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

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

Diffusion: Biophysical Modeling & Microstructure
Diffusion

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

 1730 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. 1731 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. 1759 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. 1732 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. 1733 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. 1734 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. 1735 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. 1736 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. 1737 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. 1738 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. 1739 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 https://github.com/cbclab. 1740 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. 1741 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. 1742 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. 1743 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. 1744 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. 1745 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. 1746 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. 1747 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. 1748 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. 1749 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. 1750 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. 1751 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. 1752 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 (mriferretatlas.nichd.nih.gov). 1753 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. 1754 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. 1755 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. 1756 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. 1757 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. 1758 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. 1760 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. 1761 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. 1762 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. 1763 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. 1764 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. 1765 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. 1766 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. 1767 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. 1768 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. 1769 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. 1770 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. 1771 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. 1772 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. 1773 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. 1774 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. 1775 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. 1776 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
Diffusion

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

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