| Computer # |
| 2435.
 | 113 | Comparison of time-division multiplexing and multi-echo sequences for accelerated relaxation diffusion MRI Qiang Liu1,2, Ante Zhu3, Imam Ahmed Shaik1, Maxim Zaitsev4, Thomas Foo3, Jon-Fredrik Nielsen5, Carl-Fredrik Westin1, Yogesh Rathi1, and Lipeng Ning1
1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 2School of Biomedical Engineering, Southern Medical University, Guangzhou, China, 3Technology and Innovation Center, GE Healthcare, Niskayuna, NY, United States, 4Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany, 5fMRI Laboratory and Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States Keywords: Diffusion Acquisition, Quantitative Imaging Motivation: Compare multi-echo and time-division multiplexing (TDM) sequences that accelerate multi-TE dMRI scans.
Goal(s): To investigate the accuracy of multi-TE diffusion measures using multi-echo and TDM sequences.
Approach: Standard single-TE spin-echo echo-planar imaging (EPI), dual-echo EPI, and TDM-EPI sequences were implemented using Pulseq with matched diffusion and readout gradients. A calibration phantom and a human subject were scanned on two scanners to examine the accuracy of R2 (1/T2) and apparent diffusivity coefficient (ADC) maps. Results: TDM demonstrates up to 160% reduction in estimated R2 on phantom and 30% in in-vivo data compared to dual-echo sequence.
Impact: The proposed TDM sequence allows for fast and accurate T2 and ADC estimation compared to the conventional multi-echo sequence, making it a potential tool for relaxation-diffusion imaging. |
| 2436.
 | 114 | Ultra-high resolution b-tensor encoding using gSlider on a clinical scanner Qiang Liu1,2, Congyu Liao3,4, Borjan Gagoski5, William Grissom6, Maxim Zaitsev7, Jon-Fredrik Nielsen8, Berkin Bilgic9,10, Carl-Fredrik Westin1, Lipeng Ning1, and Yogesh Rathi1
1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 2School of Biomedical Engineering, Southern Medical University, Guangzhou, China, 3Department of Radiology, Stanford University, Stanford, CA, United States, 4Department of Electrical Engineering, Stanford University, Stanford, CA, United States, 5Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States, 6Department of Biomedical Engineering, Case School of Engineering, Case Western Reserve University, Cleveland, OH, United States, 7Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany, 8fMRI Laboratory and Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, 9Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 10Department of Radiology, Harvard Medical School, Boston, MA, United States Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques Motivation: Spherical tensor encoding (STE) reveals microstructural information about tissues, which is hidden in conventional diffusion MRI techniques. However, existing STE acquisition techniques have low spatial resolution which masks intricate anatomical details. Goal(s): To increase the spatial resolution of STE using the SNR-efficient gSlider sequence.
Approach: Isotropic b-tensor encoding diffusion-gradient waveforms were synergistically combined with the gSlider sequence using Pulseq vendor-neutral sequence development platform to obtain high resolution data. Results: We demonstrate in-vivo results with the highest spatial resolution to-date of 1 mm isotropic voxels using the proposed STE-gSlider sequence.
Impact: High spatial resolution for b-tensor encoding will enable investigation of microstructural information in intricate detail in the brain in health and disease. Further, the proposed open-source sequence can be used on any vendor platform. |
| 2437.
 | 115 | Submillimeter Isotropic Whole Brain DTI at 3T with 2D Multi-band Multi-shot EPI Acquisition and Deep Learning Reconstruction Baolian Yang1, Xinzeng Wang2, Christopher Petty3, Arnaud Guidon4, R. Marc Lebel5, Suchandrima Banerjee6, and Allen Song3
1GE Healthcare, Waukee, WI, United States, 2GE Healthcare, Houston, TX, United States, 3Duke University Medical Center, Durham, NC, United States, 4GE Healthcare, Boston, MA, United States, 5GE Healthcare, Calgary, AB, Canada, 6GE Healthcare, Menlo Park, CA, United States Keywords: Tractography, Brain Connectivity Motivation: High resolution diffusion tensor imaging (DTI) is associated with low intrinsic sensitivity and therefore it is difficult to achieve simultaneously high resolution and high SNR. Goal(s): To acquire submillimeter DTI to map human brain structural connectivity networks with improved accuracy and detail than standard resolution DTI. Approach: We combine a deep learning reconstruction method with MB-MUSE to further enhance the image quality and demonstrate improved quantification of submillimeter isotropic (0.8×0.8×0.8 mm3) whole brain DTI at 3T with approximately 1 minute per diffusion direction scan time. Results: The exceptional delineation and clarity of fiber tracking was achieved from submillimeter isotropic whole brain DTI. Impact: Submillimeter
isotropic whole brain DTI with approximately 1 minute per diffusion direction
scan time at 3T with high SNR, low distortion, provides us with a powerful tool
to map whole brain structural connectivity networks with exceptional clarity
and quantification. |
| 2438.
 | 116 | Diffusion-weighted imaging of the sellar region: A comparison study of TGSE-BLADE and RESOLVE sequences Hai Shi1, Hao Hu1, Kun Zhou2, Yi-Cheng Hsu3, and Fei-Yun Wu1
1Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 2Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, 3MR Research Collaboration Team, Siemens Healthineers Ltd., Shanghai, China Keywords: DWI/DTI/DKI, New Trajectories & Spatial Encoding Methods Motivation: We aim to investigate the potential of TGSE-BLADE diffusion-weighted imaging(DWI) in mitigating image artifacts and distortions within the sellar region. Goal(s): Our study involves a comparative analysis of image quality between TGSE-BLADE diffusion-weighted imaging (DWI) and RESOLVE-DWI within the sellar region. Approach: We compared qualitative (overall imaging quality, artifacts and distortions) and quantitative (signal-to-noise ratio [SNR] and apparent diffusion coefficient [ADC]) parameters between RESOLVE-DWI and TGSE-BLADE-DWI images. Results: TGSE-BLADE-DWI exhibited higher imaging quality with less artifacts and distortions and a higher SNR than did RESOLVE-DWI (P<0.05). The tissue ADCs did not differ significantly between the groups (P>0.05). Impact: TGSE-BLADE-DWI offers a solution to diffusion imaging distortion. Comparative analysis highlights its superiority in mitigating sellar region distortion, promising enhanced quality in challenging clinical applications. |
| 2439.
 | 117 | 3D Diffusion Image Acquisition with Motion Offsetting and
Navigation-Dependent Segmentation (DIAMONDS) Jens Johansson1,2, Kerstin Lagerstrand2,3, Hanna Hebelka1,4, and Stephan E. Maier1,5
1Radiology, Clinical Scienes, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 2Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, 3Medical Radiation Sciences, Clinical Scienes, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, 4Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden, 5Radiology, Brigham and Women's Hospital, Boston, MA, United States Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques, 3D-DWI; Motion-compensated diffusion imaging; Diffusion acquisition Motivation: Investigate whether 1D navigator echo phase information can be used to correct residual phase errors in single thick-slab segmented 3D-DWI with first and second order motion-compensated diffusion encoding gradients. Goal(s): Perform high-resolution single thick-slab segmented 3D-DWI with full brain coverage. Approach: Extend a first and second order motion-compensated segmented 3D-DWI sequence with three orthogonal 1D navigators, which are utilized to correct for residual phase errors. Results: Correction of zeroth order phase shifts, which result from translation, demonstrated reduction of ghosting artifacts. First order phase terms, which arise from rotation, were also determined, but require a more complex correction strategy. Impact: Motion-compensated single thick-slab segmented 3D-DWI with orthogonal 1D navigators is a completely novel and promising approach for high resolution diffusion imaging with full brain coverage. |
| 2440.
 | 118 | Spiral interleaving for diffusion encoding and relaxometry (SPIDER) Xingwang Yong1,2,3, Hong-Hsi Lee2, Shohei Fujita2,3,4,5, Yohan Jun2,3, Jaejin Cho2,3, Qiang Liu6, Tao Zu1, Yi Zhang1, and Berkin Bilgic2,3,7
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 3Department of Radiology, Harvard Medical School, Boston, MA, United States, 4Department of Radiology, Juntendo University, Tokyo, Japan, 5Department of Radiology, The University of Tokyo, Tokyo, Japan, 6Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, 7Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States Keywords: Diffusion Acquisition, Diffusion Tensor Imaging Motivation: Current diffusion readout methods have a relatively long echo time and readout duration, which prevent multi-echo imaging. Goal(s): To implement a diffusion sequence with multiple echoes readout for performing diffusion relaxometry. Approach: A 3-echo diffusion sequence, SPIDER, with variable density spiral readout was designed. Results: The proposed SPIDER showed comparable images with reference EPI method at shorter echo time. Impact: The proposed method
showed the ability to acquire 3 echoes for 1mm2 resolution for low
b-value, which could help multi-echo diffusion modeling. |
| 2441.
 | 119 | Mitigation of Peripheral-Nerve Stimulation with Arbitrary Gradient Waveform Design for Diffusion-Weighted MRI Ariel J Hannum1,2,3,4, Michael Loecher1,2,3, Kawin Setsompop1,5, and Daniel B Ennis1,2,3
1Department of Radiology, Stanford University, Stanford, CA, United States, 2Division of Radiology, Veterans Administration Health Care System, Palo Alto, CA, United States, 3Cardiovascular Institute, Stanford University, Stanford, CA, United States, 4Department of Bioengineering, Stanford University, Stanford, CA, United States, 5Department of Electrical Engineering, Stanford University, Stanford, CA, United States Keywords: Diffusion Acquisition, Gradients, Peripheral Nerve Stimulation Motivation: Peripheral nerve stimulation (PNS) can be problematic on ultra-high-performance gradients systems, especially during diffusion encoding. We developed a gradient waveform optimization approach to mitigate PNS. Goal(s): Our goal was to investigate the minimum achievable TE (TEmin) using arbitrary gradient waveform design while mitigating PNS for brain, liver and heart DWI. Approach: We used gradient optimization (GrOpt) to design gradient waveforms for TEmin of different protocols, then imaged a phantom and a volunteer with a brain DWI protocol implemented with Pulseq. Results: GrOpt consistently reduces TEs compared to conventional approaches and avoids PNS. Image quality was the same in phantom and in vivo studies. Impact: Ultra high-performance gradient systems increase diffusion sensitivity and resolution, but their application can be constrained due to peripheral nerve stimulation (PNS). We used open-source gradient optimization (GrOpt) to design arbitrary gradient waveforms for minimum time that mitigate PNS. |
| 2442.
 | 120 | Three-dimensional phase-based diffusion imaging using RF phase-modulated gradient echo imaging with Stack-of-Stars Daiki Tamada1, Diego Hernando1,2, and Scott B Reeder1,2,3,4,5
1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 3Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 4Department of Medicine, University of Wisconsin-Madison, Madison, WI, United States, 5Department of Emergency, University of Wisconsin-Madison, Madison, WI, United States Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques Motivation: There is increased interest in high-resolution diffusion-weighted imaging (DWI); however, conventional DWI methods have limitations such as image distortion and motion sensitivity. Goal(s): To demonstrate the feasibility of high-resolution DWI using phase-based diffusion with radial Stack-of-Stars acquisition (PBD-SoS). Approach: To evaluate PBD-SoS, quantitative ADC measurements were performed with a phantom and compared with conventional methods. In vivo imaging was performed to demonstrate the clinical feasibility of PBD-SoS. Results: The results showed ADC values of the phantom measured using PBD-SoS were consistent (R2=0.99) with conventional DWI, and there were fewer motion artifacts compared to conventional methods in vivo. Impact: PBD-SoS enables high-resolution DWI that is robust to motion, which can be particularly beneficial for body imaging where motion artifacts are common. While current PBD-SoS scans may take longer, future implementation of acceleration techniques could overcome this limitation. |
| 2443.
 | 121 | 3D diffusion MRI at 7T with Universal Pulses for improved image uniformity Sajjad Feizollah1,2, Daniel Löwen3, Marcus J. Couch1,2,4, Eberhard D. Pracht3, Tony Stöcker3,5, and Christine L. Tardif1,2,6
1Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada, 2McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada, 3German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, 4Siemens Healthcare Limited, Montreal, QC, Canada, 5Department of Physics and Astronomy, University of Bonn, Bonn, Germany, 6Department of Biomedical Engineering, McGill University, Montreal, QC, Canada Keywords: Diffusion Acquisition, Brain, Universal Pulses Motivation: 2D multi-slice diffusion-weighted MRI (dMRI) suffers from severe signal non-uniformity caused by B1+ inhomogeneity at ultra-high fields. Goal(s): To design a 3D dMRI sequence with Universal parallel transmission radio-frequency Pulses (UPs) to improve image uniformity across the brain at 7T without lengthening workflow. Approach: We propose a 3D spin-echo sequence with an inversion pulse before excitation to enhance SNR. 3D UPs were designed for inversion, excitation, and refocussing and implemented in a sequence with a stack-of-EPI readout. Results: Diffusion-weighted image uniformity was significantly improved using the 3D sequence with UPs in comparison to 2D dMRI at 7T. Impact: We propose a 3D dMRI sequence that includes UPs to improve
image uniformity across the brain at 7T, including
the temporal lobes and cerebellum. This improvement in image
quality is critical for precision mapping of whole brain structural
connectivity. |
| 2444.
 | 122 | Diffusion-weighted GRASE sequence with 3D navigator for high-resolution time-dependency measurements in the human cortical gray matter Haotian Li1, Qinfeng Zhu1, Jie Lu1, Ruicheng Ba1, Yi-Cheng Hsu2, Xu Yan2, and Dan Wu1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2Siemens Healthineers Ltd, Hangzhou, China Keywords: Diffusion Acquisition, Brain Motivation: Oscillating gradient sequences enable diffusion measurement at short diffusion-time (td), but it suffered from low resolution and SNR on clinical systems. Goal(s): To explore the td-dependency in sophisticated structures, like cortical gray matter Approach: We proposed a 3D navigator-based 3D gradient spin-echo (GRASE) sequence for whole-brain td–dMRI at 1.5 mm isotropic resolution, which enabled us to depict the cerebral cortex. Results: We unveiled unique td-dependency patterns across cortical regions with different diffusion dispersion exponent (θ) based on the power-law, which was higher in the sensory cortex, like the occipital region, and lower in the high-order cortex like the temporal region. Impact: The
high-resolution td-dMRI
technique provided a new approach to characterize the cortical
micro-environment and is potentially useful to capture changes due to
neurological diseases. |
| 2445.
 | 123 | Motion-Corrected Distortion Reduction Around Metallic Implant Using Diffusion Tensor Imaging at 3T Slimane Tounekti1, Berkin Bilgic2, Devon Middleton1, Adam Leibold3, Mahdi Alizadeh1, Laura Krisa1, Choukri Mekkaoui*2, and Feroze Mohamed*1
1Radiology, Thomas Jefferson University, Philadelphia, PA, United States, 2Radiology, Harvard Medical School, Charlestown, MA, United States, 3Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States Keywords: Diffusion Acquisition, Spinal Cord, Metal Artifact, DTI, 3T Motivation: The presence of metallic implants results in severe geometric distortion, limiting the ability of performing quantitative DTI measurement near the hardware. Goal(s): Goal: develop an acquisition method to address metal artifact DTI on post-operative patients with metallic hardware. Approach: A custom-built pulse sequence based on the combination of the reduced-Field-Of-View strategy and multi-shot EPI is suggested. Results: : In-vivo and in-vitro results show that the proposed approach provides distortion-reduced and signal void at the level of the metal hardware compared to the standard method. Impact: The ability of
collecting reduced metal-artifact DTI maps around the hardware enables establishing
imaging biomarkers to assess injury evolution and thoroughly evaluate microstructure changes after surgery. |
| 2446.
 | 124 | Submillimeter in vivo human brain diffusion MRI at 500 mT/m with concurrent field monitoring Gabriel Ramos-Llordén1, Mirsad Mahmutovic2, Daniel J. Park1, Chiara Maffei1, Yixin Ma1, Hong-Hsi Lee1, Lawrence L. Wald1, Thomas Witzel3, Boris Keil2,4, and Susie Y. Huang1
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, 2Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany, 3Q Bio Inc, San Carlos, CA, United States, 4Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps University of Marburg, Marburg, Germany Keywords: Diffusion Acquisition, Data Acquisition Motivation: High-fidelity, artifact-free diffusion MRI (dMRI) in high-performance gradient systems requires more advanced encoding and reconstruction approaches than those widely used. Goal(s): To achieve ghosting- and eddy current distortion-free in vivo submillimeter human brain dMRI with concurrent field monitoring. Approach: A 16-ch clip on field probe system was integrated onto custom-built 72ch to map high-order field perturbations during the acquisition. SENSE-based reconstruction was informed with the monitored phase evolution as expressed in a 3rd-order spherical harmonic model. Results: Concurrent field monitoring reconstruction reduces non-linear Nyquist ghosting and geometric distortions generated by high-order eddy currents from ultra-strong diffusion gradients. Impact: We expect concurrent field monitoring to become essential in achieving high-quality image reconstruction as the adoption of high-performance gradients systems grows and image acquisition strategies evolve with more sophisticated image encodings. |
| 2447.
 | 125 | Low-rank Constrained Reacquired-navigator reconstruction of multi-shot diffusion weighted image Jiantai Zhou1, Huabin Zhang1, Penghui Luo1, Changliang Wang1, Fulang Qi1, Kecheng Yuan1, Jiaojiao Hu 1, and Bensheng Qiu1
1Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China Keywords: Diffusion Reconstruction, Diffusion/other diffusion imaging techniques, Low-rank, Phase correction,Reacquired-navigator Motivation: Multi-Shot Diffusion-Weighted Imaging (MS-DWI) requires additional phase correction data and parallel imaging prescans to respectively suppress artifacts caused by positive-negative readout gradient and motion-induced phase variation. Goal(s): Our objective is to mitigate two common artifacts without the need for additional linear-phase corrections and parallel imaging prescans. Approach: We propose subtle modifications to the dual spin-echo DW sequence 1, where positive and negative gradients are employed to separately acquire complete navigator-echo data for low-rank constrained reconstruction. Results: Simulation studies and in vivo brain imaging experiments demonstrate that the proposed method effectively mitigates image artifacts caused by phase variations, resulting in better image quality. Impact: This paper presents a novel artifact correction method applied to spin-echo DW sequence, offering an effective prescan-free acquisition and reconstruction strategy that mitigates the impact of prescan data mismatch and additional prescan time consumption. |
| 2448.
 | 126 | Inversion Recovery Quasi-Diffusion Tensor Imaging Thomas R Barrick1 and Franklyn A Howe1
1Neurosciences Research Centre, St George's, Univerisity of London, London, United Kingdom Keywords: Diffusion Acquisition, Brain Motivation: To provide a clinically feasible Quasi-Diffusion Tensor Imaging (QDTI) acquisition with free water suppression. Goal(s): To assess the effect of inversion recovery (IR) on QDTI measures in grey and white matter and determine measurement accuracy in clinically feasible data acquisitions. Approach: dMRI were acquired (8 b-values) with and without IR. QDTI measures were computed in brain tissue. Measurement bias was quantified for 4 and 3 b-value data subsets. Results: IR reduced free water effects by lowering grey matter diffusion coefficients in grey matter and raising tissue anisotropy. QDTI $$$\alpha$$$ was robust to effects of IR. Clinically feasible acquisitions provide accurate IR-QDTI measures. Impact: Our results suggest that IR-QDTI is a straightforward and robust
method applicable to clinical studies for accurately characterising non-Gaussian
diffusion in diseases of cortical grey matter, and white matter lesions/tumour
where substantial numbers of voxels have high free water content. |
| 2449.
 | 127 | A Least Difference Block Sharing (LDBS) Method for Optimizing the View-sharing iblocks-DTI Liyuan Liang1,2, Mei-Lan Chu3, Nan-Kuei Chen4,5, Shihui Chen1, Chenglang Yuan1, Hailin Xiong1, Xiaorui Xu6, and Hing-Chiu Chang1,2
1Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, 2Multi-Scale Medical Robotics Center, Shatin, Hong Kong, 3Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan, 4Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States, 5Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, United States, 6Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, Hong Kong Keywords: Diffusion Acquisition, Diffusion Tensor Imaging, multi-shot DTI; data sharing; high-resolution DTI Motivation: View-sharing iblocks-DTI (VSiblocks-DTI) can substantially reduce the long scan time of iblocks-DTI while providing accurate DTI tensor calculations. However, its neighbor sharing method may limit its performance when using a randomized ordering of diffusion directions or small imaging matrix. Goal(s): This work aims to optimize the sharing method for VSiblocks-DTI. Approach: The least difference block sharing (LDBS) method was proposed and evaluated under different conditions. Results: The proposed LDBS method provided more accurate DTI tensor calculations than the previous neighbor sharing method under six different conditions, demonstrating its robustness to provide accurate DTI tensor calculation for VSiblocks-DTI. Impact: This
study proposes a least difference block sharing (LDBS) method for optimizing view-sharing
iblocks-DTI. It alleviates the limitation of previous sharing method on the
ordering of diffusion directions and shows robust and accurate DTI tensor
calculation with different matrix sizes. |
| 2450.
 | 128 | Acceleration of Diffusion-Relaxation Multidimensional MRI acquisition exploiting Locally low-rank with Block Adaptive Regularization Joon Sik Park1 and Dan Benjamini1
1National Institute on Aging, Baltimore, MD, United States Keywords: Microstructure, Microstructure, Multidimensional MRI, Diffusion and Relaxation Motivation: Multidimensional (MD)-MRI provides valuable sub-voxel information. However, it suffers from prohibitively long acquisition time making it impractical for routine clinical use.
Goal(s): To reduce MD-MRI scan time via partial k-space sampling in conjunction with a novel reconstruction framework. Approach: Achieve data reduction by using random incoherent sampling, followed by locally low-rank reconstruction with block adaptive regularization, and comparison with ground-truth. Results: In-vivo performance of MD-MRI image reconstruction method that achieves R=4 reduction factor was demonstrated. This framework provides whole-brain coverage with 2mm$$$^3$$$ voxels in 20 minutes, while maintaining robustness and accuracy. This innovation has significant potential for clinical neurological applications. Impact: Multidimensional MRI is crucial for investigating tissue microstructure, brain connectivity, and pathology in clinical study. Here we present a novel image reconstruction framework that allows R=4 k-space data reduction factor, providing whole-brain coverage with 2mm$$$^3$$$ voxels MD-MRI data in 20minutes. |