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Lastowski RJ, Vogiatzis KD, Girolami GS. Measuring the Magnetic Anisotropy of Metal-Metal Multiple Bonds: The Importance of Correcting for Ligand Effects. Inorg Chem 2024; 63:15546-15556. [PMID: 39141829 DOI: 10.1021/acs.inorgchem.4c02329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
We describe the synthesis and characterization of the quadruply-bonded dimer Mo2(CH2NMe2BH3)4 in which each molybdenum(II) center is bound to two chelating boranatodimethylaminomethyl (BDAM) ligands. The BDAM anions bind to the metal at one end by a metal-carbon σ bond and at the other by a three-center M-H-B interaction. Each BDAM ligand chelates to a single Mo atom so that the metal-metal bond is unbridged; the Mo-Mo distance is 2.114(2) Å. Structural and solution NMR data, analyzed via McConnell's equation and supported by DFT calculations, show that the magnetic anisotropies associated with highly polarizable and π-bonding ligands (such as chloride groups and aryl rings) can greatly affect the NMR chemical shifts of reporter groups, so that ignoring their contributions leads to significant overestimates of the anisotropy due just to the metal-metal bond. We propose a method to quantify and correct for the magnetic anisotropy effects arising from the ligands. Application of this method to Mo2(BDAM)4 indicates that the magnetic anisotropy of the Mo-Mo quadruple bond in this molecule is about -800 × 10-36 m3 molecule-1. Anisotropies significantly higher than this value (as sometimes reported in the prior literature) are most likely incorrect.
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Affiliation(s)
- R Joseph Lastowski
- School of Chemical Sciences, University of Illinois at Urbana-Champaign, 600 South Mathews Avenue, Urbana, Illinois 61801, United States
| | | | - Gregory S Girolami
- School of Chemical Sciences, University of Illinois at Urbana-Champaign, 600 South Mathews Avenue, Urbana, Illinois 61801, United States
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Wang B, Wang Y, Wang J, Jin C, Zhou R, Guo J, Zhang H, Wang M. Multiparametric Magnetic Resonance Investigations on Acute and Long-Term Kidney Injury. J Magn Reson Imaging 2024; 59:43-57. [PMID: 37246343 DOI: 10.1002/jmri.28784] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 04/29/2023] [Accepted: 05/01/2023] [Indexed: 05/30/2023] Open
Abstract
Acute kidney injury (AKI) is a frequent complication of critical illness and carries a significant risk of short- and long-term mortality. The prediction of the progression of AKI to long-term injury has been difficult for renal disease treatment. Radiologists are keen for the early detection of transition from AKI to long-term kidney injury, which would help in the preventive measures. The lack of established methods for early detection of long-term kidney injury underscores the pressing needs of advanced imaging technology that reveals microscopic tissue alterations during the progression of AKI. Fueled by recent advances in data acquisition and post-processing methods of magnetic resonance imaging (MRI), multiparametric MRI is showing great potential as a diagnostic tool for many kidney diseases. Multiparametric MRI studies offer a precious opportunity for real-time noninvasive monitoring of pathological development and progression of AKI to long-term injury. It provides insight into renal vasculature and function (arterial spin labeling, intravoxel incoherent motion), tissue oxygenation (blood oxygen level-dependent), tissue injury and fibrosis (diffusion tensor imaging, diffusion kurtosis imaging, T1 and T2 mapping, quantitative susceptibility mapping). The multiparametric MRI approach is highly promising but the longitudinal investigation on the transition of AKI to irreversible long-term impairment is largely ignored. Further optimization and implementation of renal MR methods in clinical practice will enhance our comprehension of not only AKI but chronic kidney diseases. Novel imaging biomarkers for microscopic renal tissue alterations could be discovered and benefit the preventative interventions. This review explores recent MRI applications on acute and long-term kidney injury while addressing lingering challenges, with emphasis on the potential value of the development of multiparametric MRI for renal imaging on clinical systems. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Bin Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Yongfang Wang
- Department of Medical Imaging, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jing Wang
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Jinxia Guo
- GE Healthcare, MR Research China, Beijing, China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Min Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
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3
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Si W, Guo Y, Zhang Q, Zhang J, Wang Y, Feng Y. Quantitative susceptibility mapping using multi-channel convolutional neural networks with dipole-adaptive multi-frequency inputs. Front Neurosci 2023; 17:1165446. [PMID: 37383103 PMCID: PMC10293650 DOI: 10.3389/fnins.2023.1165446] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 05/17/2023] [Indexed: 06/30/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) quantifies the distribution of magnetic susceptibility and shows great potential in assessing tissue contents such as iron, myelin, and calcium in numerous brain diseases. The accuracy of QSM reconstruction was challenged by an ill-posed field-to-susceptibility inversion problem, which is related to the impaired information near the zero-frequency response of the dipole kernel. Recently, deep learning methods demonstrated great capability in improving the accuracy and efficiency of QSM reconstruction. However, the construction of neural networks in most deep learning-based QSM methods did not take the intrinsic nature of the dipole kernel into account. In this study, we propose a dipole kernel-adaptive multi-channel convolutional neural network (DIAM-CNN) method for the dipole inversion problem in QSM. DIAM-CNN first divided the original tissue field into high-fidelity and low-fidelity components by thresholding the dipole kernel in the frequency domain, and it then inputs the two components as additional channels into a multichannel 3D Unet. QSM maps from the calculation of susceptibility through multiple orientation sampling (COSMOS) were used as training labels and evaluation reference. DIAM-CNN was compared with two conventional model-based methods [morphology enabled dipole inversion (MEDI) and improved sparse linear equation and least squares (iLSQR) and one deep learning method (QSMnet)]. High-frequency error norm (HFEN), peak signal-to-noise-ratio (PSNR), normalized root mean squared error (NRMSE), and the structural similarity index (SSIM) were reported for quantitative comparisons. Experiments on healthy volunteers demonstrated that the DIAM-CNN results had superior image quality to those of the MEDI, iLSQR, or QSMnet results. Experiments on data with simulated hemorrhagic lesions demonstrated that DIAM-CNN produced fewer shadow artifacts around the bleeding lesion than the compared methods. This study demonstrates that the incorporation of dipole-related knowledge into the network construction has a potential to improve deep learning-based QSM reconstruction.
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Affiliation(s)
- Wenbin Si
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Yihao Guo
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Qianqian Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Jinwei Zhang
- Department of Biomedical Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
- Department of Radiology, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | - Yi Wang
- Department of Biomedical Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
- Department of Radiology, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence and Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, China
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Relaxation anisotropy of quantitative MRI parameters in biological tissues. Sci Rep 2022; 12:12155. [PMID: 35840627 PMCID: PMC9287339 DOI: 10.1038/s41598-022-15773-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/29/2022] [Indexed: 11/16/2022] Open
Abstract
Quantitative MR relaxation parameters vary in the sensitivity to the orientation of the tissue in the magnetic field. In this study, the orientation dependence of multiple relaxation parameters was assessed in various tissues. Ex vivo samples of each tissue type were prepared either from bovine knee (tendon, cartilage) or mouse (brain, spinal cord, heart, kidney), and imaged at 9.4 T MRI with T1, T2, continuous wave (CW-) T1ρ, adiabatic T1ρ and T2ρ, and Relaxation along fictitious field (RAFF2-4) sequences at five different orientations with respect to the main magnetic field. Relaxation anisotropy of the measured parameters was quantified and compared. The highly ordered collagenous tissues, i.e. cartilage and tendon, presented the highest relaxation anisotropy for T2, CW-T1ρ with spin-lock power < 1 kHz, Ad-T2ρ and RAFF2-4. Maximally anisotropy was 75% in cartilage and 30% in tendon. T1 and adiabatic T1ρ did not exhibit observable anisotropy. In the other measured tissue types, anisotropy was overall less than 10% for all the parameters. The results confirm that highly ordered collagenous tissues have properties that induce very clearly observable relaxation anisotropy, whereas in other tissues the effect is not as prominent. Quantitative comparison of anisotropy of different relaxation parameters highlights the importance of sequence choice and design in MR imaging.
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Bachrata B, Trattnig S, Robinson SD. Quantitative susceptibility mapping of the head-and-neck using SMURF fat-water imaging with chemical shift and relaxation rate corrections. Magn Reson Med 2022; 87:1461-1479. [PMID: 34850446 PMCID: PMC7612304 DOI: 10.1002/mrm.29069] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 09/23/2021] [Accepted: 10/15/2021] [Indexed: 12/19/2022]
Abstract
PURPOSE To address the challenges posed by fat-water chemical shift artifacts and relaxation rate discrepancies to quantitative susceptibility mapping (QSM) outside the brain, and to generate accurate susceptibility maps of the head-and-neck at 3 and 7 Tesla. METHODS Simultaneous Multiple Resonance Frequency (SMURF) imaging was extended to 7 Tesla and used to acquire head-and-neck gradient echo images at both 3 and 7 Tesla. Separated fat and water images were corrected for Type 1 (displacement) and Type 2 (phase discrepancy) chemical shift artefacts, and for the bias resulting from differences in T1 and T 2 ∗ relaxation rates, recombined and used as the basis for QSM. A novel phase signal-based masking approach was used to generate head-and-neck masks. RESULTS SMURF generated well-separated fat and water images of the head-and-neck. Corrections for chemical shift artefacts and relaxation rate differences removed overestimation of the susceptibility values, blurring in the susceptibility maps, and the disproportionate influence of fat in mixed voxels. The resulting susceptibility maps showed high correspondence between the paramagnetic areas and the locations of fatty tissues and the susceptibility estimates were similar to literature values. The proposed masking approach was shown to provide a simple means of generating head-and-neck masks. CONCLUSION Corrections for Type 1 and Type 2 chemical shift artefacts and for fat-water relaxation rate differences, mainly in T1 , were shown to be required for accurate susceptibility mapping of fatty-body regions. SMURF made it possible to apply these corrections and generate high-quality susceptibility maps of the entire head-and-neck at both 3 and 7 Tesla.
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Affiliation(s)
- Beata Bachrata
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria
| | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia
- Department of Neurology, Medical University of Graz, Graz, Austria
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Stone AJ, Tornifoglio B, Johnston RD, Shmueli K, Kerskens C, Lally C. Quantitative susceptibility mapping of carotid arterial tissue ex vivo: Assessing sensitivity to vessel microstructural composition. Magn Reson Med 2021; 86:2512-2527. [PMID: 34270122 DOI: 10.1002/mrm.28893] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/27/2021] [Accepted: 05/31/2021] [Indexed: 01/01/2023]
Abstract
PURPOSE To characterize microstructural contributions to the magnetic susceptibility of carotid arteries. METHOD Arterial vessels were scanned using high-resolution quantitative susceptibility mapping (QSM) at 7 Tesla. Models of vessel degradation were generated using ex vivo porcine carotid arteries that were subjected to several different enzymatic digestion treatments that selectively removed microstructural components (smooth muscle cells, collagen, and elastin). Magnetic susceptibilities measured in these tissue models were compared to those in untreated (native) porcine arteries. Magnetic susceptibility measured in native porcine carotid arteries was further compared to the susceptibility of cadaveric human carotid arteries to investigate their similarity. RESULTS The magnetic susceptibility of native porcine vessels was diamagnetic (χnative = -0.1820 ppm), with higher susceptibilities in all models of vessel degradation (χelastin-degraded = -0.0163 ppm; χcollagen-degraded = -0.1158 ppm; χdecellularized = -0.1379 ppm; χfixed native = -0.2199 ppm). Magnetic susceptibility was significantly higher in collagen-degraded compared to native porcine vessels (Tukey-Kramer, P < .01) and between elastin-degraded and all other models (including native, Tukey-Kramer, P < .001). The susceptibility of fixed healthy human arterial tissue was diamagnetic, and no significant difference was found between fixed human and fixed porcine arterial tissue susceptibilities (analysis of variance, P > .05). CONCLUSIONS Magnetic susceptibility measured using QSM is sensitive to the microstructural composition of arterial vessels-most notably to collagen. The similarity of human and porcine arterial tissue susceptibility values provides a solid basis for translational studies. Because vessel microstructure becomes disrupted during the onset and progression of carotid atherosclerosis, QSM has the potential to provide a sensitive and specific marker of vessel disease.
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Affiliation(s)
- Alan J Stone
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland
| | - Brooke Tornifoglio
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland
| | - Robert D Johnston
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Caitríona Lally
- Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Mechanical, Manufacturing and Biomedical Engineering, School of Engineering, Trinity College Dublin, Dublin, Ireland.,Advanced Materials and Bioengineering Research Centre (AMBER), Royal College of Surgeons in Ireland and Trinity College Dublin, Dublin, Ireland
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7
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Bao L, Xiong C, Wei W, Chen Z, van Zijl PCM, Li X. Diffusion-regularized susceptibility tensor imaging (DRSTI) of tissue microstructures in the human brain. Med Image Anal 2020; 67:101827. [PMID: 33166777 DOI: 10.1016/j.media.2020.101827] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Revised: 08/19/2020] [Accepted: 08/31/2020] [Indexed: 10/23/2022]
Abstract
Susceptibility tensor imaging (STI) has been proposed as an alternative to diffusion tensor imaging (DTI) for non-invasive in vivo characterization of brain tissue microstructure and white matter fiber architecture, potentially benefitting from its high spatial resolution. In spite of different biophysical mechanisms, animal studies have demonstrated white matter fiber directions measured using STI to be reasonably consistent with those from diffusion tensor imaging (DTI). However, human brain STI is hampered by its requirement of acquiring data at more than 10 head rotations and a complicated processing pipeline. In this paper, we propose a diffusion-regularized STI method (DRSTI) that employs a tensor spectral decomposition constraint to regularize the STI solution using the fiber directions estimated by DTI as a priori. We then explore the high-resolution DRSTI with MR phase images acquired at only 6 head orientations. Compared to other STI approaches, the DRSTI generated susceptibility tensor components, mean magnetic susceptibility (MMS), magnetic susceptibility anisotropy (MSA) and fiber direction maps with fewer artifacts, especially in regions with large susceptibility variations, and with less erroneous quantifications. In addition, the DRSTI method allows us to distinguish more structural features that could not be identified in DTI, especially in deep gray matters. DRSTI enables a more accurate susceptibility tensor estimation with a reduced number of sampling orientations, and achieves better tracking of fiber pathways than previous STI attempts on in vivo human brain.
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Affiliation(s)
- Lijun Bao
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China.
| | - Congcong Xiong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China
| | - Wenping Wei
- Medical Imaging Diagnostic Center, First Affiliated Hospital of Xiamen University, Xiamen 361000, China
| | - Zhong Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361000, China
| | - Peter C M van Zijl
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Xu Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
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Kan H, Uchida Y, Arai N, Takizawa M, Miyati T, Kunitomo H, Kasai H, Shibamoto Y. Decreasing iron susceptibility with temperature in quantitative susceptibility mapping: A phantom study. Magn Reson Imaging 2020; 73:55-61. [PMID: 32853756 DOI: 10.1016/j.mri.2020.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/03/2020] [Accepted: 08/20/2020] [Indexed: 01/04/2023]
Abstract
To clarify the temperature dependence of susceptibility estimated by quantitative susceptibility mapping (QSM) analysis, we investigated the relationship between temperature and susceptibility using a cylinder phantom with varying temperatures. Six solutions with various concentrations of superparamagnetic iron oxide (SPIO) nanoparticles were employed. These tubes were placed in a cylinder phantom and surrounded with water. The temperature of the circulated water was adjusted to change the temperature in the cylinder phantom from 25.8 °C to 42.5 °C. The cylinder phantom was scanned via a three-dimensional multiple spoiled gradient-echo sequence for R2* and QSM analyses with varying temperatures. The relationships between temperature, susceptibility, and R2* values were determined. Moreover, the temperature coefficients of susceptibility (χ-Tc) and (R2*-Tc) were calculated at each concentration and the linearities in these indices against each SPIO concentration were validated. Significant inverse correlations were found between temperature, susceptibility, and R2* values at each SPIO concentration due to the decrease in paramagnetic iron susceptibility that occurred with increasing temperature based on Curie's law. Moreover, although there were significant correlations between the susceptibility and R2* values at any temperature, the slopes of the regression lines grew in height with greater temperatures. The percentage of difference per Celsius degree in susceptibility in any SPIO concentration was lower than the corresponding finding among the R2* results. There were strong linearities between the SPIO concentration, χ-Tc (r = -0.994; p < 0.001), and R2*-Tc (r = -0.998; p < 0.001). The χ-Tc and R2*-Tc outcomes in a particular voxel varied considerably with the iron contents. Although there was an inverse correlation noted between temperature and susceptibility, the susceptibility analysis showed smaller temperature dependence relative to the R2* analysis. QSM analysis might be a more suitable option for magnetic resonance-based iron quantification in comparison with R2* relaxometry.
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Affiliation(s)
- Hirohito Kan
- Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, 1-1-20, Daiko-Minami, Higashi-ku, Nagoya, Aichi 461-8673, Japan; Department of Radiology, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-ku, Nagoya, Aichi 467-8601, Japan.
| | - Yuto Uchida
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-ku, Nagoya, Aichi 467-8601, Japan; Department of Neurology, Toyokawa City Hospital, 23 noji, Yahata-cho, Toyokawa, Aichi 442-8561, Japan
| | - Nobuyuki Arai
- Department of Radiology, Nagoya City University Hospital, 1 Kawasumi, Mizuho-ku, Nagoya, Aichi 467-8601, Japan.
| | - Masahiro Takizawa
- Healthcare Business Unit, Hitachi Ltd., 2-16-1 Higashi-Ueno, Daito-ku, Tokyo 110-0015, Japan.
| | - Tosiaki Miyati
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa 920-0942, Japan.
| | - Hiroshi Kunitomo
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa 920-0942, Japan.
| | - Harumasa Kasai
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa 920-0942, Japan
| | - Yuta Shibamoto
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-ku, Nagoya, Aichi 467-8601, Japan.
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Wei H, Cao S, Zhang Y, Guan X, Yan F, Yeom KW, Liu C. Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction. Neuroimage 2019; 202:116064. [PMID: 31377323 PMCID: PMC6819263 DOI: 10.1016/j.neuroimage.2019.116064] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 07/29/2019] [Accepted: 07/30/2019] [Indexed: 01/11/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. This inaccuracy has thus hindered the application of QSM for measuring susceptibility of tissues near the brain edges, e.g., quantifying cortical layers and generating superficial venography. To address these challenges, we propose a learning-based QSM reconstruction method that directly estimates the magnetic susceptibility from total phase images without the need for brain extraction and background phase removal, referred to as autoQSM. The neural network has a modified U-net structure and is trained using QSM maps computed by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82 years were employed for patch-wise network training. The network was validated on data dissimilar to the training data, e.g., in vivo mouse brain data and brains with lesions, which suggests that the network generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. Quantitative and qualitative comparisons were performed between autoQSM and other two-step QSM methods. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction, and high reconstruction speed demonstrate autoQSM's potential for future applications.
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Affiliation(s)
- Hongjiang Wei
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
| | - Steven Cao
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fuhua Yan
- Department of Radiology, Rui Jin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China
| | - Kristen W Yeom
- Department of Radiology, Lucile Packard Children's Hospital, Stanford University, Palo Alto, CA, USA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
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10
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Wei H, Decker K, Nguyen H, Cao S, Tsai TY, Dianne Guy C, Bashir M, Liu C. Imaging diamagnetic susceptibility of collagen in hepatic fibrosis using susceptibility tensor imaging. Magn Reson Med 2019; 83:1322-1330. [PMID: 31633237 DOI: 10.1002/mrm.27995] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Revised: 08/22/2019] [Accepted: 08/24/2019] [Indexed: 12/16/2022]
Abstract
PURPOSE To characterize the magnetic susceptibility changes of liver fibrosis using susceptibility tensor imaging. METHODS Liver biopsy tissue samples of patients with liver fibrosis were obtained. Three-dimensional gradient-echo and diffusion-weighted images were acquired at 9.4 T. Susceptibility tensors of the samples were calculated using the gradient-echo phase signal acquired at 12 different orientations relative to the B0 field. Susceptibility anisotropy of the liver collagen fibers was quantified and compared with diffusion anisotropy, measured by DTI. For validation, a comparison was made to histology including hematoxylin and eosin staining, iron staining, and Masson's trichrome staining. RESULTS Areas with strong diamagnetic susceptibility were observed in the tissue samples forming fibrous patterns. This diamagnetic susceptibility was highly anisotropic. Both the mean magnetic susceptibility and susceptibility anisotropy of collagen fibers exhibited a strong contrast against the surrounding nonfibrotic tissues. The same regions also showed an elevated diffusion anisotropy but with much lower tissue contrast. Masson's trichrome staining identified concentrated collagens in the fibrous regions with high susceptibility anisotropy, and a linear correlation was found between the susceptibility anisotropy and the histology-based staging. CONCLUSION Diamagnetic susceptibility indicates the presence of collagen in the fibrotic liver tissues. Mapping magnetic susceptibility anisotropy may serve as a potential marker to quantify collagen fiber changes in patients with liver fibrosis.
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Affiliation(s)
- Hongjiang Wei
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California
| | - Kyle Decker
- Center for In Vivo Microscopy, Duke University, Durham, North Carolina
| | - Hien Nguyen
- Department of Pathology, Duke University, Durham, North Carolina
| | - Steven Cao
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California
| | - Tsung-Yuan Tsai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | | | - Mustafa Bashir
- Department of Radiology, Duke University, Durham, North Carolina.,Center for Advanced Magnetic Resonance Development, Duke University, Durham, North Carolina.,Division of Gastroenterology, Department of Medicine, Duke University, Durham, North Carolina
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California.,Helen Wills Neuroscience Institute, University of California, Berkeley, California
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Zhang Y, Shi J, Wei H, Han V, Zhu WZ, Liu C. Neonate and infant brain development from birth to 2 years assessed using MRI-based quantitative susceptibility mapping. Neuroimage 2018; 185:349-360. [PMID: 30315906 DOI: 10.1016/j.neuroimage.2018.10.031] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Revised: 09/10/2018] [Accepted: 10/09/2018] [Indexed: 12/23/2022] Open
Abstract
The human brain rapidly develops during the first two years following birth. Quantitative susceptibility mapping (QSM) provides information of iron and myelin variations. It is considered to be a valuable tool for studying brain development in early life. In the present work, QSM is performed on neonates, 1-year and 2-year old infants, as well as a group of adults for the purpose of reference. Age-specific templates representing common brain structures are built for each age group. The neonate and infant QSM templates have shown some unique findings compared to conventional T1w and T2w imaging techniques. The contrast between the gray and white matters on the QSM images did not change through brain development from neonate to adult. A linear correlation was found between brain myelination determined in this study and the microscopic myelin degree determined by a previous autopsy study. Also, the magnetic susceptibility values of the cerebral spinal fluid (CSF) exhibit a gradually decreasing trend from birth to 2 years old and to adulthood. The findings suggest that the macromolecular content, myelin, and iron may play the most important contributing factors for the magnetic susceptibility of neonate and infant brain. QSM can be a powerful means to study early brain development and related pathologies that involve alterations in macromolecular content, iron, or brain myelination.
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Affiliation(s)
- Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jingjing Shi
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongjiang Wei
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA
| | - Victor Han
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA
| | - Wen-Zhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Chunlei Liu
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California at Berkeley, CA, USA.
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12
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Zhang Y, Wei H, Sun Y, Cronin MJ, He N, Xu J, Zhou Y, Liu C. Quantitative susceptibility mapping (QSM) as a means to monitor cerebral hematoma treatment. J Magn Reson Imaging 2018; 48:907-915. [PMID: 29380461 PMCID: PMC6066470 DOI: 10.1002/jmri.25957] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 01/10/2018] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) offers a consistent hemorrhage volume measurement independent of imaging parameters. PURPOSE To investigate the magnetic susceptibility of intracerebral hemorrhage (ICH) as a quantitative measurement for monitoring treatment in hematoma patients. STUDY TYPE Prospective. POPULATION Twenty-six patients with acute ICH were recruited and enrolled in treatment including surgery or medication (mannitol) for 1 week. FIELD STRENGTH/SEQUENCE A 3D gradient echo sequence at 3.0T. ASSESSMENT The hematoma volumes on computed tomography (CT) and QSM were calculated and used for correlation analysis. Magnetic susceptibility changes from pre- to posttreatment were calculated and compared to the National Institutes of Health stroke scale (NIHSS) measure of neurological deficit for each patient. STATISTICAL TESTS Mean susceptibility values were calculated over each region of interest (ROI). A one-sample t-test was used to assess the changes of total volumes and mean magnetic susceptibility of ICH identified between pre- and posttreatment images (P < 0.05 was considered significant) and the Bland-Altman analysis with 95% limits of agreement (average difference, ±1.96 SD of the difference). Regression of volume measurements on QSM vs. CT and fitted linear regression of mean susceptibility vs. CT signal intensity for hematoma regions were conducted in all patients. RESULTS Good correlation was found between hemorrhage volumes calculated from CT and QSM (CT volume = 0.94*QSM volume, r = 0.98). Comparison of QSM pre- and posttreatment showed that the mean ICH volume was reduced by a statistically insignificant amount from 5.74 cm3 to 5.45 cm3 (P = 0.21), while mean magnetic susceptibility was reduced significantly from 0.48 ppm to 0.38 ppm (P = 0.004). A significant positive association was found between changes in magnetic susceptibility values and NIHSS following hematoma treatment (P < 0.01). DATA CONCLUSIONS QSM in hematoma assessment, as compared with CT, offers a comparably accurate volume measurement; however, susceptibility measurements may enable improved monitoring of ICH treatment compared to volume measurements alone. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:907-915.
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Affiliation(s)
- Yuyao Zhang
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Yawen Sun
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Matthew J. Cronin
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Naying He
- Department of Radiology, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianrong Xu
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yan Zhou
- Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
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13
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Nykänen O, Rieppo L, Töyräs J, Kolehmainen V, Saarakkala S, Shmueli K, Nissi MJ. Quantitative susceptibility mapping of articular cartilage: Ex vivo findings at multiple orientations and following different degradation treatments. Magn Reson Med 2018; 80:2702-2716. [PMID: 29687923 PMCID: PMC6220965 DOI: 10.1002/mrm.27216] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 03/16/2018] [Accepted: 03/19/2018] [Indexed: 01/23/2023]
Abstract
Purpose We investigated the feasibility of quantitative susceptibility mapping (QSM) for assessing degradation of articular cartilage by measuring ex vivo bovine cartilage samples subjected to different degradative treatments. Specimens were scanned at several orientations to study if degradation affects the susceptibility anisotropy. T2*‐mapping, histological stainings, and polarized light microscopy were used as reference methods. Additionally, simulations of susceptibility in layered geometry were performed. Methods Samples (n = 9) were harvested from the patellae of skeletally mature bovines. Three specimens served as controls, and the rest were artificially degraded. MRI was performed at 9.4T using a 3D gradient echo sequence. QSM and T2* images and depth profiles through the centers of the samples were compared with each other and the histological findings. A planar isotropic model with depth‐wise susceptibility variation was used in the simulations. Results A strong diamagnetic contrast was seen in the deep and calcified layers of cartilage, while T2* maps reflected the typical trilaminar structure of the collagen network. Anisotropy of susceptibility in cartilage was observed and was found to differ from the T2* anisotropy. Slight changes were observed in QSM and T2* following the degradative treatments. In simulations, anisotropy was observed. Conclusions The results suggest that QSM is not sensitive to cartilage proteoglycan content, but shows sensitivity to the amount of calcification and to the integrity of the collagen network, providing potential for assessing osteoarthritis. The simulations suggested that the anisotropy of susceptibility might be partially explained by the layered geometry of susceptibility in cartilage.
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Affiliation(s)
- Olli Nykänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Lassi Rieppo
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Juha Töyräs
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.,Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Ville Kolehmainen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Simo Saarakkala
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, University of Oulu and Oulu University Hospital, Oulu, Finland.,Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Karin Shmueli
- Department of Medical Physics & Biomedical Engineering, University College London (UCL), London, United Kingdom
| | - Mikko J Nissi
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
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14
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Quantifying MRI frequency shifts due to structures with anisotropic magnetic susceptibility using pyrolytic graphite sheet. Sci Rep 2018; 8:6259. [PMID: 29674616 PMCID: PMC5908955 DOI: 10.1038/s41598-018-24650-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 03/26/2018] [Indexed: 01/23/2023] Open
Abstract
Magnetic susceptibility is an important source of contrast in magnetic resonance imaging (MRI), with spatial variations in the susceptibility of tissue affecting both the magnitude and phase of the measured signals. This contrast has generally been interpreted by assuming that tissues have isotropic magnetic susceptibility, but recent work has shown that the anisotropic magnetic susceptibility of ordered biological tissues, such as myelinated nerves and cardiac muscle fibers, gives rise to unexpected image contrast. This behavior occurs because the pattern of field variation generated by microstructural elements formed from material of anisotropic susceptibility can be very different from that predicted by modelling the effects in terms of isotropic susceptibility. In MR images of tissue, such elements are manifested at a sub-voxel length-scale, so the patterns of field variation that they generate cannot be directly visualized. Here, we used pyrolytic graphite sheet which has a large magnetic susceptibility anisotropy to form structures of known geometry with sizes large enough that the pattern of field variation could be mapped directly using MRI. This allowed direct validation of theoretical expressions describing the pattern of field variation from anisotropic structures with biologically relevant shapes (slabs, spherical shells and cylindrical shells).
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15
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Duyn JH. Studying brain microstructure with magnetic susceptibility contrast at high-field. Neuroimage 2018; 168:152-161. [PMID: 28242317 PMCID: PMC5569005 DOI: 10.1016/j.neuroimage.2017.02.046] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 02/03/2017] [Accepted: 02/16/2017] [Indexed: 12/14/2022] Open
Abstract
A rapidly developing application of high field MRI is the study of brain anatomy and function with contrast based on the magnetic susceptibility of tissues. To study the subtle variations in susceptibility contrast between tissues and with changes in brain activity, dedicated scan techniques such as susceptibility-weighted MRI and blood-oxygen level dependent functional MRI have been developed. Particularly strong susceptibility contrast has been observed with systems that operate at 7T and above, and their recent widespread use has led to an improved understanding of contributing sources and mechanisms. To interpret magnetic susceptibility contrast, analysis approaches have been developed with the goal of extracting measures that report on local tissue magnetic susceptibility, a physical quantity that, under certain conditions, allows estimation of blood oxygenation, local tissue iron content, and quantification of its changes with disease. Interestingly, high field studies have also brought to light that not only the makeup of tissues affects MRI susceptibility contrast, but that also a tissue's sub-voxel structure at scales all the way down to the molecular level plays an important role as well. In this review, various ways will be discussed by which sub-voxel structure can affect the MRI signal in general, and magnetic susceptibility in particular, sometimes in a complex fashion. In the light of this complexity, it appears likely that accurate, brain-wide quantification of iron will require the combination of multiple contrasts that may include diffusion and magnetization transfer information with susceptibility-weighted contrast. On the other hand, this complexity also offers opportunities to use magnetic susceptibility contrast to inform about specific microstructural aspects of brain tissue. Details and several examples will be presented in this review.
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Affiliation(s)
- Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institutes of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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16
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Wei H, Gibbs E, Zhao P, Wang N, Cofer GP, Zhang Y, Johnson GA, Liu C. Susceptibility tensor imaging and tractography of collagen fibrils in the articular cartilage. Magn Reson Med 2017; 78:1683-1690. [PMID: 28856712 PMCID: PMC5786159 DOI: 10.1002/mrm.26882] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Revised: 07/24/2017] [Accepted: 07/30/2017] [Indexed: 12/17/2022]
Abstract
PURPOSE To investigate the B0 orientation-dependent magnetic susceptibility of collagen fibrils within the articular cartilage and to determine whether susceptibility tensor imaging (STI) can detect the 3D collagen network within cartilage. METHODS Multiecho gradient echo datasets (100-μm isotropic resolution) were acquired from fixed porcine articular cartilage specimens at 9.4 T. The susceptibility tensor was calculated using phase images acquired at 12 or 15 different orientations relative to B0 . The susceptibility anisotropy of the collagen fibril was quantified and diffusion tensor imaging (DTI) was compared against STI. 3D tractography was performed to visualize and track the collagen fibrils with DTI and STI. RESULTS STI experiments showed the distinct and significant anisotropic magnetic susceptibility of collagen fibrils within the articular cartilage. STI can be used to measure and quantify susceptibility anisotropy maps. Furthermore, STI provides orientation information of the underlying collagen network via 3D tractography. CONCLUSION The findings of this study demonstrate that STI can characterize the orientation variation of collagen fibrils where diffusion anisotropy fails. We believe that STI could serve as a sensitive and noninvasive marker to study the collagen fibrils microstructure. Magn Reson Med 78:1683-1690, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Eric Gibbs
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Peida Zhao
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Nian Wang
- Center for In Vivo Microscopy, Duke University, Durham, NC, USA
| | - Gary P. Cofer
- Center for In Vivo Microscopy, Duke University, Durham, NC, USA
| | - Yuyao Zhang
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | | | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
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17
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Hänninen N, Rautiainen J, Rieppo L, Saarakkala S, Nissi MJ. Orientation anisotropy of quantitative MRI relaxation parameters in ordered tissue. Sci Rep 2017; 7:9606. [PMID: 28852032 PMCID: PMC5574987 DOI: 10.1038/s41598-017-10053-2] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 08/02/2017] [Indexed: 12/04/2022] Open
Abstract
In highly organized tissues, such as cartilage, tendons and white matter, several quantitative MRI parameters exhibit dependence on the orientation of the tissue constituents with respect to the main imaging magnetic field (B0). In this study, we investigated the dependence of multiple relaxation parameters on the orientation of articular cartilage specimens in the B0. Bovine patellar cartilage-bone samples (n = 4) were investigated ex vivo at 9.4 Tesla at seven different orientations, and the MRI results were compared with polarized light microscopy findings on specimen structure. Dependences of T2 and continuous wave (CW)-T1ρ relaxation times on cartilage orientation were confirmed. T2 (and T2*) had the highest sensitivity to orientation, followed by TRAFF2 and adiabatic T2ρ. The highest dependence was seen in the highly organized deep cartilage and the smallest in the least organized transitional layer. Increasing spin-lock amplitude decreased the orientation dependence of CW-T1ρ. T1 was found practically orientation-independent and was closely followed by adiabatic T1ρ. The results suggest that T1 and adiabatic T1ρ should be preferred for orientation-independent quantitative assessment of organized tissues such as articular cartilage. On the other hand, based on the literature, parameters with higher orientation anisotropy appear to be more sensitive to degenerative changes in cartilage.
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Affiliation(s)
- Nina Hänninen
- Department of Applied Physics, University of Eastern Finland, POB 1627, FI-70211, Kuopio, Finland
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, FI-90014, Oulu, Finland
| | - Jari Rautiainen
- Department of Applied Physics, University of Eastern Finland, POB 1627, FI-70211, Kuopio, Finland
| | - Lassi Rieppo
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, FI-90014, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Simo Saarakkala
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, FI-90014, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
| | - Mikko Johannes Nissi
- Department of Applied Physics, University of Eastern Finland, POB 1627, FI-70211, Kuopio, Finland.
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18
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Wei H, Dibb R, Decker K, Wang N, Zhang Y, Zong X, Lin W, Nissman DB, Liu C. Investigating magnetic susceptibility of human knee joint at 7 Tesla. Magn Reson Med 2017; 78:1933-1943. [PMID: 28097689 DOI: 10.1002/mrm.26596] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 12/06/2016] [Accepted: 12/12/2016] [Indexed: 11/07/2022]
Abstract
PURPOSE To evaluate the magnetic susceptibility properties of different anatomical structures within the knee joint using quantitative susceptibility mapping (QSM). METHODS A collagen tissue model was simulated and ex vivo animal cartilage experiments were conducted at 9.4 Tesla (T) to evaluate the B0 orientation-dependent magnetic susceptibility contrast observed in cartilage. Furthermore, nine volunteers (six healthy subjects without knee pain history and three patients with known knee injury, between 29 and 58 years old) were scanned using gradient-echo acquisitions on a high-field 7T MR scanner. Susceptibility values of different tissues were quantified and diseased cartilage and meniscus were compared against that of healthy volunteers. RESULTS Simulation and ex vivo animal cartilage experiments demonstrated that collagen fibrils exhibit an anisotropic susceptibility. A gradual change of magnetic susceptibility was observed in the articular cartilage from the superficial zone to the deep zone, forming a multilayer ultrastructure consistent with anisotropy of collagen fibrils. Meniscal tears caused a clear reduction of susceptibility contrast between the injured meniscus and surrounding cartilage illustrated by a loss of the sharp boundaries between the two. Moreover, QSM showed more dramatic contrast in the focal degenerated articular cartilage than R2* mapping. CONCLUSION The arrangement of the collagen fibrils is significant, and likely the most dominant source of magnetic susceptibility anisotropy. Quantitative susceptibility mapping offers a means to characterize magnetic susceptibility properties of tissues in the knee joint. It is sensitive to collagen damage or degeneration and may be useful for evaluating the status of knee diseases, such as meniscal tears and cartilage disease. Magn Reson Med 78:1933-1943, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Hongjiang Wei
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Russell Dibb
- Center for In Vivo Microscopy, Duke University, Durham, North Carolina, USA
| | - Kyle Decker
- Center for In Vivo Microscopy, Duke University, Durham, North Carolina, USA
| | - Nian Wang
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
| | - Yuyao Zhang
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Xiaopeng Zong
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Weili Lin
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Daniel B Nissman
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Chunlei Liu
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
- Department of Radiology, School of Medicine, Duke University, Durham, North Carolina, USA
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