ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore Traditional Poster Session: Diffusion
 1991 Anna Auria1, David Romascano1, Erick J. Canales-Rodriguez2, Tim B. Dyrby3, Daniel C. Alexander4, Jean-Philippe Thiran1,5, Yves Wiaux6, and Alessandro Daducci1,5 1LTS5, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland, 2Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Barcelona, Spain, 3Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 4Department of Computer Science and Centre for Medical Image Computing, University College London, London, United Kingdom,5University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 6Institute of Sensors, Signals, and Systems, Heriot-Watt University, Edimburgh, United Kingdom State-of-the-art microstructure imaging methods usually fit biophysical models to the diffusion MRI data on a voxel-by-voxel basis using non-linear procedures that require both long acquisitions and processing time. We recently introduced AMICO, a framework to reformulate these techniques as efficient linear problems and enable faster reconstructions. Here, we propose an extension that enables robust reconstructions from a reduced number of diffusion measurements, thus leading to faster acquisitions, too. Our novel formulation estimates simultaneously the microstructure configuration in all voxels as a global optimization problem, exploiting information from neighboring voxels that cannot be taken into account with existing techniques. 1992 Yasar Goedecke1 and Jürgen Finsterbusch1 1Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany Double-diffusion-encoding (DDE) or double-wave-vector (DWV) experiments show a signal behavior that is specific for restricted diffusion. Thus, these experiments could provide more direct insight into tissue microstructure than conventional experiments, especially when targeting axon diameters. In this study, a previous DDE-based approach to estimate axon diameters is extended (i) to be applicable without prior knowledge of the fiber orientation, (ii) by considering a more complex tissue composition including spherical cells and an unrestricted compartment to model glial cells and extracellular space, and (iii) using the multiple correlation function framework that provides a more accurate approximation of the MR signal. 1993 Yasar Goedecke1 and Jürgen Finsterbusch1 1Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany In a conventional diffusion-weighted MRI experiment, the signal amplitude depends on the squared magnitude of the Fourier transformation of the pore or cell geometry, i.e. the underlying cell or pore geometry cannot be reconstructed. Several approaches have been proposed that determine the otherwise missing phase information and, thus, can image the pore or cell geometry directly. Here, the performance of these methods is compared with respect to their applicability in practice, e.g. considering the impact of the noise level, mixtures of pore sizes, orientations, and shapes, and gradient pulse durations and diffusion times achievable on standard MRI systems. 1994 Michiel Kleinnijenhuis1, Jeroen Mollink1, Errin E Johnson2, Vitaly L Galinsky3, Lawrence R Frank3, Saad Jbabdi1, and Karla L Miller1 1Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom, 2Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom, 3Center for Scientific Computation in Imaging, University of California San Diego, La Jolla, CA, United States The cylindrical models often used in Monte Carlo diffusion simulations do not resemble the shape of axons very well. In this work, a more realistic substrate derived from electron microscopy data is used to investigate the influence of axon shape and myelination on the diffusion signal. In the DifSim simulation environment, diffusion signals from EM-derived substrates are compared to those from cylindrical substrates matched for volume fraction. Furthermore, the effect of removing the impermeable myelin sheath from the substrate is assessed. 1995 Sisi Liang1, Madiha Yunus2, Eleftheria Panagiotaki 3, Byung Kim4, Timothy Stait-Gardner5, Mikhail Zubkov5, Brian Hawkett4, William Price5, Carl Power6, and Roger Bourne2 1College of Engineering and Science, Victoria University, Melbourne, Australia, 2Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, Australia, 3Center for Medical Image Computing, University College London, London, United Kingdom, 4Key Centre For Polymer Colloids, University of Sydney, Sydney, Australia, 5Nanoscale Organisation and Dynamics Group, School of Science and Health, Western Sydney University, Sydney, Australia, 6Mark Wainright Analytical Centre, The university of New South Wales, Sydney, Australia Cultured epithelial cell spheroids demonstrate many of the physiological properties of glandular epithelia and provide an ideal experimental model for investigation of the distinctive structural properties that may contribute to the reported low water mobility in prostate, breast, and gut epithelia. The structural connections are very similar to those in intact tissue and thus they provide a more realistic model of tissue than previously investigated models based on pelleted yeast or erythrocyte cells. We report an investigation of the correlation between known cell sizes in a spheroid culture and restriction radius estimated by a model of diffusion MRI signals. 1996 Dan Wu1, Frances J Northington2, and Jiangyang Zhang1,3 1Radiology, Johns Hopkins University School of Medicine, BALTIMORE, MD, United States, 2Pediatrics, Johns Hopkins University School of Medicine, BALTIMORE, MD, United States, 3Radiology, New York University School of Medicine, New Yourk, NY, United States The dispersion profile of the temporal diffusion spectrum has been linked to key properties of tissue microstructures, however, its directional variance has not been shown. In this study, we extended the conventional one-dimensional dispersion profile to three-dimensional profile, and characterized its directionality with a tensor representation. The temporal diffusion dispersion (TDD) tensor demonstrated unique contrasts that reflected distinct microstructural organization in the mouse brain, and the high anisotropy from TDD tensors correlated with anisotropic structural arrangements, e.g., in the crossing fiber regions. The TDD contrasts are also sensitive to disrupted microstructures in a neonatal mouse model of hypoxic-ischemic injury. 1997 Tina Jeon1, Aristeidis Sotiras2, Minhui Ouyang1, Min Chen3, Lina Chalak4, Christos Davatzikos2, and Hao Huang1,5 1Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States, 2Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, United States,3Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX, United States, 4Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, United States, 5Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States From early 3rd trimester to around birth, the cerebral cortex undergoes dramatic microstructural changes including dendritic arborization that disrupts the radial scaffold, a well-organized columnar organization. Decrease of cortical fractional anisotropy (FA) derived from DTI has been well documented. In this study, we hypothesized that non-Gaussian water diffusion properties (e.g. mean kurtosis or MK) from diffusion kurtosis imaging (DKI) offers unique and complementary information on cortical microstructural changes during this period. The spatiotemporal changes and patterns of cortical FA and MK from 32 to 41 postmenstrual weeks were revealed, demonstrating unique cortical MK maps and clustering patterns during preterm development. 1998 Silvia De Santis1, Yaniv Assaf2, and Derek Jones1 1Cardiff University, CUBRIC, Cardiff, United Kingdom, 2Department of Neurobiology, Tel Aviv University, Tel Aviv, Israel With the increasing popularity of multi-shell diffusion techniques to measure axonal density and diameter, the investigation of the exact origin of the contrast has become a hot topic. Here, we investigate the impact of the echo time in measuring the axonal density and show that the two water compartments are characterised by a different relaxation time T2, making the measures of the volume strongly dependent on the echo time. This suggests caution when comparing data acquired with different setups and introduces a new way of measuring the differential T2 properties of intra- and extra-axonal water pools. 1999 Marco Reisert1, Elias Kellner1, Bibek Dhital1, Jürgen Hennig1, and Valerij G. Kiselev1 1Department of Radiology, Medical Physics, University Medical Center Freiburg, Freiburg, Germany Diffusion-sensitized MRI probes the cellular structure of the human brain, but the primary microstructural information gets lost  in averaging over higher-level, mesoscopic tissue organization such as different orientations of neuronal fibers. While such averaging is inevitable due to the limited imaging resolution, we propose a method for disentangling the microscopic cell properties from the effects of mesoscopic structure. The proposed method finds detectable parameters of a given microstructural model and calculates them within seconds, which makes it suitable for a broad range of applications. 2000 Sjoerd B Vos1,2, Andrew Melbourne1, John S Duncan2,3, and Sebastien Ourselin1 1Translational Imaging Group, University College London, London, United Kingdom, 2MRI Unit, Epilepsy Society, Chalfont St Peter, United Kingdom, 3Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom Intracellular volume fraction (ICVF) is a valuable biomarker of neurological disease. As one of two factors in g-ratio estimates it could potentially reveal axonal function from structural MRI measurements. Reliable ICVF estimation is critical for both purposes. With various diffusion models in existence for ICVF estimation, we compared the obtained ICVF values and their reproducibility in voxels with 1, 2, and 3 fibre populations between three diffusion modelling approaches. Absolute ICVF values vary significantly between models as well as between voxels with different fibre complexity. 2001 Marco Palombo1,2, Clémence Ligneul1,2, and Julien Valette1,2 1CEA/DSV/I2BM/MIRCen, Fontenay-aux-Roses, France, 2CNRS Université Paris-Saclay UMR 9199, Fontenay-aux-Roses, France We investigate how metabolite diffusion measured up to very high b (60 ms/µm2) at relatively short diffusion time (63.2 ms) in the mouse brain can be explained in terms of simple geometries. We model cell fibers as isotropically oriented cylinders of infinite length, and show this can account very well for measured non-monoexponential attenuation. The only exception is NAA, for which the model extracts fiber diameter equal to 0. We show that is theoretically and experimentally compatible with a small fraction of the NAA pool being confined in highly restricted compartments (with short T2), e.g. a mitochondrial pool. 2002 Tara Ganepola1,2, Jiaying Zhang2, Hui Zhang2, Martin I Sereno3, and Daniel C Alexander2 1Department of Cognitive, Perceptual and Brain Sciences, University College London, London, United Kingdom, 2Centre for Medical Image Computing, University College London, London, United Kingdom, 3Birkbeck-UCL Centre for Neuroimaging, University College London, London, United Kingdom In the following work several diffusion based feature vectors (DTI, NODDI, spherical harmonic (SH) invariants and fourth order tensor invariants (T4)) are compared in order to validate their usability in grey matter investigations. It was found that using multi-shell data and non-biophysical models such as SH and T4 achieves the highest classification accuracy between the primary motor and somatosensory cortical areas, and thus is likely to characterise grey matter tissues domains more effectively. 2003 Farshid Sepehrband1 and Kristi A Clark1 1Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States Recent diffusion-weighted imaging techniques have enabled the inference of axon diameter, a valuable neuroanatomical measure1,2. Current techniques fit a cylindrical model of axons to the acquired signal, primarily in the transverse direction. Despite many improvements, sensitivity to small axons is difficult to achieve, primarily due to the scanner’s physical limitations. Even with a strong gradient strength system such as the connectome scanner and high SNR, the minimum resolvable axon diameters are greater than 2μm, which accounts for only a small proportion of axons in the human brain. Here we utilize Neuman’s cylindrical model3, and generalize it to the geocentric direction in the longitudinal plane of axons (Figure 1) to decrease the minimum axon diameter resolvable with a given scanner. 2004 Tom A Roberts1, Giulia Agliardi1, Andrada Ianus2, Ben Jordan1, James O Breen-Norris1, Rajiv Ramasawmy1, Angela D'Esposito1, Valerie Taylor1, Bernard Siow1, Eleftheria Panagiotaki2, Daniel C Alexander2, Mark F Lythgoe1, and Simon Walker-Samuel1 1Centre for Advanced Biomedical Imaging, London, United Kingdom, 2Centre for Medical Image Computing, London, United Kingdom Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT) is a diffusion MRI technique which uses a 3-compartment model to characterise the vascular (V), extracellular-extravascular (EES) and intracellular (IC) compartments in tumours. VERDICT allows for quantitation of tumour morphology including vascular fraction (fv), intracellular fraction (fic) and cellular radius, hence providing a non-invasive ‘biopsy’ that can be performed longitudinally. Previously, VERDICT has been applied to subcutaneous mouse tumours1 and human prostate cancer2. For the first time, we apply VERDICT in a mouse model of glioma, examine it in the context of other multi-compartment models and optimise it based on comparison with histological analysis. 2005 Leandro Beltrachini1 and Alejandro Frangi1 1The University of Sheffield, Sheffield, United Kingdom In silico studies of diffusion MRI are becoming a standard tool for testing the sensitivity of the technique to changes in white matter (WM) structures. To perform such simulations, realistic models of brain tissue microstructure are needed. However, most of the computational results are obtained considering straight and parallel cylinders models, which are known to be too simplistic for representing real-scenario situations. We present a statistical-driven approach for obtaining random models of WM tissue samples based on histomorphometric data available in the literature. We show the versatility of the method for characterising WM voxels representing bundles and disordered structures. 2006 Kevin D Harkins1 and Mark D Does1,2,3,4 1Institute of Image Science, Vanderbilt University, Nashville, TN, United States, 2Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, 3Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States, 4Electrical Engineering, Vanderbilt University, Nashville, TN, United States The presence and movement of myelin water is often neglected from models of DWI signal. This study presents a Monte Carlo simulation illustrating that myelin water diffusion can have a subtle but important impact on measured Dapp and Kapp values, and that incorporating myelin water diffusion can influence myelin-content dependent changes in Dapp and Kapp. 2007 Silvia De Santis1,2, Matteo Bastiani2, Henk Jansma2, Amgad Droby3, Pierre Kolber3, Eberhard Pracht4, Tony Stoecker4, Frauke Zipp3, and Alard Roebroeck2 1Cardiff University, CUBRIC, Cardiff, United Kingdom, 2Dept. of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, Maastricht, Netherlands, 3Department of Neurology and Neuromaging Center, University Medical Center of the Johannes Gutenberg University, Mainz, Germany, 4German Center for Neurodegenerative diseases, Bonn, Germany Aim of this work was to test the ability of conventional (i.e., DTI) and advanced (i.e., CHARMED, stretched exponential) diffusion methods to differentiate between Multiple Sclerosis lesions, normal appearing white matter and healthy controls, at both 3T and 7T. Advanced dMRI at 7T gives the best discriminating power between MS lesions and healthy tissue across WM; DTI is appropriate in areas of low fiber dispersion like the corpus callosum. 2008 Jonathan Phillips1 1Institute of Life Science, College of Medicine, Swansea University, Swansea, United Kingdom This work aims at introducing methods of molecular dynamics (MD) simulation into diffusion MRI modelling. MD allows the study of transport properties (e.g. diffusion), structural properties (e.g. radial distribution functions) and thermodynamic properties (e.g. pressure). Access to all of these properties allows investigation into the links between them. We present the first steps into studying all of these properties (including the diffusion coefficient and kurtosis) in model systems for comparison with MRI data. The system is a binary mixture which includes a diffusing species (the solvent e.g. water) and a larger spatially-fixed species (modelling cellular-sized colloid particles). 2009 Francesco Grussu1, Torben Schneider1,2, Ferran Prados1,3, Carmen Tur1, Sébastien Ourselin3, Hui Zhang4, Daniel C. Alexander4, and Claudia Angela Michela Gandini Wheeler-Kingshott1,5 1NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London, United Kingdom, 2Philips Healthcare, Guildford, Surrey, England, United Kingdom, 3Translational Imaging Group, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 4Department of Computer Science and Centre for Medical Image Computing, University College London, London, United Kingdom, 5Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy Diffusion MRI-derived neurite density is a potential biomarker in neurological conditions. In the brain, neurites are commonly modelled as sticks for sufficiently long diffusion times and gradient durations. However, in the spinal cord, large axons are present and typical diffusion times (20-30 ms) may not be sufficiently long to support this model. We investigate via simulations and in vivo whether neurite density estimation is affected by the diffusion time in the spinal cord. Short diffusion times lead to bias, while long diffusion times improve accuracy but reduce precision. Therefore, a trade-off accuracy-precision needs to be evaluated depending on the application. 2010 Takayuki Obata1, Jeff Kershaw2, Yasuhiko Tachibana1, Youichiro Abe3, Sayaka Shibata2, Yoko Ikoma2, Hiroshi Kawaguchi4, Ichio Aoki2, and Masato Yasui3 1Applied MRI Research, National Institute of Radiological Sciences, Chiba, Japan, 2Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, Japan, 3Department of Pharmacology, Keio University, Tokyo, Japan, 4Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan We performed multi-b and multi-diffusion-time DWI on aquaporin-4-expressing and non-expressing cells, and demonstrated a clear difference between the signals from the two cell types. The data was interpreted with a two-compartment model including inter-compartmental exchange. It was also assumed that restricted diffusion of water molecules inside the cells leads to the intracellular diffusion coefficient being inversely proportional to the diffusion-time. Estimates of the water-exchange times with this model were comparable with those measured using an independent optical imaging technique, which suggests that this method might be used to characterize cell-membrane water permeability. As the technique can be applied in routine clinical examination, it has the potential to improve clinical diagnosis. 2011 Jonathan I Sperl1, Ek Tsoon Tan2, Miguel Molina Romero1,3, Marion I Menzel1, Chris J Hardy2, Luca Marinelli2, and Thomas K.F. Foo2 1GE Global Research, GARCHING, Germany, 2GE Global Research, NISKAYUNA, NY, United States, 3Institute of Medical Engineering, Technische Universität München, GARCHING, Germany The measurement of axonal diameter by diffusion MRI techniques has assumed major interest in the research community. While most work has focused on developing and comparing various multi-compartment models, only minor efforts have been undertaken to optimize corresponding acquisition protocols. In this work we perform simulations using a rather simple two-compartment model, but study the effect of various choices of acquisition parameters on the precision and the bias of the fitted parameters. More precisely, we analyze potential sampling strategies in the 2D design space spanned by the two timing parameters (Δ, δ) of the diffusion encoding. 2012 Ahmad Joman Alghamdi1,2, Hari K Ramachandran3, Ian M Brereton1, and Nyoman D Kurniawan1 1Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, 2College of Health Sciences, Taif University, Taif, Saudi Arabia, 3Computer Science and Engineering, SRM University, Kattankulathur, India DTI has been used to measure changes in spinal cord WM, but lacks the specificity in measuring changes in GM and axonal diameter. This study aims to apply NODDI and AxCaliber techniques to measure characteristics of the lumbar spine in C57BL/6 mice, in-vivo at 9.4T and ex-vivo at 16.4T. The GM orientation distribution index is 3 times that of the WM, and the correlation of ODI to FA is r=–0.9, P<<0.01 for GM and r=–0.56, P<<0.01 for WM. AxCaliber analysis determined WM axon diameter populations with an average of 1.55±0.15mm (in-vivo); and 1.37±0.20 mm (ex-vivo). 2013 Zach Eaton-Rosen1, Andrew Melbourne1, Joanne Beckmann2, Eliza Orasanu1, Nicola Stevens3, David Atkinson4, Neil Marlow2, and Sebastien Ourselin1 1TIG, UCL, London, United Kingdom, 2UCL EGA Institute for Women's Health, London, United Kingdom, 3UCLH, London, United Kingdom, 4CMIC, UCL, London, United Kingdom We used NODDI and DTI in order to investigate the differences in white matter between young adults born at term, and those born at fewer than 26 weeks completed gestation, using TBSS. The differences in FA were closely mirrored by the differences in orientation dispersion index (ODI) while the intra-axonal volume fraction (Vi) did not show significant differences in the same regions. This suggests that the ODI may be more sensitive to indicators of being born preterm than Vi in the white matter. 2014 Matthew R Orton1, Neil P Jerome1, Thorsten Feiweier2, Dow-Mu Koh3, Martin O Leach4, and David J Collins4 1Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom, 2Siemens Healthcare, Erlangen, Germany, 3Department of Radiology, Royal Marsden NHS Foundation Trust, London, United Kingdom, 4CRUK Cancer Imaging Centre, Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom The IVIM model is essentially a two-compartment model, and it has previously been noted that the T2 relaxation times in each compartment may not be equal.  This work uses the Akaike Information Criterion to compare two combined IVIM-T2 models using data acquired in various abdominal organs with all combinations of five echo-times and six b-values.  The first model has the same T2 in each compartment, the second has different T2s, and we show that the second model has greater statistical support in the liver (but not spleen or kidney), implying that both T2 values can be measured in this organ. 2015 Tomohiro Takamura1, Shou Murata2, Koji Kamagata3, Kouhei Tsuruta2, Masaaki Hori3, Michimasa Suzuki3, and Shigeki Aoki3 1University of Yamanashi, Yamanashi, Japan, 2Tokyo Metropolitan University, Tokyo, Japan, 3Juntendo University, Tokyo, Japan Recently, patients with neuromyelitis optica (NMO) have shown extensive white matter damage, which could be related not only to Wallerian degeneration resulting from lesions of spinal cord or optic tracts but also to demyelination by using diffusion-tensor (DT) MRI imaging. This study aimed to evaluate the expansion of white matter damage in NMO assessed using neurite orientation dispersion and density imaging (NODDI), as well as its relationship with disease severity by applying Tact Based Spatial Statistics (TBSS). 2016 Ganna Blazhenets1,2, Farida Grinberg1,3, Ezequiel Farrher1, Xiang Gao1, Mikheil Kelenjeridze4, Tamo Xechiashvili4, and N. Jon Shah1,3 1Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich, Juelich, Germany, 2Institute of Nuclear Physics, University of Cologne, Cologne, Germany, 3Department of Neurology, Faculty of Medicine, JARA, RWTH Aachen University, Aachen, Germany, 4Department of Physics, Georgian Technical University, Tbilisi, Georgia We compare the sensitivity and applicability of two methods for the estimation of mean kurtosis in a multi-sectional, anisotropic diffusion phantom using conventional diffusion kurtosis imaging and a fast protocol for rapid mean kurtosis metric estimation suggested by Hansen et al. (2013). Both methods provide similar image quality and it can be concluded that fast estimation of mean kurtosis is a useful tool that can be used as a fast method for clinical applications. An interesting finding of this work is a stronger dependence of fast computed kurtosis metrics on the orientation of fibres with respect to the static magnetic field than of the conventional method. 2017 Chia-Wen Chiang1, Shih-Yen Lin1,2, Yi-Ping Chao3, Yeun-Chung Chang4,5, Teh-Chen Wang6, and Li-Wei Kuo1 1Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 2Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan, 3Gradulate Institute of Medical Mechatronics, Chang Gang University, Taoyuan, Taiwan, 4Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan, 5Department of Radiology, National Taiwan University College of Medicine, Taipei, Taiwan, 6Department of Radiology, Taipei City Hospital Yang-Ming Branch, Taipei, Taiwan Diffusion kurtosis imaging (DKI), evaluating the non-Gaussianity of water diffusion, has been demonstrated to be sensitive biomarker in many neurological diseases. However, number of repetition is one of the factors, but people is trying less to investigate it. In this study, normal rats were performed using two different diffusion scheme protocols (15 b-values with six diffusion directions vs. 3 b-values with thirty directions) and with different repetitions. Our results suggesting the protocol with one repetition provides good image quality for DKI analysis in this case. 2018 Miao Sha1, Yuanyuan Chen1, Xin Zhao1, Man Sun2, Weiwei Wang1, Hongyan Ni2, and Dong Ming1 1Tianjin University, Tianjin, China, People's Republic of, 2Tianjin First Center Hospital, Tianjin, China, People's Republic of Diffusion kurtosis imaging is a powerful technique to measure the non-gaussion diffusion as well as the complicated microstructure. In this paper, we conducted a comparison between different acquisitions with different maximum b-value on normal volunteers. We found that the outcome of diffusion kurtosis imaging was influenced by the maximum b-value in the acquisition. And this influence was highly associated with the microstructure, including both radial profile and angular profile in the structure reconstruction, which indicated the mechanism of non-gaussion under high b-value. 2019 Robert J Loughnan1,2, Damien McHugh1,3, Hamied A Haroon1, Douglas Garratt2, Rishma Vidyasagar1,4, Hojjatollah Azadbakht1, Penny H Cristinacce1, Geoff JM Parker1,5, and Laura M Parkes1 1Centre for Imaging Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Manchester, United Kingdom, 2School of Physics and Astronomy, The University of Manchester, Manchester, United Kingdom, 3CRUK & EPSRC Cancer Imaging Centre in Cambridge & Manchester, Manchester, United Kingdom, 4Melbourne Brain Centre, The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia, 5Bioxydyn Limited, Manchester, United Kingdom Diffusion imaging has been used to probe microstructure and to investigate perfusion via the IVIM model. However, the contribution of microvasculature structure to the diffusion signal has largely been overlooked. Presented here is a novel method for imaging blood velocity and capillary segment length using diffusion-weighted images. We apply a model for extracting perfusion parameters from diffusion-weighted images from 23 people with a range of diffusion times (?=18, 35 and 55ms) and b-values (0-100s/mm2). Mean blood velocity was significantly slower (P<0.005) in white matter (0.92±0.03mm/s) compared to grey matter (0.95±0.04mm/s). Mean vessel segment length was significantly shorter (P<0.0001) in white matter (7.97±0.13µm) than in grey matter (10.35±0.20µm). 2020 Johannes Riegler1, Maj Hedehus1, and Richard A. D. Carano1 1Biomedical Imaging, Genentech, South San Francisco, CA, United States Inflammation and T-cell infiltration are important prognostic biomarkers for cancer immunotherapies.1 Current clinical practice relies on histological assessment of tissue biopsies which is invasive and prone to sampling errors. Temporal diffusion spectroscopy, particularly with short effective diffusion times can estimate cell sizes.2,3 Lymphocytes have small diameters compared to typical tumor cells. We therefore tested the ability of temporal diffusion spectroscopy to differentiate between pellets of tumor cells mixed with a varying amount of activated lymphocytes. We observed clearly separable diffusion characteristics for samples containing > 20% lymphocytes indicating that this approach may have potential to quantify inflammation in highly inflamed tissues. 2021 Hong-Hsi Lee1, Gregory Lemberskiy1, Els Fieremans1, and Dmitry S. Novikov1 1New York University, Center for Biomedical Imaging, New York, NY, United States Finite pulse duration $$\delta$$$of diffusion gradient has typically been a source of bias for quantifying microstructure. Here, we suggest to use the diffusivity dependence on $$\delta$$$ to reveal the correlation length of the fiber packing, an essential μm–level characteristic of microstructure, thereby turning the finite pulse duration to our advantage. We validate our method in a fiber phantom that mimics an axonal packing geometry, and the estimated correlation length matches the fiber radius. Future work will focus on the evaluation of its potential as biomarkers for in vivo brain scans, such as axonal density and outer axonal diameters. 2022 Weiwei Ruan1, Jianping Zhong1, Ke Wang2, Yeqing Han1, and Xin Zhou1 1Wuhan Institute of Physical and Mathematics,Chinese Academy of Sciences, Wuhan, China, People's Republic of, 2Department of MRI, zhongnan hospital of wuhan university, Wuhan, China, People's Republic of To detect the early emphysema, hyperpolarized xenon diffusion MRI with multi-b values was used to quantify the lung terminal airways in five initial stages of emphysematous rats and five control rats. The DL(longitudinal diffusion coefficient), r, h, LM and S/V in the emphysematous group showed significant differences compared to those in the control group (P<0.05) and also exhibited a strong linear correlation (|r|>0.8) to Lm from histology for all the rats. The results showed multi-b diffusion MRI of hyperpolarized xenon has potential for the diagnosis of emphysema at the early stage. 2023 Farshid Sepehrband1,2, Kieran O’Brien1,3, and Markus Barth1 1Centre for Advanced Imaging, University of Queensland, Brisbane, Australia, 2Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, United States, 3Siemens Healthcare Pty Ltd, Brisbane, Australia Several diffusion-weighted MRI techniques for modeling tissue microstructure have been developed and validated during the past two decades. While offering various neuroanatomical inferences, these techniques differ in their proposed optimal acquisition design, which impede clinicians and researchers to benefit from all potential inference methods, particularly when limited time is available. We examined the performance of the most common diffusion models with respect to acquisition parameters at 7T when limiting the acquisition time to about 10 minutes. The most balanced compromise among all combinations in terms of the robustness of the estimates was a two-shell scheme with b-values of 1,000 and 2,500 s/mm2 with 75 diffusion-encoding gradients, 25 and 50 samples for low and high b-values, respectively. 2024 Qiqi Tong1, Mu Lin1, Hongjian He1, Xu Yan2, Thorsten Feiweier3, Hui Liu2, and Jianhui Zhong1 1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China, People's Republic of, 2MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China, People's Republic of, 3Siemens Healthcare, Erlangen, Germany Multi-component diffusion models with each component of its own T2 value have been studied previously. When the diffusion signal is decomposed into three compartments (short, intermediate and long T2), the respective ADC values can be obtained. Our results from simulations and in vivo measurements show that the model successfully separates signal from different tissue types, allows extraction of tissue-specific ADC, and results are mostly free of partial volume problem. Moreover, an ADC without T2 effect can also be generated by combining the ADCs of all components. 2025 Eric Lessard1, Alexei Ouriadov1, David G McCormack2, and Grace Parraga1 1Robarts Research Institute, The University of Western Ontario, London, ON, Canada, 2Department of Medicine, The University of Western Ontario, London, ON, Canada Diffusion-weighted MRI provides a way to non-invasively estimate in vivo morphometry measurements of the alveolar ducts. Current modelling approaches may not be appropriate for cases of severe tissue destruction where the geometry of the acinar ducts may not be uniform, nor cylindrical.  Therefore, in this proof-of-concept evaluation, we used a single-compartment model and multiple b-value diffusion-weighted noble gas pulmonary MRI to generate estimates of acinar duct surface-to-volume ratio and mean-linear-intercept.  In cases of very severe emphysema that accompany alpha-one antitrypsin deficiency, this approach well-approximated the severity of lung disease, while the cylindrical model did not. 2026 Cheng-Ping Chien1, Feng Mao Chiu2, and Queenie Chan3 1Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, 2Philips Healthcare, Taipei, Taiwan, 3Philips Healthcare, Hong Kong, China, People's Republic of Intravoxel incoherent motion (IVIM) model is useful tool to observe the microcirculatory perfusion, but its stability still needs to be improved. We propose the envelope bounding technique to reduce the fluctuated signal at low b-value, and use this new signal profile to fit IVIM model. This improvement gives a more stable outcome with fast diffusion (D*) and perfusion fraction (PF). 2027 Luke J. Edwards1, Siawoosh Mohammadi1,2, Pierre-Louis Bazin3, Michiel Kleinnijenhuis4, Kerrin J. Pine1, Anne-Marie van Cappellen van Walsum5, Hui Zhang6, and Nikolaus Weiskopf1,3 1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, UCL, London, United Kingdom, 2Institut für Systemische Neurowissenschaften, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany,3Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 4FMRIB Centre, University of Oxford, Oxford, United Kingdom, 5Department of Anatomy, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, 6Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom The structure of neocortical grey matter is complex due to the crossing intracortical neuronal connections involved in cortical processing. Herein we present a two-step method to capture radial and tangential fibre structure of neocortex from diffusion data: first the radial cortical orientation is extracted voxelwise using surface-based methods, and then a three-compartment diffusion model extracts radial and tangential fibre volume fractions. We demonstrate in a post mortem sample of human V1 tissue that this method captures structure known from histology and comparable diffusion models, implying potential future use as a probe of intracortical neuronal connectivity. 2028 Narina Norddin1,2, Nyoman Kurniawan3, Gary Cowin3, Carl Power4, Geoffrey Watson5, Esther Myint6, Laurence Gluch7, and Roger Bourne1 1University of Sydney, Sydney, Australia, 2International Islamic University Malaysia, Pahang, Malaysia, 3University of Queensland, Brisbane, Australia, 4University of New South Wales, Sydney, Australia, 5Royal Prince Alfred Hospital, Sydney, Australia, 6Douglass Hanly Moir Pathology, Sydney, Australia, 7The Strathfield Breast Centre, Sydney, Australia Although diffusivity (ADC) changes in tissue are commonly attributed to variations in ‘cellularity’, direct evidence from breast tissue studies is limited and inconsistent. Here we report a diffusion microimaging and histology investigation of the correlation of mean diffusivity (MD) with cellularity in the glandular component of breast tissue. Diffusion microimaging was performed at 16.4T on fixed normal and cancer tissue samples and matched with post MRI histology. There was a moderate correlation between MD and nuclear count, but only a weak correlation between MD and nuclear area. 2029 Sune Nørhøj Jespersen1,2, Brian Hansen1, Daniel Nunes3, and Noam Shemesh3 1CFIN, Aarhus University, Aarhus, Denmark, 2Dep. Physics and Astronomy, Aarhus University, Aarhus, Denmark, 3Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal Non-vanishing diffusion kurtosis and time-dependent diffusion are both hallmarks of nongaussian diffusion in biological tissues. Here we combine measurements of time-dependent DTI parameters and time dependence of mean kurtosis using fast kurtosis imaging in rat spinal cord. We observe substantial time dependence of all parameters in both white and gray matter. 2030 Damien J. McHugh1,2 and Geoff J.M. Parker1,2,3 1Centre for Imaging Sciences, The University of Manchester, Manchester, United Kingdom, 2CRUK & EPSRC Cancer Imaging Centre in Cambridge & Manchester, United Kingdom, 3Bioxydyn Ltd., Manchester, United Kingdom This work investigates the use of optimised diffusion-weighted acquisitions for distinguishing between different microstructural changes relevant to characterising tumour tissue. Optimised protocols are found for a 'baseline' microstructure, and for two distinct changes which would lead to an ADC increase: (1) volume fraction decrease with cell size constant (therefore a decrease in cell density), (2) cell size decrease and coupled volume fraction decrease (therefore a constant cell density). Model fitting simulations are performed with optimised and non-optimised protocols, demonstrating that the improved precision achieved with optimised protocols may be beneficial in terms of distinguishing between these microstructural changes. 2031 Christian Beaulieu1, Corey Baron1, Penny Smyth2, Roxane Billey2, Leah White2, Fabrizio Giuliani1, Derek Emery3, and Robert Stobbe1 1Biomedical Engineering, University of Alberta, Edmonton, AB, Canada, 2Neurology, University of Alberta, Edmonton, AB, Canada, 3Radiology, University of Alberta, Edmonton, AB, Canada In diffusion tensor imaging, oscillating gradient spin echo (OGSE) gradient waveforms enable much shorter diffusion times (4 ms) than the typical pulsed gradient spin echo (PGSE, 40 ms) and OGSE was applied here for the first time in multiple sclerosis patients. A different dependence on diffusion time would suggest a change in micro-structural scale within the MS lesions. Compared to normal appearing white matter (NAWM), FLAIR-visible lesions showed reductions of fractional anisotropy (FA) on both PGSE and OGSE. The proportional FA decrease between NAWM and lesions was similar for OGSE and PGSE. 2032 Koji Sakai1, Toshiaki Nakagawa1, and Kei Yamada1 1Kyoto Prefectural University of Medicine, Kyoto, Japan To obtain anisotropic diffusion phantom with ease, we evaluated the longitudinal stability of commercially available astriction cotton as an anisotropic diffusion phantom. DTI examinations were performed at 3 T using a whole-body scanner by 20ch head coil for 131 days intermittently (18 times). The DTI analysis was performed and diffusion metrics (ADC and FA) of the phantom were evaluated by comparing standard deviation in one day to the averaged change between two consequence days. The averaged changes of ADC and FA within the experimental term were 0.03 x 10-3sec/mm2  and 0.002, respectively. The commercially available astriction cotton showed stability on its diffusivity over four months.