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Guangqi Li¹, Xiaodong Ma², Sisi Li¹, Xinyu Ye¹, Peter Börnert^3,4, Xiaohong Joe Zhou⁵, and Hua Guo^1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, ²Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States, ³Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, Netherlands, ⁴Philips Research, Hamburg, Germany, ⁵Center for MR Research and Departments of Radiology, Neurosurgery, and Biomedical Engineering, University of Illinois College of Medicine at Chicago, Chicago, IL, United States

Keywords: Data Acquisition, Diffusion Tensor Imaging

Different multi-shot spiral sampling schemes have been developed for high-resolution DWI. However, the performances of these sampling strategies such as variable-density spiral (VDS), dual-density spiral (DDS) and uniform-density spiral (UDS) have not been compared comprehensively. In this study, we compare multi-shot UDS, VDS and DDS in brain DWI in terms of inter-shot phase error correction, overall image quality and SNR performance. Both theoretical analysis and in-vivo results demonstrate that UDS exhibits the best off-resonance performance among the three spiral sampling patterns. Additionally, UDS achieves the highest SNR in diffusion imaging over the VDS and DDS acquisitions.

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Yiming Dong¹, Kirsten Koolstra², Laurens Beljaards³, Marius Staring³, Matthias J.P. van Osch⁴, and Peter Börnert^4,5
1LUMC, Leiden, Netherlands, ²Philips, Best, Netherlands, ³Division of Image Processing, Department of Radiology, LUMC, Leiden, Netherlands, ⁴C.J. Gorter MRI Center, Department of Radiology, LUMC, Leiden, Netherlands, ⁵Philips Research, Hamburg, Germany

Keywords: Machine Learning/Artificial Intelligence, Diffusion/other diffusion imaging techniques

Advanced diffusion weighted self-navigated multi-shot MRI can run at high scan efficiencies resulting in good image quality. However, the model-based image reconstruction is rather time consuming. Deep learning-based reconstruction approaches could function as a faster alternative. Tailored network architectures with appropriately set physical model constraints can help to shorten reconstruction times, resulting in good image quality with reduced noise propagation.

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Guangqi Li¹, Sisi Li¹, and Hua Guo^1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques

Navigator-free multi-shot spiral and EPI acquisitions have been developed to achieve 2D high-resolution diffusion imaging. In this study, we investigated the off-resonance effects of spiral and iEPI samplings with different partial Fourier factors based on a signal model. Moreover, the SNR performances of the two multi-shot acquisitions at different resolutions and TEs were also explored. In summary, compared with iEPI, spiral provides superior SNR in multi-shot navigator-free DWI at various resolutions and TEs, even when the TE of spiral acquisition is slightly longer than that of iEPI. However, off-resonance correction for spiral sampling with ultra-long readout durations is more challenging.

Mi zhou¹, Meining Chen², and Yuting Wang^1
1Sichuan Provincial People's Hospital, chengdu, China, ²MR Scientific Marketing, Siemens Healthcare, Shanghai, China

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques

DWI has an important role in the staging and treatment response assessment of patients with rectal cancer, but its resolution is much lower than dynamic contrast-enhanced MRI and T2W images. We achieved a high-resolution scan of the rectal cancer using SMS HR rs-EPI sequences with a resolution of 1.1×1.1×2 mm³. The SMS HR rs-EPI provided a significantly better image quality and more valuable ADC than conventional HR rs-EPI when assessing rectal cancer. The pretreatment ADC values of HR rs-EPI could be utilized to distinguish well and poorly differentiated rectal cancer.

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Phillip Andrew Martin¹, Maria Altbach^2,3, and Ali Bilgin^1,2,3,4
1Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States, ²Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States, ³Department of Medical Imaging, University of Arizona, Tucson, AZ, United States, ⁴Department of Applied Mathematics, University of Arizona, Tucson, AZ, United States

Keywords: Machine Learning/Artificial Intelligence, Diffusion/other diffusion imaging techniques

In this work, we aim to accelerate diffusion weighted MRI (dMRI) by predicting diffusion -weighted images (DWIs) across different shells using deep learning (DL), while remaining independent of a diffusion-model constraint. The proposed approach enables the predictions of unacquired DWIs in multiple shells from a small set of acquired DWIs from a given shell. This relaxes the need for applying multiple diffusion gradient weightings for obtaining a fully-acquired dataset over multiple shells. Without the constraint of a diffusion model, accurate diffusion metrics over multiple diffusion models can potentially be obtained by acquiring a small number of DWIs.

 

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Zhilang Qiu¹, Siyuan Hu¹, Walter Zhao¹, Ken Sakaie², Mark A. Griswold³, Derek K. Jones⁴, and Dan Ma^1
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ²Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, ³Radiology, Case Western Reserve University, Cleveland, OH, United States, ⁴Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom

Keywords: Image Reconstruction, Diffusion/other diffusion imaging techniques

We propose a new reconstruction method, named self-calibrated subspace reconstruction, for multidimensional MR fingerprinting (mdMRF), in order to correct the artifacts due to inter-shot (segment) magnitude and phase variations, without the need for extra navigator or calibration data. Different options for utilizing the low-rank property and the signal structure of mdMRF data are investigated and the optimal scheme is determined. Such that aliasing-free high-resolution image reconstruction and high-quality quantification, can be achieved.

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Xinyu Ye¹, Karla Miller¹, and Wenchuan Wu^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK, Oxford, United Kingdom

Keywords: Image Reconstruction, Diffusion/other diffusion imaging techniques, Signal modelling

Diffusion-weighted MRI suffers from relatively long acquisition time, especially for high spatial- resolution and/or high angular- resolution acquisitions. Thus, methods to increase the acquisition speed are urgently needed. Recently, increasing attention has been paid to utilize the relations between k- and q-space points for further acceleration. Here, we extend the Diffusion Acceleration with Gaussian process Estimated Reconstruction (DAGER) to leverage shared information in multi-shell acquisitions and incorporate eddy-induced distortion correction.  

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Frank Z Tan¹, Patrick Alexander Liebig², Robin Martin Heidemann², Frederik Bernd Laun³, and Florian Knoll^1
1Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, ²Siemens Healthcare GmbH, Erlangen, Germany, ³Institute of Radiology, University Hospital Erlangen, Erlangen, Germany

Keywords: Image Reconstruction, Diffusion/other diffusion imaging techniques, Ultra high field, multi-shell, q-space, crossing fiber

The pursuit of high-spatial-angular-temporal resolution for in vivo diffusion MRI at 7T is challenging, but also receives continuous interest. We hereby propose shift-encoded interleaved EPI and a joint reconstruction technique with LLR regularization. Preliminary results achieve up to 8.7-fold acceleration per shot in 2-shot EPI acquisition with 1.4 mm isotropic nominal resolution. Moreover, with the integrated joint reconstruction for noise reduction, high-quality diffusion-weighted images render more spatially-continuous fiber anisotropy maps and clearer fiber crossing in the fiber orientation distribution function.

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Yan Wen¹, Liling Long¹, Chenhui Li¹, Huiting Zhang², and Alto Stemmer^3
1Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China, ²MR Scientific Marketing, Siemens Healthineers Ltd., Wuhan, China, ³MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany

Keywords: Data Analysis, Diffusion/other diffusion imaging techniques

This study aimed to investigate the value of integrated shimming (iShim) technique in the ultrahigh-b-value DWI images in laryngeal and hypopharyngeal squamous cell carcinoma (SCC) by comparing with the conventional volume shimming technique. Our results showed that the ultrahigh-b-value DWI images with iShim technique had significantly higher image quality based on subjective (edge, artifact, and confidence) and objective (signal-to-noise ratio, contrast, and contrast-to-noise ratio) assessments compared with conventional single-shot-EPI DWI images with volume shimming. Therefore, ultrahigh-b-value DWI images with iShim technique can be well applied in laryngeal and hypopharyngeal SCC examination.

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Xinzeng Wang¹, Daniel Litwiller², Arnaud Guidon³, Patricia Lan⁴, and Tim Sprenger^5
1GE Healthcare, Houston, TX, United States, ²GE Healthcare, Denver, CO, United States, ³GE Healthcare, Boston, MA, United States, ⁴GE Healthcare, Menlo Park, CA, United States, ⁵GE Healthcare, Stockholm, Sweden

Keywords: Data Processing, Diffusion/other diffusion imaging techniques

In the past decade, complex signal averaging has been investigated for diffusion weighted imaging to address the well-known noise floor issue. The robustness of complex signal averaging highly depends on the performance of phase correction to remove the shot-to-shot background phase variations. To achieve optimal phase correction, parameters (kernel size, regularization terms, etc.) need to be tuned for different anatomies, SNR levels and/or image size.  In this work, we evaluated a deep-learning based phase correction method for various DWI applications, including brain, liver, prostate and showed improved complex signal averaging with lower noise floor and less artifacts.

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Frederik Testud¹, Arthur Chakwizira², and Markus Nilsson^2
1Siemens Healthcare AB, Malmö, Sweden, ²Department of Medical Radiation Physics, Lund University, Lund, Sweden

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques, Neuro, Microstructure

Filter EXchange Imaging (FEXI) is sensitive to the rate of diffusional water exchange, which depends among other factors on the cell membrane permeability. FEXI maps the so-called apparent exchange rate (AXR), however, previous FEXI protocols were limited to few slices because of very long acquisition times. In this proof-of-concept work, Simultaneous MultiSlice was included in the FEXI sequence and with protocol optimization allowed for a 12-minute whole-brain scan. FEXI accelerated with or without SMS showed similar AXR values.

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Bramsh Qamar Chandio^1,2, Sophia I Thomopoulos¹, Paul M Thompson¹, Jaroslaw Harezlak³, and Eleftherios Garyfallidis^2
1Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States, ²Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States, ³Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, IN, United States

Keywords: Software Tools, Diffusion/other diffusion imaging techniques, Tractography, tractometry, bundle segmentation, white matter tracts, group analysis

We propose BUAN 2.0, which adds new advancements to its predecessor BUAN. It sub-segments bundles with varying substructures in them. It uses nonlinear registration of bundles to find accurate correspondences among bundle segments across subjects. The number of horizontal segments is decided based on the bundle and data specifications. More importantly, in BUAN 2.0, instead of treating each point on the streamline as an independent observation, we treat each streamline as a complete entity, as a function. Streamlines are analyzed by deploying functional data analysis (FDA) methods for studying group differences in populations along the length of the tracts.

Yishi Wang¹, Zhen Zhang², Rui Wang², Xiuzheng Yue¹, Fang Wang², Rongrong Zhu², and Ruoshui Ha^2
1Philips Healthcare, Beijing, China, ²Medical Imaging Center, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, China

Keywords: Pulse Sequence Design, Diffusion/other diffusion imaging techniques, Cardiac Diffusion, Black Blood, Motion Compensation

Second-order motion-compensated diffusion imaging is a robust solution for cardiac diffusion imaging but prone to bright blood signals due to motion compensation itself. In this work, we incorporated black blood module into second-order motion-compensated sequence to achieve cardiac diffusion imaging with blood signal suppressed. 

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Yuichi Suzuki¹, Katsutoshi Murata², Hideyuki Iwanaga¹, and Osamu Abe^1
1Radiology Center, The University of Tokyo Hospital, Tokyo, Japan, ²Siemens Healthineers, Tokyo, Japan

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques

We examined the application order of MPG pulses (called reordered MPG) that can uniformly collect spatial diffusion information even if the examination is interrupted, compare it with the an electrostatic repulsion method (conventional method, called original MPG), and verify its usefulness. In conclusion, The reordered MPG, which was rearranged based on the MPG direction of the original, could collect diffusion information more uniformly than the original MPG even if the inspection examination was interrupted.

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Chu-Yu Lee¹ and Merry Mani^1
1University of Iowa, Iowa City, IA, United States

Keywords: Artifacts, Diffusion/other diffusion imaging techniques

Diffusion weighted images are usually acquired using 2D EPI methods. This technique has the limitation of low spatial resolution and low SNR. 3D diffusion weighted images are attractive option for improved SNR, however the motion-induced phase inconsistencies pose a challenge for the reconstruction of such data. We present a navigator-free phase-compensated reconstruction, which can be implemented as a regular parallel imaging framework. This two-step method involves first estimating a low-resolution phase from the data itself and then integrating the phase information in the forward encoding operator. We show good phase compensation from accelerated datasets using the proposed approach. 

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Wei Liu¹, Thomas Benkert¹, and Elisabeth Weiland^1
1MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany

Keywords: Pulse Sequence Design, Diffusion/other diffusion imaging techniques

In this work, we propose to further minimize the distortion and T2* blurring in DWI by the combination of readout-segmented EPI and 2D spatially-selective RF excitation. We demonstrate its application to DWI of the temporal lobe and the uterus. The experimental results based on volunteer scans show substantial distortion reduction in the proposed method, compared to the conventional 2DRF based single-shot EPI with reduced FOV.

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Takayuki SAKAI¹, Masami Yoneyama², Diachi Murayama¹, Iain Ball³, Tosiaki MIYATI⁴, Shigehiro Ochi¹, and Atsuya Watanabe^5,6
1Radiology, Eastern Chiba Medical Center, Chiba, Japan, ²Philips Japan, Tokyo, Japan, ³Philips Australia & New Zealand, North Ryde, Australia, ⁴Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan, ⁵General Medical Services, Chiba University Graduate School of Medicine, Chiba, Japan, ⁶Orthopaedic Surgery, Eastern Chiba Medical Center, Chiba, Japan

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques

We hypothesized that LIPO-only (LION) DWI might be one of the best solutions to improve the image quality of volumetric thin-slice DWI if it is further optimized to increase the robustness of fat suppression. We investigated the clinical usefulness of proposed LION fat suppression combined with thin-slice DWI for brain volumetric DWI in patients with acute stroke. LION-DWI has improved SNR compared to conventional DWI and has superior visual lesion detectability in patients with acute stroke. Therefore, it is possible to improve the image quality and shorten the imaging time of thin-slice DWI by changing the fat suppression to LION.

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Marta M. Correia¹, Stefan Winzeck^2,3, Marc Golub⁴, and Rita G. Nunes^4
1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, ²BioMedIA Group, Department of Computing, Imperial College London, London, United Kingdom, ³Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, United Kingdom, ⁴Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

Keywords: Data Analysis, Diffusion/other diffusion imaging techniques, Ageing, Free-Water

Two different algorithms for free-water elimination (FWE) were applied to single-shell and multi-shell diffusion MRI data. Positive correlations were found between age and fractional anisotropy (FA) estimated with the FWE algorithm for single-shell, but this was not replicated with multi-shell diffusion data. Because only the multi-shell FWE algorithm is well-posed, we postulated that the positive correlations between age and FA must be a false positive finding, resulting from inappropriate fitting using single-shell data. FWE estimates from single-shell modelling have been shown to be biologically plausible, but this does not imply specificity, and more work is required to validate these approaches.

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Seong-Eun Kim¹, Henrick Carl Axel Odeen ¹, John A Roberts¹, and Dennis L Parker^1
1UCAIR, Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States

Keywords: Pulse Sequence Design, Diffusion/other diffusion imaging techniques, non-cartesian trajectory

Non-Cartesian sampling schemes offer advantages over Cartesian schemes. Recently 2D radial and 3D hybrid radial-Cartesian approaches such as 3D stack of stars have gained popularity. Despite of many advantages, the current hybrid trajectory is presently limited by drawbacks including the degradation of sampling efficiency and the k-space coverage per unit time for diffusion application. For more flexible, rapid, and motion-robust 3D DWI, we implemented a 3D hybrid radial-EPI(RZAER) sequence and demonstrated the feasibility of 3D diffusion weighted RAZER sequence for carotid vessel wall. 

 

Yousef Mazaheri^1
1Memorial Sloan Kettering Cancer Center, New York, NY, United States

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

The aim of this aim of this study is to use numerical simulation to compare the performance of the standard bi-exponential IVIM model to an extended model which incorporates tissue and blood relaxometry for the estimation of IVIM parameters.