencing MFAML from ccRCC compared with mean ADC, Dp, fp, and DDC values in clinical setting.


Preliminary Investigation on NODDI for Studying Spinal Cord Microstructure of Postoperative CSM Patients
Xiaodong Ma, Xiao Han, Wen Jiang, Zhe Zhang, Erpeng Dai, Yishi Wang, Xiaoguang Cheng, Hua Guo
In this study, the neurite orientation dispersion and density imaging (NODDI) was used to investigate the spinal cord microstructure for postoperative CSM patients. MRI data were acquired on eleven patients with a long time after surgery. The value of the calculated parameters (OD, Viso and Vic) were preliminarily evaluated. Statistical results show that OD of grey matter is lower at the stenotic level than the normal level, and Viso in both grey and white matter is higher. To the best of our knowledge, this is the first time that the application of NODDI in the spinal cord disease was reported.


Exploring ex vivo brainstem complex pathways with diffusion microstructure at 11.7T
Sophie Sébille, Anne-Sophie Rolland, Carine Karachi, Marie-Laure Welter, Eric Bardinet, Mathieu Santin
We performed multi-shell 3D segmented EPI on a post mortem macaque brain at 11.7T (resolution 200 μm iso, 120 directions) and evaluated NODDI as a tool to accurately extract brainstem pathways. We showed that the orientation dispersion map can help in segmenting ROIs used for tractography. Microstructure information opens promising perspectives for the exploration of the brainstem complex organization ex vivo in human and non-human primate.


Introducing axonal myelination in connectomics: a preliminary analysis of g-ratio distribution in healthy subjects
Matteo Mancini, Giovanni Giulietti, Nick Dowell, Barbara Spanò, Neil Harrison, Marco Bozzali, Mara Cercignani
We estimated the g-ratio (i.e., the ratio of the inner and the outer diameters of myelinated axons) in-vivo in two different datasets of healthy subjects using diffusion and magnetization data. We used this measure to characterize the organization of the structural connectome and compared it to the information obtained by the streamlines reconstructed using tractography. The g-ratio significantly differentiated hub-related aspects of the connections and subcortico-cortical organization. These preliminary results showed that this measure could provide complementary information to the connectome structure.


Population averaged ferret brain templates for in-vivo and ex-vivo anatomical and diffusion tensor MRI
Elizabeth Hutchinson, Susan Schwerin, Kryslaine Radomski, Neda Sadeghi, Michal Komlosh, Jeffrey Jenkins, Okan Irfanoglu, Sharon Juliano, Carlo Pierpaoli
In-vivo and Ex-vivo anatomical MRI and DTI templates were generated for the ferret brain along with region of interest segmentation masks based on known ferret neuroanatomy.  Templates were built from multiple ferret brain images for each modality using advanced template building tools including symmetric normalization transformation for structural templates and Diffeomorphic Registration for Tensor Accurate AlignMent of Anatomical Structures (DRTAMAS) for DTI templates.  The resulting templates are made available on an interactive web site (  


In-vivo whole-brain Neurite Orientation Dispersion and Density Imaging at sub-millimeter scale using gSlider-SMS
Elda Fischi-Gomez, Susie Y. Huang, Hui Zhang, Kawin Setsompop
We demonstrate the feasibility of applying microstructural models of diffusion to sub-millimeter isotropic resolution whole brain images in-vivo. The NODDI model was successfully fitted to a 700µm DWI dataset acquired using the generalized SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (gSlider-SMS) acquisition1. We demonstrate the ability to map finer-scale structures using this high-resolution data when compared to traditional multi-shell 2 mm isotropic acquisition.


Cerebellar connectivity influences brain network topology
Fulvia Palesi, Giovanni Savini, Letizia Casiraghi, Gloria Castellazzi, Paolo Vitali, Giancarlo Germani, Egidio D'Angelo, Claudia Gandini Wheeler-Kingshott
Graph theory based approaches applied to diffusion weighted MRI data have been used for understanding cerebral processing at whole-brain scale. Nevertheless, a few studies have considered including the connectivity with the cerebellum. In this work, the cerebellar role in the whole-brain connectomic was investigated by combining automatic tools and a priori information about cerebellar connections. We assert that it is important to incorporate the knowledge that cerebro-cerebellar connections are all contralateral. Moreover, our findings demonstrate that network topology is highly influenced by the presence or the absence of the cerebellum suggesting that it plays a key role in brain processing. 


Comparison of between-subject and single-subject between-session variability in in vivo DKI brain studies
Nino Kobala, Farida Grinberg, Ezequiel Farrher, Ketevan Kotetishvili, Jon Shah
The knowledge of intra- and inter-subject variability of diffusion kurtosis imaging metrics plays an important role for interpretation of the results of the clinical trials. The purpose of this work is to investigate and compare between-session variability of a single subject with between-subject variability diffusion kurtosis parameters in different anatomical regions. Variability is quantified in terms of the coefficient of variation, which can provide the baseline for interpretation of clinical trials and single-subject longitudinal examinations.


MR imaging of the cervical spinal cord in patients with spinal muscular atrophy and healthy controls
Wieke Haakma, Marloes Stam, Martijn Froeling, Marielle Philippens, Clemens Bos, Alexander Leemans, Ludo van der Pol, Jeroen Hendrikse
We studied the architecture and diffusion characteristics in the cervical spine and nerves in spinal muscular atrophic (SMA) patients and healthy controls. We showed the asymmetrical architectural configuration of the cervical nerves in SMA patients. We computed diffusion values of which the mean, axial, and radial diffusivity were lower in the SMA patients than in healthy controls which are in accordance with the clinical symptoms of these patients. Diffusion values of the cervical spine (grey, white and the whole myelum) showed no differences.  


T2 relaxation rates of the fast and slow bi-exponential diffusion components in the in vivo corpus callosum
Qiuyun Fan, Susie Huang, Aapo Nummenmaa, Thomas Witzel, Lawrence Wald
Bi-exponential diffusion model is widely used to fit for non-Gaussian diffusion. T2 relaxation rates differ between structural compartments, which may bias the results of fits to microstructure models. We incorporate T2 relaxation into the bi-exponential model and leveraged the Gmax = 300mT/m gradient strength of the Connectome scanner to study the apparent T2 times of the two diffusion components. A longer T2 was found for the fast diffusion component when the model allows for different T2 times, but both multiple T2s and single T2 models seem to fit to the data fairly well. The added T2 parameter affects volume fraction more than diffusivity estimates. 


Determining how varying the number of gradients measurements affects fitted surface to volume ratios in tube samples using oscillating spin echo gradients
Morgan Mercredi, Sheryl Herrera, Richard Buist, Melanie Martin
There is an increasing drive to use diffusion spectroscopy to infer the sizes of structures in samples. Here, we use apodised cosine gradient spin echo sequences (OGSE) to infer the surface to volume ratio of a collection of packed capillary tubes. Aiming to reduce imaging times, this study examines how the number of gradients affects the accuracy and precision of the fitted parameters. We found that collecting OGSE data with two b-values may be sufficient to infer information about small structures, especially if higher gradients strengths are used.


Translating AxCaliber on a clinical system : 600mT/m versus optimized 80mT/m protocol
Tanguy Duval, Tom Mingasson, Eric Klawiter, Nikola Stikov, Julien Cohen-Adad
Most model-based diffusion metrics (AxCaliber metrics) have been shown to be less stable and more biased on clinical systems due to the limited gradient strength (40-80mT/m versus >300mT/m on preclinical scanners). In this work we wanted to (i) find the best AxCaliber protocol at 80mT/m and (ii) quantify the bias in the estimated metrics. For these aims, we first optimized an 80mT/m AxCaliber protocol using simulations, then compared experimentally (on an ex vivo cat spinal cord) a 600mT/m protocol versus the optimized 80mT/m protocol. Using the 600mT/m maps as a ground truth, our results show that even though axon diameter cannot be estimated robustly, the fraction of restricted water can be measured accurately (<3% error) and precisely (r2 >0.76) on clinical systems. The short duration of the optimized protocol opens the way to the use of reliable model-based diffusion MRI metrics on a clinical system, metrics that would be particularly useful to measure the degree of myelination through the fiber g-ratio.


Multi-Spherical Diffusion MRI: An in-vivo Test-Retest Study of Time-Dependent q-space Indices
Rutger Fick, Alexandra Petiet, Mathieu Santin, Anne-Charlotte Philippe, Stephane Lehericy, Rachid Deriche, Demian Wassermann
Effective representation of the diffusion signal's dependence on diffusion time is a sought-after challenge in diffusion MRI (dMRI). As a solution, we recently proposed Multi-Spherical Diffusion MRI (MS-dMRI) to represent the dMRI signal in this four-dimensional space - varying over gradient strength, direction and diffusion time. Our representation allows for the estimation of time-dependent q-space features, providing unique insights on the tissue microstructure. In the study, we assess test-retest reproducibility of these indices in three C57Bl6 wild-type mice. We find that due to our effective regularization methodology during signal fitting, these time-dependent features can be estimated reliably without overfitting the data.


Value of MR DWI with different mathmatical models in the differential diagnosis liver neoplasms
Qu Zhaohui, Gao Xuemei, Cheng Jingliang, Wang Shaoyu
To investigate the utility value of monoexponential model,biexponential model and diffusion kurtosis model diffusion weighted imaging in diagnosis of liver neoplasms.


Accelerated Diffusion-weighted 129Xe MRI Morphometry of Emphysema in COPD and Alpha-1 Antitrypsin Deficiency Patients
Alexei Ouriadov, Eric Lessard, Fumin Guo, Heather Young, Anurag Bhalla, David McCormack, Grace Parraga
In this proof-of-concept evaluation, we evaluated 129Xe MRI ADC/morphometry estimates using two different acceleration factors (AF) in a small group of never-smokers, COPD ex-smokers with emphysema and Alpha-1 Antitrypsin Deficiency patients.  Such estimates were obtained for three different cases: fully sampled k-space; 50% under-sampling in the phase-encoding direction, AF=2; and 66% undersampling, AF=3.  The results of this study showed that the difference in ADC/morphometry estimates from fully sampled and under-sampled k-space were similar to that observed with accelerated 3He multi-b diffusion-weighted MRI in healthy subjects.  These differences increase however, with increasing emphysema severity, which requires further investigation.


Can fast diffusion kurtosis imaging be quantitative in the brain?
Yen-Shu Kuo, Shun-Chung Yang, Ya-Fang Chen, Wen-Chau Wu
This study was aimed to investigate the applicability of fast DK imaging for both cerebral gray matter and white matter as a quantitative method. Our experimental data reveal that the dependence of D and K on b-values predominantly exists in areas containing a noticeable amount of cerebrospinal fluid. D is more sensitive to b-value choice than K. With b-values carefully chosen to account for signal-to-noise ratio and model fidelity, fast DK imaging-derived indexes can be quantitative with negligible dependence on b-values in most gray matter and white matter.


Can we trust structural connectivity?
Silvia Obertino, Flora Danti, Mauro Zucchelli, Francesca Pizzini, Gloria Menegaz
Structural connectivity models result from a complex processing chain involving many different steps, each having an impact on the reliability of the final measures. One of the hottest questions in the state-of-the-art is thus “To which extent can we trust the structural connectome?”. In this work, we tackled this issue by focusing on the typical processing pipeline and investigating the impact of the main involved steps. MRTrix CSD-based probabilistic tractography provided the highest stability across subjects and MRTrix reached the largest distance with respect to other softwares in both individual subject and group analysis. 


Diffusion Imaging Reveals White Matter Damage in Ice Hockey Players for Up To Two Months Post-Concussion
Alexander Weber, Michael Jarrett, Enedino Hernandez-Torres, Shiroy Dadachanji, David Li, Jack Taunton, Alexander Rauscher
Traumatic brain injury (TBI) is a leading cause of disability in adults. More sophisticated methods are required in order to understand its underlying pathophysiology and disease progression. Recent interest in an assumption-free DTI analysis, diffusion entropy (DE), has produced some promising results for investigating white matter (WM) and grey matter (GM) microstructure. We set out to test DE against the much more common fractional anisotropy (FA) analysis, in both WM and GM, in 45 hockey players over one season. 11 players sustained a concussion and were scanned at 72 hours, 2 weeks, and 2 months post-injury.


Fast Linear Fitting of Bi-Exponential Intra-Voxel Incoherent Motion (IVIM) Models
Eric Peterson, Natalie Zahr, Edith Sullivan, Adolf Pfefferbaum
This work introduces an extremely fast (whole image in ~5s) IVIM fitting procedure based on two sequential linear fits and demonstrates that it is comparable to the more traditional but much slower non-linear fitting. This method is valuable because current fitting methods typically take a significant amount of time, typically from minutes to hours, due to their iterative and non-linear nature. Therefore, this technique can be used as a fitting method alone and also as a way to seed more advanced techniques with accurate starting values.


Sensitivity of STEAM diffusion MRI to permeability in white matter tissue: a simulation study
Ioana Oprea, Andrada Ianus, Olga Ciccarelli, Ivana Drobnjak
This study investigates the sensitivity of the Stimulated-Echo Acquisition Mode (STEAM) diffusion-weighted signal to permeability quantified with water exchange time $$$\tau_{ex}$$$. In order to do this, Monte Carlo simulations were generated for a range of histologically-plausible  $$$\tau_{ex}$$$ and practical scanner acquisition parameters. The results suggest that on the standard clinical scanner (G=70mT/m), STEAM estimates short exchange times (<0.9s), which are characteristic in tissue with myelin damage, while tissue with longer exchange times (>1.5s) is practically indistinguishable from impermeable tissue. The Connectome scanner (G=300mT/m) estimates a much wider range, however needs careful optimisation since the resolution limit is highly dependent on the sequence parameters and SNR’s.


Diffusion kurtosis metrics as sensitive biomarkers of ageing
Farida Grinberg, Nino Kobalia, Ezequiel Farrher, N. Jon Shah
Diffusion tensor imaging is an established tool for the examination of WM connectivity and microstructural changes across the lifespan. More recently, advanced diffusion MRI techniques, such as diffusion kurtosis imaging (DKI), have been shown to provide richer information on tissue microstructure. Thus far, only a few works have been published related to DKI in healthy ageing. In this work, we examined, in a large cohort of subjects, the potential of DKI metrics to unravel microstructural changes due to ageing in different brain regions. 


Stability of co-electrospun brain-mimicking fibers for diffusion MRI
Fenglei Zhou, Matthew Grech-Sollars, Adam Waldman, Geoffrey Parker, Penny Hubbard Cristinacce
This work investigates the stability and reproducibility of brain-mimicking microfiber phantoms. These microfibers were produced by co-electrospinning (co-ES) and characterized by scanning electron microscopy (SEM). Grey matter (GM) and white matter (WM) phantoms were constructed from random and aligned microfibers, respectively. MR data were acquired from these phantoms over a period of 17 months. SEM images reveal that there were some changes in the pore size and porosity of co-ES fibers over a period of 30 months. MR measurements showed variations within the limits expected for intra-scanner variability, thereby confirming the phantom stability over 17 months.


Abnormal white matter integrity in parkinson’s disease patients with cognitive impairment revealed by tract-based spatial statistics
Hui Yu, Mingming Huang
Results from recent neuroimaging studies suggest that PD patients with cognitive impairment(PDCI) is associated with abnormal white matter integrity. In this study, we used tract-based spatial statistics (TBSS) method combined with diffusion tensor imaging (DTI) to investigate the microstructural integrity of the white matter in PDCI. Results from TBSS demonstrated that PDCI patients had significantly lower FA than healthy controls in anterior thalamic radiation(atr), corticospinal tract (cst), cingulated gyrus(cg), forceps minor(fi), the right inferior fronto-occipital fasciculus(ifo), inferior longitudinal fasciculus(ilf), superior longitudinal fasciculus(slf) and uncinate fasciculus(uf). There were no white matter integrity changes in PD patients without cognitive dysfunction, And also significantly correlation was found between FA in the right ifo and MoCA scores.  


Changes of non-Gaussian diffusion MRI parameters at different diffusion times in a human breast carcinoma xenograft model
Mami Iima, Tomomi Nobashi, Hirohiko Imai, Sho Koyasu, Akira Yamamoto, Masako Kataoka, Yuji Nakamoto, Tetsuya Matsuda, Kaori Togashi
The relationship between diffusion time and diffusion parameters obtained from 7.0T MRI using a human breast carcinoma xenograft model was investigated. There was an increase in K values and decrease in ADCo as well as sADC values in 27.6ms compared to 9.6 ms.  Some tumor showed heterogeneous sADC change derived from two different diffusion times.


Gray matter cellular volume fraction imaging and Alzheimer’s disease
Farshid Sepehrband, Nyoman Kurniawan, Kristi Clark
Neuronal loss is one of the major outcomes of neurodegenerative diseases such as Alzheimer’s disease (AD) [1,2]. Given the microscopic level of changes associated with neurodegeneration, it is challenging to image with conventional MRI techniques. Microstructural diffusion-weighted MRI is a powerful tool, which has been shown to be sensitive to microscopic brain tissue characteristics [3,4]. However, a relative lack of specificity has impeded its transition to clinic.  

Here we focus primarily on deriving cell content information in gray matter and apply it to AD. We acquired multi-shell dMRI of two postmortem samples of human hippocampal tissue (one AD and one control) at the same time, with isotropic resolution of 200 mm, using a 16.4T scanner. We modeled signal attenuation based on the observed evidence of faster signal decay of the cellular compartment. Then, we derived the cell volume fraction by fitting the model to the data and compared it within and between our tissues.


Clinically Feasible Optic Nerve Diffusion Basis Spectrum Imaging at 3T
Joo-won Kim, Peng Sun, Sheng-Kwei Song, Samantha Lancia, Courtney Dula, Robert Naismith, Junqian Xu
Optic nerve MRI is susceptible to eyeball movement. The relatively long acquisition time of advanced diffusion MRI (dMRI) methods exacerbates the motion sensitivity in optic nerve dMRI and limits the clinical implementation of these methods. In this work, we evaluate a short (less than 2.5 min per eye) single slice coronal optic nerve dMRI acquisition protocol at 3T and propose a 2D optic nerve center searching algorithm customized for such dMRI data. We demonstrate improved optic nerve center contrast after image alignment and the expected benefits of reduced partial volume effects from diffusion basis spectrum imaging (DBSI) analysis.


Detection of abnormal brain neural circuits in draxin knockout mice using DTI-MRI
Yuri Kitamoto, Tatsuya Higuma, Makoto Hirakane, Mitsuhiro Takeda, Sosuke Yoshinaga, Rikita Araki, Hideaki Tanaka, Yohei Shinmyo, Hiroaki Terasawa
The aim of this study is to clarify the role of the axon guidance molecule Draxin in the construction of brain neural circuits by DTI-MRI. MRI was performed on draxin knockout, dra(–), and normal mice both in vivo and ex vivo. The in vivo study of dra(–) revealed that the nerve fibers in the corpus callosum did not intersect with the midline. The ex vivo study of dra(–) demonstrated that the thalamocortical nerve fibers did not extend toward the cerebral neocortex through the internal capsule. We successfully evaluated the influences caused by the Draxin loss with DTI-MRI.


Characteristic analysis of in vivo and ex vivo rat brains by 7.0 T DTI MR
Chunhua Wang, Li Song, Ruzhi Zhang, Fabao Gao
Ex vivo diffusion tensor imaging (DTI) are widely used in experimental studies for excellent images. The comparison between in vivo and ex vivo DTI has been conducted without the same scan parameters. We aimed to compare the living and fixed white and gray matters under the same condition and explore the effects of coil and signal average. Diffusivities were significant different between living and fixed brains. Coil and signal average significantly affected the signal-to-noise ratio of ex vivo white and gray matters. The results indicate that fixation and MR conditions should be considered in clinical and experimental DTI studies.
Diffusion: Processing, Analysis, & Visualization
Traditional Poster

Tuesday, 25 April 2017
Exhibition Hall  13:45 - 15:45



Evaluation of the Quality of Eddy-Currents and EPI Distortion Correction for Diffusion MRI: A Dataset for Benchmarking
Mustafa Irfanoglu, Amritha Nayak, Joelle Sarlls, Carlo Pierpaoli
In recent years, numerous methodologies have been proposed for the correction of motion, eddy-currents and echo planar imaging (EPI) distortions for diffusion MRI data. The typical strategy to assess the quality of these corrections is to compare them to an undistorted image, such as a T1-weighted or T2-weighted structural image, with different quality measures such as outlines, similarity metrics or segmentation overlaps. Even though several of these measures are quantitative, the use of wide range of validation strategies in combination with data with significantly different distortion properties complicates a direct comparison of these techniques. In this work, we propose a quantitative, unbiased and robust strategy to evaluate the performances of these correction techniques and provide a publicly available benchmarking dataset.


Compressed Sensing to Accelerate Connectomic Histology in the Mouse Brain
Nian Wang, Gary Cofer, Robert J. Anderson, Russell Dibb, Yi Qi, Alexandra Badea, G. Allan Johnson
We evaluated the utility of compressed sensing (CS) for diffusion tensor (connectomic) histology in the mouse brain at high field (9.4T). We explored the effect of b values, compression factors, and k-space sampling strategies. We were able to achieve compression factors of 4X through judicious choice of k-space sampling patterns. Comparison to a comprehensively acquired data set (full sampling at 43 μm with 120 angles) allowed us to reduce the acquisition time by nearly 30X with minimal loss in the resulting connectome.


Prediction of outcome in bilateral common carotid artery occlusion (BCCAO) rats by intravoxel incoherent motion (IVIM) analysis at 11.7 Tesla
Shunrou Fujiwara, Yuki Mori, Daniela de la Mora, Kuniaki Ogasawara, Yoshichika Yoshioka
Rats with the bilateral carotid artery occlusion (BCCAO) was often used for assessment of the brain damage caused by chronic cerebral hypoperfusion as a longitudinal ischemic animal model; however, the mortality is high and it has remained unclear what kinds of initial cerebral hemodynamic changes occurred in the brain in the hyperacute phase after BCCAO and whether the changes related with the mortality in rats or not. Intravoxel incoherent motion (IVIM), which is the basic concept of diffusion-weighted imaging (DWI), can non-invasively demonstrate various hemodynamic situations at one time DWI scan with multiple b values. Here, we investigated whether the outcome of BCCAO rats associated with cerebral hemodynamic changes assessed using IVIM- DWI.


Correction of nonuniform diffusion weighting in DWI using vendor-provided gradient characteristics
Dariya Malyarenko, Yuxi Pang, Lisa Wilmes, Ek Tsoon Tan, John Kirsch, Julien Sénégas, Michael Jacobs, David Newitt, Thomas Chenevert
System-specific gradient nonlinearity (GNL) causes spatially nonuniform weighting in diffusion weighted imaging (DWI). This leads to systematic bias and variability in derived apparent diffusion coefficient (ADC) maps, diminishing their quantitative utility for multi-site, multi-platform clinical trials. An ADC error correction methodology for three-direction DWI acquisition was developed previously using an empiric system GNL approximation.  Here we demonstrate implementation of correction for three clinical scanners using the system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. Implemented correction substantially improves precision and removes ADC bias for ice-water phantoms.  Comparable accuracy and performance is achieved across all gradient platforms.


Toward Analytic Computation of Fiber-Radial Diffusional Kurtosis by Q-space Data Representation with Radial Basis Functions
Yoshitaka Masutani, Koh Sasaki
To enhance the robustness of the fiber-radial diffusional kurtosis computation, the signal decay in the Q-space can be averaged among the fiber-radial orientations. By using the radial basis functions with Gaussian basis, it is shown that the fiber-radial signal decay can be represented in a pseudo-analytic form with the Bessel function. By using in-vivo diffusion MRI data, the computation results were presented in comparison with those by diffusion kurtosis tensor of 4th order to prove the effectiveness of the proposed method.


Directional sensitivity of anomalous diffusion assessed using a tensorial fractional motion model
Boyan Xu, Gaolang Gong, Yaoyu Zhang, Yang Fan, Bing Wu, Jia-Hong Gao
Anisotropic diffusion in the nervous system is most commonly modeled by the apparent diffusion tensor, which is based on normal diffusion theory. However, the departure of the diffusion-induced signal attenuation from the mono-exponential form indicates the existence of anomalous diffusion. The fractional motion (FM) model, which is considered as the appropriate anomalous diffusion theory for biological tissues, has been applied to diffusion MRI. However, the directional sensitivity of the FM model in biological tissues remains elusive. In this study, this issue was addressed via tensor analysis in analogy with the diffusion tensor.


Solving the free water elimination estimation problem by incorporating T2 relaxation properties
Quinten Collier, Jelle Veraart, Arnold den Dekker, Floris Vanhevel, Paul Parizel, Jan Sijbers
The free water elimination (FWE) model fitting problem is inherently ill-conditioned, leading to the need for solutions that can avoid or deal with these kinds of fitting problems. In this work, we evaluate a model extension to the FWE model that exploits the T2-relaxation properties and subsequently leads to a well-posed fitting problem that can be easily solved using standard estimation techniques. 


Investigating the Effects of Concurrent Magnetic Field Monitoring on High Angular Resolution Diffusion Imaging: Application to Cortical Parcellation
Yoojin Lee, Bertram Wilm, Tara Ganepola, Alexander Leemans, Martin Sereno, Daniel Alexander, Klaas Pruessmann, Zoltan Nagy
The concurrent field monitoring has been proposed to eliminate image artifacts in diffusion imaging introduced by the long lasting eddy currents from the diffusion-encoding gradients. In this work we investigated the effects of field monitoring system on HARDI and applied the improved HARDI data to cortical parcellation. We showed that the field monitoring improved the HARDI data quality especially in anterior/posterior poles of the brain and air-tissue interfaces. This regional improvement was also clear in the cortical classification results, where the field monitoring improved the accuracy of the V1/V2 by 3%, compared to ~0.5% in the motor strip.


Predicting patient survival in hepatocellular carcinoma (HCC) from diffusion weighted magnetic resonance imaging (DW-MRI) data using neural networks
Florian Ettlinger, Patrick Christ, Georgios Kaissis, Freba Ahmaddy, Felix Grün, Sebastian Schlecht, Alexander Valentinitsch, Seyed-Ahmad Ahmadi, Bjoern Menze, Rickmer Braren
In this work we present a method to predict patient survival in hepatocellular carcinoma (HCC). We automatically segment HCC from DW-MRI images using fully convolutional neural networks. In a second step we predict patient survival rates by calculating different features from ADC maps. We calculate Histogram features, Haralick features and propose new features trained by a 3D Convolutional Neural Network (SurvivalNet). Applied to 31 HCC cases, SurvivalNet accomplishes a classification accuracy of 65% at a precision and sensitivity of 64% and 65% when trained using our automatic tumor segmentation in a fully automatic fashion.


Automatic detection of volumes affected by subvolume movement
Kerstin Pannek, Jurgen Fripp, Joanne George, Roslyn Boyd, Paul Colditz, Stephen Rose
Diffusion-weighted MRI is prone to a number of artefacts, including movement between subvolumes in an interleaved acquisition. Affected volumes need to be identified and dealt with before further processing. We use a registration based approach to identify volumes affected by subvolume motion, and demonstrate that a single metric, calculated from all subjects acquired using the same acquisition protocol, is sufficient to reliably identify such volumes. Importantly, the detection threshold is determined from the data itself, and can be applied to multi-shell data.


Characterization of Spinal Cord DTI Metrics in Clinically Asymptomatic Pediatric Subjects with Incidental Congenital Lesions
Sona Saksena, Mahdi Alizadeh, Devon Middleton, Laura Krisa, MJ Mulcahey, Feroze Mohamed, Scott Faro
Synopsis: Hydromyelia and syringomyelia are essentially cystic abnormalities of the spinal cord (SC). The prevalence of these abnormalities in the clinically normal pediatric population is uncommon to rare. Out of 26 healthy typically developing (TD) pediatric subjects scanned in this study, 4 subjects had incidental findings of hydromyelia (n=3) and syringomyelia (n=1) lesions within the thoracic SC. These subjects were healthy and clinically normal. DTI parameters were calculated by using ROIs drawn on the whole cord along the entire SC. DTI parameters were significantly different in the cord above the subject with syringomyelia lesion compared to the TD subjects. However, no significant difference in DTI parameters was found in the cord above the subjects with hydromyelia lesions. This study demonstrates that DTI has the potential to be used as an imaging biomarker to evaluate the SC above and below the congenital lesions in asymptomatic subjects and one should use caution while including them into a normative data population.  


Exploring the potentials and limitations of improved free-water elimination DTI techniques
Rafael Neto Henriques, Ørjan Bergmann, Ariel Rokem, Ofer Pasternak, Marta Correia
Free-water diffusion tensor imaging (fwDTI) was previously proposed to remove CSF partial volume effects of measures based on the diffusion tensor. Nevertheless, this diffusion-weighted technique is still subject to several pitfalls. In this study, an improved algorithm to fit the fwDTI to data acquired with two or more diffusion-weighting gradients is proposed. This algorithm is then used to explore the advantages and limitations of suppressing free-water in synthetic and in vivo diffusion-weighted data. 


Impact of Prior Distribution and Central Tendency Measure on Bayesian IVIM Model Fitting
Oscar Gustafsson, Mikael Montelius, Göran Starck, Maria Ljungberg
Bayesian model fitting has been shown to yield robust estimates of the IVIM parameters. However, various methodological choices have differed between studies, which may have substantial effect on the results. This study investigates the effect that the prior distributions and central tendency measures may have, using both in vivo data and simulations. The results show that the prior distribution can play a significant role at commonly seen signal-to-noise levels. The choice of central tendency measure has less effect on the estimates. However, it may be chosen to emphasize either accuracy or precision.


Simulation study for the evaluation of DWI data with the IVIM-Kurtosis model based on artificial neural networks
Marco Bertleff, Sebastian Domsch, Lothar Schad
In this work we present an evaluation approach based on artificial neural networks (ANN) for fitting the IVIM-Kurtosis model parameters on the basis of simulated DWI data. The ANN approach is compared to an ordinary bounded least squares regression (LSR) in terms of correlation between estimates and ground truth, systematic, statistical and total estimation error. While for D and K high correlations and low errors were found for both LSR and ANN, a significant improvement was observed for f and D* regarding correlation coefficients, precision and the total estimation error when using ANN.


Characterization of the ulnar nerve using multislice DTI using a multiband factor of 1, 2, and 3
Tina Jeon, Ek Tan, Maggie Fung, Darryl Sneag
Multiband (MB) echo planar MR imaging (EPI) excites and refocuses multiple slice locations simultaneously using MB radiofrequency excitation and refocusing pulses that are subsequently un-aliased by exploiting differences in coil sensitivities. In this study, we investigated the feasibility of using MB diffusion tensor (DT) EPI with a multiband factor of 1, 2, and 3 to interrogate the ulnar nerve at different locations in the arm.


Fractional anisotropy spatial covariance analysis in Parkinson’s disease suggests a disease related degeneration pattern
Xingfeng Li, Yue Xing, Antonio Bastida, Stefan Schwarz, Piccini Paola, Dorothee Auer, Xingfeng Li Yue Xing
Parkinson’s disease (PD) is characterised by disrupted functional and structural brain networks. Structural network changes are thought to better reflect progression of the neurodegeneration. To study the pattern of neurodegeneration in Parkinson’s disease (PD), we investigated the correlation pattern of fractional anisotropy (FA) with substantia nigra (SN) using a structural covariance analysis method. We also correlated FA maps with the unified Parkinson's disease rating scale (UPDRS); we found a disruption of SN covariance FA maps in PD compared to controls. Moreover, disease severity was significantly correlated with FA in cerebellar and anterior cingulate cortex (ACC). 


Novel application of the reversed gradient method in Diffusion Weighted-MRI for tumor response assessment in head and neck squamous cell carcinoma patient undergoing radiation therapy.
David Aramburu Nuñez, Jose Luis del Olmo Claudio, Silvia Reigosa Montes, Antonio López Medina, Moises Mera Iglesias, Francisco Salvador Gómez , Íñigo Nieto, Alfonso Calzado, Amita Shukla-Dave, Victor M Muñoz
Reversed gradient method can reduce geometric distortion leading to accurate measurement of ADC. We designed a new phantom for distortion assessment and tested the reversed gradient method in both phantom and head and neck cancer patients, obtaining a relevant increase in mutual information values (phantom: 13% – 35%; patients: 6% - 100%). The voxel-wise analysis of the tumor showing variation of ADC with treatment exhibits significant difference (p<0.01) in calculated ADC between corrected and raw images. In future studies, the reverse gradient method may be included as part of clinical DW-MRI that focus on tumor response assessment.


Age-related effect on white matter changes and lexical retrieval
Natalie Wang, Fan-pei Yang, Yiyang Chen, Toshiharu Nakai, Makoto Miyakoshi
Identifying age-related white matter change is vital to understanding neurodegeneration. With studies focusing mainly on memory, little is known of age-related change in language function. This current study bridges the gap by investigating the relationship between changes of WM integrity and task-based language performance. The behavioural evidence revealed significant different between young and healthy elderly people in phonemic as well as semantic retrieval. Also, TBSS analysis suggest significant difference in white matter volume between the two groups. However, correlation between white matter indices, FA and MD, was not found, indicating  that degeneration of language function cannot be account for solely on white matter changes or particular task type.


Robust mapping of diffusion parameters of the combined IVIM-Kurtosis-model using artificial neural networks in the human brain
Marco Bertleff, Sebastian Domsch, Lothar Schad
In this work we present an artificial neural network (ANN) approach for the evaluation of the combined IVIM-Kurtosis model and robust mapping of the diffusion parameters in the human brain. Measuring seven healthy subjects the parameter map quality could be improved compared to an ordinary least squares regression by significantly reducing outliers and decreasing the variance while preserving the tissue contrast. An ROI-based analysis additionally showed a better agreement of the mean parameter values with the literature along with a better distinction between white and grey matter for the ANN approach.


New approach to improve the reliability of IVIM parameters using computed DWI based on stretched exponential model
Eunju Kim, Jinwoo Hwang, Jae-Hun Kim, Marc Van Cauteren
We propose a new approach to IVIM analysis using computed DWI (cDWI) based on stretched exponential model. IVIM analysis is widely studied clinically to evaluate tissue perfusion and diffusivity using a range of low and high b values. However, signal attenuation curves of different b values are heterogeneous because of biological effects from multiple components and patient’s motion during the acquisition. So we generated cDWI first using stretched exponential model which can better fit for signal attenuation curve and analyse IVIM parametric maps using cDWI. The proposed approach can fit more robustly the IVIM model parameters.


Longitudinal tissue changes in tumefactive demyelinating lesion associated with the administration of disease modifying drugs: a free water diffusion MRI study.
Salvatore Lacava, Ofer Pasternak, Maurizia Chiusole, Giorgio Rossi, John Port, Nivedita Agarwal
It is challenging to diagnostically distinguish tumefactive demyelinating lesions (TDLs) from tumors surrounded by massive edema and mid-line shift such as high grade gliomas. We demonstrate free water diffusion MRI analysis to identify water diffusivity compartments in the lesion, and to monitor effects of medical treatment over time. We believe that free water diffusion analysis can be important adjunct to conventional MR, and adds value by improving our understanding of the histologic components of a lesion, which can help clinical diagnosis and potentially avoid biopsy.


Multi-Tensor Filtering based on Expectation-Maximization Framework
Etienne St-Onge, Benoit Scherrer, Maxime Taquet, Simon Warfield
In this abstract, we introduce a new multi-tensor regularization and denoising technique based on Expectation-Maximization framework. To reduce filtering blurring effect and preserve sharp edges, we incorporated anisotropic regularization weight to the framework. We also utilize a tensor similarity metric, made from a quaternion representation, to improve the regularization and preserve tensor characteristics. Finally, we evaluate and compare filtering methods using a diffusion MRI synthetic phantom and in-vivo acquisition.


Cortical Diffusion Analysis of Human Connectome Project Data Identifies Granular Cortices
Qiyuan Tian, Christoph Leuze, Hua Wu, Grant Yang, Jingyuan Chen, Jonathan Polimeni, Jennifer McNab
We performed whole-brain cortical surface-based analysis of diffusion orientations on 100 subjects from the Human Connectome Project. Correlations between diffusion angles (angles between primary diffusion orientations and cortical surface normals) and cortical thickness and curvature were removed using rank-based linear regression. The resulting diffusion angle maps show radial diffusion orientations in all regions except for a few granular cortices which have predominantly tangential diffusion orientations. Identification of the granular cortices is greatly enhanced in the group-averaged map compared to a single-subject dataset. 


A Bayesian approach for diffusional kurtosis imaging
Eizou Umezawa, Daichi Ishihara, Yasunari kono, Toshiaki Nakai, Ryoichi Kato
We propose a Bayesian approach for improving the accuracy of diffusional kurtosis imaging in a small number of data acquisitions. Gaussian-approximated prior distributions are made from primary maximum-likelihood estimation (MLE). The approach was tested using a healthy volunteer data in which a part of signals was replaced with simulated glioma signals. Although the approach does not yield further improvement when MLE has a certain degree of accuracy, the approach has effect to reduce large misestimations and did not cause false shrinkage of dispersions that the sample parameters inherently have. The approach reduces the burden of data acquisition.


Low Rank plus Sparse Decomposition of ODF Distributions: Whole brain Statistical Analysis of Higher Order Diffusion Datasets
Steven Baete, Ying-Chia Lin, Ricardo Otazo, Fernando Boada
Recent advances in data acquisition make it possible to use high quality diffusion data for routine in vivo study of white matter architecture. The dimensionality of these data sets requires a more robust methodology for their statistical analyses than currently available. Here we propose a apply Low-Rank plus Sparse (L+S) matrix decomposition to reliably detect voxelwise group differences in the Orientation Distribution Function that are robust against the effects of noise and outliers. We demonstrate the performance of this approach to replicate the established negative association between global white matter integrity and physical obesity in the Human Connectome dataset.


Robust identification of rich-club organization in weighted and dense structural connectomes
Xiaoyun Liang, Chun-Hung Yeh, Robert Smith, Alan Connelly, Fernando Calamante
Rich-club organizations, characterizing the higher-level topology of the brain network, has been commonly identified from structural connectomes constructed using DTI based on network degrees. This analysis can however be compromised by the following issues: (i) DTI limitations in resolving crossing-fibers; and (ii) the original degree-metric based approach is unsuitable for highly-connected connectomes, because it leads to nodes with indistinguishably high degrees. Importantly, increasing evidence suggests that brain connectomes could be very dense. To address these issues, we propose a robust framework by: (i) applying advanced-tractography to construct connectomes; and (ii) developing a h-degree based method, RICHER, to identify rich-club organization.


Assessment of Inherent Variation in Diffusion Tensor Measurements with Multi-band EPI in Rhesus Monkeys
Yuguang Meng, Xiaodong Zhang
     Multi-band EPI technique is becoming prevalent in diffusion MRI because it can reduce the scanning time substantially by simultaneously exciting multiple slices and then decoding signal by parallel MR imaging reconstruction algorithms. However, little is known about its influence on the inherent variations of diffusion measurements with or without multi-band parallel acquisitions. This study compared the variations of the in-vivo diffusion MRI measurement results by multi-band and conventional parallel acquisitions. The results showed that the inherent variations of diffusion MRI measurements can be reduced by multi-band parallel acquisition compared to conventional parallel MRI acquisition.


Individualized prediction of mild cognitive impairment based on patterns of altered tract integrity over the whole brain using diffusion spectrum imaging
Yu-Jen Chen, Yun-Chin Hsu, Yu-Ling Chang, Ming-Jang Chiu, Wen-Yih Tseng
In this study, we tested the capability of individualized prediction for mild cognitive impairment (MCI) by using the information of whole brain tract integrity produced by tract-based automatic analysis method. The information was trained to search the tract segments that could most accurately separate the MCI patients and healthy participants. The optimal tract segments were searched with the area under receiver operating characteristic curve of 0.76. These specific segments of white matter tracts could potentially serve as imaging biomarker for predicting patients with MCI.


Histogram Analysis of Intravoxel Incoherent Motion MR Imaging–Related Parameters in Brain Glioma Grading: A Comparison Between 2D and 3D methods
Chunhong Wang, Yihao Guo, Maodong Chen, Yingjie Mei, Xiaodong Zhang, Jing Zhang, Xiang xiao, Yanqiu Feng, Yikai Xu
Gliomas are the most common primary neoplasms of the brain, World Health Organization (WHO) clarify it from low grade(LGGs; grade II) to high grade(HGGs; grades III, IV). The objective of this study was to explore which method is the best method with little time consuming and good grading of glioma.


Preliminary analysis of micro-structural changes in different locations of brain tissue affected by acute ischemic stroke using diffusional kurtosis imaging
Liuhong Zhu, Zhongping Zhang, Qihua Cheng, Funan Wang, Gang Guo
The performance of diffusion kurtosis imaging (DKI) in the analysis of micro-structural changes of brain tissue affected by acute ischemic stroke was explored. 199 lesions in common affected locations were divided into six groups. The value of DKI-derived indices and their changed percentage relative to normal contralateral ROI were calculated. Multiple comparisons among groups indicated that kurtosis indices (especially MK and Ka) showed better performance compared to diffusion indices (ADC, MD, Da and Dr) in detecting structure changes of brain tissues affected by acute ischemic stroke. 


Rapid Measurement of Perfusion Fraction in Clinical Neuroimaging
Emma Meeus, Jan Novak, Hamid Dehghani, Andrew Peet
This study investigated the reliability of using a rapid three b-value diffusion-weighted imaging to determine intravoxel incoherent motion (IVIM) parameters. Grey matter simulations were conducted to assess the bias and reproducibility of the parameters with b-value distributions: b0,300,500,1000, b0,500,1000 and b0,300,1000. The same b-value distributions were assessed with a volunteer cohort. The results showed that the use of two high b-values provided a good estimate of the perfusion fraction, which was further improved by an increase in the SNR level. In conclusion, the measurement of IVIM-fwas achievable using a three b-value protocol.


Minimizing the error in finding peak orientations of fiber ODF in diffusion MRI using Nelder-Mead simplex method
Kuan-Hung Cho, Chun-Hung Yeh, Yi-Ping Chao, Ching-Po Lin, Li-Wei Kuo
Discrete mesh search method is commonly used to determine fiber orientations by searching orientations corresponding local maxima of orientation distribution function (ODF). However, this method may produce extra errors relating to the number of sampling points of ODF in fiber orientation estimate. We address this problem and minimize the error of fiber orientation estimate by using Nelder-Mead simplex method. The results from computer simulation and phantom experiment show that Nelder-Mead simplex method gives accurate fiber orientation estimation better than discrete mesh search method with ODF sampling points less than 163,842.


Application of Weighted Diffusion Subtraction (WDS) to Synovial Sarcomas: Possibility of Visualising Tumor Cellularity
Manabu Arai, Shigeo Okuda, Sota Oguro, Kuniaki Ohori, Koichi Oshio
DWI and ADC values are widely used for tissue characterization. However, the relationship between the ADC values and the histological findings is still controversial. Weighted diffusion subtraction (WDS) was originally developed to eliminate T2 shine-through ambiguity in diffusion MRI evaluations. In this study, we applied WDS technique to diffusion weighted images of synovial sarcomas to evaluate the complex and heterogeneous tissue. Correspondence was found between WDS and histological findings on visual inspection. WDS seems to be a valuable visualization tool.


Quantifying Reconstruction Uncertainty with Image Quality Transfer
Ryutaro Tanno, Aurobrata Ghosh, Francesco Grussu, Enrico Kaden, Antonio Criminisi, Daniel Alexander
Image quality transfer employs machine learning techniques to enhance quality of images by transferring information from rare high-quality datasets. Despite its successful applications in super-resolution and parameter map estimation of diffusion MR images, it still remains unclear how to assess the veracity of the predicted image in practice, especially in the presence of pathology or features not observed in the training data. Here we show that one can derive a measure of uncertainty from the IQT framework and demonstrate its values as a surrogate measure of reconstruction accuracy (e.g. root mean square error).


Analyses of Diffusion kurtosis imaging for spleen with liver disease
Yuhki Hamada, Daisuke Yoshimaru, Yuhichi Suzuki, Nozomi Mogi, Ayumu Funaki
We evaluated the relationship between the mean kurtosis values (MK) and spleen size for the prediction of liver disease. As a result, there was no difference between the regular spleen and spleen with liver disease in the MK. Therefore, we consider that the splenic cell density and inner pressure remain unchanged even if patients have the enlarged spleen with liver diseases.


Compact representation of the diffusion signal for multi-shell HARDI
Daan Christiaens, J-Donald Tournier, Maria Kuklisova-Murgasova, Joseph Hajnal
With the advent of multi-shell acquisition, there is an increasing need for compact linear orthonormal representations of the DWI signal that extend over the radial as well as angular domain. In this work, we evaluate and compare 3 candidate basis function sets: spherical Bessel functions with and without reparametrization and the SHORE basis. Results show that the reparametrized Bessel functions and SHORE basis can faithfully represent the DWI signal with low numbers of parameters, and can be tuned to the properties of the signal independently of acquisition parameters.


Characterizing diffusion weighted images using Clustering Analysis of Spherical Harmonics (CASH)
Manish Amin, Guita Banan, Matthew Hey, Luis Colon-Perez, Haiqing Huang, Mingzhou Ding, Catherine Price, Thomas Mareci
Diffusion weighted imaging has become an important tool for understanding how pathology affects brain structure. However, the standard method of diffusion tensor imaging (DTI) is inadequate in complex fiber regions. Other more complex diffusion models calculate the diffusion displacement probability function (DPF) 1, but current methods to extract the information from the DPF are limited. To this end, we introduce a data-driven method combining spherical harmonic representations of the DPF with the clustering analysis of spherical harmonic (CASH) coefficients, to provide an enhanced diffusion data characterization that includes information about the number of unique fiber orientations present in each voxel. 


Can DTI Predict the MRI Level of Injury in Pediatric Spinal Cord Injury Subjects?
Sona Saksena, John Gaughan, Devon Middleton, Laura Krisa, MJ Mulcahey, Chris Conklin, Mahdi Alizadeh, Scott Faro, Feroze Mohamed
The purpose of this study was to determine whether DTI parameters can be used to predict the level of injury as observed on conventional MRI data in pediatric spinal cord injury (SCI) subjects and to estimate the cut points for the DTI parameters which best discriminates the abnormal MRI from normal appearing MRI regions. Ten subjects with chronic SCI underwent repeat axial DTI scans based on inner field of view sequence. FA, MD, AD and RD were calculated by using ROIs drawn on the whole cord along the entire spinal cord for both scans. FA, MD, RD were significant predictors of the MRI level of injury. The cut points for FA, MD, AD and RD discriminated the abnormal MRI from normal appearing MRI regions in these subjects. DTI has the potential to serve as a surrogate for an abnormal MRI level corresponding to a region of SCI in instances where the MRI scans are unavailable, unreliable or there is an equivocal clinical exam.
Traditional Poster

Tuesday, 25 April 2017
Exhibition Hall  13:45 - 15:45



Towards interpretation of 3-tissue constrained spherical deconvolution results in pathology
Thijs Dhollander, David Raffelt, Alan Connelly
Multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) and single-shell 3-tissue CSD (SS3T-CSD) resolve WM fibre orientation distributions and GM and CSF tissue compartments by deconvolving WM, GM and CSF response functions from the diffusion MRI data. We aim for more general interpretation of the “WM/GM/CSF” compartments obtained from 3-tissue CSD methods, specifically in the presence of pathology. We demonstrate their potential in this context and provide a simple framework that aids interpretation, with healthy tissues as a frame of reference. “CSF-like” partial volume is related to interstitial fluid, while “GM-like” partial volume may indicate gliosis, given an appropriate context.


Evaluation of Motion-Compensated Spatially-Constrained IVIM (MC-SCIM) Model of Diffusion-weighted MRI for Assessment of Fibrosis in Crohn’s Disease using Surgical Histopathology Scores
Sila Kurugol, Moti Freiman, Jeffrey Goldsmith, Ryne Didier, Onur Afacan, Jeanette Perez-Rossello, Michael Callahan, Athos Bousvaros, Simon Warfield
Distinguishing bowel regions with fibrosis and regions with active inflammation would be clinically useful in Crohn’s disease to determine best therapy.  Commonly used ADC model of DW-MRI, which encapsulates multiple diffusion components into a single parameter, may not suffice to fully describe tissue microenvironments. IVIM model, which describes fast and slow diffusion components, is not commonly used in clinic because of challenges of reliably estimating its parameters due to noise and physiological motion. We recently introduced a motion-compensated spatially-constrained incoherent motion model (MC-SCIM) for reliable parameter estimation. Here we compared MC-SCIM parameters to  scores of inflammation and fibrosis from histopathology.


Potential value of turbo-spin echo diffusion-weighted imaging in nasopharynx: primary study for differential diagnosis between recurrent nasopharyngeal carcinoma and post-chemoradiation fibrosis
Shui Zhang
In our study, we found significantly higher image quality, lesion conspicuity and less distortion of TSE-DWI based on Alsop method compared with SS-EPI according to image quality scores. Frustratingly, the SNR for TSE-DWI was lower than for SS-EPI and the result was consistent with other non EPI-DWI sequences in previous studies. Clinically, the low SNR of TSE-DWI remains a major concern. May be it is contributed to the long reception time and higher actual resolution of TSE images compared with SS-EPI and the more efficient k-space coverage of SS-EPI. The CNR of nasopharynx lesions on DW images was significantly better for TSE-DWI imaging than for SS-EPI imaging, which enables a better visual discrimination of nasopharynx lesions with TSE-DWI imaging. In conclusion, TSE-DWI with fewer artifacts and much higher resolutions, which was near impossible before, will make up for the slightly poorer SNR. The ADC values of the brainstem, which was less affected by the susceptibility artifacts and ghosts, showed no significant differences between the two DWI techniques. However, the ADC values of the lesions on TSE were significantly different than those on SS-EPI. This result is obtained coincide with the previous result.These differences may be primarily attributed to susceptibility artifacts and ghost that also resulted in inhomogeneous ADC maps because nasopharyngeal DWI is vulnerable to these artifacts. Therefore, the ADC measurements from TSE-DWI might be more accurate than those from SS-EPI. 


Intravoxel Incoherent Motion Diffusion-weighted MR Imaging of the Liver: Influence of Combined Respiratory-cardiac Triggering Method on Signal-to-noise Ratio and Repeatability of Quantitative Parameters
Jinning Li, Caiyuan Zhang, Yanfen Cui, Huanhuan Liu, Weibo Chen, Dengbin Wang
As extremely susceptible to various kinds of motions, diffusion-weighted magnetic resonance imaging always leads to insufficient image quality and poor reproducibility of quantitative measurements, especially for the liver. However, the use of combined respiratory-cardiac triggering, sychronizing data acquisitions with respiratory and cardiac cycles, could effective improve the signal-to-noise ratio and the repeatability of apparent diffusion coefficient and intravoxel incoherent motion parameters in the liver compared with respiratory triggering and free breathing without triggering method.


High-Resolution Intravoxel Incoherent Motion (IVIM) with Generalized SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (gSlider-SMS): Effect on CSF Partial Volume Contamination
John Conklin, Thomas Witzel, Kawin Setsompop
In this work, we introduce a high-resolution acquisition strategy for IVIM brain imaging using generalized Slider Simultaneous MultiSlice (gSlider-SMS) diffusion MRI. An SNR efficient multi b-value 10 simultaneous slice acquisition was used to obtain IVIM parameter maps with submillimeter isotropic resolution. Compared to a conventional acquisition (2 mm isotropic), high resolution IVIM provided improved delineation of the cortex and reduced partial volume contamination with CSF. Cortical perfusion measurements using the standard acquisition were falsely elevated by approximately 40% compared to gSlider-SMS IVIM. High resolution IVIM may provide more reliable perfusion information for evaluation of cortically based pathology.


Diffusion weighted imaging of the cerebello-thalamic pathway after MR guided high intensity focused ultrasound (HIFU) thalamotomy
José A. Pineda-Pardo, Raul Martínez-Fernández, Rafael Rodríguez-Rojas, Marta Del-Alamo, Frida Hernández, Lydia Vela, José A. Obeso
In here we aimed at characterizing the impact of the HIFU thalamotomy over the cerebello-thalamic pathway. We used probabilistic tractography to map the subject-specific anatomy of this pathway, we defined a set of regions along a group average pathway, and we extracted DTI based average values in these regions. We found local and distant alterations along the pathway 3-months post-treatment. These changes were strongly correlated with the clinical improvement of the patients. These findings serve to strengthen DWI, as a tool to aid in the targeting of HIFU in the treatment of essential tremor.


Value of the Intravoxel Incoherent Motion MRI in Pretreatment Predicting and Monitoring the Early Response to Chemoradiotherapy in Esophageal Squamous Cell Carcinoma
fei ping li, zhongping zhang, Xiaoping Yu
Chemoradiotherapy (CRT) was considered to be a very effective treatment regimen for locally advanced or unresectable esophageal cancer (EC). Usually the therapy-induced early changes of tumor microenvironment were prior to morphological changes, which cannot be detected by traditional imaging techniques. This study used intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to investigate the early response to CRT in esophageal squamous cell carcinoma (ESCC). It was found that the IVIM-DWI parameters (ADC and D) might be valuable in pretreatment predicting and monitoring the early treatment response to CRT in ESCC.  


Intravoxel incoherent motion (IVIM) diffusion-weighted imaging for response evaluation of hepatocellular carcinoma after resin- and glass-based radioembolization
Claus Pieper, Alois Sprinkart, Carsten Meyer, Hans Schild, Guido Kukuk, Petra Mürtz
Intravoxel incoherent motion (IVIM) model-based analysis of diffusion-weighted imaging (DWI) is increasingly employed in oncologic imaging. Although first experiences with IVIM DWI for response analysis of hepatocellular carcinoma (HCC) after embolization therapies in general have recently been reported, response characteristics of specific treatment options are so far unknown. We describe differences in treatment response parameters of HCCs obtained by IVIM DWI in resin-radioembolization and glass-radioembolization.


Rectal Adenocarcinoma: Diagnostic Accuracy of Diffusion Kurtosis Imaging (DKI) and its Correlation with Prognostic Factors
Lan Zhu, Xu Yan, Cai xia Fu, Huan Zhang, Zilai Pan, Fuhua Yan
The high resolution MRI and conventional DWI suffers from unsatisfying accuracy in assessment of some prognostic factors of rectal adenocarcinoma. We employed DKI, a protocol mainly for evaluating the complexity of biologic tissues, to explore its diagnostic accuracy and correlation with prognostic factors. The kurtosis of DKI exhibited highest correlation with histologic grades especially the new grading criterion and higher potential in differentiation of high- and low grade tumors, and also in predicting nodal status, with higher specificity than or equivalent sensitivity to diffusivity and ADC. In conclusion, DKI could be a promising tool in predicting prognosis of rectal adenocarcinoma.


A Comparison of Readout Segmented EPI and  Interleaved EPI in High Resolution Diffusion Weighted Imaging
Yishi Wang, Xiaodong Ma, Zhe Zhang, Erpeng Dai, Ha-Kyu Jeong, Bin Xie, Chun Yuan, Hua Guo
Multi-shot interleaved EPI (iEPI) and readout segmented EPI (RS-EPI) are two alternative strategies for high resolution diffusion imaging. This study made a comparison of the two methods in different aspects. Our comparison showed that the iEPI had the advantage of largely reducing the geometric distortion. Both RS-EPI and iEPI could achieve high resolution diffusion tensor imaging.


Evaluation of diffusion weighted imaging (DWI), kurtosis imaging (DKI) and q-space imaging (QSI) for profiling whole human breast tumour tissue microstructure
Nicholas Senn, Yazan Masannat, Ehab Husain, Bernard Siow, Steven Heys, Jiabao He
We investigated a clinically viable QSI protocol in whole breast tumours excised from patients on a clinical scanner within a clinically feasible time frame. QSI has been largely limited to the preclinical setting, requiring strong gradients and a long acquisition time. We compared QSI against conventional DWI and DKI and found that diffusion indices across these techniques were consistent. Previous studies have shown that QSI provides a comprehensive characterisation of tissue microstructure, particularly in the presence of restricted diffusion. These results provide pivotal foundation for the clinical translation of QSI in breast cancer diagnosis and prognosis.


Effect of hyperglycemia on deep nucleus microstructure and iron deposition in people with type 2 diabetes: a DKI and SWI study
Junyi Dong, Chengcheng Zheng, Qingwei Song, Qiang Wei, Weiwei Wang, Yanwei Miao, Bing Wu
In this paper,the experimental group and the control group were respectively used as the people with type 2 diabetes and the health people ,the effect of high blood glucose on the microstructure and iron deposition in patients with type 2 diabetes mellitus was studied used DKI and SWI study,and it is concluded that the high blood glucose level may have certain damage to the microstructure of the deep core.Furthermore,iron deposition may exacerbate the damage of microstructure.In conclusion,DKI and SWI study can evaluate secondary brain microstructure changes from hyperglycemia in T2DM patients.


Optimal strategy for measuring intraventricular temperature using second-order motion compensation DWI
Shuhei Shibukawa, Tetsu Niwa, Naoki Ohno, Toshiaki Miyati, Tomohiko Horie, Susumu Takano, Nao Kajihara, Toshiki Saito, Tetsuo Ogino, Yutaka Imai
A method for monitoring the intraventricular cerebrospinal fluid (CSF) temperature calculated from the DWI is affected by the CSF pulsation. Moreover, DWI should be obtained by optimal b value according to the diffusion coefficient of the measuring tissues. We investigated the second-order motion compensation DWI (2nd-MC DWI) to the determination of the intraventricular temperature to improve that accuracy with optimal b value. In the case of using the optimal b value based on the literature (ie., approximately 400 s/mm2), the intraventricular temperature can be more accurately estimated with 2nd-MC DWI than conventional no-motion compensation DWI. 


Estimation of a novel set of intra and extracellular diffusivity parameters from modern DW-MRI
Mario Ocampo-Pineda, Alessandro Daducci, Alonso Ramirez-Manzanares
We present a novel framework to estimate on in-vivo data a) independent intra and extracellular axial-diffusivities, b) extracellular radial-diffusivity, c) non-parametric bundle dispersion, d) axonal diameter indexes, and e) intracellular volume fractions. Our methodology does not fix a priori the value of any of these parameters or uses tortuosity models on the extracellular radial diffusivity. The proposal is an extension of the ED^3 method, which provided the best solution on the signal prediction on the White Matter Modelling Challenge 2015. We perform a comprehensive set of synthetic experiments under realistic conditions to validate the capabilities of the proposal.


Prediction of Radiotherapy Response in Nasopharyngeal Carcinoma Patients Using Diffusion-Kurtosis Imaging
Weiyuan Huang, Jiianjun Li, Feng Chen, Yingman Zhao, Xiaolei Zhu
The first row: A 62-year-old man with NPC who was a nonresponder. The lesions located at the left nasopharyngeal wall and cavum. Manual draw an ROI within the boundaries of the NPC on Kmean map. The tumor’s maximum diameter was 3.5 before radiotherapy. Residual tumor was detected after radiotherapy. Mean Dmean and Kmean values were 1.48 10-3 mm2/s and 0.72 before treatment. The second row: A 63–year-old man with NPC who was a responder. The lesion affect the bilateral mucous membrane of the nasopharynx. The tumor’s maximum diameter was 3.09 before radiotherapy. No residual tumor was detected after radiotherapy. Mean Dmean and Kmean values were 1.22 10-3 mm2/s and 0.83 before treatment. NRG: non response group RG: reponse group


Effect of gadolinium contrast agent on IVIM derived parameters of abdominal organs
Yukun Chen, Chao Ma, Aiguo Jin, Li Wang, Minjie Wang, Luguang Chen, Caixia Fu, Xu Yan, Jianping Lu
This study investigated potential effects of gadolinium contrast agent on the IVIM derived parameters such as Dfast (blood microcirculation), Dslow (pure extravascular water diffusion), f (perfusion fraction) and the commonly used DWI-derived ADC of abdominal organs. The result shows that gadolinium administration does not make statistically significant differences in Dslow, Dfast, f or ADC of the liver, spleen, or pancreas. In the kidney, however, ADC values are significantly lower with post-contrast than pre-contrast.


Imaging energy landscapes
Evren Özarslan, Kadir Simsek, Cem Yolcu, Carl-Fredrik Westin
We discuss the usage of a recently-proposed diffusion-sensitising gradient waveform for the purpose of imaging the potential energy landscape in which water molecules diffuse. The energy landscape encodes information about bulk heterogeneities of the medium as well as effects such as adsorption at the boundaries.  


IVIM-derived parameters in evaluating the pathological features and hypoxia of nasopharyngeal carcinoma xenografts
Youping Xiao, Yunbin Chen, Xiang Zheng, Ying Chen, Li Peng, Jianji Pan, Weibo Chen
Intravoxel incoherent motion diffusion weighted imaging was conducted on different radio-sensitive human NPC xenografts (CNE-1 and CNE-2) in order to investigate its application value in assessing the pathological features and tumor’s hypoxia of xenografts. CNE-2 xenografts of higher radio-sensitivity behaved greater changes on IVIM-parameters than CNE-1 xenografts of lower radio-sensitivity after fractional radiations. D and f values correlated significantly with the pathological features and tumor’s hypoxia of xenografts. Thus, IVIM-parameters is potentially valuable in evaluating the effect of radiotherapy in NPC.


High-resolution diffusion imaging of post-mortem monkey brain: comparison of 3D Spin Echo and 3D segmented EPI sequence at 11.7T
Sophie Sébille, Anne-Sophie Rolland, Carine Karachi, Marie-Laure Welter, Eric Bardinet, Mathieu Santin
Diffusion-weighted spin echo (SE) acquisition is the golden-standard of diffusion imaging, yet it is limited by a very long acquisition time. This work present the optimization of a 3D segmented Echo Planar Imaging (EPI) sequence with the goal of reducing acquisition time and be able to perform tractography and to promote further analysis such as microstructure or histology correlation.


Comparison of MUSSELS vs MUSE for Multi-Shot Diffusion Imaging
Merry Mani, Mathews Jacob, Baolian Yang, Vincent Magnotta
Multi-shot diffusion weighted (MS-DW) imaging can offer reduced echo-time (TE) and improved SNR to enable high spatial resolution applications. However, the reconstruction of the high resolution diffusion weighted images (DWI) from the multiple shots is challenging because of the presence of motion-induced phase variations between shots. Recently, two methods were proposed to reconstruct the phase-compensated DWIs. In this work, we compare the performance of the methods, MUSE and MUSSELS, to reconstruct the DWIs from a MS-DW acquisition.


Fiber connection density differences detected in patients with sickle cell disease
Julie Coloigner, Jacob Antony, Roza Vlosova, Adam Bush, Soyoung Choi, Maxime Descoteaux, Jean-Christophe Houde, Thomas Coates, Natasha Lepore, John Wood
Sickle cell disease (SCD) is a chronic disorder characterize by progressive cerebrovascular damage. We hypothesized that subtle cerebral injury might be visible with diffusion imaging data in these patients. Tractography based on the fiber orientation distribution function (ODF) was applied in order to investigate the character and severity of white matter injury in patients with SCD. We found both decreased and increased fiber density in patients, compared to control subjects that co-localized with silent cerebral infarctions. These data suggest progressive white matter injury and compensatory mechanisms in SCD patients. 


Diffusion weighted imaging in thyroid nodule: comparison of readout-segmented EPI and single-shot EPI Techniques
Luguang Chen, Peipei Sun, Bin Xu, Qiang Hao, Caixia Fu, Minjie Wang, Jianping Lu
Diffusion weighted imaging showed the potential to evaluate thyroid disease. This study aimed to evaluate whether readout-segmented EPI (RS-EPI) can provide better image quality in imaging thyroid gland in comparison with single-shot EPI (SS-EPI), and to compare ADC values, acquired from RS-EPI with those of SS-EPI. Sixteen patients were examined using both techniques. There were significant differences in susceptibility, motion artifacts, except for detectability of thyroid nodules and ADC measurements between RS-EPI and SS-EPI. The present study found that the RS-EPI technique provides significant image quality improvement compared with SS-EPI in imaging thyroid gland at 3 Tesla.


Towards a practical protocol for accurate and reliable MR-derived diffusion changes of the optic nerve in optic neuritis
Weiling Lee, Soo Lee Lim, Ling Ling Chan, Winston Lim, Helmut Rumpel

Optic neuritis is a demyelinating inflammation of the optic nerve that often occurs in association with multiple sclerosis and neuromyelitis optica. Magnetic resonance imaging (MRI), especially diffusion-tensor imaging (DTI) is highly sensitive for inflammatory changes in the optic nerves. We propose a DTI protocol which balances susceptibility artefacts, scan time, and resolution for better image quality and clinical practicality. It allows a 1 mm in-plane resolution in order to avoid partial volume averaging with cerebrospinal fluid (CSF) surrounding the optic nerve in examining fractional anisotropy (FA) values and apparent diffusion coefficient (ADC) for severity of optic neuritis.



Joint estimation of free water and perfusion fraction in human brain
Anna Scherman Rydhög, André Ahlgren, Filip Szczepankiewicz, Ronnie Wirestam, Carl-Fredrik Westin, Linda Knutsson, Ofer Pasternak
The perfusion of blood affects the estimation of diffusivities, especially fast components such as free water. Here, we acquired human data to demonstrate the applicability of a three-compartment model for the joint estimation of tissue diffusivities, free water, and the perfusion fraction. We evaluated the feasibility of the model by comparing a multiple b-value approach with a shorter, clinically feasible approach. The conclusion is that the two-compartment free-water estimation is affected by both water and blood. The three-compartment model disentangles these effects, useful in distinguishing between changes originating from capillary blood from those originating from the extracellular space.


Fractional motion related diffusion MRI in the detection of acute ischemic stroke
Yang Fan, Boyan Xu, Lu Su, Bing Wu, Zhenyu Zhou, Peiyi Gao, Jia-Hong Gao
The use of FM model has been demonstrated in distinguishing low- and high-grade pediatric brain tumors. However, its feasibility in detecting acute stroke has not yet been investigated. In this work, FM model was applied in patients with acute ischemic stroke and compared with traditional ADC to investigate its clinical potential. 


Model-Based Joint Reconstruction for Multi b-Value Diffusion-Weighted Imaging
Zhongbiao Xu, Li Guo, Wenxing Fang, Chenguang Zhao, Yingjie Mei, Zhifeng Chen, Wufan Chen, Ed X. Wu, Feng Huang, Yanqiu Feng
In current multi b-value DWI, each b-value image is usually reconstructed independently by using parallel MRI techniques. In this work, we propose a model-based joint reconstruction method for the reconstruction of under-sampled multi b-value DWI data. The proposed method can directly estimate quantitative parameters form k-space data, and exploit inter-image constraint to improve the quality of reconstructed image.


High Resolution Cardiac DTI - Fiber Tractography Statistics of the ex Vivo pig Heart
David Lohr, Maxim Terekhov, Andreas Weng, Anja Schroeder, Heike Walles, Laura Schreiber
A whole heart, high resolution diffusion tensor data set with 1.3 mm isotropic voxels was acquired in 15 ex vivo pig hearts using a Stejskal-Tanner sequence at 3T. ADC, FA and HA values were calculated and analyzed for the whole heart. Purpose was to create a reliable statistical reference of diffusion parameters. Sharp modes for median and interquartile range of the ADC and median and mean values of the helix angle indicate similar distributions of those values for the individual hearts. This provides a statistically compelling reference for future cardiac DTI pig studies in vivo and at higher field strengths.


In Vivo 3D Single-Shot Echo-Planar DWI at 7T for Mapping Tissue Microstructure using Mean Apparent Propagator (MAP) MRI
Alexandru Korotcov, Asamoah Bosomtwi, Elizabeth Hutchinson, Michal Komlosh, Carlo Pierpaoli, Peter Basser, Andrew Hoy, Bernard Dardzinski
A number of advanced diffusion models have demonstrated great promise for mapping tissue microstructure in ex vivo studies with high resolution and fidelity using a wide range of diffusion weightings, but the increased acquisition time (days) is not feasible in vivo. In this study we have addressed some basic DWI acquisition pitfalls by using 3D single-shot EPI on a high-field (7 Tesla) pre-clinical MRI system, and adapted one of the most promising diffusion modeling techniques, mean apparent propagator (MAP) MRI in vivo to derive information about rat brain microstructure within a reasonable time frame.


Intravoxel Incoherent Motion (IVIM) in Evaluation of Orbital Masses
Ya-wen AO, Jun Chen , Liang Zhang, Fei Sang, Hong-yan Nie, Dong-jie Huang, Hui Lin, Bing Wu
Diffusion-weighted imaging (DWI) has been proven that malignant orbital masses demonstrate significantly and visually appreciable lower apparent diffusion coefficient (ADC) than benign orbital masses[1-2]. Nevertheless, ADC cannot separate the pure molecular diffusion from the motion of water molecules in the capillary network; thus, perfusion contamination would increase the ADC value. According to the IVIM DWI model[3], both microscopic perfusion and diffusivity can be separated using a biexponential decay function, providing additional parameters for tissue characterization. From the result we can see that it is feasible that quantitative parameters of orbital masses can be derived from IVIM DWI. 


Harmonization for DTI measurements mapping across sites in multi-center MRI study
Chuanzhu Sun, Lijun Bai, Hao Yan, Shan Wang, Xiaocui Wang, Xianjun Li, Chao Jin, Xiaocheng Wei, Hong Yin, Zengjun Zhang, Xiaoqun Yao, Xiaoling Zhang, Jian Yang, Jian Yang, Jian Yang
Despite the fact that multi-site diffusion imaging studies are increasingly used to study brain disorders, but it is noteworthy that there are large differences among diffusion measurements from different sites. The current study aimed to confirm the variability and to harmonize data across sites. Our results indicated that not only DTI metrics in human brain within inter-site but also within inter-site changed obviously. Furthermore, a brain voxel-based model was developed to harmonize the DTI metrics and to reduce the deviation compared with reference site data and thus improve the reliability of group analysis in multi-center  study.


Benefits of flow, eddy current and concomitant field compensation in diffusion weighted MRI
Lars Mueller, Andreas Wetscherek, Tristan Kuder, Frederik Laun
Diffusion-weighted MRI suffers from artifacts due to flow, concomitant fields and eddy currents. Different combinations of compensation for these effects were examined in phantom measurements as well as in vivo in the brain and in the prostate. The signal variations in the phantom measurements indicate that it could be advantageous to simultaneously compensate of all three effects over only flow and concomitant field compensation. This could not be seen in the in vivo results, where flow and concomitant field compensation proved to be as good as the full compensation.


Diffusion Diffraction Inside Out
Valerij Kiselev, Alexander Ruh, Bibek Dhital
Diffusion diffraction, a famous result on NMR in porous media founds little application to in-vivo MRI. Beyond the high technical requirements, the reason can be seen in the principal limitations of this technique. It probes the shape of identical closed pores, which are not typical in-vivo. In this work, we generalize diffusion diffraction for an infinite connected compartment outside impermeable inclusions such as space external to biological cells with low membrane permeability. The signal at high diffusion weighting is  expressed in terms of the inclusions' correlation function. The developed theory is supported by experiments in aqueous suspension of polystyrene microbeads.


Investigation of Diffusion Tensor Indices by ROI analysis and TBSS of Patients with Depressive Symptoms in the Elderly with Dementia
Tsung-Yuan Li, Ni-Jung Chang, Clayton Chi-Chang Chen, Jyh-Wen Chai
The differences of indices in diffusion tensor images (DTI) of patients with dementia are well-discussed in recent years. However, the comorbidity of dementia and depression was observed. In this study, we focused on the white matter changes associated with depressive symptoms in dementia and the relationship between DTI indices and cognitive functions in depressed and non-depressed patients. By an ROI-based analysis of the indices and TBSS analysis in DTI, we investigated the differences between patients of dementia with depression and without depression. Furthermore, we correlate the differences with the score of some clinical cognitive test to figure out the subtle differences.


Myocardium Tissue DTI with Stimulated Echo at Large Susceptibility Induced B0 gradients: Examination of the Shimming Strategies Efficiency and Errors.
Maxim Terekhov, David Lohr, Laura Schreiber
 In this paper, we investigated experimentally and statistically the effect of distortions of myocardium DTI with STEAM-EPI due to susceptibility induced gradients varied in a range of factor 10 to 20 to the reference. The special focus was given to examining the effect of prolonged EPI-readout, B0-shimming effect and motion-induced shimming errors relevant for high-resolution DTI in-vivo. Fresh ex-vivo pig hearts were used for DTI measurements with an in-house developed STEAM-EPI sequence. The distribution of diffusion directions components was found well preserved for prolonged readout even at high internal gradient.  


Validating Particle Dynamics in Monte Carlo Diffusion Simulation using the Finite Element Method
Jonathan Rafael-Patiño, Alonso Ramirez-Manzanares, Joaquin Peña, Hui Zhang
Monte-Carlo Diffusion Simulation (MCDS) is commonly used to develop and validate analytical models for quantifying tissue microstructure using diffusion MRI.  However, the validation of the tools implementing MCDS has been limited, especially for complex domains, such as the extra-cellular space of brain tissue.  To address this challenge, we propose a novel framework using the Finite Element Method (FEM), an established method for solving the diffusion equation with complex domains, to provide the ground-truth to assess MCDS.  We demonstrate the framework by assessing how the accuracy of MCDS is influenced by the number of particles and the number of diffusion steps.


Distortion free whole-body diffusion weighted imaging using a self-adaptive post deformation algorithm
Lizhi Xie, Bo Hou, Zhenyu Zhou
Conventional Whole-Body DWI that consists of several sequential stations often troubled geometric distortions and signal drops in areas with strong susceptibility, such as the neck and lumbar vertebra. The aim of this study was to propose a new WBDWI protocol and post process deformation algorithm to get distortion free whole body images. Consistently good results were received and in helps to diagnose several cases of tumors that were previously unclear to the volunteers and patients.


A longitudinal follow-up study of levator ani muscle injury during vaginal delivery using diffusion tensor imaging
yujiao zhao, zhizheng zhuo, wen shen
Levator ani muscle (LAM) injury has been known to be highly associated with vaginal delivery, the natural recovery course of injured LAM is unclear recurrently. Diffusion tensor imaging (DTI) with fiber tracking is a useful noninvasive MRI technique, which can be used to assess pelvic floor muscles injury and recovery quantitatively, and the fiber tract can display the direction and thickness of LAM fibers. In this study, we tried to apply DTI imaging to explore the natural recovery course of LAM injury during vaginal delivery. And the results showed that the injured LAM during vaginal delivery has some degree of repair as time goes on. 


Shortening acquisition time and increasing resolution to (1 mm)³ isotropic in 7T diffusion MRI (dMRI) still allows resolving fiber orientations and fiber crossings: a step towards clinical applications?
Ralf Lützkendorf, Robin Heidemann, Sebastian Baecke, Michael Luchtmann, Jörg Stadler, Thorsten Feiweier, Jörn Kaufmann, Johannes Bernarding
Prior results in single-shot diffusion weighted EPI indicated that voxel sizes below (1.4mm)3 prohibit reliable resolution of fiber orientations and fiber crossings. Here we compare zoomed single-shot EPI with (1mm)³ isotropic resolution with readout-segmented EPI with (1.4mm)³ and (1.0mm)³ isotropic at ultra-high field strength of 7 Tesla.  In all cases, fiber density orientation maps could be determined reliably thus enabling a resolution of main fiber directions and crossings even at (1mm)³ resolution.


Applied Research of Diffusion Tensor Imaging in traumatic tibial nerve injury
Xiaojuan Wang, Chen Zhao, Kening Xu, Lizhi Xie
DTI plays an important role in detecting nerve injury. It offers a great opportunity for imaging the tibial nerve injury follow trauma.In this work, we demonstrated DTI combined with DTT can clearly review the  morphological transformation of Nerve fiber after tibial nerve injured; quantitatively analyze the damage degree,which can provide detailed information for clinical treatment.


Comparaison of in vivo and ex vivo high resolution imaging of the mouse brain at 11.7T
Sophie Sébille, Isaac Adanyeguh, Elise Marsan, Sirenia Mondragon-Gonzalez, Fatma Gargouri, Mathieu Santin
This study compares high resolution in vivo and ex vivo diffusion imaging of mouse brain at 11.7T. The study shows that even with the advancement in image sequences and equipment, ex vivo imaging remains superior to in vivo imaging in terms of resolution with clear delineation of brain structures. However, fractional anisotropy values obtained from ex vivo imaging may not be a true representation of the in vivo condition. Nonetheless, the resolution obtained from in vivo imaging should allow for longitudinal studies.


Scan time reduction in DWI of the pancreas using simultaneous multislice technique with different acceleration factors: how fast can we go?
Jana Taron, Petros Martirosian, Thomas Kuestner, Mike Notohamiprodjo, Jakob Weiss, Ahmed Othman, Konstantin Nikolaou, Christina Schraml
We investigated the feasibility of simultaneous multislice-accelerated diffusion-weighted imaging of the pancreas using an acceleration factor of 2 and 3 (sms2/sms3-DWI) and its influence on image quality, acquisition time and apparent diffusion coefficients in comparison to conventional sequences (c-DWI) in ten healthy volunteers and 20 patients at 1.5 T. Images recorded with sms2-DWI offered high quality with a scan time reduction to one third; sms3-DWI showed significantly poorer overall image quality. In conclusion, sms2-DWI is feasible in clinical routine providing high image quality and a substantial reduction of acquisition time, whereas the use of higher acceleration factors is currently not recommended.


Robustness of kurtosis acquisition via simultaneous multi-slice EPI: a test-retest in children
Antonio Napolitano, Chiara Carducci, Laura Filograna, Vittorio Cannatà, Giovanna Stefania Colafati
Diffusion kurtosis imaging is an emerging technique based on non-gaussian diffusion of water in biologic systems and provides complementary information to the traditional diffusion. Although the method is very promising in identifying new biomarkers, it suffers from long time acquisition, which is very challenging in . However, a recent technique, named simultaneous multi-slice (SMS) acquisition, allows multiple slices acquisition thus drastically reducing the acquisition time. The purpose of this work is then to study the robustness of diffusion kurtosis in children when acquired via sms method.


Mental training effects on adolescent brain networks
Olga Tymofiyeva, Eva Henje Blom, Justin Yuan, Colm Connolly, Tiffany Ho, Lisa Baldini, Trevor Flynn, Matthew Sacchet, Kaja LeWinn, Rebecca Dumont Walter, Tony Yang, Duan Xu
In this study we used diffusion MRI network analyses to examine the effects of a 12-week training of attention and emotion regulation. Our preliminary results in 24 healthy adolescents demonstrate an improvement of executive attention and an increase of the node strength of the left anterior cingulate cortex.


Analytical Solutions of Bloch NMR Flow Equations: Emerging and Future Diffusion Magnetic Resonance Imaging
Bamidele Awojoyogbe, Michael Dada
Diffusion imaging has proved to be very important in clinical diagnosis and its exclusive application to numerous medical problems is currently plagued with some limitations which is most pronounced in heterogeneous voxels. In order to address this problem, we have presented an analytical method with which diffusion MR signals can be evaluated from point to point within a voxel of interest. The proposed method is shown to be useful in brain tumor diagnosis and general computational tissue imaging. The interesting part of this method is that only few data are required for image reconstruction.


Diffusion Tensor Imaging of human muscle at ultra-high-field (7T) MR.
Chiara Giraudo, Stanislav Motyka, Christoph Resinger, Thorsten Feiweier, Siegfried Trattnig, Wolfgang Bogner
Ultra-high-field (7T) imaging already demonstrated to provide more robust DTI measurements in comparison to 1.5 and 3T in the brain but, to the best of our knowledge, it was not applied for DTI measurements on human muscles. Our results showed higher SNR as well as an overall improvement in DTI metrics for the entire calf muscle at 7T than at 3T. Single muscle analyses (gastrocnemii, tibialis anterior) demonstrated more heterogeneous results. Future studies including a larger population and considering technical challenges (e.g.,RF inhomogeneity, gradient performance) are necessary to assess if 7T may provide higher benefits in specific muscles.


Effect of Velocity-compensated Diffusion Preparation for Spinal Cord Diffusion Imaging
Zhe Zhang, Xiaodong Ma, Chun Yuan, Hua Guo
The spinal cord and surrounding cerebrospinal fluid undergo significant cardiac pulsations, which can influence the microscopic motion-sensitive diffusion preparation and cause signal void in the diffusion images. In this work, velocity-compensated diffusion-encoding gradient waveform was implemented in spinal cord diffusion imaging and the images are compared with traditional monopolar preparation and cardiac gating approaches. Results show that with velocity-compensated diffusion preparation, the spinal cord diffusion imaging shows fewer signal voids compared to the traditional monopolar diffusion preparation. Using velocity-compensated diffusion preparation without cardiac triggering can provide a new approach for spinal cord diffusion imaging.


The diffusion kurtosis imaging findings of preoperative glioma-related epilepsy
Ankang GAO, Jingliang Cheng, Jie Bai, Yong Zhang, Shujian Li, Zanxia Zhang, Yijie Zhang, Xiao Cheng, Shaoyu Wang
MK not only reflects the microstructure of the glioma, but also may reflect neurotransmitter metabolism microenvironment.


Diffusion Entropy of Fractional Anisotropy Values in White Matter in Mild Traumatic Brain Injury
Alexander Weber, Michael Jarrett, Shiroy Dadachanji, David Li, Jack Taunton, Alexander Rauscher
A paper in Radiology by Delic et al. in 2016 looked at the Shannon entropy of fractional anisotropy values in white matter in the brains of people with mTBI and controls, and found significant differences between the two. We attempted to replicate their findings with retrospective mTBI data of our own. We did not find any significant differences with controls, and ice hockey athletes concussed after two weeks. We also did not find any changes in concussed athletes comparing data before injury with data after 3 days, 2 weeks, and 2 months.


Exploring Cortical Fiber Crossings in Mice using Diffusional Kurtosis Imaging
Emilie McKinnon, Jens Jensen, G Glenn, Andy Shih, Joseph Helpern
The ability of diffusional kurtosis imaging (DKI) to detect multiple intravoxel fiber directions in vivo is demonstrated for mouse cortex, with two or more directions being detected in the majority of voxels. The distribution of angular differences between the different fiber directions for individual voxels peaked at near 90o, suggestive of a grid-like pattern of neurites. Our findings support the feasibility of DKI-based tractography in mouse cortex. 


A Study on Total-Variation Regularization for Model-Based Reconstruction in DTI
Kazem Hashemizadeh, Samer Merchant, Dong Liang, Rong-Rong Chen, Edward Dibella, Edward Hsu, Leslie Ying
In this work, we study total-variation (TV) regularization for model-based reconstruction from undersampled DTI data. Various TV regularization methods are examined. Using ex-vivo brain DTI data, we show that imposing TV constraints on DWI provide more reliable quantitative estimates of diffusion than those imposing TV constraints directly on the tensor. A gradient descent algorithm with line backtracking is used for  better convergence to optimal solution. For highly undersampled data of 12 diffusion encoding directions and a reduction factor of R=4, we show that good estimates of primary eigen-vector, fractional anisotropy, and mean diffusivity can still be obtained using TV-based regularization.


Repeatability of apparent diffusion coefficient and intravoxel incoherent motion parameters at 3.0 Tesla in orbital masses.
Augustin Lecler, Julien Savatovsky, Laure Fournier
-          IVIM technique is feasible in the orbit with a good to acceptable repeatability of ADC and D. (coefficient of variation range 12%-25%) -          Interobserver repeatability agreement is excellent for all the IVIM parameters in the orbit. (intraclass correlation coefficient range 90-95%) -          The use of PF or D* as biomarkers should be cautious because of high test-retest and interobserver variabilities.


Functional Assessment of Lumbar Nerve Roots Using Direct Coronal Single-Shot Turbo Spin-Echo Diffusion Tensor Imaging    - Application to Patients with Bilateral Spinal Canal Stenosis Showing Unilateral Neurological Symptom -
Takayuki Sakai, Masami Yoneyama, Yasuchika Aoki, Toshiaki Miyati, Noriyuki Yanagawa
Clinically, there are some patients with spinal canal stenosis who have unilateral neurological symptom despite the existence of bilateral nerve compression on the conventional MRI images.  The purpose of this study was to investigate the availability of TSE-DTI for patients with bilateral spinal canal stenosis who have unilateral neurological symptom.  At the level responsible for symptom, the average FA values of symptomatic side were significantly lower than those of asymptomatic side.  FA values of TSE-DTI might be helpful in identification of responsible lumbar nerves roots for patients with bilateral spinal canal stenosis who have unilateral neurological symptom.


Investigation of Diffusion Tensor Indices by TBSS analysis and of Patients with symptoms of neuropsychiatric systemic lupus erythematosus
In this project, we attempted to study the NPSLE subjects without abnormal lesion in conventional MR imaging in order to investigate the effective imaging biomarkers in early detection of neurological degeneration. Brain diffusion-tensor imaging with TBSS analysis was performed for studying the micro-structural alternations in NPSLE patients. The preliminary results illustrated statistically significant differences of FA and MD in some important nerve tracts between NPSLE patients and normal volunteers. There also existed a significant difference between NPSLE patients with and without depression.


Age Related Diffusion and Tractography Changes in Typically Developing Pediatric Cervical and Thoracic Spinal Cord
Mahdi Alizadeh, Yusra Sultan, Sona Saksena, Chris Conklin, Devon Middleton, Joshua Fisher, Laura Krisa, Scott Faro, MJ Mulcahey, Feroze Mohamed
This study investigates age related changes in diffusion tensor imaging and tractography parameters in pediatric spinal cord. This will help to understand maturation process in pediatric population and consequently will help for detection of diseased or injured spinal cord. 


Observing the evolution of MS plaques using SWI and DCS-PWI
Liang Han, Lemei Tang, Weiwei Wang, Qingwei Song, Ailian Liu, Yanwei Miao, Bing Wu
In this study,we aim to study the morphologic and micro-hemodynamic changes of MS plaques using SWI and DSC-PWI. We selected twenty-one MS patients diagnosed by the McDonald criteria (Revised Edition 2010) underwent MR scans including SWI and dynamical susceptibility contrasted MR perfusion weighted imaging (DSC-PWI) at baseline. Then Results were obtained by follow-up and scan. The MS plaques shows decreased phase value and blood perfusion. The characteristic of MS plaque is hypointense foci with small veins and only “abnormal vessels” region predict early changes.


The influence of rat strain on multi-parametric white matter metrics – a Tractometry study
Daniel Barazany, Debbie Anaby, Derek Jones
White ­­matter macrostructural organization and its microstructural  composition are two complementary features that may help understand intact brain development, function and brain impairment. The Tractometry framework, which aims to characterise white matter by multi parametric MR metrics, was applied on 3 rat strains (Wistar, SD and Lewis). In this study we examined the impact of rat strain on microstructural features of white matter in the brain, which is suspected to origin from their genetics background.


Targeted-FOV DWI can better depict the microemboli-induced renal lesions comparing to conventional full-FOV DWI
Chengyan Wang, Li Jiang, Hanjing Kong, Fei Gao, Wenjian Huang, Rui Wang, Lian Ding, Yan Jia, Hui Xu, He Wang, Xiaodong Zhang, Li Yang, Jue Zhang, Xiaoying Wang, Jing Fang
DWI suffers from problems of severe geometric distortion and artifacts due to the susceptibility gradients and long echo train length (ETL), and the spatial resolution is quite limited due to the single-shot EPI acquisition scheme. This study investigates the utility of a targeted-FOV (TFOV) DWI technique in characterizing acute renal injure caused by microemboli injection in animal models. Compared with full-FOV DWI, the TFOV DW images show apparently higher image quality and better depiction of renal lesions. The advantage of TFOV DWI technique in characterizing microemboli-induced acute renal injure in is quite obvious. 


Diffusion MRI and magnetic resonance spectroscopy reveal microstructural and functional alteration in chronic mild stress exposed rat brains: A CMS recovery study
Ahmad Khan, Brian Hansen, Ove Wiborg, Christopher Kroenke, Sune Jespersen
Chronic mild stress (CMS) exposure leads to depression and other psychiatric disorder. Temporal changes post CMS exposure is still unclear. Present study employed CMS exposure on rats and utilised in-vivo longitudinal diffusion MRI and magnetic resonance spectroscopy (MRS) to reveal microstructural and functional alterations up to eight weeks post CMS exposure. Advanced diffusion kurtosis metrics have revealed significant alteration in stress sensitive regions, such as amygdala, hippocampus, prefrontal cortex and caudate putamen. MRS also showed significant metabolic alteration in ventral hippocampus, particularly on week1 post CMS exposure. Present finding could be useful in treatment of depression or similar disorders.


Diffusion-weighted images super resolution via external and internal patch-based regularization
ying fu, xi wu, yangzhi peng, jiliu zhou
Super-resolution (SR) of diffusion weighted imaging (DWI) data is an ill-posed problem, which can be regularized by exploiting diverse priors learned from image patches. In this work, based on patch-based strategy of SR, we propose a new regularization method to reconstruct DW images, which integrates the sparse representation prior with dictionary learned from external image patches and non-local self-similarity prior learned from internal image patches. Meanwhile, in dictionary learning part, nonparametric Bayesian method is adopted to infer dictionary learning variables such as the size of the dictionary from data automatically. Experimental results demonstrate that the proposed method outperforms current methods in DWI reconstruction.


Changes of intravoxel incoherent motion (IVIM) diffusion-weighted imaging based parameters in patients undergoing transjugular intrahepatic portosystemic shunt (TIPS) creation – An initial analysis
Claus Pieper, Alois Sprinkart, Daniel Thomas, Carsten Meyer, Wolfgang Block, Hans Schild, Guido Kukuk, Petra Mürtz
The creation of a transjugular intrahepatic portosystemic shunt (TIPS) influences hepatic blood flow dynamics. TIPS-related changes of diffusion-weighted imaging based intravoxel incoherent motion (IVIM) parameters at 1.5 T were investigated in liver parenchyma of cirrhotic patients. An increase of the IVIM perfusion fraction was found, indicating improved microvascular flow within the liver tissue after decompression of the portal vein. Diffusion parameters were not significantly influenced by TIPS-creation.


White matter abnormalities of brain and cervical spinal cord in Hepatic Myelopathy patients: a diffusion tensor imaging study
Liu-Xian Wang, Lin Liu, Kang Liu, Ning-Bo Fei, Long-Biao Cui, Yi-Bin Xi, Ting-Ting Liu, Wei Qin, Hong Yin
The prominent syndrome of HM such as spastic paraparesis is usually considered resulting from abnormal function of thoracic segments, nevertheless, the involvement of intracranial fibers and cervical spinal cord is not clear. In this study, we found a widespread and robust white matter tract abnormality in brain of HM and non-HM patients, without significant difference with cervical spinal cord. Our finding may help shedding light on the underlying pathological mechanism of HM.


Signal behavior of Ultra-High-b radial DWI (UHb-rDWI) signal in different tract of the cervical spinal cord
Bijaya Thapa, Nabraj Sapkota, YouJung Lee, EunJu Kim, John Rose, Lubdha Shah, Eun-Kee Jeong
The ultrahigh-b radial DWI (UHb-rDWI) technique is used to study the white matter disease in the spinal cord. The diffusion signal from the extra axonal (EA) space drops to noise level while that from the intra axonal (IA) space is almost constant at UHb region for the myelinated axons where the myelin layers prohibit the exchange of water molecules between IA and EA spaces. However for partially or unmyelinated axons, the diffusion signal from IA space is no longer constant. The signal behavior at UHb region could be used as a biomarker for the demyelination and axonal loss.  

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