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Ezequiel Farrher¹, Chia-Wen Chiang², Chang-Hoon Choi¹, Kuan-Hung Cho², Sheng-Min Huang², Ming-Jye Chen², Li-Wei Kuo^2,3, and N. Jon Shah^1,4,5,6
1Institute of Neuroscience and Medicine 4, Forschungszentrum Jülich, Jülich, Germany, ²Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, ³Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan, ⁴Department of Neurology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany, ⁵JARA – BRAIN – Translational Medicine, RWTH Aachen University, Aachen, Germany, ⁶Institute of Neuroscience and Medicine – 11, Forschungszentrum Jülich, Jülich, Germany

Keywords: Stroke, Diffusion/other diffusion imaging techniques, NODDI, ischemia, multi-echo, transverse relaxation, intra-neurite, extra-neurite

Neurite orientation dispersion and density imaging (NODDI) has been broadly used in diffusion MRI for the characterisation of tissue microstructure in healthy ageing and the diseased brain. However, the compartment-specific volume fractions provided by NODDI suffer from echo-time (TE) dependence due to differences in the compartment-specific transverse relaxation times. The recently proposed multi-TE NODDI (MTE-NODDI) model provides both TE-independent compartmental volume fractions and compartment-specific transverse relaxation times. Here we aim to assess the benefits and limitations of using MTE-NODDI for studying the brain tissue microstructure affected by transient ischaemic stroke in MCAo animal models.

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Tales Santini¹, Naila Rahman¹, Alyson Shim¹, Matthew Budde², Stefan Everling¹, and Corey Baron^1
1Western University, London, ON, Canada, ²Medical College of Wisconsin, Milwaukee, WI, United States

Keywords: Microstructure, Microstructure

Previous work showed that advanced diffusion metrics (OGSE and μFA) are sensitive to microstructural changes between in vivo and ex vivo marmoset brain tissues. Here, we utilized Monte Carlo simulations to investigate potential microstructure changes that could be occurring during tissue perfusion and fixation. A comparison between simulations and experiments showed that beading and decreased extracellular space are in agreement with the experimental trends observed. Changing microstructural properties during these processes has implications for studies that compare ex vivo tissue samples with in vivo findings.

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Siyuan Fang¹, Jian Hai², Gaiying Li¹, Yupeng Wu¹, Weiwei Zhao¹, and Jianqi Li^1
1Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China, ²Department of Neurosurgery, Tong Ji Hospital, School of Medicine, Tong Ji University,, Shanghai, China

Keywords: Data Analysis, Diffusion Tensor Imaging, free-water elimination DTI

The objective of this study was to explore the relationship between cognitive impairment and free-water elimination DTI (FWE-DTI) metrics in patients with intracranial vascular occlusion disease (IVOD) and transient ischemic attack (TIA). 22 IVOD with TIA patients were tested with cognitive scales and scanned using a 3T echo-planar imaging sequence. The results show global FWE-DTI metrics were associated with patients' cognitive performance in some domains, which indicated the potential of FWE-DTI  as new  indices for assessing global brain changes in this disease.

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Kuiyuan Liu¹, Tianshu Zheng¹, Ruicheng Ba¹, Hongxi Zhang², and Dan Wu^1
1Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, ²Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China

Keywords: Signal Modeling, Microstructure

In this study, we proposed Bayesian estimation of tissue microstructures in t_d-dMRI model, and compared its performance with the traditional non-linear least square fitting method in simulation data and glioma patient data. We found that the performance of Bayesian fitting was dependent on the prior distribution and choice of hyperparameters, and the combination of Bayesian and least-square fitting could achieve reasonable performance without prior information.

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Sisi Li¹, Diwei Shi², Xiaoyu Jiang^3,4, Li Chen², Quanshui Zheng², Hua Guo¹, and Junzhong Xu^3,4,5,6
1Center for Biomedical Imaging Research, Tsinghua University, Beijing, China, ²Center for Nano and Micro Mechanics, Department of Engineering Mechanics, Tsinghua University, Beijing, China, ³Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, ⁴Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ⁵Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, ⁶Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States

Keywords: Signal Modeling, Microstructure

This study proposed and validated a general diffusion MRI biophysical model enabling simultaneous estimation of cell size, intracellular volume fraction, and transcytolemmal water exchange. The model introduces two-mode intracellular diffusion, corrects for restriction-induced “edge-enhancement” effect, and handles arbitrary diffusion gradient waveforms. The results of both in silico and in vitro experiments suggest this model not only improves the accuracy of estimated microstructural parameters such as cell size but also provides reasonable estimates of water exchange rate constant that is usually ignored previously. Such a comprehensive model may have potential to probe tumor status more precisely which is feasible in clinics.

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Melisa L. Gimenez^1,2, Leonardo A. Pedraza Pérez^1,2, and Gonzalo A. Álvarez^1,2,3
1Instituto Balseiro, CNEA, Universidad Nacional de Cuyo, San Carlos de Bariloche, Argentina, ²Centro Atómico Bariloche, CNEA, CONICET, San Carlos de Bariloche, Argentina, ³Instituto de Nanociencia y Nanotecnologia, CNEA, CONICET, San Carlos de Bariloche, Argentina

Keywords: Microstructure, Quantitative Imaging

Changes in tissue microstructure are promising biomarkers of neurological diseases. However, achieving robust and reliable, non-invasive diagnostic tools to estimate microstructural features is a major challenge. We perform a systematic analysis using Non-uniform Oscillating Gradient Spin Echo (NOGSE) sequences to estimate size distributions of white-matter phantoms. We evaluate the reliability and self-consistency of the inference method. We find that estimation of the distribution’s mode is very robust and reliable for sharp and smooth gradient modulations. These results contribute to developing reliable diagnostic tools based on quantitative images of tissue microstructure.

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Mert Şişman^1,2, Dominick J. Romano^2,3, Alexey V. Dimov², Ilhami Kovanlikaya², Pascal Spincemaille², Thanh D. Nguyen², and Yi Wang^2,3
1Electrical and Computer Engineering, Cornell University, Ithaca, NY, United States, ²Department of Radiology, Weill Cornell Medicine, New York, NY, United States, ³Biomedical Engineering, Cornell University, Ithaca, NY, United States

Keywords: Microstructure, White Matter

Myelin Volume Fraction (MVF) is an important biomarker of demyelination various diseases Multiple Sclerosis. In this study, we propose a method that provides quantitative MVF maps from routine multiple echo gradient echo acquisitions and dictionary matching. The dictionary is generated using the Hollow Cylindrical Fiber Model (HCFM) and employs both the magnitude signal decay and QSM obtained from the mGRE phase. The obtained maps show both qualitative and quantitative superiority over the standard multiexponential fitting-based myelin water fraction (MWF) maps. 

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Tigris Joseph^1,2, Sarah Morris^1,2,3, Shannon H. Kolind^1,2,3,4, Alex MacKay^1,3, Irene M. Vavasour^2,3, and Cornelia Laule^1,2,3,5
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, ²International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada, ³Radiology, University of British Columbia, Vancouver, BC, Canada, ⁴Medicine, University of British Columbia, Vancouver, BC, Canada, ⁵Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada

Keywords: Microstructure, Relaxometry, myelin, white matter, orientation dependence, fiber direction, BedpostX, myelin water fraction, myelin water imaging

Previous work suggests myelin water fraction (MWF) may be fibre orientation dependent. We compared MWF to fiber angle (from diffusion tensor imaging (DTI)) in white matter (WM) from 16 healthy participants using BedpostX to estimate the number of fiber directions. MWF vs. fiber angle graphs showed trends which varied between participants, suggesting that real myelination differences may be at least partly responsible for apparent orientation dependence of MWF. There were little obvious differences between trends with 1, 2, or 3+ fiber orientations in WM, suggesting number of fibers directions within a voxel does not impact orientation dependence.

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Shir Filo¹ and Aviv A Mezer^1
1The Edmond and Lily Safra Center for Brain Science, The Hebrew University of Jerusalem, Jerusalem, Israel

Keywords: Microstructure, Magnetization transfer

We present an array of new quantitative maps, highlighting different aspects of the tissue’s water. Furthermore, our technique allows to calculate the voxel-wise tissue relaxivity, associated with the molecular composition of the brain. Our approach is based on the pioneering two-site exchange model. We implemented it for magnetization-transfer weighted water content mapping of brain tissue for the first time. The new in-vivo MRI measurements conform well with the theory. They can be easily acquired with the standard quantitative MRI protocol and do not require complex data fitting. Therefore, the proposed technique may further advance human brain research and diagnosis.

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Daniel Z.L. Kor¹, Hossein Rafipoor¹, Michiel Cottaar¹, Saad Jbabdi¹, Karla L. Miller¹, and Amy F.D. Howard^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford, United Kingdom

Keywords: Diffusion/other diffusion imaging techniques, Microstructure, biophysical diffusion modelling

Biophysical modelling of diffusion MRI (dMRI) may elucidate key microstructural features. However, most models include many input parameters, making simultaneous estimations of all parameters ill-posed. To overcome this, the recently published Bayesian framework EstimatioN for CHange (BENCH) characterises changes (variation) in parameters across multiple measurements/samples, rather than inferring the actual parameters from a single measurement/sample. BENCH has been previously applied to understand group-wise changes (e.g., patients vs. controls) in biophysical parameters. Here, we adapted BENCH to interpret situations of continuous change and validate its behaviour using synthetic dMRI data from numerical simulations.

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Chantal Tax^1,2, Sila Genc³, Claire L MacIver^1,4, Markus Nilsson⁵, Mark Wardle⁶, Filip Szczepankiewicz⁵, Derek K Jones¹, and Kathryn Peall^4
1CUBRIC, Cardiff University, Cardiff, United Kingdom, ²Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands, ³Department of Neurosurgery, The Royal Children's Hospital, Parkville, Australia, ⁴Neuroscience and Mental Health Research Institute, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom, ⁵Diagnostic Radiology, Clinical Sciences Lund, Lund Unversity, Lund, Sweden, ⁶Cardiff and Vale University Health Board, University Hospital of Wales Cardiff, Cardiff, United Kingdom

Keywords: Diffusion/other diffusion imaging techniques, Microstructure, Movement disorders

Most work on understanding movement disorder pathophysiology has focused on grey/white matter volumetric (macrostructural) and white matter microstructural effects, limiting understanding of frequently implicated grey matter microstructural differences. Using ultra-strong diffusion MRI with spherical tensor encoding, a persistent MRI signal was seen in healthy cerebellar grey matter at ultra-high diffusion-weightings. This work quantifies the proportion of this signal, previously ascertained to originate from small spherical spaces, in a clinical cohort, including patients with diagnosed movement disorders where the cerebellum has been implicated in symptom pathophysiology. Significant differences were found in individuals diagnosed with SCA6 and dystonia compared to age-matched controls.

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Pippa Storey¹ and Dmitry S. Novikov^1
1Department of Radiology, New York University School of Medicine, New York, NY, United States

Keywords: Microstructure, Relaxometry, T2* decay

In the absence of macroscopic magnetic field inhomogeneity, the decay of gradient-echo signals is generally observed to be approximately monoexponential, with time constant $$$T_2^*$$$. The monoexponential behavior is typically attributed to diffusion, which averages out the dephasing of spins due to microstructural sources of magnetic susceptibility. The rationale is that, over times long enough for spins to have explored the microstructure, the cumulants of the spins’ phase distribution should increase linearly with time. By means of a simple counterexample, we demonstrate that this assumption is incorrect, thereby calling into question the mechanism underlying the monoexponential decay of gradient-echo signals.

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Kulam Najmudeen Magdoom^1,2, Alexandru V. Avram^1,2, Dario Gasbarra³, Thomas Witzel⁴, Susie Yi Huang⁴, and Peter J Basser^2
1The Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF) Inc., Bethesda, MD, United States, ²National Institute of Health, Bethesda, MD, United States, ³University of Helsinki, Helsinki, Finland, ⁴Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

Keywords: Diffusion/other diffusion imaging techniques, Microstructure, Multiple diffusion encoding

Whole brain DTD MRI was performed at 1.2 mm isotropic resolution in-vivo using 300 mT/m gradients. An efficient and easy to implement interfused-PFG (iPFG) sequence was used to acquire multiple diffusion encoded images. Size, shape and orientation heterogeneity are measured and mapped from the estimated DTD along with a new form of tractography. The results show varying heterogeneity in different areas of the cerebral cortex, and subcortical and white matter regions. DTD tractography captured complex fiber configurations absent in DTI tractography.

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Rita Alves¹, Rafael Neto Henriques¹, Jonas Olesen^2,3, Sune Nørhøj Jespersen^2,3, and Noam Shemesh^1
1Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal, ²Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, ³Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark

Keywords: Diffusion/other diffusion imaging techniques, Microstructure, Exchange

Apparent diffusion coefficient (ADC) contrasts in stroke are still debated over 30 years after their discovery, mainly because of the nonspecific nature of ADC. Here, we harness Standard Model with Exchange (SMEX) measurements in ex-vivo stroked brains, to investigate how tissue microstructure is changed with ischemia. SMEX provides insight into neurite density, diffusivity and – importantly – exchange between neurite and extracellular environments.  Using an extensive dataset, we find changes in neurite density and diffusivity that are consistent with neurite beading effects, which were further confirmed histologically. Dramatic reductions in exchange rates in the ischemic core were also observed.

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Kevin D Harkins^1,2,3, Junzhong Xu^1,2, John C Gore^1,2,3, and Mark D Does^2,3
1Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ²Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, ³Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

Keywords: Simulations, Microstructure

This study explores the role of extra-axonal environment on the time dependent diffusion coefficient of extra-axonal water in white matter. Monte Carlo simulations of water diffusion in geometries with varying extra-axonal heterogeneity were compared with a proposed analytic model. The results agree with previously published power-law relationships that depend on structural order, but also uncovers trends between model parameters with characteristics of extra-axonal space.

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Haley Elizabeth Wiskoski^1,2, Loi Do¹, Marc Zempare³, Natalie Carey³, Amy Delmendray³, Kimberly Young³, Kimberly Bohne³, Monica Chawla³, Pradyumna Bharadwaj⁴, Kenneth Mitchell⁵, Gene Alexander^3,4,6, Carol Barnes^3,4, and Theodore Trouard^1,3,7
1Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, United States, ²James C. Wyant College of Optical Sciences, The University of Arizona, Tucson, AZ, United States, ³Evelyn F. McKnight Brain Institute, The University of Arizona, Tucson, AZ, United States, ⁴Department of Psychology, Neurology, and Neuroscience, The University of Arizona, Tucson, AZ, United States, ⁵Health Sciences Center, Tulane University, New Orleans, LA, United States, ⁶Division of Neural Systems, Memory, and Aging, The University of Arizona, Tucson, AZ, United States, ⁷Department of Medical Imaging, The University of Arizona, Tucson, AZ, United States

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, DTI, fixels, Tractography & Fibre Modeling, Software Tools, Hypertension

Hypertension is associated with an increased risk of cardiovascular disease and cognitive decline in aging humans. This study investigated longitudinal effects of induced HTN in regional and microstructural neuroanatomy of F344 rats using noninvasive diffusion-weighted MRI and fixel-based analysis. Single-shot spin-echo EPI along 64 diffusion directions and three shells (b=1000, 2000, and 3000 s/mm²) was performed. Microstructural changes in the brain appeared in certain regions after 10 weeks of hypertension, yet, most regions remained unaffected, contrasting peripheral organs which showed dramatic fibrosis due to the HTN.  This likely demonstrates a robust protective mechanism of the central nervous system.

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Sasha Hakhu¹, Jennapher Lingo VanGilder¹, Lucas Paulson¹, Leland Hu², Yuxiang Zhou², Kurt Schilling³, and Scott Beeman^1
1School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States, ²Mayo Clinic, Scottsdale, AZ, United States, ³Vanderbilt University, Nashville, TN, United States

Keywords: White Matter, Diffusion/other diffusion imaging techniques

White matter (WM) tract detection proximal to brain tumors, surrounded by vasogenic edema during tumor resection is critical. Previous work has shown that NODDI presents a more accurate quantification of WM in edema as compared to DTI. However, these studies included gliomas and metastases, which are known to infiltrate WM. Here, we focus on validating the use of the NODDI model for WM identification in edema only in non-invasive meningiomas. Our results showed that DTI-derived FA of WM near edematous regions were lower than contralateral WM in non-edematous regions; in contrast, NODDI-derived ODI values for the same regions remained comparable.

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Arthur Chakwizira¹, Ante Zhu², Thomas Foo², Carl-Fredrik Westin³, Filip Szczepankiewicz¹, and Markus Nilsson^4
1Medical Radiation Physics, Lund, Lund University, Lund, Sweden, ²GE Research, Niskayuna, New York, NY, United States, ³Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, ⁴Clinical Sciences Lund, Lund University, Lund, Sweden

Keywords: Diffusion/other diffusion imaging techniques, Microstructure

Monitoring time dependence with diffusion MRI provides observables sensitive to restricted diffusion and exchange. Probing these phenomena by simply varying the diffusion time is a challenge because they have opposite effects on the diffusion-weighted signal and may cancel each other. A theoretical framework was recently proposed for disentangling the effects using free gradient waveforms. Here we explore the potential of the approach for neuroimaging in vivo using a high-performance gradient system. Results demonstrate unprecedented ability to disentangle the effects of restriction and exchange. Maps of the exchange rate show plausible contrast in both cortical and subcortical regions of the brain.

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Naila Rahman¹, Kathy Xu¹, Matthew Budde², Arthur Brown¹, and Corey Baron^1
1Robarts Research Institute, London, ON, Canada, ²Medical College of Wisconsin, Milwaukee, WI, United States

Keywords: Diffusion/other diffusion imaging techniques, Microstructure, Brain Injury

Single mild concussive impacts remain sparsely explored by in vivo neuroimaging techniques. Multimodal microstructural MRI has shown increased sensitivity and specificity to microstructural changes in various disease and injury models. In this work, we apply oscillating gradient spin-echo (OGSE) diffusion MRI, microscopic anisotropy (µA) diffusion MRI, and magnetization transfer (MT) MRI longitudinally to increase sensitivity to smaller spatial scales, disentangle fiber orientation dispersion from true microstructural changes, and acquire myelin sensitivity, respectively. We demonstrate that multimodal microstructural MRI provides sensitivity to evolving changes following a mild impact in both acute and chronic regimes, with OGSE demonstrating higher sensitivity than µA.

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Ali Abdollahzadeh¹, Ricardo Coronado-Leija¹, Subah Mehrin¹, Hong-Hsi Lee², Alejandra Sierra³, Els Fieremans¹, and Dmitry S. Novikov^1
1Radiology, New York University School of Medicine, New York, NY, United States, ²Radiology, Harvard Medical School, Boston, MA, United States, ³A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland

Keywords: Diffusion/other diffusion imaging techniques, Simulations, Time-dependence diffusion

We segment all myelinated and unmyelinated axons from electron microscopy (EM) images of brain white matter (WM) of a mouse and a rat and quantify their cross-sectional morphology. We provide the exact relation between the long-time limit of the along-axon diffusion coefficients and the geometry of segmented intra-axonal spaces (IAS). By performing Monte Carlo (MC) simulations of diffusion in the IASs at varying diffusion times, we establish the time-dependence of diffusion along segmented myelinated and unmyelinated axons and validate the relation between axonal geometry and the long-time behavior of the longitudinal diffusion coefficient.