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Xiaozhi Cao^1,2, Congyu Liao^1,2, Zihan Zhou³, Zheng Zhong¹, Zhitao Li¹, Erpeng Dai¹, Siddharth Srinivasan Iyer^1,4, Airel Hannum^1,5, Mahmut Yurt^1,2, Sophie Schauman^1,2, Quan Chen¹, Nan Wang¹, Yifan Yan³, Hongjian He³, Stefan Skare⁶, Jianhui Zhong⁷, Adam Kerr², and Kawin Setsompop^1,2
1Department of Radiology, Stanford university, Stanford, CA, United States, ²Department of Electrical Engineering, Stanford university, Stanford, CA, United States, ³Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China, ⁴Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States, ⁵Department of Bioengineering, Stanford university, Stanford, CA, United States, ⁶Department of Clinical Neuroscience, Karolinska Institute, Solna, Sweden, ⁷Department of Imaging Sciences, University of Rochester, Rochester, NY, United States

Keywords: Diffusion/other diffusion imaging techniques, Brain

In this work, a diffusion preparation was implemented into the 3D spiral-projection MRF sequence to introduce additional diffusion weighting and enables whole-brain T₁, T₂, PD, ADC and FA mapping with 1-mm isotropic resolution within 10min. To maximize the diffusion signal and image-encoding efficiency, a diffusion-preparation without an amplitude stabilizer is employed, where robustness against phase variations is achieved using a combination of M1-compensated encoding, cardiac-gating, and an eddy-current compensating pre-pulse gradient. The MRF acquisition scheme and subspace reconstruction were also modified to enable effective data sharing across diffusion directions, which increase acceleration capability and improve mapping quality.

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Maxime Chamberland¹, Dmitri Shastin², Derek K. Jones², David G. Norris¹, and Kurt G. Schilling^3,4
1Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, ²Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, ³Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ⁴Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States

Keywords: Tractography & Fibre Modelling, White Matter, U-fibers, Diffusion MRI, Tractometry, Visualization

Here we visualized how superficial association fiber (SAF) systems relate to deep white matter bundles. We found that various shape features can be reliably extracted from those systems. The combination of superficial white matter tractography with traditional deep white matter bundles opens possibilities to study bundle-specific SAF in health and disease.

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Gregory Simchick^1,2, Timothy J Allen², and Diego Hernando^1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin-Madison, Madison, WI, United States

Keywords: Diffusion/other diffusion imaging techniques, Data Acquisition

Intravoxel incoherent motion (IVIM) quantification in the liver suffers from instability associated with separating multiple decaying signal components sampled along a single dimension (b-value). In this work, monopolar and 2D (b-value and first-order motion moment (M₁)) noise-optimized IVIM-DWI acquisitions were acquired on three MR scanners with different MR gradient hardware. From each acquisition, IVIM estimates were obtained using pseudo-diffusion and physical (M₁ dependent) IVIM signal models. Inter-scanner reproducibility and interlobar agreement were compared across acquisitions and models. 2D (b-M₁) IVIM-DWI acquisitions combined with physical IVIM signal modeling improved reproducibility of IVIM quantification in comparison to monopolar acquisitions and pseudo-diffusion modeling.

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Richard J. Foster¹, Samo Lasič^2,3, Henrik Lundell², Filip Szczepankiewicz⁴, Leah Khazin¹, Sven Plein¹, Erica Dall'Armellina¹, Nadira Y. Yuldasheva¹, Jürgen E. Schneider¹, and Irvin Teh^1
1Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom, ²Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark, ³Random Walk Imaging, Lund, Sweden, ⁴Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden

Keywords: Diffusion/other diffusion imaging techniques, Heart, Time dependence, Myocardium, Microstructure, q-space, QTI

Tensor-valued encoding is a promising technique for improving specificity in assessing the myocardial microstructure, but can be confounded by time-dependent diffusion (TDD). Here, the influence of TDD on q-space trajectory imaging (QTI) was examined in ex vivo rat heart, using 17 diffusion encoding waveforms with different frequency content and b-tensor shapes. We report apparent over/underestimation of QTI parameters when waveforms had different sensitivity to TDD, and demonstrate a means of frequency matching that reduced the apparent bias. Acquiring QTI at higher frequencies may provide greater sensitivity to intracellular structures, complementing QTI at lower frequencies.

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Timothy J Allen¹, Srijyotsna Volety¹, Greg Simchick², and Diego Hernando^1,2
1Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ²Radiology, University of Wisconsin-Madison, Madison, WI, United States

Keywords: Diffusion/other diffusion imaging techniques, Motion Correction

M1-optimized diffusion gradient waveforms allow for motion-robust liver DWI and ADC estimation. However, existing implementations have been limited to 3.0T scanners with high-performance gradient systems. This work introduces M1-optimized waveforms using a tetrahedral diffusion encoding to allow for high quality, motion-robust DWI on a 1.5T system with conventional gradient performance. Additionally, it addresses complications of this approach, namely increased concomitant gradients and eddy currents. Phantom experiments demonstrate a reduction in geometric distortion and bias of ADC maps generated with this approach compared to Stejskal–Tanner (monopolar) and non-tetrahedral gradient designs. Human subject imaging demonstrates increased motion-robustness.

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Ilaria Gabusi¹, Matteo Battocchio^1,2, Sara Bosticardo^1,3, Simona Schiavi^1,4, and Alessandro Daducci^1
1Department of Computer Science, University of Verona, Verona, Italy, ²Department of Computer Science, University of Sherbrooke, Sherbrooke, QC, Canada, ³Department of Biomedical Engineering, University of Basel, Basel, Switzerland, ⁴Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy

Keywords: Tractography & Fibre Modelling, Tractography & Fibre Modelling

Diffusion MRI tractography allows one to characterize brain connectivity in vivo, and it is common practice to reconstruct millions of streamlines and filter them a posteriori. However, redundancy among streamlines leads to collinearity in the linear operators used by existing filtering algorithms. To solve this problem, we propose a novel streamline representation which uses a combination of clustering and spatial blur to reduce redundancy. This representation is as accurate as state-of-the-art filtering methods and more robust to noise/perturbations in the input, but requires only ≈5% of the input streamlines thus decreasing both storage requirements and computational complexity.

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Mario Corral-Bolaños^1,2, Tram Nguyen¹, Hans Martin Kjer¹, Marco Pizzolato^1,2, Casper Bo Gravesen Salinas³, Johanna Perens³, Jeppe Revall Frisvad¹, Julien Colombelli⁴, and Tim Bjørn Dyrby^1,2
1Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark, ²Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Amager & Hvidovre, Copenhagen, Denmark, ³Gubra, Hørsholm, Denmark, ⁴Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology (BIST), Barcelona, Spain

Keywords: Validation, Tractography & Fibre Modelling, 3D-Fibre orientation

This work develops a novel 3D validation technique that reveals the white matter orientation with micron resolution in cleared murine brains. Light-sheet elastic scattering microscopy (LSSM) can be used to exploit the scattering signal exhibited by white matter fibres, which is dependent on their orientation. The rotation and imaging of the sample yield a scattering profile, which corresponds to that of infinitely long cylinders. Our work combines two orthogonal acquisitions to voxel-wise reconstruct 3D-fibre orientations in large brain volumes. LSSM could be the definitive validation method for diffusion MRI orientation methods.

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Hossein Rafipoor¹, Frederik Lange¹, Michiel Cottaar¹, and Saad Jbabdi^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

Keywords: Tractography & Fibre Modelling, White Matter, Fixel based analysis

Fibre orientation distribution function (fODF) estimation is usually applied independently for each subject. This can lead to inconsistent fODF estimation across subjects complicating tract-level (i.e., fixel-based) analysis. Here we propose a hierarchical model to extract consistent tract-specific metrics across subjects that permit group comparisons and the development of more reliable biomarkers for disease and biological processes.

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Jelle Veraart¹, Stefan Winzeck^2,3, Álvaro Planchuelo-Gómez^4,5, Björn Fricke⁶, Evgenios N. Kornaropoulos^7,8, Harri Merisaari^9,10, Tomasz Pieciak⁵, Yukai Zou^11,12, and Maxime Descoteaux^13
1Center for Biomedical Imaging, Dept. Radiology, NYU Grossman School of Medicine, New York, NY, United States, ²BioMedIA Group, Department of Computing, Imperial College London, London, United Kingdom, ³Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, United Kingdom, ⁴CUBRIC, Cardiff University, Cardiff, United Kingdom, ⁵ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain, ⁶Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ⁷CRMBM, Aix-Marseille University, Marseille, France, ⁸Diagnostic Radiology, Lund University, Lund, Sweden, ⁹Department of Radiology, University of Turku, Turku, Finland, ¹⁰TBMC, University of Turku, Turku, Finland, ¹¹Medical Physics Department, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom, ¹²Clinical Neurosciences, Clinical and Experimental Sciences, University of Southampton, Southampton, United Kingdom, ¹³Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke,, Sherbrooke, QC, Canada

Keywords: Diffusion/other diffusion imaging techniques, Data Processing

The lack of a standardized preprocessing pipeline is a significant source of variability that might lower the reproducibility of studies, especially across sites and with incomplete description of the preprocessing workflows. We evaluate the downstream impact of variability in preprocessing workflow by quantifying the reproducibility and variability of  region-of-interest (ROI) analyses. While many pipelines achieve excellent reproducibility in most ROI, we observed a large variability in performance of preprocessing workflows to the extent that some pipelines are detrimental to the data quality and reproducibility.

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Siebe Leysen^1,2, Stefan Sunaert^2,3, Frederik Maes^1,2, and Daan Christiaens^1,2
1Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium, ²Medical Imaging Research Center, UZ Leuven, Leuven, Belgium, ³Translational MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium

Keywords: Diffusion/other diffusion imaging techniques, Signal Representations, Denoising

A voxel-wise rank-1 decomposition in spherical harmonics of the dMRI signal allows for a denoising method with minimal assumptions on signal and noise distributions. A voxel-wise denoising strategy is compared to MP-PCA on in vivo data and simulated data. The rank-1 decomposition and MP-PCA show visually similar results on the in vivo data, indicating that a voxel-level denoising approach has potential. However, results on the simulations differ. This may have various explanations; further investigation is necessary to strengthen the credibility of a rank-1 decomposition as a denoising approach.

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Teddy Xuke Cai^1,2, Nathan Hu Williamson¹, Rea Ravin^1,3, and Peter Joel Basser^1
1Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States, ²Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ³Celoptics, Inc., Rockville, MD, United States

Keywords: Diffusion/other diffusion imaging techniques, Data Analysis, Exchange

Contrary to prevailing views, recent work suggests that steady-state water exchange between the intra- and extracellular space is driven, in part, by active metabolic processes. To support these findings, we investigate whether exchange exhibits multiexponential behavior consistent with distinct exchange processes. We find a bimodal distribution of exchange times in live neural tissue, with only the faster peak being reduced upon the introduction of a sodium-potassium pump inhibitor, thus supporting the existence of active exchange. Furthermore, we describe a time-efficient method of isolating exchange and fitting multiexponential exchange times using diffusion exchange spectroscopy, paving the way for future studies.

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Jan Malte Oeschger¹, Francisco Javier Fritz¹, Mohammad Ashtarayeh², Maria Morozova^3,4, Tobias Streubel¹, Henriette Rusch⁴, Markus Morawski^4,5, Nikolaus Weiskopf^5,6, and Siawoosh Mohammadi^1,5
1Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ²Department of Systems Neurosciences,, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, ³Department of Neurophysics,, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ⁴Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig, Germany, ⁵Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ⁶Faculty of Physics and Earth Sciences, Felix Bloch Institute for Solid State Physics, Leipzig, Germany

Keywords: Diffusion/other diffusion imaging techniques, Diffusion/other diffusion imaging techniques, G-ratio

In vivo MR g-ratio mapping relies on a calibrated method that relates myelin and axon  MR markers to volume fractions. To estimate the calibration parameter, fixed ex vivo tissue measured with MRI and histology is used. The so-determined calibration parameter is then applied in vivo, neglecting the difference in the MR markers due to fixation. Here, we proposed a new calibration method accounting for this difference. The new calibration reduced the variability across MR g-ratios based on different myelin and axon markers, indicating that it can improve the accuracy of MR g-ratios.

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Sune Jespersen^1,2 and Dmitry S. Novikov^3
1Department of Clinical Medicine, Aarhus University, Aarhus, Denmark, ²Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark, ³Radiology, New York University School of Medicine, New York, NY, United States

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, diffraction, disordered systems, exchange

We identify a new regime for the diffusion signal in non-confining disordered systems with locally varying diffusivity. It occurs at long times and large diffusion wavevectors, reminiscent of diffusion diffraction in closed pores. Remarkably, while for free diffusion the signal is exponentially strongly dephased, scattering off heterogeneities results in a much weaker, power-law decrease of the signal, thereby offering an enhanced sensitivity to the medium’s structure. In particular, we show how correlation functions of the medium’s microstructure to arbitrary order can be measured. We compare our theoretical predictions for the second order correlation function to  numerical simulations with good agreement.

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Ruicheng Ba¹, Yuhui Ma², Kuiyuan Liu¹, Tianshu Zheng¹, Haotian Li¹, Chen Li², Xiaoli Wang², and Dan Wu^1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hanzhou, China, ²Department of Medical Imaging, Weifang Medical University, Shandong, China

Keywords: Diffusion/other diffusion imaging techniques, Brain

Transcytolemal water exchange can be estimated using diffusion-time-dependent diffusion kurtosis imaging acquired at long diffusion times. However, dMRI signals acquired at long diffusion times using STEAM sequences are typically noisy, and fitting of the nonlinear kurtosis model and the Kärger model accumulates fitting errors. Here, we proposed a Bayesian method for estimating transcytolemal exchange time from the Kärger model and compared accuracy and robustness with conventional least square fitting method in both simulated data and rat brain data in a model of transient middle cerebral artery occlusion. Results indicated improved fitting accuracy and robustness against noise using the Bayesian approach.

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Samo Lasic¹, Nathalie Just¹, Matthew Budde², and Henrik Lundell^1
1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark, ²Department of Neurosurgery, Neurobiology, and Anatomy, Medical College of Wisconsin, Milwaukee, , USA, WI, United States

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, Tensor-valued encoding, time-dependent diffusion

Accounting for time-dependent diffusion (TDD) in tensor-valued encoding is required for unbiased assessment of microscopic anisotropy (µA). We have previously introduced the spectral principle axis system (SPAS) to find linear tensor encoding (LTE) projections of spherical tensor encoding (STE) with maximum spread of sensitivity to TDD. This can be used to simultaneously achieve unbiased µA and TDD contrasts within a single protocol. Here we present results from in vivo experiments in a mouse brain. The two independent contrasts (µA- TDD) indicate consistent variations in different brain regions.

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Elizabeth Powell¹, Geoff JM Parker^1,2,3, and Marco Palombo^4,5
1Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Queen Square MS Centre, Institute of Neurology, University College London, London, United Kingdom, ³Bioxydyn Limited, Manchester, United Kingdom, ⁴Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom, ⁵School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom

Keywords: Diffusion/other diffusion imaging techniques, Simulations, Pseudo-diffusivity

The pseudo-diffusivity effect - arising from blood flow in capillaries - is used to characterise the diffusion-weighted MRI signal at low b-values (b<200 s/mm²) in several biophysical models. We propose here a generative model for producing vascular meshes with tunable properties - such as vessel segment radius and length, and vessel volume fraction – that are compatible with common Monte Carlo diffusion simulation frameworks. Monte Carlo simulations of pseudo-diffusivity are performed, under varying conditions, by adapting the Camino simulation toolkit to include a plug flow component to spin dynamics inside the vascular mesh; the resulting signals are validated against analytical solutions.

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Zhaohuan Zhang¹, Shu-Fu Shih¹, and Holden H. Wu^1
1Department of Radiology, University of California, Los Angeles, Los Angeles, CA, United States

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

Three-dimensional (3D) dual-echo steady-state (DESS) MRI can produce multi-contrast (MC)images with T2 and diffusion weighting (DW) for simultaneous T2 and D mapping in knee and prostate. A primary challenge of MC DESS is the low signal-to-noise ratio (SNR) of DW DESS leads to less reliable diffusion mapping. In this work, we investigated a new random matrix theory-based denoising reconstruction to improve MC T2W/DW DESS by taking advantages of the inherent redundancy in noise statistics across multiple coil channel and contrasts dimensions. Our in-vivo knee and prostate experiments showed promising improvements in SNR and quality of T2 and D mapping. 

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Andres Saucedo^1,2 and M. Albert Thomas^1,2
1Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States, ²Physics and Biology in Medicine Interdepartmental Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States

Keywords: Diffusion/other diffusion imaging techniques, Spectroscopy, Spectroscopic Imaging

We present the first demonstration of single shot diffusion trace spectroscopic imaging using radial echo planar k-space trajectories on a clinical 3T scanner. Conventional DW-MRS requires three separate acquisitions to compute the trace apparent diffusion coefficient (ADC), whereas the single shot technique generates a trace-weighted signal in one measurement, although this has so far only been applied in NMR and to a limited extent in DW-MRI. Our preliminary results indicate good agreement with expected trace ADC values both in phantom and in healthy brain, showing a promising approach for determining the orientation-independent trace ADC value with non-Cartesian diffusion-weighted spectroscopic imaging.

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Kerrin J Pine¹, Luke J Edwards¹, Marianna Schmidt^1,2, Juliane Damm¹, Fuyixue Wang³, Susie Huang³, Evgeniya Kirilina¹, and Nikolaus Weiskopf^1,4
1Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ²Max Planck School of Cognition, Leipzig, Germany, ³A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States, ⁴Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany

Keywords: Diffusion/other diffusion imaging techniques, Motion Correction, DTI

High resolution diffusion weighted imaging (DWI) is required to map cortical fibres and short association fibres in superficial white matter. The recently developed gSlider sequence allows high-resolution whole-brain DWI but is prone to motion-induced artefacts due to the long volume acquisition. We combined gSlider with prospective motion correction (PMC) using optical tracking to acquire high angular, high spatial resolution DWI. In three healthy participants, we demonstrated that PMC led to a reduction of motion artifacts, an increase of temporal SNR of around 15% and better estimates of fibre characteristics in the cortex and superficial white matter.