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Lu X, Ma Y, Chang EY, He Q, Searleman A, von Drygalski A, Du J. Simultaneous quantitative susceptibility mapping (QSM) and R2* for high iron concentration quantification with 3D ultrashort echo time sequences: An echo dependence study. Magn Reson Med 2018; 79:2315-2322. [PMID: 29314215 DOI: 10.1002/mrm.27062] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Revised: 12/05/2017] [Accepted: 12/05/2017] [Indexed: 12/12/2022]
Abstract
PURPOSE To evaluate the echo dependence of 3D ultrashort echo time (TE) quantitative susceptibility mapping (3D UTE-QSM) and effective transverse relaxation rate ( R2*) measurement in the setting of high concentrations of iron oxide nanoparticles. METHODS A phantom study with iron concentrations ranging from 2 to 22 mM was performed using a 3D UTE Cones sequence. Simultaneous QSM processing with morphology-enabled dipole inversion (MEDI) and R2* single exponential fitting was conducted offline with the acquired 3D UTE data. The dependence of UTE-QSM and R2* on echo spacing (ΔTE) and first TE (TE1 ) was investigated. RESULTS A linear relationship was observed between UTE-QSM measurement and iron concentration up to 22 mM only, with the minimal TE1 of 0.032 ms and ΔTE of less than 0.1 ms. A linear relationship was observed between R2* and iron concentration up to 22 mM only when TE1 was less than 0.132 ms and ΔTE was less than 1.2 ms. UTE-QSM with MEDI processing showed strong dependence on ΔTE and TE1 , especially at high iron concentrations. CONCLUSION UTE-QSM is more sensitive than R2* measurement to TE selection. Both an ultrashort TE1 and a small ΔTE are needed to achieve accurate QSM for high iron concentrations. Magn Reson Med 79:2315-2322, 2018. © 2018 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Xing Lu
- Department of Radiology, University of California, San Diego, California, USA.,Institute of Electrical Engineering, Chinese Academy of Science, Beijing, China
| | - Yajun Ma
- Department of Radiology, University of California, San Diego, California, USA
| | - Eric Y Chang
- Department of Radiology, University of California, San Diego, California, USA.,Radiology Service, VA San Diego Healthcare System, San Diego, California, USA
| | - Qun He
- Department of Radiology, University of California, San Diego, California, USA
| | - Adam Searleman
- Department of Radiology, University of California, San Diego, California, USA
| | - Annette von Drygalski
- Department of Medicine, Division of Hematology/Oncology, University of California, San Diego, California, USA
| | - Jiang Du
- Department of Radiology, University of California, San Diego, California, USA
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Liu S, Buch S, Chen Y, Choi HS, Dai Y, Habib C, Hu J, Jung JY, Luo Y, Utriainen D, Wang M, Wu D, Xia S, Haacke EM. Susceptibility-weighted imaging: current status and future directions. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3552. [PMID: 27192086 PMCID: PMC5116013 DOI: 10.1002/nbm.3552] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 04/01/2016] [Accepted: 04/11/2016] [Indexed: 05/14/2023]
Abstract
Susceptibility-weighted imaging (SWI) is a method that uses the intrinsic nature of local magnetic fields to enhance image contrast in order to improve the visibility of various susceptibility sources and to facilitate diagnostic interpretation. It is also the precursor to the concept of the use of phase for quantitative susceptibility mapping (QSM). Nowadays, SWI has become a widely used clinical tool to image deoxyhemoglobin in veins, iron deposition in the brain, hemorrhages, microbleeds and calcification. In this article, we review the basics of SWI, including data acquisition, data reconstruction and post-processing. In particular, the source of cusp artifacts in phase images is investigated in detail and an improved multi-channel phase data combination algorithm is provided. In addition, we show a few clinical applications of SWI for the imaging of stroke, traumatic brain injury, carotid vessel wall, siderotic nodules in cirrhotic liver, prostate cancer, prostatic calcification, spinal cord injury and intervertebral disc degeneration. As the clinical applications of SWI continue to expand both in and outside the brain, the improvement of SWI in conjunction with QSM is an important future direction of this technology. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Saifeng Liu
- The MRI Institute for Biomedical Research, Waterloo, ON, Canada
| | - Sagar Buch
- The MRI Institute for Biomedical Research, Waterloo, ON, Canada
| | - Yongsheng Chen
- Department of Radiology, Wayne State University, Detroit, MI, US
| | - Hyun-Seok Choi
- Department of Radiology, St. Mary’s Hospital, The Catholic University of Korea, Seoul, Korea
| | - Yongming Dai
- The MRI Institute of Biomedical Research, Detroit, Michigan, US
| | - Charbel Habib
- Department of Radiology, Wayne State University, Detroit, MI, US
| | - Jiani Hu
- Department of Radiology, Wayne State University, Detroit, MI, US
| | - Joon-Yong Jung
- Department of Radiology, St. Mary’s Hospital, The Catholic University of Korea, Seoul, Korea
| | - Yu Luo
- Department of Radiology, the Branch of Shanghai First Hospital, Shanghai, China
| | - David Utriainen
- The MRI Institute of Biomedical Research, Detroit, Michigan, US
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People’s Hospital, Zhengzhou, Henan, China
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Shuang Xia
- Department of Radiology, Tianjin First Central Hospital, Tianjin, China
| | - E. Mark Haacke
- The MRI Institute for Biomedical Research, Waterloo, ON, Canada
- Department of Radiology, Wayne State University, Detroit, MI, US
- The MRI Institute of Biomedical Research, Detroit, Michigan, US
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
- Address correspondence to: E. Mark Haacke, Ph.D., 3990 John R Street, MRI Concourse, Detroit, MI 48201. 313-745-1395,
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Deistung A, Schweser F, Reichenbach JR. Overview of quantitative susceptibility mapping. NMR IN BIOMEDICINE 2017; 30:e3569. [PMID: 27434134 DOI: 10.1002/nbm.3569] [Citation(s) in RCA: 184] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 05/03/2016] [Accepted: 05/09/2016] [Indexed: 06/06/2023]
Abstract
Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Andreas Deistung
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, NY, USA
- MRI Clinical and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, The State University of New York at Buffalo, NY, USA
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany
- Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University Jena, Jena, Germany
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Foundations of MRI phase imaging and processing for Quantitative Susceptibility Mapping (QSM). Z Med Phys 2015; 26:6-34. [PMID: 26702760 DOI: 10.1016/j.zemedi.2015.10.002] [Citation(s) in RCA: 79] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2015] [Revised: 09/18/2015] [Accepted: 10/27/2015] [Indexed: 01/27/2023]
Abstract
Quantitative Susceptibility Mapping (QSM) is a novel MRI based technique that relies on estimates of the magnetic field distribution in the tissue under examination. Several sophisticated data processing steps are required to extract the magnetic field distribution from raw MRI phase measurements. The objective of this review article is to provide a general overview and to discuss several underlying assumptions and limitations of the pre-processing steps that need to be applied to MRI phase data before the final field-to-source inversion can be performed. Beginning with the fundamental relation between MRI signal and tissue magnetic susceptibility this review covers the reconstruction of magnetic field maps from multi-channel phase images, background field correction, and provides an overview of state of the art QSM solution strategies.
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Ma YJ, Liu W, Zhao X, Tang W, Li H, Fan Y, Tang X, Zhang Y, Gao JH. 3D interslab echo-shifted FLASH sequence for susceptibility weighted imaging. Magn Reson Med 2015; 76:222-8. [DOI: 10.1002/mrm.25872] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Revised: 07/15/2015] [Accepted: 07/16/2015] [Indexed: 11/07/2022]
Affiliation(s)
- Ya-Jun Ma
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Wentao Liu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Xuna Zhao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Weinan Tang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Huanjie Li
- Department of Biomedical Engineering; Dalian University of Technology; Dalian China
| | - Yang Fan
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Xin Tang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Yaoyu Zhang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University; Beijing China
- Beijing City Key Lab for Medical Physics and Engineering; Institute of Heavy Ion Physics, School of Physics, Peking University; Beijing China
- McGovern Institute for Brain Research, Peking University; Beijing China
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