ISMRM & SMRT Virtual Conference • 08-14 August 2020

Digital Poster Session

Diffusion: Diffusion Acquisition, Reconstruction and Signal Analysis

Digital Posters

Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis
Session Sub-Topic: Diffusion: Acquisition 1
Digital Poster
Diffusion

 4297 SNR efficient diffusion imaging at 7T with B1+ mitigated multi-shot SMS-EPI, using semi adiabatic PINS RF and low-rank completion reconstruction SoHyun Han1, Rebecca E. Feldman2, Mary Kate Manhard3,4, Congyu Liao3,4, Seong-Gi Kim1, Priti Balchandani5, and Kawin Setsompop3,4 1Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of, 2Department of Computer Science, Mathematics, Physics, and Statistics, University of British Columbia, Kelowna, BC, Canada, 3Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 4Department of Radiology, Harvard Medical School, Boston, MA, United States, 5Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States View the Poster B1+ inhomogeneity, SAR, and shortened T2-relaxation are the main challenges to leverage the higher SNR at ultra-high-field MRI. Here, we develop a new method by combining navigation-free multi-shot SMS-EPI with low-rank matrix completion reconstruction with semi-adiabatic PINS pulse for B1+ insensitive SMS imaging. Using this combined approach, we demonstrated mitigated B1+ inhomogeneity by comparing with conventional-SE pulse and the feasibility of low-rank completion reconstruction at high b-value. Finally, 1.2 mm isotropic whole-brain diffusion MRI was acquired across 64 diffusion directions with high-SNR in 11 minutes at 7T. 4298 Noninvasive Detection of Cell Membrane Permeability with Filter-Exchange Imaging Athanasia Kaika1,2, Mathias Schillmaier1,2, Geoffrey J. Topping1,2, and Franz Schilling1,2 1Technical University of Munich, Munich, Germany, 2Nuclear Medicine, Klinikum rechts der Isar, Munich, Germany View the Poster Filter-Exchange Imaging (FEXI) is a noninvasive double-diffusion imaging method, sensitive to transmembrane water exchange, which is strongly connected to cell viability. A FEXI sequence was implemented and tested in vitro with baker’s yeast. Upon permeabilization with ethanol, AXR increased whereas ADC decreased, more so with increasing ethanol concentration. AXR reduced over time, but only minor changes in ADC, intracellular volume and Trypan staining were detected. 4299 Rapid DTI-based free water elimination and mapping with explicit T2 modelling using a dual-echo Stejskal-Tanner EPI sequence Ezequiel Farrher1, Richard P. Buschbeck1, Kuan-Hung Cho2, Ming-Jye Chen2, Seong Dae Yun1, Zaheer Abbas1, Chang-Hoon Choi1, Li-Wei Kuo2,3, and N. Jon Shah1,4,5,6 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, RWTH Aachen University, Aachen, Germany, 5JARA - BRAIN - Translational Medicine, Aachen, Germany, 6Institute of Neuroscience and Medicine 11, JARA, Forschungszentrum Jülich, Jülich, Germany View the Poster We propose and investigate a dual-echo (DE) Stejskal-Tanner EPI sequence for rapid DTI-based free water elimination and mapping with explicit T2 modelling (FWET2) in vivo. DTI maps from the DE sequence are artefact-free and similar to the standard, individual echo (IE) approach. Compared to the IE case, an underestimation of T2 values calculated from the DE sequence is observed. The T2 underestimation stems from reduced signal amplitudes in the second echo of the DE sequence, which we demonstrate to correlate with imperfect refocusing RF pulses. A simple correction method is proposed. FWET2 model parameters derived from both sequences are comparable. 4300 Time-dependent and anisotropic diffusion in the heart: linear and spherical tensor encoding with varying degree of motion compensation Samo Lasic1,2, Henrik Lundell2, Filip Szczepankiewicz3,4,5, Markus Nilsson3, Jürgen E. Schneider6, and Irvin Teh6 1Random Walk Imaging, Lund, Sweden, 2Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark, 3Clinical Sciences, Lund University, Lund, Sweden, 4Harvard Medical School, Boston, MA, United States, 5Brigham and Women's Hospital, Boston, MA, United States, 6Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom View the Poster Spherical tensor encoding (STE) can potentially shorten acquisition of mean diffusivity (MD) compared to the traditional linear tensor encoding (LTE). To avoid negative effects of motion, e.g. in the heart, motion compensation is needed. However, motion compensation requires altering diffusion gradient waveforms and their sensitivities to time-dependent diffusion. To exclude motion, we first investigated LTE and STE with different degrees of motion compensation in ex vivo pig hearts. We observed significantly different MD, which can be attributed to time-dependent diffusion and microscopic diffusion anisotropy. Our analysis suggests that time-dependent diffusion is a critical determinant of MD in the myocardium. 4301 SENSE accelerated multishot spiral diffusion: application in brain on a clinical platform Maarten J. Versluis1, Kim van de Ven1, Velmurugan Gnanaprakasam1, Viswanath Kasireddy2, Suthambhara Nagaraj2, and Silke Hey1 1BIU MR, Philips Healthcare, Best, Netherlands, 2BIU MR, Philips Healthcare, Bangalore, India View the Poster In this study we compare SENSE accelerated multi-shot variable density spiral diffusion to the current clinical standards: single shot EPI and MultiVane TSE diffusion. A variable density sampling strategy was employed to correct for the phase of the different shots and iterative SENSE was used to reduce the number of shots and scanning duration. This technique was applied on a clinical platform with clinically acceptable reconstruction times. We showed that spiral diffusion reduces distortions in difficult to shim brain regions compared to ssh-EPI, and spiral diffusion has at a reduced scan duration compared to the TSE-based approach. 4302 Robust Diffusion-Weighted Imaging near Metallic Objects with Inner-FOV Single-Shot STEAM based on 2D-Selective RF Excitations Caspar Florin1 and Jürgen Finsterbusch1 1Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany View the Poster The potential of a single-shot stimulated echo acquisition mode (STEAM) sequence based on RF refocused echoes for DW imaging close to metallic objects is evaluated. It is optimized for spinal cord applications by combining it with inner-FOV technique based on 2D-selective RF (2DRF) excitations and half-Fourier sampling which improves its signal-to-noise ratio (SNR) efficiency significantly. Its robustness in the presence of metallic objects is investigated and compared to EPI showing a better performance with smaller regions suffering from signal losses. 4303 Simultaneous Acquisition of Dynamic Diffusion Imaging and Diffusion Tensor Imaging in the Brain Mihika Gangolli1, Wen-Tung Wang1, Neville Gai2, Dzung L. Pham1, and John Butman1,2 1Center for Neuroscience and Regenerative Medicine, Bethesda, MD, United States, 2National Institutes of Health, Bethesda, MD, United States Watch the Video We propose a diffusion acquisition scheme, called “nested cubes”, consisting of five triplets of three unique mutually orthogonal directions, providing diffusion weighted data sampled across fifteen noncollinear directions distributed uniformly across a spherical shell. Data acquired using this setup facilitates the simultaneous acquisition of dynamic maps of trace and other diffusion metrics while producing DTI measurements comparable to those from a standard DTI sequence. 4304 Diffusion tensor imaging in human subjects wearing metallic orthodontic braces Xinyuan Miao1,2, Yuankui Wu1,2,3, Dapeng Liu1,2, Hangyi Jiang1, Qin Qin1,2, Peter C.M van Zijl1,2, Jay J. Pillai4,5, and Jun Hua1,2 1Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 2F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 3Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China, 4Johns Hopkins University School of Medicine, Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, United States, 5Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States View the Poster Metallic objects such as dental braces bring substantial susceptibility artifacts in MR images acquired using echo-planar-imaging (EPI) sequences. Here, we demonstrate that diffusion-prepared diffusion tensor imaging (DTI) with three-dimensional fast gradient-echo readout can significantly reduce susceptibility artifacts that are commonly seen in conventional spin-echo (SE) EPI DTI in the presence of metallic orthodontic braces. 4305 Reproducibility of Diffusion MRI Metrics Using 4-way Phase-Encoding Acquisition Design M. Okan Irfanoglu1, Neda Sadeghi2, Joelle Sarlls3, and Carlo Pierpaoli2 1QMI, NIBIB/NIH, Bethesda, MD, United States, 2NIBIB/NIH, Bethesda, MD, United States, 3NINDS/NIH, Bethesda, MD, United States Watch the Video In this work, we assessed the reproducibility of diffusion MRI metrics w.r.t different experimental and acquisition designs within the same scan time limits. The design that employed identical diffusion gradients and b-values for blip-up phase-encoding and blip-down phase-encoding provided significant improvements in terms of data reproducibility compared to the design using a single b=0 blip-down image in terms of distortions. The proposed 4-way encoding scheme not only improved upon this design but also consistently reduced the effects of other imaging artifacts; therefore, is suggested to be the acquisition scheme of choice for dMRI studies where biological differences are subtle. 4306 Improving X-PROP with a more stable echo train for diffusion weighted MRI Zhiqiang Li1, Melvyn B Ooi1,2, and John P Karis1 1Neuroradiology, Barrow Neurological Institute, Phoenix, AZ, United States, 2Philips Healthcare, Gainesville, FL, United States Watch the Video EPI-based DWI is widely used in the clinic but suffers from geometric distortions. DW-PROPELLER, based on FSE, is free from geometric distortions but has low scan efficiency. X-PROP was developed to improve FSE-based DW-PROPELLER scan efficiency by employing a GRASE readout. Although more efficient, XY2 phase modulation used in X-PROP is sensitive to the flip angles of the RF pulse train. This project improves X-PROP image quality by incorporating LRX phase modulation to increase SNR and signal stability. Image quality improvement was illustrated by comparing in vivo images produced with LRX phase modulation, XY2 phase modulation, and SPLICE PROPELLER imaging. 4307 Practical considerations of DW-MRS with ultra-strong diffusion gradients Christopher Jenkins1, Elena Kleban1, Lars Mueller1, John Evans1, Umesh Rudrapatna1, Derek Jones1, Francesca Branzoli2, Itamar Ronen3, and Chantal M.W Tax1 1CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Centre for NeuroImaging Research - CENIR, Brain and Spine Institute - ICM, Paris, France, 3Department of Radiology, Leiden University Medical Center, Leiden, Netherlands View the Poster Diffusion-weighted magnetic resonance spectroscopy benefits from the use of ultra-strong gradients. Slow diffusing metabolites necessitate a large range of b-values to accurately model the diffusion properties. Ultra-strong gradients open the possibility of higher b-values and reduced diffusion times, alleviating some of these constraints. We present initial data acquired with DW-PRESS on a 300mT/m gradient Connectom scanner, and introduce the practical considerations associated with ultra-strong gradients. 4308 50-Fold Acceleration of Diffusion MRI via Slice-Interleaved Diffusion Encoding (SIDE) Yoonmi Hong1, Wei-Tang Chang1, Geng Chen2, Ye Wu1, Weili Lin1, Dinggang Shen1, and Pew-Thian Yap1 1University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 2Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates View the Poster We present a sampling and reconstruction scheme that,  when combined with multi-band imaging, accelerates dMRI acquisition by as much as 50 folds. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume for each diffusion wavevector, we acquire for each repetition time (TR) a volume consisting of interleaved slice groups, each corresponding to a different diffusion wavevector. This in effect results in a subsample of slices for each diffusion wavevector, based on which we can recover the full volumes for all wavevectors using a graph convolutional neural network (GCNN). 4309 Investigating the effect of diffusion MRI acquisition parameters on free water signal fraction estimates from 3-tissue CSD techniques Benjamin T Newman1,2, Thijs Dhollander3,4, and T. Jason Druzgal1,2 1Department of Radiology & Medical Imaging, Division of Neuroradiology, University of Virginia Health System, University of Virginia, Charlottesville, VA, United States, 2Brain Institute, University of Virginia, Charlottesville, VA, United States, 3The Florey Department of Neuroscience, University of Melbourne, Melbourne, Australia, 4The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia Watch the Video The CSF-like free water signal fraction is an advanced diffusion MRI metric representing the freely diffusing water in brain tissue. Different methods to calculate the free water signal fraction using constrained spherical deconvolution exist but it is still unknown how variation in data quality and acquisition affect measurements. Using a large clinical dataset with highly variable acquisition schemes, this study shows that the various acquisition parameters significantly affect outcome free water signal fraction, though the multi-shell analysis method is more susceptible than the single-shell method. This highlights the importance of harmonization and quality clinical imaging. 4310 Clinical Microscopic Fractional Anisotropy Imaging in 4 Minutes: an Optimization Approach Nico J. J. Arezza1,2, Desmond H. Y. Tse2, Aidin Arbabi2, and Corey A. Baron1,2 1Medical Biophysics, Western University, London, ON, Canada, 2Center for Functional and Metabolic Mapping, Robarts Research Institute, London, ON, Canada Watch the Video Microscopic diffusion anisotropy ($$\mu A$$$) and microscopic fractional anisotropy ($$\mu FA$$$) quantify water diffusion anisotropy in tissue with no influence from neuron fiber orientation. Here, we characterized $$\mu A^2$$$signal-to-noise ratio using standard error propagation to determine the b-value and ratio of linear to isotropic encodings needed to maximize image quality. This optimization enabled an MRI protocol that utilizes efficient isotropic diffusion encoding to acquire high-quality full-brain $$\mu A^2$$$ and $$\mu FA$$maps in 2.4 and 4 minutes, respectively, which are demonstrated in two healthy volunteers at 3T. 4311 Novel practical SNR determination method for MRI using combined largest b-value and echo time (COLBET) Hirotaka Oyabu1, Tosiaki Miyati1, Naoki Ohno1, Toshifumi Gabata1, and Satoshi Kobayashi1 1Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan Poster Permission Withheld We developed a novel practical SNR measurement method using combined the largest b-value and echo time (COLBET). The COLBET method makes it possible to simply and practically perform image SNR quantitation including the long T2 region in human with parallel imaging. 4312 Investigating the reproducibility of 4th order Spherical Harmonics dMRI Rotation Invariant Features in White Matter Mauro Zucchelli1, Samuel Deslauriers-Gauthier1, and Rachid Deriche1 1Athena Project-Team, Inria Sophia Antipolis - Méditerranée, Université Côte d'Azur, Sophia Antipolis - Méditerranée, France Watch the Video Rotation invariant features can potentially be used as biomarkers for diffusion MRI. One of the most important characteristics of biomarkers is their reproducibility. In the case of diffusion MRI, reproducibility means that if we acquire data from the same subject twice with a short time gap between the two acquisitions we should obtain the same values for the biomarkers. In this work, we investigate the reproducibility of 12 new rotation invariant features that we obtained from 4th order spherical harmonics. Our results suggest that the new invariants are reproducible and can be selected as biomarker-candidates for white matter. Back to Top Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis Session Sub-Topic: Diffusion: Acquisition 2 Digital Poster Diffusion  4313 Whole-Tumor Histogram Analysis of Breast Lesions Based on Simultaneous Multi-slice Readout-segmented Echo-planar Imaging Xue Li1, Kun Sun1, Wei Liu2, Robert Grimm3, Caixia Fu2, and Fuhua Yan1 1Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, 3Application Predevelopment, Siemens Healthcare, Erlangen, Germany View the Poster This study compared the diagnostic performance of the ADC derived from the diffusion-weighted readout-segmented EPI DWI accelerated with SMS technique (SMS rs-EPI DWI) with that derived from the conventional rs-EPI DWI on breast lesions using whole-tumor histogram analysis. Our results showed that the SMS technique can increase the spatial resolution of the rs-EPI DWI sequence without prolonging the scan time. It can also improve the diagnostic performance of the derived ADC map based on whole-tumor histogram analysis in distinguishing benign and malignant breast lesions. 4314 Determination of the optimal set of b-values for Intravoxel Incoherent Motion (IVIM) parameter mapping in liver Diffusion-Weighted MRI Óscar Peña-Nogales1, Rodrigo de Luis-Garcia1, and Santiago Aja-Fernández1 1Laboratorio de Procesado de Imagen, Universidad de Valladolid, Valladolid, Spain View the Poster Estimation of Intravoxel Incoherent Motion (IVIM) parameter maps from a set of diffusion-weighted (DW) images acquired at multiple b-values usually suffers from low SNR, which may increase the variance of the estimated maps. Unfortunately, there is no consensus on the optimal b-values to maximize the noise performance of IVIM parameters. In this work, we determine the optimal b-values to maximize the performance of IVIM parameter mapping by using a Cramér-Rao Lower Bound approach under realistic noise assumptions. The reduction of the estimation variance on the IVIM parameters compared to state-of-the-art b-values suggests the utility of this approach to optimize DW-MRI. 4315 Intravoxel incoherent motion analysis of the brain with second-order motion-compensated diffusion encoding Naoki Ohno1, Tosiaki Miyati1, Tetsuo Ogino2, Yu Ueda2, Yuki Koshino1,3, Yudai Shogan1,3, Toshifumi Gabata4, and Satoshi Kobayashi1 1Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan, 2Philips Japan, Tokyo, Japan, 3Radiology Division, Kanazawa University Hospital, Kanazawa, Japan, 4Department of Radiology, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Japan Poster Permission Withheld In this study, we compared diffusion parameters with intravoxel incoherent motion (IVIM) analysis of the brain between second-order motion-compensated (2nd-MC) and conventional (non-MC) diffusion encoding schemes. Perfusion-related diffusion coefficient with non-MC was strongly affected by bulk motion in the pons which has the largest motion in the brain. By contrast, the 2nd-MC diffusion gradients compensated the bulk motion-induced signal loss and improved the fitting accuracy of biexponential model. The 2nd-MC diffusion encoding reduces the bulk motion effect on IVIM analysis of the brain, thereby improving the measurement accuracy. 4316 Oscillating Gradient (OG) Prepared 3D-GRASE Sequence for Improved OG-Diffusion MRI Dan Wu1, Dapeng Liu2, Yi-Cheng Hsu3, Haotian Li1, Yi Sun3, Qin Qin2, and Yi Zhang1 1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2Johns Hopkins University School of Medicine, BALTIMORE, MD, United States, 3MR Collaboration, Siemens Healthcare Ltd., Shanghai, China Watch the Video Oscillating gradient enables access of short diffusion times for time-dependent diffusion MRI (dMRI), but poses challenges for clinical use, including limited oscillating frequencies and b-values, low SNR, and relatively long scan times. This study proposes a 3D oscillating gradient prepared gradient spin-echo sequence (OGprep-GRASE) to improve the SNR and shorten the acquisition time for OG-dMRI. The proposed sequence reduced the scan time by a factor of 1.38 and increased the SNR by 1.74 times, compared with the existing 2D echo-planar imaging (EPI) approach, leading to improved diffusion tensor reconstruction. Diffusivity measurements showed similar time-dependency using the GRASE and EPI sequences. 4317 TGSE diffusion-weighted pulse sequence in the evaluation of optic neuritis: A comprehensive comparison of image quality with RESOLVE DWI Ting Yuan1, Yan Sha2, Zhongshuai Zhang3, Xilan Liu4, Xinpei Ye5, Yaru Sheng5, Kun Zhou6, and Caixia Fu6 1Shanghai Insititute of Medical Imaging, Shanghai, China, 2Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, China, 3Siemens Healthcare Ltd, Shanghai, China, 4Department of Radiology, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University, Shanghai, China, 5Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, China, 6Department of Digitalization, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China This study investigated the role of RESOLVE and TGSE DWI sequences in the evaluation of optic neuritis and compared their image qualities qualitatively and quantitatively. We found that TGSE significantly improved the image quality for the evaluation of optic neuritis by reducing the susceptibility induced image distortion compared with RESOLVE. However, it appeared lower SNR and CNR than that of RESOLVE images. 4318 Automatic no-reference image quality evaluation of DWI in uterine malignancy at 3T with iShim, RESOLVE, and ss-EPI sequences – a feasibility study Qi Zhang1, Xiaoduo Yu1, Jieying Zhang1, Xinming Zhao1, Han Ouyang1, Hongmei Zhang1, Qinglei Shi2, Xiang Feng2, and Xiaoye Wang2 1Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China, 2MR Scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Beijing, China This study proposed an automatic image quality evaluation method using no-reference image quality metrics of structural similarity index (SSIM), blind/referenceless image spatial quality evaluator (BRISQUE), perception based Image quality evaluator (PIQE), SNR Wavelet and Contrast. The SNR Wavelet was calculated by the quotient of the image before wavelet filtering and the difference between the image before wavelet filtering and the image after wavelet filtering. The contrast was calculated using the average signal difference of three to five gray bars in the middle position. This study showed the automatic no-reference image quality metrics have potentials in future application of evaluating the image quality of uterine malignancy DWI at 3T with a higher efficiency. 4319 Performance comparison of three b-value sampling schemes in multiple diffusion models, including DTI, DKI, NODDI and MAP-MRI Huiting Zhang1, Ankang Gao2, Shaoyu Wang1, Yang Song3, Jingliang Cheng2, Guang Yang3, and Xu Yan1 1MR Scientific Marketing, Siemens Healthcare, Shanghai, China, 2The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal Univeristy, Shanghai, China View the Poster This study aimed to evaluate the performance of three b-value sampling schemes in calculating multiple diffusion models, including the DTI, DKI, NODDI and the newly proposed mean apparent propagator (MAP)-MRI models. The three schemes includes the conventional diffusion spectrum imaging (DSI) acquisition scheme based on Cartesian grid sampling in q-space, multi-shell sampling with the same (MDDW) or different (FREE) gradient directions in each shell. Each scheme supports the estimation of all the four models. The results showed that generally three schemes generated very similar parameters, and could be all used in future studies. 4320 Isotropic sampling for skewed encoding: novel rotation schemes for non-axisymmetric encoding objects in diffusion MRI Carl-Fredrik Westin1,2 and Filip Szczepankiewicz1,2 1Harvard Medical School, Boston, MA, United States, 2Brigham and Women's Hospital, Boston, MA, United States View the Poster In this work we propose novel sampling schemes for diffusion MRI required for encoding with objects with more than one directional axis. The presented solution is general and suitable for both axisymmetric and non-axisymmetric encoding schemes. An important feature of the presented sampling schemes is that they can be interleaved and be complimentary. This means that any combination of them can be used to define an isotropic sampling scheme with number of samples: (15, 30, 45, 60, 75, 90). 4321 Optimal experimental design for multi-tissue spherical deconvolution of diffusion MRI Jan Morez1, Jan Sijbers1, and Ben Jeurissen1 1imec-Vision Lab, Dept. Physics, University of Antwerp, Antwerp, Belgium View the Poster Multi-tissue constrained spherical deconvolution of multi-shell diffusion weighted MRI data estimates the white matter fiber orientation distribution function, together with the densities of gray matter and cerebrospinal fluid. In this work, we propose a 5-minute scanning protocol that allows a more precise estimation of WM and GM densities, while maintaining a high angular resolution. 4322 Ultra-high b-value single-shot echo planar diffusion-weighted imaging with Compressed SENSE Kayoko Abe1, Kazufumi Suzuki1, Masami Yoneyama2, and Shuji Sakai1 1Diagnostic Imaging and Nuclear Medicine, Tokyo Women's Medical University, Tokyo, Japan, 2Philips Japan, Tokyo, Japan View the Poster High b-value single-shot echo planar diffusion-weighted imaging (EPI-DWI) has been expected to provide more detail information about brain structure and diseases. However, higher b-value causes lower image quality due to an increase in noise-like artifacts. Compressed SENSE (C-SENSE), which is a combination of compressed sensing and parallel imaging technique: SENSE is an accelerating scan technique, which includes noise reduction methods. In this study, we revealed that EPI-DWI images with C-SENSE using high b-values (b:1000, 2000, 3000, 4000, 5000 s/mm2) showed higher SNR and ADC values than EPI-DWI images with SENSE. 4323 Q-Space Trajectory Imaging Using the MAGNUS High-Performance Head Gradient Grant Kaijuin Yang1,2, Ek Tsoon Tan3, Eric Fiveland4, Thomas Foo4, and Jennifer McNab2 1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States, 3Hospital for Special Surgery in Manhattan, New York, NY, United States, 4GE Global Research, Niskayuna, NY, United States View the Poster In this work, q-space trajectory imaging was implemented on a whole-body system equipped with a high-performance head-only gradient system capable of 200 mT/m maximum gradient amplitude and 500 T/m/s slew rate. The improved gradient performance enabled the acquisition of q-space trajectory imaging with sub-millimeter in-plane resolution and reduced voxel volume compared to previously published work, while simultaneously improving head coverage, and reducing susceptibility induced image distortions. 4324 Implementation of a Diffusion-Weighted Echo Planar Imaging sequence using the Open Source Hardware-Independent PyPulseq Tool Rita G. Nunes1, Keerthi Sravan Ravi2, Sairam Geethanath2, and J. Thomas Vaughan Jr2 1Instituto Superior Técnico, Lisbon, Portugal, 2Columbia University Magnetic Resonance Research Center, New York, NY, New York, NY, United States View the Poster Diffusion-weighted imaging is an essential sequence for many clinical applications. While the post-processing tools for diffusion are widely available, vendor-neutral, open-source acquisition implementations have not been shared for research purposes. We develop a cross-vendor, open source package of a multi-slice single-shot spin echo-planar imaging based diffusion pulse sequence, capable of multiple b values and directions. We demonstrate this on an in vitro phantom, measuring plausible Apparent Diffusion Coefficient values and in vivo human brain data, obtaining good quality Fractional Anisotropy and Mean Diffusivity maps. We process our data with freely available post-processing tools to generate quantitative diffusion maps. 4325 Feasibility and evaluation of whole brain single-slab 3D DWI and comparison to 2D multi-slice DWI Neville D Gai1 and John A Butman1 1National Institutes of Health, Bethesda, MD, United States View the Poster While most brain imaging sequences now favor their 3D counterparts, diffusion imaging is an exception. This is due to large diffusion gradients resulting in increased sensitivity to motion exhibited by 3D acquisition. Prior schemes have used limited brain coverage and/or triggering or acquired multiple 3D slabs along with modified reconstruction schemes. The modified sequence used here employs first-order motion compensated diffusion gradients in addition to real-time alignment to acquire whole brain 3D-DWI images as a single slab. Relatively shorter TE (using enhanced gradients) and TR along with other modifications result in faster, reduced artifact diffusion images while providing higher SNR. 4326 Investigating restricted diffusion within different cortical regions using double-diffusion encoding Qiuyun Fan1, Thomas Witzel1, Slimane Tounekti1, Qiyuan Tian1, Chanon Ngamsombat1, Maya Polackal1, Aapo Nummenmaa1, and Susie Huang1 1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States View the Poster We report the acquisition of whole brain, 2-mm isotropic resolution DDE data in a healthy volunteer using an orientationally invariant sampling scheme and quantify the mean DDE signal intensity across cortical regions as a measure of diffusion restriction within different cortices. Higher mean signal intensities were observed in the cerebellum and limbic cortices, which are thought to reflect a higher degree of restriction in the tissue microstructural environment and may correspond to densely packed, small granule and pyramidal cells known to be present in these regions. Back to Top Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis Session Sub-Topic: Diffusion: Acquisition & Reconstruction Digital Poster Diffusion  4327 Radial diffusion-weighted MRI enables motion-robustness and reproducibility for orthotopic pancreatic cancer in mouse Jianbo Cao1, Stephen Pickup1, Hanwen Yang1, Victor Castillo1, Cynthia Clendenin2,3, Peter O’Dwyer2,3, Mark Rosen1,3, and Rong Zhou1,3 1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Pancreatic Cancer Research Center, University of Pennsylvania, Philadelphia, PA, United States, 3Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, United States View the Poster Diffusion weighted (DW)-MRI is sensitive to tumor microenvironment (TME) thus useful for assessing pancreatic cancer responses to stroma-directed drugs, as they change TME by degradation or reduction of extracellular matrix. Motion-sensitive location of pancreatic tumor and fast respiration rate of mice impose a big challenge for quantitative DW-MRI. We compared radial k-space and echo-planar imaging based DW protocol for their accuracy and test-retest reproducibility. EPI-DW consistently underestimates water ADC value at 37C (reference to literature) where radial-DW does not. Better test-retest producibility measured by within-subject CV is obtained with radial-DW compared to EPI-DW. 4328 Correction for the influence of transmit-inhomogeneity in DW-SSFP on signal and ADC estimates in whole post-mortem brains at 7T Benjamin C Tendler1, Sean Foxley2, Moises Hernandez-Fernandez3, Michiel Cottaar1, Olaf Ansorge4, Saad Jbabdi1, and Karla Miller1 1Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 2Department of Radiology, University of Chicago, Chicago, IL, United States, 3Centre for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, United States, 4Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom Watch the Video Diffusion-weighted steady-state free precession (DW-SSFP) generates high SNR diffusivity estimates in whole, post-mortem human brains. Improved estimates at 7T has motivated its use at ultra-high field. However, the DW-SSFP signal has a strong dependence on flip angle. This translates into both variable signal amplitude and diffusion contrast. At 7T, transmit-($$B_{1}^{+}$$) inhomogeneity leads to $$B_{1}^{+}$$$-dependent SNR and ADC estimates. Previous work corrected for $$B_{1}^{+}$$$-inhomogeneity by acquiring DW-SSFP datasets at two flip angles. Here, this approach is extended, utilising the full Buxton model of DW-SSFP to model non-Gaussian diffusion. A noise-floor correction and signal weighting are also incorporated to improve diffusivity estimates. 4329 Acceleration of multidimensional diffusion MRI data acquisition and post-processing using convolutional neural networks Yuan Zheng1, Tao Feng1, Sirui Li2, Wenbo Sun2, Qing Wei3, Samo Lasic4, Danielle van Westen5, Karin Bryskhe4, Daniel Topgaard4,5, and Haibo Xu2 1UIH America, Houston, TX, United States, 2Zhongnan Hospital of Wuhan University, Wuhan, China, 3United Imaging Healthcare, Shanghai, China, 4Random Walk Imaging, Lund, Sweden, 5Lund University, Lund, Sweden View the Poster Multidimensional diffusion MRI (dMRI) is a powerful tool that even in its simplest form provides more detailed microstructural information than conventional dMRI, such as microscopic anisotropy (µFA) unconfounded by orientation dispersion. However, it requires multiple diffusion encoding modes (usually directional and isotropic encodings) and, for the more advanced versions, prolonged scan and post-processing times. We proposed using convolutional neural networks (CNN) to accelerate multidimensional dMRI data acquisition and analysis, and have demonstrated that satisfactory µFA maps can be generated in real-time with only 50% of the encodings, which might help to better adapt multidimensional dMRI to clinical practices. 4330 Accelerating myelin-water imaging by extracting myelin content from anatomical and diffusion images through machine learning Gerhard S Drenthen1,2, Walter H Backes1, and Jacobus FA Jansen1,2 1Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands, 2Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands View the Poster In this study we aim to accelerate the acquisition time of myelin-water imaging by acquiring fewer slices and applying machine learning to extract myelin-specific information from anatomical (T1w and T2w) and diffusion-weighted imaging (DWI), which are commonly available in many clinical research studies. It is shown that with a 6-fold acceleration (from 7:30min to 1:15min) the myelin content can be reconstructed using neural networks with an agreement to the ground-truth that is comparable to the reproducibility of the scan itself. 4331 Single-Shot Diffusion-Weighted Spatiotemporal Encoding (SPEN) using Polarities Average Mode (PAM) to Correct Spatial-Dependent b-Values Lisha Yuan1, Yi-Cheng Hsu2, Dan Wu1, Hongjian He1, and Jianhui Zhong1,3 1Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China, 2MR Collaboration, Siemens Healthcare Ltd., Shanghai, China, 3Department of Imaging Sciences, University of Rochester, Rochester, NY, United States View the Poster Compared to traditional echo-planar imaging (EPI)-based schemes, spatiotemporal encoding (SPEN) is largely insensitive to magnetic field and chemical shift heterogeneities. However, excitation gradient has different effects for each position, thus the interaction between imaging and diffusion gradients introduces spatial-dependent diffusion weightings along the SPEN axis. A new method named polarities average mode (PAM) was proposed to obtain accurate apparent diffusion coefficient (ADC) map, with two acquisitions of different polarities between excitation and diffusion gradients. Simulation, phantom, and human experiments were designed to assess method performance. The proposed method enables SPEN to obtain ADC maps easily and accurately. 4332 Feasibility Study of applying Simultaneous Multi-slice technique in Diffusion Weighted Imaging of Breast Lesions Fei Wang1, Mengxiao Liu2, and Juan Zhu1 1Department of MRI,AnQing Municipal Hospital, Anqing, China, 2MR scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Shanghai, China View the Poster To evaluate the feasibility of applying simultaneous multi-slice (SMS) single-shot echo planar imaging (EPI) to accelerate MR diffusion imaging for breast carcinoma, fibroadenoma of breast and normal breast. SMS sequences with double and triple acceleration were compared with conventional DWI sequences, respectively. These SMS DWI sequences were compared to conventional DWI in terms of image quality parameters (5-point Likert scale) and SNR, ADC measurements. Comparing with conventional EPI-DWI, the SMS markedly reduces the diffusion scan time and the image SNR still shows a good quality. Thus, SMS technique is recommended for DWI of the MR breast examinations. 4333 The Use of Stimulated-Echo EPI to Obtain High b-Value DTI Data at Short TEs on a Clinical Scanner R. Allen Waggoner1, Thorsten Feiweier2, and Keiji Tanaka1 1Laboratory for Cognitive Brain Mapping, RIKEN - Center for Brain Science, Wako-shi, Japan, 2Siemens Healthcare GmbH, Erlangen, Germany Watch the Video On clinical scanners, high b-value diffusion studies using SE-EPI suffer from the need for long TEs, which leads to signal loss due to T2 decay.  Stimulated-Echo EPI permits high b-values together with short TEs on clinical scanners.  We demonstrate that tractograms obtained from high b-value STE-EPI images are clean even in regions where tractograms from SE-EPI images with the same b-values break down. 4334 Evaluating Diffusion Kurtosis Imaging Precision at Varying Gradient Strength in High Spatial Resolution 3T MRI Loxlan W Kasa1, Terry Peters2, Roy AM Haast3, and Ali R Khan4 1School of Biomedical Engineering, Imaging Research Laboratories, Robarts Research Institute, Western University, LONDON, ON, Canada, 2Imaging Research Laboratories, Robarts Research Institute, School of Biomedical Engineering,,Department of Medical Biophysics,Departments of Medical Imaging, Western University, London, ON, Canada, 3Imaging Research Laboratories, Robarts Research Institute, Western University, London, ON, Canada, 4Imaging Research Laboratories, Robarts Research Institute, School of Biomedical Engineering, Department of Medical Biophysics, Western University, London, ON, Canada View the Poster Diffusion kurtosis imaging (DKI), an extension to diffusion tensor imaging (DTI), aims to improve quantification of the hindered/restricted diffusion pattern due to microstructural complexity in the brain. But in order to capture the non-Gaussian diffusion behaviour of water molecules in biological tissues, stronger gradients larger than those employed in standard diffusion weighted imaging (DWI) are required. Here, we explored the test-retest reliability of DKI derived metrics with respect to different gradient strength in a high spatial resolution dataset. It was observed that DKI precision was comparable between b-value=1000, 2000, 3000 s/mm2 and b-value=1000 & 3000 s/mm2 dataset. 4335 Comparison of iShim, RESOLVE, and ss-EPI diffusion-weighted MR imaging with high b value at 3T MR in the evaluation of uterine malignancy Qi Zhang1, Jieying Zhang1, Xiaoduo Yu1, Han Ouyang1, Xinming Zhao1, Hongmei Zhang1, Qinglei Shi2, Xiang Feng2, and Xiaoye Wang2 1Department of Imaging Diagnosis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China, 2MR Scientific Marketing, Diagnostic Imaging, Siemens Healthcare Ltd, Beijing, China In the evaluation of uterine malignancy, conventional DWI based on single-shot echo-planar imaging (ss-EPI) is prone to imaging artifacts, including susceptibility artifacts from gas, imaging blurring, which limit its diagnostic value, especially in detecting and staging uterine malignancy. The purpose of this study is to compare the detection of uterine malignancy and image quality among DWI based on integrated slice-specific dynamic shimming (iShim), readout segmentation of long variable echo trains (RESOLVE) and ss-EPI sequence. Our results indicated that iShim DWI showed better image quality than ss-EPI and RESOLVE DWI in the terms of subjective image scores and objective quantitative metrics. 4336 Evaluation of simple acceleration strategy for advanced neural diffusion models based on half q-space under-sampling Min-xiong Zhou1, Huiting Zhang2, Yang Song3, Guang Yang3, and Xu Yan2 1Shanghai University of Medicine & Health Sciences, Shanghai, China, 2MR Scientific Marketing, Siemens Healthcare, Shanghai, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal Univeristy, Shanghai, China Advanced diffusion models such as NODDI, MAP-MRI are of high interests in brain research, but suffer from long acquisition time. Advanced under-sampling scheme were reported in previous studies for acceleration but are not commercially available. This study evaluates a simple and commercial available under-sampling scheme using the symmetric property of q-space, which could accelerate the acquisition by 2 fold. Results showed that it did not significant sacrifice the accuracy of quantitative maps. In addition, a symmetrically data copy step is needed to improve the estimation accuracy for both MAP-MRI and NODDI models. 4337 Readout-Segment Echo-Planar Imaging of Prostate, a Strategy to Reduce Geometrical Distortion in Prostate Diffusion Weighted Imaging Melina Hosseiny1, KyungHyun Sung1, Teeravut Tubtawee1, Voraparee Suvannarerg1, Shabnam Mortazavi1, Soheil Kooraki1, Saurab Gupta1, Afshin Azadikhah1, Justin Ching1, Ely R Felker1, David Lu1, and Steven S Raman1 1Abdominal Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States View the Poster Single-Shot Echo-Planar Imaging (ssEPI)is highly susceptible to T2* blurring and geometrical distortion. This study aimed to compare the image quality between ssEPI and Readout-Segment Echo-Planar Imaging (rsEPI) for acquiring prostate DWI on 162 patients. Geometrical distortion was ranked on ssEPI and rsEPI using a five-point scale. The geometrical distortion was significantly less observed in rsEPI compared to ssEPI (P<0.01).  Geometrical distortion scores of three and higher were observed in 30 individuals in ssEPI, with all having scores < 3 on rsEPI. In conclusion, using rsEPI for DWI acquisition may augment or replace ssEPI on 3T prostate mpMRI. 4338 DTI in early RRMS patients with correlation to clinical parameters and comparison to Healthy Controls Abdulaziz Alshehri1,2, Oun Al-iedani1,2, Jameen Arm1,2, Neda Gholizadeh1, Rodney Lea3, Jeannette Lechner-Scott3,4,5, and Saadallah Ramadan1,2 1School of Health Sciences, University of Newcastle, Newcastle, Australia, 2Imaging center, Hunter Medical Research Institute, Newcastle, Australia, 3Hunter Medical Research Institute, Newcastle, Australia, 4School of Medicine and Public Health, University of Newcastle, Newcastle, Australia, 5Department of Neurology, John Hunter Hospital, Newcastle, Australia View the Poster This study aims to evaluate and compare DTI parameters in relapsing-remitting MS patients with age and sex-matched healthy controls, and to correlate these DTI metrics with clinical symptoms and brain volumetric measures. As a result, There was a statistically significant increase in most of DTI parameters for RRMS patients compared with healthy controls. FA correlated positively with clinical parameters like EDSS and cognitive assessment. Both MD and RD correlated negatively with cognition parameters and positively with EDSS. Quantitative DTI parameters not only differentiate between RRMS patients and HCs, but are also associated with disability and mental health of RRMS. 4339 SENSE-based Multi-shot DWI Reconstruction with Extra-navigated Rigid Motion and Contrast Correction for Brain EPI Malte Steinhoff1, Alfred Mertins1, and Peter Börnert2,3 1Institute for Signal Processing, University of Luebeck, Luebeck, Germany, 2Philips Research Europe, Hamburg, Germany, 3Department of Radiology, LUMC, Leiden, Netherlands Watch the Video We propose an extra-navigated SENSE-based multi-shot DWI reconstruction algorithm that comprises navigator-based phase and rigid in-plane motion corrections at fast reconstruction times. Furthermore, this approach exploits the low-resolution navigator signal to perform diffusion contrast corrections explicitly within the model. The extra-navigated method is compared in-vivo to a self-navigated reference algorithm. The extra-navigated motion estimation from low-resolution navigator data yields decent reconstructions which perfectly coincide with self-navigated results. Moreover, extra-navigation allows for fast reconstruction at the cost of lower scan efficiency and appears to be more robust for strong motion corruption and high segmentations. 4340 Diffusion Weighted Imaging using PROPELLER Acquisition and a Deep Learning based Reconstruction Xinzeng Wang1, Daniel Litwiller2, Ali Ersoz3, Marc Lebel4, Sagar Mandava5, Lloyd Estkowski3, Arnaud Guidon6, Ann Shimakawa7, and Ersin Bayram1 1Global MR Applications & Workflow, GE Healthcare, Houston, TX, United States, 2Global MR Applications & Workflow, GE Healthcare, New York, NY, United States, 3Global MR Applications & Workflow, GE Healthcare, Waukesha, WI, United States, 4Global MR Applications & Workflow, GE Healthcare, Calgary, AB, Canada, 5Global MR Applications & Workflow, GE Healthcare, Tucson, AZ, United States, 6Global MR Applications & Workflow, GE Healthcare, Boston, MA, United States, 7Global MR Applications & Workflow, GE Healthcare, Menlo Park, CA, United States View the Poster PROPELLER DWI, a FSE based DWI method, is increasingly used to reduce susceptibility artifacts and motion artifacts. Multi-shot Echo-Planar diffusion method also can reduce susceptibility artifacts, but PROPELLER DWI shows better image quality where susceptibility artifacts are most problematic, such as in skull base, head-neck and pelvis. However, the acquisition time is often longer compared to ms-DW-EPI, therefore SNR is usually compromised to reduce acquisition time. In this work, we evaluated a deep-learning based reconstruction method (DL Recon PROP) intended to improve image quality and ADC measurements by reducing the noise and artifacts without increasing acquisition time. 4341 Model-Free, Fast, and Automated Correction of Diffusion Gradient Orientations Ye Wu1, Yoonmi Hong1, Weili Lin1, Pew-Thian Yap1, and the UNC/UMN Baby Connectome Project Consortium1 1Department of Radiology and BRIC, University of North Carolina, Chapel Hill, Chapel Hill, NC, United States View the Poster We propose a rapid and automated method to rectify incorrect gradient orientations resulting from inconsistencies in coordinate frame conventions across scanners, file formats, and processing tools. Using these incorrect gradient orientations will invalidate subsequent derived quantities that are dependent on local orientation information, particularly tractography. Our approach to correcting the gradient orientations is based on maximizing an orientation continuity index that is computed directly from the diffusion-weighted images without the need for model fitting. 4342 High-resolution distortion-free single-shot EPI enabled by deep-learning Zhangxuan Hu1, Zhe Zhang2, Yishi Wang3, Yajing Zhang4, and Hua Guo1 1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2China National Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 3Philips Healthcare, Beijing, China, 4MR Clinical Science, Philips Healthcare (Suzhou), Suzhou, China View the Poster Single-shot EPI (SS-EPI) is widely used for diffusion-weighted imaging (DWI), but suffers from susceptibility-induced distortion and T2* blurring, which limit its resolution and ability to detect detailed structures. Parallel imaging and multi-shot techniques can be used to improve the resolution and reduce image distortion. However, these techniques have their own drawbacks, such as limited achievable acceleration factors or prolonged acquisition time. In this study, a deep-learning based method is proposed to achieve high-resolution distortion-free DWI using SS-EPI thus to improve the acquisition efficiency and clinical applicability.

Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis
Session Sub-Topic: Diffusion: Reconstruction & Artefact Correction 1
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Diffusion

Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis
Session Sub-Topic: Diffusion: Reconstruction & Artefact Correction 2
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Diffusion

Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis
Session Sub-Topic: Diffusion: Methods
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Diffusion

Session Topic: Diffusion Acquisition, Reconstruction and Signal Analysis
Session Sub-Topic: Diffusion Signal Analysis 1
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Diffusion

 4405 DeepHIBRID: How to condense the sampling in the k-q joint space for microstructural diffusion metric estimation empowered by deep learning Qiuyun Fan1, Qiyuan Tian1, Chanon Ngamsombat1, and Susie Y. Huang1 1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States View the Poster Conventional diffusion imaging protocols may require tens or hundreds of samples in the q-space to generate reliable maps. Knowing that the k-q joint space is highly redundant and given the tradeoffs between k, q and SNR, we trained a deep convolutional neural network using a HIgh B-value and high Resolution Integrated Diffusion (HIBRID) sampling scheme, dubbed DeepHIBRID. We show DeepHIBRID outperforms conventional sampling schemes, and is capable of outputting 14 synthesized diffusion metric maps simultaneously with only 10 input images, without sacrificing the quality of the output maps, using 30x angular downsampling. 4406 A Theoretical Framework for Representing and Estimating a Normal Diffusion Tensor Distribution Magdoom Kulam Najmudeen1, Dario Gasbarra2, and Peter J Basser1 1SQITS/NICHD, National Institute of Health, Bethesda, MD, United States, 2University of Helsinki, Helsinki, Finland Video Permission Withheld A new signal model is introduced for diffusion tensor distribution imaging which is monotonically decreasing for all b-values unlike the cumulant and kurtosis models. A constrained multi-normal distribution is used as the tensor distribution which is fully characterized by the 2nd order mean and 4th order covariance tensors. A theoretical framework is presented showing the richness of covariance tensor, using synthetic gray and white matter voxels, and the ability to estimate the mean and covariance tensor from noisy MR signal. 4407 Estimating distributions of diffusion tensors and longitudinal relaxation rates in the brain via Monte-Carlo inversion: a proof of principle Alexis Reymbaut1,2, Jeffrey Critchley3, Giuliana Durighel3, Tim Sprenger4,5, Michael Sughrue6, and Daniel Topgaard1,2 1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Spectrum Medical Imaging, Sydney, Australia, 4Karolinska Institute, Stockholm, Sweden, 5GE Healthcare, Stockholm, Sweden, 6Charlie Teo Foundation, Sydney, Australia View the Poster Conventional $$T_1$$$-mapping techniques are only sensitive to voxel-averaged $$T_1$$$ values, which hinders the study of fiber-specific myelination changes in the developing, aging or diseased brain. While recent works have focused on combining diffusion- and $$T_1$$$- weightings to access orientation-resolved $$T_1$$$ values, they rely on assumptions regarding the voxel content. This work combines a prototype diffusion-relaxation MR acquisition and a Monte-Carlo inversion method to extract intra-voxel nonparametric 5D distributions of diffusion tensors and longitudinal relaxation rates $$R_1=1/T_1$$$without the use of limiting assumptions. Estimated $$R_1$$$ values are then mapped onto nonparametric orientation distribution functions, thereby yielding fiber-specific longitudinal relaxation rates. 4408 General tools for diffusion tensor distributions, and matrix-variate Gamma approximation for multidimensional diffusion MRI data Alexis Reymbaut1,2 1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden View the Poster Either on the voxel scale or within sub-voxel diffusion compartments, tissue microstructure can be described using a diffusion tensor distribution $$\mathcal{P}(\mathbf{D})$$$. One way to resolve microstructural heterogeneity relies on choosing a plausible parametric functional form to approximate $$\mathcal{P}(\mathbf{D})$$$. However, such a high-dimensional mathematical object is usually intractable. Here, we define matrix moments enabling the computation of diffusion metrics for any arbitrary functional choice approximating $$\mathcal{P}(\mathbf{D})$$$. Applying these general tools to the matrix-variate Gamma distribution on the voxel scale, we obtain a new signal representation, the matrix-variate Gamma approximation, that we validate in vivo and in silico. 4409 Resolving orientation-specific diffusivities and transverse relaxation rates in heterogenous brain tissue Alexis Reymbaut1,2, João Pedro de Almeida Martins1,2, Chantal M. W. Tax3, Filip Szczepankiewicz2,4,5, Derek K. Jones3, and Daniel Topgaard1,2 1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 4Harvard Medical School, Boston, MA, United States, 5Radiology, Brigham and Women’s Hospital, Boston, MA, United States View the Poster Due to their cubic-millimeter scale, white-matter diffusion MRI voxels are often heterogeneous, comprising not only multiple fibre bundles but also grey matter, cerebrospinal fluid, or pathological tissue. To tackle this problem, conventional approaches rely on assumptions regarding tissue properties. This work combines state-of-the-art diffusion-relaxation MR acquisition and processing methods to extract intra-voxel nonparametric 5D distributions of diffusion tensors and transverse relaxation rates $$R_2$$$ without the use of limiting assumptions. Orientation-resolved (fibre-specific) means of isotropic diffusivities, diffusion anisotropies and $$R_2$$$values are then obtained via clustering within the orientation subspace of these 5D distributions. 4410 Trueness and precision of statistical descriptors obtained from multidimensional diffusion signal inversion algorithms Alexis Reymbaut1,2, Paolo Mezzani1,3, João Pedro de Almeida Martins1,2, and Daniel Topgaard1,2 1Physical Chemistry, Lund University, Lund, Sweden, 2Random Walk Imaging AB, Lund, Sweden, 3Physics, Università degli Studi di Milano, Milan, Italy View the Poster In first approximation, the diffusion signal writes as the Laplace transform of an intra-voxel diffusion tensor distribution (DTD). Several algorithms have been introduced to estimate the DTD’s statistical descriptors (mean diffusivity, variance of isotropic diffusivities, mean squared diffusion anisotropy, etc.) by inverting data obtained from tensor-valued diffusion encoding schemes. However, the trueness and precision of these estimations have not been systematically assessed and compared across methods. Here, we compare such estimations in silico for a 1D Gamma fit, a generalized two-term cumulant approach, and 2D and 4D Monte-Carlo inversion techniques, using a common and clinically feasible tensor-valued acquisition scheme. 4411 Spatiotemporal evolution of ischemic lesions in stroke animal models using free-water elimination and mapping with explicit T2 modelling Ezequiel Farrher1, Chia-Wen Chiang2, Kuan-Hung Cho2, Richard Buschbeck1, Ming-Jye Chen2, Zaheer Abbas1, Kuo-Jen Wu3, Yun Wang3, Farida Grinberg1, Chang-Hoon Choi1, N. Jon Shah1,4,5,6, and Li-Wei Kuo2,7 1INM-4, Forschungszentrum Jülich, Jülich, Germany, 2Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, 3Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan, 4Department of Neurology, RWTH Aachen University, Aachen, Germany, 5JARA – BRAIN – Translational Medicine, RWTH Aachen University, Aachen, Germany, 6Institute of Neuroscience and Medicine 11, JARA, Forschungszentrum Jülich, Jülich, Germany, 7Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan View the Poster It is known that excess fluid as a result of vasogenic oedema formation following stroke onset obscures the microstructural characterisation of ischemic tissue by diffusion MRI. DTI-based free water elimination and mapping (FWE) has been proposed as a technique to potentially reduce the partial-volume effect. However, FWE estimation is ill-conditioned, leading to inaccurate results. More recently, it has been shown that the addition of a second dimension spanned by transverse relaxation weighting, mitigates the ill-conditioned problem. We aim here to investigate the latter model in a longitudinal study of MCAo stroke animal models. 4412 Impact of gradient non-linearities on B-tensor diffusion encoding Michael Paquette1, Chantal M.W. Tax2, Cornelius Eichner1, and Alfred Anwander1 1Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2CUBRIC, School of Physics, Cardiff University, Cardiff, United Kingdom Watch the Video We investigate the effect of gradient non-linearities (GNL) on free gradient waveform used for B-tensor diffusion encoding. We show the magnitude of the GNL-bias for strong gradients of $$300 m\text{T}/\text{m}$$$. We derive a closed-form formula of the voxelwise B-tensor under GNL, independent of the choice of gradient waveform used to encode the B-tensor. 4413 Multi-dimensional Moment Imaging (MMI) for probing tissue microstructure Lipeng Ning1,2, Filip Szczepankiewicz1,2, Borjan Gagoski2,3, Carl-Fredrik Westin1,2, and Yogesh Rathi1,2 1Brigham and Women's Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Boston Children's Hospital, Boston, MA, United States View the Poster Multi-dimensional imaging techniques can provide complementary information to investigate the microscopic organizations of biological tissue. Deriving meaningful indices from these multi-dimensional imaging data is important to make these techniques relevant to clinical research. In this work, we introduce a general framework to estimate the moments of the joint probability distribution of T1, T2 relaxation and diffusion coefficients. This framework is an extension of our previously introduced REDIM approach which only focused on joint moments of T2 relaxation and diffusion. We show the cross coupling between different parameters using three datasets acquired using different protocols. 4414 Anomalous diffusion MRI model parameters vary in the human corpus callosum sub-regions with age Qianqian Yang1 and Viktor Vegh2 1School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia, 2Centre for Advanced Imaging, University of Queensland, Brisbane, Australia Poster Permission Withheld Diffusion MRI measures of the human brain provide key insight into microstructural variations across individuals and into the impact of central nervous system diseases and disorders. One approach to extract information from diffusion signals has been to use biologically relevant analytical models to link millimetre scale diffusion MRI measures with microscale influences. The other approach has been to represent diffusion as an anomalous process, and infer information from the different anomalous diffusion equation parameters. Here, we show how parameters of three established anomalous diffusion equations change with age, in a microstructurally complex tissue, the human corpus callosum. 4415 Weighted linear least squares in multi-shell diffusion MRI: Should high b-shells always be weighted less? Jordan A. Chad1,2 and Ofer Pasternak3 1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States View the Poster Fitting diffusion MRI signal models with the standard weighted linear least squares (WLLS) approach necessarily places lower weight on data with lower SNR, therefore placing lower weight on shells with higher b-values. This can be non-optimal for fitting signal models that rely on information from high b-shells. In this work, we propose a “nested” WLLS approach where each shell is assigned a relative weight, with standard WLLS applied within each shell. We demonstrate that weighting shells equally may be beneficial for fitting signal models dependent on multiple shells. 4416 Exploring effects of membrane permeability on dMRI metrics with Analytical solutions and Monte Carlo simulations Zihan Zhou1, Qiuping Ding1, Hongjian He1, and Jianhui Zhong1,2 1Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China, 2School of Medicine and Dentistry, University of Rochester Medical Center, New York, NY, United States Watch the Video White Matter Tract Integrity (WMTI) is a biophysical model with specificity to underlying tissue microstructures. However, recent work has suggested that inter-compartmental water exchange may affect outcomes of the model metrics. In this work, we analytically relate the WMTI-derived dMRI metrics to membrane permeability, and validate our predictions using Monte Carlo simulations. Our results show that the water exchange has a non-trivial effect on the metrics and needs to be carefully considered in WMTI. 4417 Application of MAP diffusion modelin differential diagnosis between high-grade glioma and single brain metastatic tumor BO LI1, YANG GAO1, SHAOYU WANG2, YAN XU2, GUANG YANG3, and HUAPENG ZHANG2 1Department of Radiology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China, 2MR Sicentific Marketing, Siemens Healthineers, Shanghai, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China This study aimed at using mean-apparent-propagator (MAP) diffusion model in differential diagnosis of high-grade glioma and single brain metastatic tumor.the findings show that multiple parameters quantified by DSI quantitative model MAP MRI, especially MSD and QIV has high applicatical value and provides more information for preoperative diagnosis of patients. 4418 A New Method for Reconstructing the Orientation Distribution Function in HARDI Diwei Shi1, Xuesong Li2, Ziyi Pan2, Hua Guo2, and Quanshui Zheng1 1Center for Nano & Micro Mechanics, Tsinghua University, Beijing, China, 2Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China View the Poster We propose a novel definition of orientation distribution function (ODF), which also represents diffusion coefficients for non-Gaussian situations, thus ODF has physical meaning. Then an expression is derived to calculate ODF values through diffusion-weighted signals. Next a new HARDI (high angular resolution diffusion imaging) method called “g-OPDT” (grids orientation probability density transform) is designed for practical use. Numerical simulations are performed to verify its accuracy. ISMRM-2015-Tracto-challenge data are used to quantitatively compare g-OPDT with other methods. Results show that g-OPDT has superior performance on most indicators. In-vivo experiments are conducted to show that its glyph representations have less redundant lobes. 4517 Quantification of uncertainty in parameterisations of cardiac myofibre orientations from diffusion-weighted imaging Bianca Freytag1, Vicky Y Wang2, Alistair A Young3, and Martyn P Nash1 1Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand, 2Veterans Affairs Medical Center, San Francisco, CA, United States, 3Biomedical Engineering Department, King's College London, London, United Kingdom Watch the Video Electro-mechanical models of heart function rely upon accurate representation of microstructural orientations in the myocardium. We assessed the sensitivity of a finite element parameterisation of the myofibre orientation field derived from high-resolution DWI data of a canine heart. Eigenanalysis of the indifference region in the neighbourhood of the optimal fit of the myofibre field enabled quantification of helix angle uncertainty consistent with the DWI data. This method can be used to propagate the uncertainty in myofibre parameterisation to electro-mechanics simulation results.