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Brain Iron and Mental Health Symptoms in Youth with and without Prenatal Alcohol Exposure. Nutrients 2022; 14:nu14112213. [PMID: 35684012 PMCID: PMC9183007 DOI: 10.3390/nu14112213] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/18/2022] [Accepted: 05/19/2022] [Indexed: 12/18/2022] Open
Abstract
Prenatal alcohol exposure (PAE) negatively affects brain development and increases the risk of poor mental health. We investigated if brain volumes or magnetic susceptibility, an indirect measure of brain iron, were associated with internalizing or externalizing symptoms in youth with and without PAE. T1-weighted and quantitative susceptibility mapping (QSM) MRI scans were collected for 19 PAE and 40 unexposed participants aged 7.5–15 years. Magnetic susceptibility and volume of basal ganglia and limbic structures were extracted using FreeSurfer. Internalizing and Externalizing Problems were assessed using the Behavioural Assessment System for Children (BASC-2-PRS). Susceptibility in the nucleus accumbens was negatively associated with Internalizing Problems, while amygdala susceptibility was positively associated with Internalizing Problems across groups. PAE moderated the relationship between thalamus susceptibility and internalizing symptoms as well as the relationship between putamen susceptibility and externalizing symptoms. Brain volume was not related to internalizing or externalizing symptoms. These findings highlight that brain iron is related to internalizing and externalizing symptoms differently in some brain regions for youth with and without PAE. Atypical iron levels (high or low) may indicate mental health issues across individuals, and iron in the thalamus may be particularly important for behavior in individuals with PAE.
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Lancione M, Cencini M, Costagli M, Donatelli G, Tosetti M, Giannini G, Zangaglia R, Calandra-Buonaura G, Pacchetti C, Cortelli P, Cosottini M. Diagnostic accuracy of quantitative susceptibility mapping in multiple system atrophy: The impact of echo time and the potential of histogram analysis. Neuroimage Clin 2022; 34:102989. [PMID: 35303599 PMCID: PMC8927993 DOI: 10.1016/j.nicl.2022.102989] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/25/2022] [Accepted: 03/10/2022] [Indexed: 11/07/2022]
Abstract
We performed histogram analysis on χ maps at different TEs on MSA patients and HC. We found altered χ distribution in Pu, SN, GP, CN for MSAp and in SN, DN for MSAc. QSM diagnostic accuracy is TE-dependent and is enhanced at short TEs. Short TEs capture rapidly-decaying contributions of high χ sources. Histogram features detect χ spatial heterogeneities improving diagnostic accuracy.
The non-invasive quantification of iron stores via Quantitative Susceptibility Mapping (QSM) could play an important role in the diagnosis and the differential diagnosis of atypical Parkinsonisms. However, the susceptibility (χ) values measured via QSM depend on echo time (TE). This effect relates to the microstructural organization within the voxel, whose composition can be altered by the disease. Moreover, pathological iron deposition in a brain area may not be spatially uniform, and conventional Region of Interest (ROI)-based analysis may fail in detecting alterations. Therefore, in this work we evaluated the impact of echo time on the diagnostic accuracy of QSM on a population of patients with Multiple System Atrophy (MSA) of either Parkinsonian (MSAp) or cerebellar (MSAc) phenotypes. In addition, we tested the potential of histogram analysis to improve QSM classification accuracy. We enrolled 32 patients (19 MSAp and 13 MSAc) and 16 healthy controls, who underwent a 7T MRI session including a gradient-recalled multi-echo sequence for χ mapping. Nine histogram features were extracted from the χ maps computed for each TE in atlas-based ROIs covering deep brain nuclei, and compared among groups. Alterations of susceptibility distribution were found in the Putamen, Substantia Nigra, Globus Pallidus and Caudate Nucleus for MSAp and in the Substantia Nigra and Dentate Nucleus for MSAc. Increased iron deposition was observed in a larger number of ROIs for the two shortest TEs and the standard deviation, the 75th and the 90th percentile were the most informative features yielding excellent diagnostic accuracy with area under the ROC curve > 0.9. In conclusion, short TEs may enhance QSM diagnostic performances, as they can capture variations in rapidly-decaying contributions of high χ sources. The analysis of histogram features allowed to reveal fine heterogeneities in the spatial distribution of susceptibility alteration, otherwise undetected by a simple evaluation of ROI χ mean values.
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Affiliation(s)
- Marta Lancione
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Matteo Cencini
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genova, Genova, Italy.
| | - Graziella Donatelli
- IMAGO7 Foundation, Pisa, Italy; Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Michela Tosetti
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Giulia Giannini
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Roberta Zangaglia
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Giovanna Calandra-Buonaura
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Claudio Pacchetti
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Pietro Cortelli
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
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103
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Sung YH, Kim JS, Yoo SW, Shin NY, Nam Y, Ahn TB, Yoo D, Lee KM, Kim HG, Koh SB, Kim J, Kim I, Kwon DY, Lee Y, Kim C, Chung SJ, Jo S, Lee SH, Kim SJ, Kim M, Lyoo CH, Baek MS, Kang SY, Chang SK, Jo SW, Lee SA, Ma HI, Kim YE, Kim ES, Kim YJ, Kim HS, Woo MH, Choi HJ, Kim EY. A prospective multi-centre study of susceptibility map-weighted MRI for the diagnosis of neurodegenerative parkinsonism. Eur Radiol 2022; 32:3597-3608. [PMID: 35064313 DOI: 10.1007/s00330-021-08454-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 09/25/2021] [Accepted: 10/27/2021] [Indexed: 11/04/2022]
Abstract
OBJECTIVES This study aimed to compare susceptibility map-weighted imaging (SMwI) using various MRI machines (three vendors) with N-3-fluoropropyl-2-β-carbomethoxy-3-β-(4-iodophe nyl)nortropane (18F-FP-CIT) PET in the diagnosis of neurodegenerative parkinsonism in a multi-centre setting. METHODS We prospectively recruited 257 subjects, including 157 patients with neurodegenerative parkinsonism, 54 patients with non-neurodegenerative parkinsonism, and 46 healthy subjects from 10 hospitals between November 2019 and October 2020. All participants underwent both SMwI and 18F-FP-CIT PET. SMwI was interpreted by two independent reviewers for the presence or absence of abnormalities in nigrosome 1, and discrepancies were resolved by consensus. 18F-FP-CIT PET was used as the reference standard. Inter-observer agreement was tested using Cohen's kappa coefficient. McNemar's test was used to test the agreement between the interpretations of SMwI and 18F-FP-CIT PET per participant and substantia nigra (SN). RESULTS The inter-observer agreement was 0.924 and 0.942 per SN and participant, respectively. The diagnostic sensitivity of SMwI was 97.9% and 99.4% per SN and participant, respectively; its specificity was 95.9% and 95.2%, respectively, and its accuracy was 97.1% and 97.7%, respectively. There was no significant difference between the results of SMwI and 18F-FP-CIT PET (p > 0.05, for both SN and participant). CONCLUSIONS This study demonstrated that the high diagnostic performance of SMwI was maintained in a multi-centre setting with various MRI scanners, suggesting the generalisability of SMwI for determining nigrostriatal degeneration in patients with parkinsonism. KEY POINTS • Susceptibility map-weighted imaging helps clinicians to predict nigrostriatal degeneration. • The protocol for susceptibility map-weighted imaging can be standardised across MRI vendors. • Susceptibility map-weighted imaging showed diagnostic performance comparable to that of dopamine transporter PET in a multi-centre setting with various MRI scanners.
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Affiliation(s)
- Young Hee Sung
- Department of Neurology, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea
| | - Joong-Seok Kim
- Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sang-Won Yoo
- Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Na-Young Shin
- Department of Radiology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Tae-Beom Ahn
- Department of Neurology, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Dallah Yoo
- Department of Neurology, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Kyung Mi Lee
- Department of Radiology, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Hyug-Gi Kim
- Department of Radiology, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Seong-Beom Koh
- Department of Neurology and Parkinson's Disease Centre, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jinhee Kim
- Department of Neurology and Parkinson's Disease Centre, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Ilsoo Kim
- Department of Neurology and Parkinson's Disease Centre, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Do-Young Kwon
- Department of Neurology, Center for Movement Disorders and Neurodegenerative Diseases, Korea University Ansan Hospital, Ansan-si, Gyeonggi-do, Republic of Korea
| | - Younghen Lee
- Department of Radiology, Korea University Ansan Hospital, Ansan-si, Gyeonggi-do, Republic of Korea
| | - Chulhan Kim
- Department of Nuclear Medicine, Korea University Ansan Hospital, Ansan-si, Gyeonggi-do, Republic of Korea
| | - Sun Ju Chung
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sungyang Jo
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Seung Hyun Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Minjae Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Min Seok Baek
- Department of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Gangwon do, Wonju, Republic of Korea
| | - Suk Yun Kang
- Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong-si, Gyeonggi-do, Republic of Korea
| | - Suk Ki Chang
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong-si, Gyeonggi-do, Republic of Korea
| | - Sang-Won Jo
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong-si, Gyeonggi-do, Republic of Korea
| | - Seun Ah Lee
- Department of Radiology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong-si, Gyeonggi-do, Republic of Korea
| | - Hyeo-Il Ma
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang-si, Gyeonggi-do, Republic of Korea
| | - Young Eun Kim
- Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang-si, Gyeonggi-do, Republic of Korea
| | - Eun Soo Kim
- Department of Radiology, Hallym University Sacred Heart Hospital, Anyang-si, Gyeonggi-do, Republic of Korea
| | - Yun Joong Kim
- Department of Neurology, Center for Neurodegenerative Disorders, Yongin Severance Hospital, Yonsei University Health System, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Republic of Korea
| | - Hyun Sook Kim
- Department of Neurology, CHA Bundang Medical Center, CHA University, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Min-Hee Woo
- Department of Neurology, CHA Bundang Medical Center, CHA University, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Hye Jeong Choi
- Radiology Department, CHA Bundang Medical Center, CHA University, Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Eung Yeop Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81, Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
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Chen Y, Genc O, Poynton CB, Banerjee S, Hess CP, Lupo JM. Comparison of quantitative susceptibility mapping methods on evaluating radiation-induced cerebral microbleeds and basal ganglia at 3T and 7T. NMR IN BIOMEDICINE 2022; 35:e4666. [PMID: 35075701 PMCID: PMC10443943 DOI: 10.1002/nbm.4666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 11/04/2021] [Accepted: 11/24/2021] [Indexed: 06/14/2023]
Abstract
Quantitative susceptibility mapping (QSM) has the potential for being a biomarker for various diseases because of its ability to measure tissue susceptibility related to iron deposition, myelin, and hemorrhage from the phase signal of a T2 *-weighted MRI. Despite its promise as a quantitative marker, QSM is faced with many challenges, including its dependence on preprocessing of the raw phase data, the relatively weak tissue signal, and the inherently ill posed relationship between the magnetic dipole and measured phase. The goal of this study was to evaluate the effects of background field removal and dipole inversion algorithms on noise characteristics, image uniformity, and structural contrast for cerebral microbleed (CMB) quantification at both 3T and 7T. We selected four widely used background phase removal and five dipole field inversion algorithms for QSM and applied them to volunteers and patients with CMBs, who were scanned at two different field strengths, with ground truth QSM reference calculated using multiple orientation scans. 7T MRI provided QSM images with lower noise than did 3T MRI. QSIP and VSHARP + iLSQR achieved the highest white matter homogeneity and vein contrast, with QSIP also providing the highest CMB contrast. Compared with ground truth COSMOS QSM images, overall good correlations between susceptibility values of dipole inversion algorithms and the COSMOS reference were observed in basal ganglia regions, with VSHARP + iLSQR achieving the susceptibility values most similar to COSMOS across all regions. This study can provide guidance for selecting the most appropriate QSM processing pipeline based on the application of interest and scanner field strength.
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Affiliation(s)
- Yicheng Chen
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, CA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | - Ozan Genc
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
- Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey
| | - Clare B. Poynton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
| | | | - Christopher P. Hess
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
- Department of Neurology, University of California, San Francisco, CA
| | - Janine M. Lupo
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, Berkeley and San Francisco, CA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA
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105
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Oh G, Bae H, Ahn HS, Park SH, Moon WJ, Ye JC. Unsupervised Resolution-Agnostic Quantitative Susceptibility Mapping using Adaptive Instance Normalization. Med Image Anal 2022; 79:102477. [DOI: 10.1016/j.media.2022.102477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 05/04/2022] [Accepted: 05/06/2022] [Indexed: 11/30/2022]
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106
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Mao H, Dou W, Chen K, Wang X, Wang X, Guo Y, Zhang C. Evaluating iron deposition in gray matter nuclei of patients with unilateral middle cerebral artery stenosis using quantitative susceptibility mapping. Neuroimage Clin 2022; 34:103021. [PMID: 35500369 PMCID: PMC9065429 DOI: 10.1016/j.nicl.2022.103021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 03/17/2022] [Accepted: 04/23/2022] [Indexed: 11/18/2022]
Abstract
Iron mediated oxidative stress is involved in the process of brain injury after long-term ischemia. While increased iron deposition in the affected brain regions was observed in animal models of ischemic stroke, potential changes in the brain iron content in clinical patients with cerebral ischemia remain unclear. Quantitative susceptibility mapping (QSM), a non-invasive magnetic resonance imaging technique, can be used to evaluate iron content in the gray matter (GM) nuclei reliably. In this study, we aimed to quantitatively evaluate iron content changes in GM nuclei of patients with long-term unilateral middle cerebral artery (MCA) stenosis/occlusion-related cerebral ischemia using QSM. Forty-six unilateral MCA stenosis/occlusion patients and 38 age-, sex- and education-matched healthy controls underwent QSM. Clinical variables of history of hypertension, diabetes, hyperlipidemia, hyperhomocysteinemia, smoking, and drinking in all patients were evaluated. The iron-related susceptibility of GM nucleus subregions, including the bilateral caudate nucleus (CN), putamen (PU), globus pallidus (GP), thalamus, substantia nigra (SN), red nucleus, and dentate nucleus, was assessed. Susceptibility was compared between the bilateral GM nuclei in patients and controls. Receiver operating characteristic curve analysis was used to evaluate the efficacy of QSM susceptibility in distinguishing patients with unilateral MCA stenosis/occlusion from healthy controls. Multiple linear regression analysis was used to evaluate the relationship between ipsilateral susceptibility levels and clinical variables. Except for the CN, the susceptibility in most bilateral GM nucleus subregions was comparable in healthy controls, whereas for patients with unilateral MCA stenosis/occlusion, the ipsilateral PU, GP, and SN exhibited significantly higher susceptibility than the contralateral side (all P < 0.05). Compared with controls, susceptibility of the ipsilateral PU, GP, and SN and of contralateral PU in patients were significantly increased (all P < 0.05). The area under the curve (AUC) was greater for the ipsilateral PU than for the GP and SN (AUC = 0.773, 0.662 and 0.681; all P < 0.05). Multiple linear regression analysis showed that the increased susceptibility of the ipsilateral PU was significantly associated with hypertension, of the ipsilateral GP associated with smoking, and of the ipsilateral SN associated with diabetes (all P < 0.05). Our findings provide support for abnormal iron accumulation in the GM nuclei after chronic MCA stenosis/occlusion and its correlation with some cerebrovascular disease risk factors. Therefore, iron deposition in the GM nuclei, as measured by QSM, may be a potential biomarker for long-term cerebral ischemia.
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Affiliation(s)
- Huimin Mao
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Weiqiang Dou
- MR Research, GE Healthcare, Beijing 10076, China
| | - Kunjian Chen
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Xinyu Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Xinyi Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China.
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Chao Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China
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107
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Jung W, Bollmann S, Lee J. Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities. NMR IN BIOMEDICINE 2022; 35:e4292. [PMID: 32207195 DOI: 10.1002/nbm.4292] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 02/04/2020] [Accepted: 02/25/2020] [Indexed: 06/10/2023]
Abstract
Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo. Thereby, QSM can reveal pathological changes of these key components in a variety of diseases. QSM requires multiple processing steps such as phase unwrapping, background field removal and field-to-source inversion. Current state-of-the-art techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and require a careful choice of regularization parameters. With the recent success of deep learning using convolutional neural networks for solving ill-posed reconstruction problems, the QSM community also adapted these techniques and demonstrated that the QSM processing steps can be solved by efficient feed forward multiplications not requiring either iterative optimization or the choice of regularization parameters. Here, we review the current status of deep learning-based approaches for processing QSM, highlighting limitations and potential pitfalls, and discuss the future directions the field may take to exploit the latest advances in deep learning for QSM.
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Affiliation(s)
- Woojin Jung
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea
| | - Steffen Bollmann
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea
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108
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Yang L, Cheng Y, Sun Y, Xuan Y, Niu J, Guan J, Rong Y, Jia Y, Zhuang Z, Yan G, Wu R. Combined Application of Quantitative Susceptibility Mapping and Diffusion Kurtosis Imaging Techniques to Investigate the Effect of Iron Deposition on Microstructural Changes in the Brain in Parkinson's Disease. Front Aging Neurosci 2022; 14:792778. [PMID: 35370619 PMCID: PMC8965454 DOI: 10.3389/fnagi.2022.792778] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 02/23/2022] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVES Brain iron deposition and microstructural changes in brain tissue are associated with Parkinson's disease (PD). However, the correlation between these factors in Parkinson's disease has been little studied. This study aimed to use quantitative susceptibility mapping combined with diffusion kurtosis imaging to investigate the effects of iron deposition on microstructural tissue alterations in the brain. METHODS Quantitative susceptibility mapping and diffusion kurtosis imaging were performed on 24 patients with early PD, 13 patients with advanced PD, and 25 healthy controls. The mean values of magnetic susceptibility and diffusion kurtosis were calculated for the bilateral substantia nigra, red nucleus, putamen, globus pallidus, and caudate nucleus, and compared between the groups. Correlation analyses between the diffusion kurtosis of each nucleus and its magnetic susceptibility parameters in PD patients and healthy controls were performed. RESULTS The study found a significant increase in iron deposition in the substantia nigra, red nucleus, putamen and globus pallidus, bilaterally, in patients with PD. Mean kurtosis values were increased in the substantia nigra but decreased in the globus pallidus; axial kurtosis values were decreased in both the substantia nigra and red nucleus; radial kurtosis values were increased in the substantia nigra but showed an opposite trend in the globus pallidus and caudate nucleus. In the substantia nigra of patients with PD, magnetic susceptibility was positively correlated with mean and radial kurtosis values, and negatively correlated with axial kurtosis. None of these correlations were significantly different in the control group. In the putamen, magnetic susceptibility was positively correlated with mean, axial, and radial kurtosis only in patients with advanced-stage PD. CONCLUSION Our study provides new evidence for brain iron content and microstructural alterations in patients with PD. Iron deposition may be a common mechanism for microstructural alterations in the substantia nigra and putamen of patients with PD. Tracking the dynamic changes in iron content and microstructure throughout the course of PD will help us to better understand the dynamics of iron metabolism and microstructural alterations in the pathogenesis of PD and to develop new approaches to monitor and treat PD.
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Affiliation(s)
- Lin Yang
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, China
| | - Yan Cheng
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, China
| | - Yongyan Sun
- Department of Pharmacy, Guangdong Second Provincial General Hospital, Zhuhai Hospital, Zhuhai, China
| | - Yinghua Xuan
- Department of Basic Medicine, Xiamen Medical College, Xiamen, China
| | - Jianping Niu
- Department of Neurology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China
| | - Jitian Guan
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, China
| | - Yunjie Rong
- Department of Ultrasound, Foshan Women and Children’s Hospital Affiliated to Southern Medical University, Foshan, China
| | - Yanlong Jia
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, China
| | - Zerui Zhuang
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Gen Yan
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China
| | - Renhua Wu
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, China
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, China
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Lu Z, Li J, Wang C, Ge R, Chen L, He H, Shi J. S2Q-Net: Mining the High-Pass Filtered Phase Data in Susceptibility Weighted Imaging for Quantitative Susceptibility Mapping. IEEE J Biomed Health Inform 2022; 26:3938-3949. [PMID: 35254999 DOI: 10.1109/jbhi.2022.3156548] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Susceptibility weighted imaging (SWI) is a routine magnetic resonance imaging (MRI) sequence that combines the magnitude and high-pass filtered phase images to qualitatively enhance the image contrasts related to tissue susceptibility. Tremendous amounts of the high-pass filtered phase data with low signal to noise ratio and incomplete background field removal have thus been collected under default clinical settings. Since SWI cannot quantitatively estimate the susceptibility, it is thus non-trivial to derive quantitative susceptibility mapping (QSM) directly from these redundant phase data, which effectively promotes the mining of the SWI data collected previously and even provides potentials for synchronous imaging of both SWI and QSM based on single SWI scanning in future. To this end, a novel deep learning based SWI-to-QSM-Net (S2Q-Net) is proposed for QSM reconstruction from SWI high-pass filtered phase data. S2Q-Net firstly estimates the edge maps of QSM to integrate edge prior into features, which benefits the network to reconstruct QSM with realistic and clear tissue boundaries. Furthermore, a novel Second-order Cross Dense Block is proposed in S2Q-Net, which can capture rich inter-region interactions to provide rich non-local phase information related to local tissue susceptibility. Experimental results on both simulated and in-vivo datasets demonstrate its superiority over all the compared QSM reconstruction methods, including conventional methods and the state-of-the-art DL-based algorithms. Our results suggest the potentials of S2Q-Net to reconstruct promising QSM from the high-pass filtered phase obtained in clinical SWI sequences.
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Kan H, Uchida Y, Ueki Y, Arai N, Tsubokura S, Kunitomo H, Kasai H, Aoyama K, Matsukawa N, Shibamoto Y. R2* relaxometry analysis for mapping of white matter alteration in Parkinson's disease with mild cognitive impairment. Neuroimage Clin 2022; 33:102938. [PMID: 34998126 PMCID: PMC8741619 DOI: 10.1016/j.nicl.2022.102938] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 12/22/2021] [Accepted: 01/03/2022] [Indexed: 12/01/2022]
Abstract
R2* relaxometry analysis combined with QSM revealed detail of WM alteration in PD-MCI. R2* relaxometry analysis can detect slight demyelination in PD-MCI. R2* value shows potential for early evaluation of cognitive decline in PD.
Background R2* relaxometry analysis combined with quantitative susceptibility mapping (QSM), which has high sensitivity to iron deposition, can distinguish microstructural changes of the white matter (WM) and iron deposition, thereby providing a sensitive and biologically specific measure of the WM owing to the changes in myelin and its surrounding environment. This study aimed to explore the microstructural WM alterations associated with cognitive impairment in patients with Parkinson’s disease (PD) using R2* relaxometry analysis combined with QSM. Materials and methods We enrolled 24 patients with PD and mild cognitive impairment (PD-MCI), 22 patients with PD and normal cognition (PD-CN), and 19 age- and sex-matched healthy controls (HC). All participants underwent Montreal Cognitive Assessment (MoCA) and brain magnetic resonance imaging, including structural three-dimensional T1-weighted images and multiple spoiled gradient echo sequence (mGRE). The R2* and susceptibility maps were estimated from the multiple magnitude images of mGRE. The susceptibility maps were used for verifying iron deposition in the WM. The voxel-based R2* of the entire WM and its correlation with cognitive performance were analyzed. Results In the voxel-based group comparisons, the R2* in the PD-MCI group was lower in some WM regions, including the corpus callosum, than R2* in the PD-CN and HC groups. The mean susceptibility values in almost all brain regions were negative and close-to-zero values, indicating no detectable paramagnetic iron deposition in the WM of all subjects. There was a significant positive correlation between R2* and MoCA in some regions of the WM, mainly the corpus callosum and left hemisphere. Conclusion R2* relaxometry analysis for WM microstructural changes provided further biologic insights on demyelination and changes in the surrounding environment, supported by the QSM results demonstrating no iron existence. This analysis highlighted the potential for the early evaluation of cognitive decline in patients with PD.
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Affiliation(s)
- Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Japan; Department of Radiology, Nagoya City University, Graduate School of Medical Sciences, Japan.
| | - Yuto Uchida
- Department of Neurology, Nagoya City University, Graduate School of Medical Sciences, Japan; Department of Neurology, Toyokawa City Hospital, Japan.
| | - Yoshino Ueki
- Department of Rehabilitation Medicine, Nagoya City University, Graduate School of Medical Sciences, Japan.
| | - Nobuyuki Arai
- Department of Radiology, Suzuka University of Medical Science, Japan.
| | | | - Hiroshi Kunitomo
- Department of Radiology, Nagoya City University Hospital, Japan.
| | - Harumasa Kasai
- Department of Radiology, Nagoya City University Hospital, Japan
| | - Kiminori Aoyama
- Department of Rehabilitation Medicine, Nagoya City University, Graduate School of Medical Sciences, Japan
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University, Graduate School of Medical Sciences, Japan.
| | - Yuta Shibamoto
- Department of Radiology, Nagoya City University, Graduate School of Medical Sciences, Japan.
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Xu G, He Y, Yu Q, He H, Zhao Z, Fan M, Li J, Xu D. Improved magnetic resonance myelin water imaging using multi-channel denoising convolutional neural networks (MCDnCNN). Quant Imaging Med Surg 2022; 12:1716-1737. [PMID: 35284287 PMCID: PMC8899954 DOI: 10.21037/qims-21-404] [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: 04/15/2021] [Accepted: 11/05/2021] [Indexed: 08/18/2023]
Abstract
BACKGROUND Myelin water imaging (MWI) is powerful and important for studying and diagnosing neurological and psychiatric diseases. In particular, myelin water fraction (MWF) is derived from MWI data for quantifying myelination. However, MWF estimation is typically sensitive to noise. Improving the accuracy of MWF estimation based on WMI data acquired using a magnetic resonance (MR) multiple gradient recalled echo (mGRE) imaging sequence is desired. METHODS The proposed method employs a recently introduced the multi-channel denoising convolutional neural networks (MCDnCNN). Five different MCDnCNN models, denoted as Delevel1, Delevel2, Delevel3, Delevel4 and DelevelMix corresponding to five noise levels (Level1, Level2, Level3, Level4 and LevelMix), were trained using the data of the first echo of the mGRE brain images acquired from 15 healthy human subjects. Using simulated noisy data that employed a hollow cylinder model, we first evaluated the improvement in estimating MWF based on data denoised by the five different MCDnCNNs, by comparing the MWF maps calculated from the denoised data with ground truth. Next, we again evaluated the improvement using real-world in vivo datasets of 11 human participants acquired using the mGRE sequence. The datasets were first denoised by five different MCDnCNNs (Delevel1, 2, 3, 4 and DelevelMix), and subsequently their MWF maps were calculated and compared with the MWF maps directly calculated from the raw mGRE images without being denoised. RESULTS Experiments using the simulation data denoised by the appropriate MCDnCNN models showed that the standard deviation (SD) of the absolute error (AE) of the derived MWF results was significantly reduced (maximal reduction =15.5%, Level3 simulated noisy data, orientation angle =0, all the five MCDnCNN models). In the test using in vivo data, estimating MWF based on data particularly denoised by the appropriate MCDnCNN models was found to be the best, compared to otherwise not using the appropriate models. The results demonstrated that the appropriate MCDnCNN models may permit high-quality MWF mapping, i.e., substantial reduction of random variation in estimating MWF-maps while preserving accuracy and structural details. CONCLUSIONS Appropriate MCDnCNN models as proposed may improve both the accuracy and precision in estimating MWF maps, thereby making it a more clinically feasible alternative.
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Affiliation(s)
- Guojun Xu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
- Molecular Imaging and Neuropathology Division, Columbia University Department of Psychiatry & New York State Psychiatric Institute, New York, NY, USA
| | - Yongquan He
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Qiurong Yu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingxia Fan
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Jianqi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Dongrong Xu
- Molecular Imaging and Neuropathology Division, Columbia University Department of Psychiatry & New York State Psychiatric Institute, New York, NY, USA
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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: 0.7] [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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He J, Wang L, Cao Y, Wang R, Zhu Y. Learn Less, Infer More: Learning in the Fourier Domain for Quantitative Susceptibility Mapping. Front Neurosci 2022; 16:837721. [PMID: 35250469 PMCID: PMC8888664 DOI: 10.3389/fnins.2022.837721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/17/2022] [Indexed: 12/02/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) aims to evaluate the distribution of magnetic susceptibility from magnetic resonance phase measurements by solving the ill-conditioned dipole inversion problem. Removing the artifacts and preserving the anisotropy of tissue susceptibility simultaneously is still a challenge in QSM. To deal with this issue, a novel k-QSM network is proposed to resolve dipole inversion issues in QSM reconstruction. The k-QSM network converts the results obtained by truncated k-space division (TKD) into the Fourier domain as inputs. After passing through several convolutional and residual blocks, the ill-posed signals of TKD are corrected by making the network output close to the calculation of susceptibility through multiple orientation sampling (COSMOS)-labeled QSM. To evaluate the superiority of k-QSM, comparisons with several state-of-the-art methods are performed in terms of QSM artifacts removing, anisotropy preserving, generalization ability, and clinical applications. Compared to existing methods, the k-QSM achieves a 22.31% lower normalized root mean square error, 10.30% higher peak signal-to-noise ratio (PSNR), 33.10% lower high-frequency error norm, and 1.06% higher structural similarity. In addition, the orientation-dependent susceptibility variation obtained by k-QSM is significant, verifying that k-QSM has the ability to preserve susceptibility anisotropy. When the trained models are tested on the dataset from different centers, our k-QSM shows a strong generalization ability with the highest PSNR. Moreover, by comparing the susceptibility maps between healthy controls and drug addicts with different methods, we found the proposed k-QSM is more sensitive to the susceptibility abnormality in the patients. The proposed k-QSM method learns less—only to fix the ill-posed signals of TKD, but infers more—both COSMOS-like and anisotropy-preserving QSM results. Its generalization ability and great sensitivity to susceptibility changes can make it a potential method for distinguishing some diseases.
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Affiliation(s)
- Junjie He
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, College of Computer Science and Technology, Guizhou University, Guiyang, China
- International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Lihui Wang
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, College of Computer Science and Technology, Guizhou University, Guiyang, China
- *Correspondence: Lihui Wang
| | - Ying Cao
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, College of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Rongpin Wang
- International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
- Rongpin Wang
| | - Yuemin Zhu
- CREATIS, IRP Metislab, University of Lyon, INSA Lyon, CNRS UMR 5220, Inserm U1294, Lyon, France
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Meng Q, Liu M, Chen Z. Voxel-Based Intraclass Correlation Coefficient to Evaluate the Inter-Scanner Reproducibility of Quantitative Susceptibility Mapping over the Deep Gray Matter Structure at 3.0T MR. Curr Med Imaging 2022; 18:924-930. [PMID: 35170418 DOI: 10.2174/1573405618666220216120729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 12/04/2021] [Accepted: 12/28/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The Quantitative susceptibility mapping (QSM) technique can be used to quantitatively evaluate the cerebral iron deposition of the deep gray matter structure (DGM) in clinical practice. However, it could be significantly important to assess the reproducibility of the susceptibility values at different magnetic resonance (MR) scanners before the QSM technique can be widely used in clinical applications. OBJECTIVE To assess the reproducibility of susceptibility value of the deep gray matter structure (DGM) at two different MR systems with the same magnetic strength. METHODS Raw data of 21 normal subjects (M/F = 7/14, median age 29 (21, 63) years) were acquired from a 3D multi-echo enhanced gradient recalled echo sequence at two different 3.0T MR systems, and STI software was used to reconstruct the magnetic susceptibility images. Brain structural images were used to be coregistered with magnitude images to generate normalized parameters and normalized susceptibility images. Voxel-based intraclass correlation coefficient (VB-ICC) was used to evaluate the reproducibility of susceptibility value of DGM at different 3.0T MR systems. RESULTS DGM with ICC > 0.75 located in the bilateral posterior putamen and globus pallidus, bilateral red nuclei and left dental nucleus. DGM with 0.6 < ICC < 0.75 mainly located in the bilateral anterior putamen and globus pallidus, the margin of the bilateral red nuclei, right dental nucleus and the margin of the left dental nucleus. DGM with 0.4 < ICC < 0.6 located in anterior parts of the bilateral putamen, bilateral globus pallidus and substantia nigra, the margin of the bilateral dental nuclei and the inferior part of right dental nucleus. CONCLUSION DGM presented regional dependent reproducibility of susceptibility value at two different 3.0T MR system based on VB-ICC analysis.
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Affiliation(s)
- Qinglin Meng
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Mengqi Liu
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Zhiye Chen
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou China
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Howard CM, Jain S, Cook AD, Packard LE, Mullin HA, Chen N, Liu C, Song AW, Madden DJ. Cortical iron mediates age-related decline in fluid cognition. Hum Brain Mapp 2022; 43:1047-1060. [PMID: 34854172 PMCID: PMC8764476 DOI: 10.1002/hbm.25706] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 01/19/2023] Open
Abstract
Brain iron dyshomeostasis disrupts various critical cellular functions, and age-related iron accumulation may contribute to deficient neurotransmission and cell death. While recent studies have linked excessive brain iron to cognitive function in the context of neurodegenerative disease, little is known regarding the role of brain iron accumulation in cognitive aging in healthy adults. Further, previous studies have focused primarily on deep gray matter regions, where the level of iron deposition is highest. However, recent evidence suggests that cortical iron may also contribute to cognitive deficit and neurodegenerative disease. Here, we used quantitative susceptibility mapping (QSM) to measure brain iron in 67 healthy participants 18-78 years of age. Speed-dependent (fluid) cognition was assessed from a battery of 12 psychometric and computer-based tests. From voxelwise QSM analyses, we found that QSM susceptibility values were negatively associated with fluid cognition in the right inferior temporal gyrus, bilateral putamen, posterior cingulate gyrus, motor, and premotor cortices. Mediation analysis indicated that susceptibility in the right inferior temporal gyrus was a significant mediator of the relation between age and fluid cognition, and similar effects were evident for the left inferior temporal gyrus at a lower statistical threshold. Additionally, age and right inferior temporal gyrus susceptibility interacted to predict fluid cognition, such that brain iron was negatively associated with a cognitive decline for adults over 45 years of age. These findings suggest that iron may have a mediating role in cognitive decline and may be an early biomarker of neurodegenerative disease.
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Affiliation(s)
- Cortney M. Howard
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Shivangi Jain
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Psychological and Brain SciencesUniversity of IowaIowa CityIowaUSA
| | - Angela D. Cook
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Lauren E. Packard
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Hollie A. Mullin
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Nan‐kuei Chen
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Biomedical EngineeringUniversity of ArizonaTucsonArizonaUSA
| | - Chunlei Liu
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Electrical Engineering and Computer SciencesUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Allen W. Song
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - David J. Madden
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke University Medical CenterDurhamNorth CarolinaUSA
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Uchida Y, Kan H, Inoue H, Oomura M, Shibata H, Kano Y, Kuno T, Usami T, Takada K, Yamada K, Kudo K, Matsukawa N. Penumbra Detection With Oxygen Extraction Fraction Using Magnetic Susceptibility in Patients With Acute Ischemic Stroke. Front Neurol 2022; 13:752450. [PMID: 35222239 PMCID: PMC8873150 DOI: 10.3389/fneur.2022.752450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 01/25/2022] [Indexed: 12/14/2022] Open
Abstract
Background The oxygen extraction fraction (OEF) has been applied to identify ischemic penumbral tissue, but is difficult to use in an urgent care setting. This study aimed to investigate whether an OEF map generated via magnetic resonance quantitative susceptibility mapping (QSM) could help identify the ischemic penumbra in patients with acute ischemic stroke. Materials and Methods This prospective imaging study included 21 patients with large anterior circulation vessel occlusion who were admitted <24 h after stroke onset and 21 age-matched healthy controls. We identified the ischemic penumbra as the region with a Tmax of >6 s during dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) and calculated the perfusion-core mismatch ratio between the ischemic penumbra and infarct core volumes. The OEF values were measured based on magnetic susceptibility differences between the venous structures and brain tissues using rapid QSM acquisition. Volumes with increased OEF values were compared to the ischemic penumbra volumes using an anatomical template. Results Eleven patients had a perfusion-core mismatch ratio of ≥1.8, and reperfusion therapy was recommended. In these patients, the volumes with increased OEF values of >51.5%, which was defined using the anterior circulation territory OEF values from the 21 healthy controls, were positively correlated with the ischemic penumbra volumes (r = 0.636, 95% CI: 0.059 to 0.895, P = 0.035) and inversely correlated with the 30-day change in the National Institutes of Health Stroke Scale scores (r = −0.624, 95% CI: −0.891 to −0.039, P = 0.041). Conclusion Tissue volumes with increased OEF values could predict ischemic penumbra volumes based on DSC-MRI, highlighting the potential of the QSM-derived OEF map as a penumbra biomarker to guide treatment selection in patients with acute ischemic stroke.
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Affiliation(s)
- Yuto Uchida
- Department of Neurology, Nagoya City University, Nagoya, Japan
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University, Nagoya, Japan
| | - Hiroyasu Inoue
- Department of Neurology, Nagoya City University, Nagoya, Japan
| | - Masahiro Oomura
- Department of Neurology, Nagoya City University, Nagoya, Japan
| | - Haruto Shibata
- Department of Neurology, Nagoya City East Medical Center, Nagoya, Japan
| | - Yuya Kano
- Department of Neurology, Nagoya City East Medical Center, Nagoya, Japan
| | - Tomoyuki Kuno
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Toshihiko Usami
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Koji Takada
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan
| | - Kentaro Yamada
- Department of Neurology, Nagoya City East Medical Center, Nagoya, Japan
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Hokkaido University, Hokkaido, Japan
- Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Hokkaido, Japan
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University, Nagoya, Japan
- *Correspondence: Noriyuki Matsukawa
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Wang JY, Grigsby J, Placido D, Wei H, Tassone F, Kim K, Hessl D, Rivera SM, Hagerman RJ. Clinical and Molecular Correlates of Abnormal Changes in the Cerebellum and Globus Pallidus in Fragile X Premutation. Front Neurol 2022; 13:797649. [PMID: 35211082 PMCID: PMC8863211 DOI: 10.3389/fneur.2022.797649] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 01/12/2022] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Fragile X premutation carriers (55-200 CGG triplets) may develop a progressive neurodegenerative disorder, fragile X-associated tremor/ataxia syndrome (FXTAS), after the age of 50. The neuroradiologic markers of FXTAS are hyperintense T2-signals in the middle cerebellar peduncle-the MCP sign. We recently noticed abnormal T2-signals in the globus pallidus in male premutation carriers and controls but the prevalence and clinical significance were unknown. METHODS We estimated the prevalence of the MCP sign and pallidal T2-abnormalities in 230 male premutation carriers and 144 controls (aged 8-86), and examined the associations with FXTAS symptoms, CGG repeat length, and iron content in the cerebellar dentate nucleus and globus pallidus. RESULTS Among participants aged ≥45 years (175 premutation carriers and 82 controls), MCP sign was observed only in premutation carriers (52 vs. 0%) whereas the prevalence of pallidal T2-abnormalities approached significance in premutation carriers compared with controls after age-adjustment (25.1 vs. 13.4%, p = 0.069). MCP sign was associated with impaired motor and executive functioning, and the additional presence of pallidal T2-abnormalities was associated with greater impaired executive functioning. Among premutation carriers, significant iron accumulation was observed in the dentate nucleus, and neither pallidal or MCP T2-abnormalities affected measures of the dentate nucleus. While the MCP sign was associated with CGG repeat length >75 and dentate nucleus volume correlated negatively with CGG repeat length, pallidal T2-abnormalities did not correlate with CGG repeat length. However, pallidal signal changes were associated with age-related accelerated iron depletion and variability and having both MCP and pallidal signs further increased iron variability in the globus pallidus. CONCLUSIONS Only the MCP sign, not pallidal abnormalities, revealed independent associations with motor and cognitive impairment; however, the occurrence of combined MCP and pallidal T2-abnormalities may present a risk for greater cognitive impairment and increased iron variability in the globus pallidus.
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Affiliation(s)
- Jun Yi Wang
- Center for Mind and Brain, University of California, Davis, Davis, CA, United States
| | - Jim Grigsby
- Departments of Psychology and Medicine, University of Colorado Denver, Denver, CO, United States
| | - Diego Placido
- Department of Psychology, University of California, Davis, Davis, CA, United States
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute for Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
| | - Flora Tassone
- Department of Biochemistry and Molecular Medicine, University of California Davis School of Medicine, Sacramento, CA, United States
- The MIND Institute, University of California Davis Medical Center, Sacramento, CA, United States
| | - Kyoungmi Kim
- Department of Public Health Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
| | - David Hessl
- The MIND Institute, University of California Davis Medical Center, Sacramento, CA, United States
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Susan M. Rivera
- Center for Mind and Brain, University of California, Davis, Davis, CA, United States
- Departments of Psychology and Medicine, University of Colorado Denver, Denver, CO, United States
- The MIND Institute, University of California Davis Medical Center, Sacramento, CA, United States
| | - Randi J. Hagerman
- The MIND Institute, University of California Davis Medical Center, Sacramento, CA, United States
- Department of Pediatrics, University of California Davis School of Medicine, Sacramento, CA, United States
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Yu FF, Yi Huang S, Kumar A, Witzel T, Liao C, Duval T, Cohen-Adad J, Bilgic B. Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps. Magn Reson Med 2022; 87:781-790. [PMID: 34480768 PMCID: PMC8627440 DOI: 10.1002/mrm.28995] [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: 11/29/2020] [Revised: 07/13/2021] [Accepted: 08/10/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE A major obstacle to the clinical implementation of quantitative MR is the lengthy acquisition time required to derive multi-contrast parametric maps. We sought to reduce the acquisition time for QSM and macromolecular tissue volume by acquiring both contrasts simultaneously by leveraging their redundancies. The joint virtual coil concept with GRAPPA (JVC-GRAPPA) was applied to reduce acquisition time further. METHODS Three adult volunteers were imaged on a 3 Tesla scanner using a multi-echo 3D GRE sequence acquired at 3 head orientations. Macromolecular tissue volume, QSM, R2∗ , T1 , and proton density maps were reconstructed. The same sequence (GRAPPA R = 4) was performed in subject 1 with a single head orientation for comparison. Fully sampled data was acquired in subject 2, from which retrospective undersampling was performed (R = 6 GRAPPA and R = 9 JVC-GRAPPA). Prospective undersampling was performed in subject 3 (R = 6 GRAPPA and R = 9 JVC-GRAPPA) using gradient blips to shift k-space sampling in later echoes. RESULTS Subject 1's multi-orientation and single-orientation macromolecular tissue volume maps were not significantly different based on RMSE. For subject 2, the retrospectively undersampled JVC-GRAPPA and GRAPPA generated similar results as fully sampled data. This approach was validated with the prospectively undersampled images in subject 3. Using QSM, R2∗ , and macromolecular tissue volume, the contributions of myelin and iron content to susceptibility were estimated. CONCLUSION We have developed a novel strategy to simultaneously acquire data for the reconstruction of 5 intrinsically coregistered 1-mm isotropic resolution multi-parametric maps, with a scan time of 6 min using JVC-GRAPPA.
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Affiliation(s)
- Fang Frank Yu
- Radiology, University of Texas Southwestern Medical Center, Dallas, TX, United States,,Corresponding author. Fang Frank Yu, MD, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, Ph: 214-648-7813, Fax: 214-648-3904,
| | - Susie Yi Huang
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Ashwin Kumar
- Vanderbilt University, Nashville, TN, United States
| | | | - Congyu Liao
- Radiological Sciences Laboratory, Stanford Medicine, Stanford, CA, United States
| | - Tanguy Duval
- Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada
| | - Berkin Bilgic
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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Mao H, Dou W, Wang X, Chen K, Wang X, Guo Y, Zhang C. Iron Deposition in Gray Matter Nuclei of Patients With Intracranial Artery Stenosis: A Quantitative Susceptibility Mapping Study. Front Neurol 2022; 12:785822. [PMID: 35069414 PMCID: PMC8766754 DOI: 10.3389/fneur.2021.785822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: This study aimed to use quantitative susceptibility mapping (QSM) to systematically investigate the changes of iron content in gray matter (GM) nuclei in patients with long-term anterior circulation artery stenosis (ACAS) and posterior circulation artery stenosis (PCAS). Methods: Twenty-five ACAS patients, 25 PCAS patients, and 25 age- and sex-matched healthy controls underwent QSM examination. Patients were scored using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) to assess the degree of neural function deficiency. On QSM images, iron related susceptibility of GM nuclei, including bilateral caudate nucleus, putamen (PU), globus pallidus (GP), thalamus (TH), substantia nigra (SN), red nucleus, and dentate nucleus (DN), were assessed. Susceptibility was compared between bilateral GM nuclei in healthy controls, ACAS patients, and PCAS patients. Partial correlation analysis, with age as a covariate, was separately performed to assess the relationships of susceptibility with NIHSS and mRS scores. Results: There were no significant differences between the susceptibilities for left and right hemispheres in all seven GM nucleus subregions for healthy controls, ACAS patients, and PCAS patients. Compared with healthy controls, mean susceptibility of bilateral PU, GP, and SN in ACAS patients and of bilateral PU, GP, SN, and DN in PCAS patients were significantly increased (all P < 0.05). In addition, mean susceptibility of bilateral TH and SN in PCAS patients was significantly higher than in ACAS patients (both P < 0.05). With partial correlation analysis, mean susceptibility at bilateral PU of ACAS patients was significantly correlated with mRS score (r = 0.415, P < 0.05), and at bilateral PU in PCAS patients was correlated with NIHSS score (r = 0.424, P < 0.05). Conclusion: Our findings indicated that abnormal iron metabolism may present in different subregions of GM nuclei after long-term ACAS and PCAS. In addition, iron content of PU in patients with ACAS and PCAS was correlated with neurological deficit scores. Therefore, iron quantification measured by QSM susceptibility may provide a new insight to understand the pathological mechanism of ischemic stroke caused by ACAS and PCAS.
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Affiliation(s)
- Huimin Mao
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | | | - Xinyi Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Kunjian Chen
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Xinyu Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Chao Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
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120
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Du J, Ji Y, Zhu J, Mai X, Zou J, Chen Y, Gu N. Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction. Quant Imaging Med Surg 2022; 12:510-525. [PMID: 34993097 DOI: 10.21037/qims-21-243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 07/07/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Compared with conventional magnetic resonance imaging methods, the quantitative magnetic susceptibility mapping (QSM) technique can quantitatively measure the magnetic susceptibility distribution of tissues, which has an important clinical application value in the investigations of brain micro-bleeds, Parkinson's, and liver iron deposition, etc. However, the quantitative susceptibility mapping algorithm is an ill-posed inverse problem due to the near-zero value in the dipole kernel, and high-quality QSM reconstruction with effective streaking artifact suppression remains a challenge. In recent years, the performance of sparse representation has been well validated in improving magnetic resonance image (MRI) reconstruction. METHODS In this study, by incorporating feature learning into sparse representation, we propose an edge prior guided dictionary learning-based reconstruction method for the dipole inversion in quantitative susceptibility mapping reconstruction. The structure feature dictionary relies on magnitude images for susceptibility maps have similar structures with magnitude images, and this structure feature dictionary and edge prior information are used in the dipole inversion step. RESULTS The performance of the proposed algorithm is assessed through in vivo human brain clinical data, leading to high-quality susceptibility maps with improved streaking artifact suppression, structural recovery, and quantitative metrics. CONCLUSIONS The proposed edge prior guided dictionary learning method for dipole inversion in QSM achieves improved performance in streaking artifacts suppression, structural recovery and deep gray matter reconstruction.
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Affiliation(s)
- Jiacheng Du
- The State Key Laboratory of Bioelectronics and Jiangsu Key Laboratory of Biomaterials and Devices, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
| | - Yuxin Ji
- The Laboratory of Image Science and Technology, Key Laboratory of Ministry of Education, School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Jiali Zhu
- The Laboratory of Image Science and Technology, Key Laboratory of Ministry of Education, School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Xiaoli Mai
- The Radiology, Nanjing Drum Tower Hospital, Nanjing, China
| | - Junting Zou
- The Radiology, Nanjing Drum Tower Hospital, Nanjing, China
| | - Yang Chen
- The Laboratory of Image Science and Technology, Key Laboratory of Ministry of Education, School of Computer Science and Engineering, Southeast University, Nanjing, China
| | - Ning Gu
- The State Key Laboratory of Bioelectronics and Jiangsu Key Laboratory of Biomaterials and Devices, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
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121
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Chen J, Zhang Z, Nie X, Xu Y, Liu C, Zhao X, Wang Y. Predictive value of thrombus susceptibility for cardioembolic stroke by quantitative susceptibility mapping. Quant Imaging Med Surg 2022; 12:550-557. [PMID: 34993100 DOI: 10.21037/qims-21-235] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 05/20/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND The hypointense blooming signal of thrombi on susceptibility-weighted imaging (SWI), known as the susceptibility vessel sign (SVS), is predictive of cardioembolic stroke. The SVS originates from the local magnetic susceptibility effect; thus, the susceptibility value of thrombi may provide useful information in discriminating stroke etiology. We aim to utilize quantitative susceptibility mapping (QSM) to assess thrombus's susceptibility value in acute ischemic stroke patients and explore the relationship of thrombus susceptibility with cardioembolic stroke. METHODS From 2018 to 2020, 132 consecutive acute ischemic stroke patients with middle cerebral artery occlusion were recruited within 48 hours of onset. All patients underwent a three-dimensional multi-echo SWI scan using a 3 Tesla magnetic resonance imaging scanner. The SVS presence and the diameter of the SVS-related hypointense signal were assessed on SWI. QSM was applied to compute the susceptibility value of the thrombus. The receiver operating characteristic (ROC) methodology was used to define the optimal cutoff value of the susceptibility in QSM and the diameter on SWI for predicting cardioembolic stroke. RESULTS The SVS was identified in 93 (70.5%) patients with symptomatic middle cerebral artery occlusion and was significantly associated with cardioembolism. The hyperintense signal on QSM in the corresponding middle cerebral artery occlusion was present in 116 (87.9%) patients. ROC analysis indicated that thrombus susceptibility had a greater area under the curve than that of the SVS diameter (0.88 vs. 0.70, P<0.001) and that the optimal cutoff value of thrombus susceptibility for cardioembolism was 0.35 ppm. Multivariate analysis demonstrated that thrombus susceptibility (≥0.35 ppm) was an independent predictor of cardioembolic stroke (odds ratio =20.75; 95% CI, 7.19-59.87; P<0.001), with sensitivity, specificity, a positive predictive value, and a negative predictive value of 85.2%, 80.8%, 75.4%, and 88.7%, respectively, while the SVS presence showed sensitivity, specificity, a positive predictive value, and a negative predictive value of 90.7%, 43.6%, 87.2%, and 52.7%, respectively. CONCLUSIONS Thrombus susceptibility provides superior diagnostic performance over the SVS for discriminating between cardioembolism and other stroke subtypes. Quantitative susceptibility measurements of thrombi may help predict cardioembolic stroke in patients with acute middle cerebral artery occlusion.
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Affiliation(s)
- Jie Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhe Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Ximing Nie
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuyuan Xu
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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122
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Milovic C, Lambert M, Langkammer C, Bredies K, Irarrazaval P, Tejos C. Streaking artifact suppression of quantitative susceptibility mapping reconstructions via L1-norm data fidelity optimization (L1-QSM). Magn Reson Med 2022; 87:457-473. [PMID: 34350634 DOI: 10.1002/mrm.28957] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 07/15/2021] [Accepted: 07/17/2021] [Indexed: 01/05/2023]
Abstract
PURPOSE The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts. METHODS QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages. RESULTS The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups. CONCLUSION The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Mathias Lambert
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | - Christian Langkammer
- Department of Neurology, Medical University of Graz, Graz, Austria
- BioTechMed Graz, Graz, Austria
| | - Kristian Bredies
- BioTechMed Graz, Graz, Austria
- Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Pablo Irarrazaval
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Institute for Biological and Medical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
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123
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Lancione M, Costagli M, Handjaras G, Tosetti M, Ricciardi E, Pietrini P, Cecchetti L. Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research. Neuroimage 2021; 244:118574. [PMID: 34508897 DOI: 10.1016/j.neuroimage.2021.118574] [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: 05/13/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 10/20/2022] Open
Abstract
Functional Quantitative Susceptibility Mapping (fQSM) allows for the quantitative measurement of time-varying magnetic susceptibility across cortical and subcortical brain structures with a potentially higher spatial specificity than conventional fMRI. While the usefulness of fQSM with General Linear Model and "On/Off" paradigms has been assessed, little is known about the potential applications and limitations of this technique in more sophisticated experimental paradigms and analyses, such as those currently used in modern neuroimaging. To thoroughly characterize fQSM activations, here we used 7T MRI, tonotopic mapping, as well as univariate (i.e., GLM and population Receptive Field) and multivariate (Representational Similarity Analysis; RSA) analyses. Although fQSM detected less tone-responsive voxels than fMRI, they were more consistently localized in gray matter. Also, the majority of active gray matter voxels exhibited negative fQSM response, signaling the expected oxyhemoglobin increase, whereas positive fQSM activations were mainly in white matter. Though fMRI- and fQSM-based tonotopic maps were overall comparable, the representation of frequency tunings in tone-sensitive regions was significantly more balanced for fQSM. Lastly, RSA revealed that frequency information from the auditory cortex could be successfully retrieved by using either methods. Overall, fQSM produces complementary results to conventional fMRI, as it captures small-scale variations in the activation pattern which inform multivariate measures. Although positive fQSM responses deserve further investigation, they do not impair the interpretation of contrasts of interest. The quantitative nature of fQSM, its spatial specificity and the possibility to simultaneously acquire canonical fMRI support the use of this technique for longitudinal and multicentric studies and pre-surgical mapping.
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Affiliation(s)
- Marta Lancione
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy; IMAGO7 Foundation, Pisa, Italy.
| | - Mauro Costagli
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
| | - Giacomo Handjaras
- Social and Affective Neuroscience (SANe) Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Michela Tosetti
- IMAGO7 Foundation, Pisa, Italy; Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Pisa, Italy
| | - Emiliano Ricciardi
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Pietro Pietrini
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Luca Cecchetti
- Social and Affective Neuroscience (SANe) Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
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Xu J, Guan X, Wen J, Wang T, Zhang M, Xu X. Substantia nigra iron affects functional connectivity networks modifying working memory performance in younger adults. Eur J Neurosci 2021; 54:7959-7973. [PMID: 34779047 DOI: 10.1111/ejn.15532] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 01/19/2023]
Abstract
Brain iron affects working memory (WM) but the impact of iron content in deep grey matter nuclei on WM networks is unknown. We aimed to test whether deep grey matter nuclei iron concentration can affect resting-state functional connectivity (rsFC) within brain networks modifying WM performance. An N-back WM paradigm was applied in a hundred healthy younger adults. The participants then underwent a resting-state functional magnetic resonance imaging (fMRI) for brain network analysis and quantitative susceptibility mapping (QSM) imaging for assessment of deep grey matter nuclei iron concentration. Higher substantia nigra (SN) iron concentration was associated with lower rsFC between SN and brain regions of the temporal/frontal lobe but with better WM performance after controlling for age, gender and education. A follow-up mediation analysis also indicated that functional connectivity may mediate the link between SN iron and WM performance. Our results suggest that high SN iron concentration may affect communication between the SN and temporal/frontal lobe and is associated with strengthened WM performance in younger adults.
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Affiliation(s)
- Jingjing Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaqi Wen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Kan H, Tsuchiya T, Yamada M, Kunitomo H, Kasai H, Shibamoto Y. Delineation of prostatic calcification using quantitative susceptibility mapping: Spatial accuracy for magnetic resonance-only radiotherapy planning. J Appl Clin Med Phys 2021; 23:e13469. [PMID: 34726833 PMCID: PMC8833270 DOI: 10.1002/acm2.13469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/07/2021] [Accepted: 10/19/2021] [Indexed: 11/16/2022] Open
Abstract
To investigate the spatial accuracy of delineating prostatic calcifications by quantitative susceptibility mapping (QSM) in comparison with computed tomography (CT), we conducted phantom and human studies. Five differently‐sized spherical hydroxyapatites mimicking prostatic calcification (pseudo‐calcification) were arranged in the order of their sizes at the center of a plastic container filled with gelatin. This calcification phantom underwent magnetic resonance (MR) imaging, including the multiple spoiled gradient‐echo sequences (SPGR) for the QSM and CT as a reference. The volume of each pseudo‐calcification and center‐to‐center distance between the pseudo‐calcifications delineated by QSM and CT were measured. In the human study, eight patients with prostate cancer who underwent radiation therapy and had some prostatic calcifications were included. The patients underwent CT and SPGR and modified DIXON sequence for MR‐only simulation. The hybrid QSM processing combined with the complex signals in the SPGR and water and fat fraction maps estimated from the modified DIXON sequence were used to reconstruct the pelvic susceptibility map in humans. The threshold of CT numbers was set at 130 HU, while the QSM images were manually segmented in the calcification phantom and human studies. In the phantom study, there was an excellent agreement in the pseudo‐calcification volumes between QSM and CT (y = 1.02x – 7.38, R2 = 0.99). The signal profiles had similar trends in CT and QSM. The center‐to‐center distances between the pseudo‐calcifications in the phantom were also identical in QSM and CT. The calcification volumes were almost identical between the QSM and CT in the human study (y = 0.95x – 9.32, R2 = 1.00). QSM can offer geometric and volumetric accuracies to delineate prostatic calcifications, similar to CT. The prostatic calcification delineated by QSM may facilitate image‐guided radiotherapy in the MR‐only simulation workflow.
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Affiliation(s)
- Hirohito Kan
- Department of Integrated Health Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan.,Department of Radiology, Graduate School of Medical Sciences, Nagoya City University, Nagoya, Japan
| | - Takahiro Tsuchiya
- Department of Radiology, Nagoya City University Hospital, Nagoya City University, Nagoya, Japan
| | - Masato Yamada
- Department of Radiology, Nagoya City University Hospital, Nagoya City University, Nagoya, Japan
| | - Hiroshi Kunitomo
- Department of Radiology, Nagoya City University Hospital, Nagoya City University, Nagoya, Japan
| | - Harumasa Kasai
- Department of Radiology, Nagoya City University Hospital, Nagoya City University, Nagoya, Japan
| | - Yuta Shibamoto
- Department of Radiology, Graduate School of Medical Sciences, Nagoya City University, Nagoya, Japan
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Griffanti L, Raman B, Alfaro-Almagro F, Filippini N, Cassar MP, Sheerin F, Okell TW, Kennedy McConnell FA, Chappell MA, Wang C, Arthofer C, Lange FJ, Andersson J, Mackay CE, Tunnicliffe EM, Rowland M, Neubauer S, Miller KL, Jezzard P, Smith SM. Adapting the UK Biobank Brain Imaging Protocol and Analysis Pipeline for the C-MORE Multi-Organ Study of COVID-19 Survivors. Front Neurol 2021; 12:753284. [PMID: 34777224 PMCID: PMC8586081 DOI: 10.3389/fneur.2021.753284] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 10/06/2021] [Indexed: 01/08/2023] Open
Abstract
SARS-CoV-2 infection has been shown to damage multiple organs, including the brain. Multiorgan MRI can provide further insight on the repercussions of COVID-19 on organ health but requires a balance between richness and quality of data acquisition and total scan duration. We adapted the UK Biobank brain MRI protocol to produce high-quality images while being suitable as part of a post-COVID-19 multiorgan MRI exam. The analysis pipeline, also adapted from UK Biobank, includes new imaging-derived phenotypes (IDPs) designed to assess the possible effects of COVID-19. A first application of the protocol and pipeline was performed in 51 COVID-19 patients post-hospital discharge and 25 controls participating in the Oxford C-MORE study. The protocol acquires high resolution T1, T2-FLAIR, diffusion weighted images, susceptibility weighted images, and arterial spin labelling data in 17 min. The automated imaging pipeline derives 1,575 IDPs, assessing brain anatomy (including olfactory bulb volume and intensity) and tissue perfusion, hyperintensities, diffusivity, and susceptibility. In the C-MORE data, IDPs related to atrophy, small vessel disease and olfactory bulbs were consistent with clinical radiology reports. Our exploratory analysis tentatively revealed some group differences between recovered COVID-19 patients and controls, across severity groups, but not across anosmia groups. Follow-up imaging in the C-MORE study is currently ongoing, and this protocol is now being used in other large-scale studies. The protocol, pipeline code and data are openly available and will further contribute to the understanding of the medium to long-term effects of COVID-19.
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Affiliation(s)
- Ludovica Griffanti
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Betty Raman
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Fidel Alfaro-Almagro
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Nicola Filippini
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Camillo Hospital, Venice, Italy
| | - Mark Philip Cassar
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
| | - Fintan Sheerin
- Department of Radiology, Oxford University Hospitals National Health Service (NHS) Foundation Trust, Oxford, United Kingdom
| | - Thomas W. Okell
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Flora A. Kennedy McConnell
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom
| | - Michael A. Chappell
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom
| | - Chaoyue Wang
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Christoph Arthofer
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Frederik J. Lange
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Jesper Andersson
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Clare E. Mackay
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Elizabeth M. Tunnicliffe
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
| | - Matthew Rowland
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Oxford Biomedical Research Centre (BRC) National Institute for Health Research (NIHR), University of Oxford, Oxford, United Kingdom
- Radcliffe Department of Medicine, British Heart Foundation Centre for Research Excellence, University of Oxford, Oxford, United Kingdom
| | - Karla L. Miller
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Peter Jezzard
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
| | - Stephen M. Smith
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, United Kingdom
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Bossoni L, Hegeman-Kleinn I, van Duinen SG, Bulk M, Vroegindeweij LHP, Langendonk JG, Hirschler L, Webb A, van der Weerd L. Off-resonance saturation as an MRI method to quantify mineral- iron in the post-mortem brain. Magn Reson Med 2021; 87:1276-1288. [PMID: 34655092 PMCID: PMC9293166 DOI: 10.1002/mrm.29041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 09/17/2021] [Accepted: 09/20/2021] [Indexed: 12/24/2022]
Abstract
Purpose To employ an off‐resonance saturation method to measure the mineral‐iron pool in the postmortem brain, which is an endogenous contrast agent that can give information on cellular iron status. Methods An off‐resonance saturation acquisition protocol was implemented on a 7 Tesla preclinical scanner, and the contrast maps were fitted to an established analytical model. The method was validated by correlation and Bland‐Altman analysis on a ferritin‐containing phantom. Mineral‐iron maps were obtained from postmortem tissue of patients with neurological diseases characterized by brain iron accumulation, that is, Alzheimer disease, Huntington disease, and aceruloplasminemia, and validated with histology. Transverse relaxation rate and magnetic susceptibility values were used for comparison. Results In postmortem tissue, the mineral‐iron contrast colocalizes with histological iron staining in all the cases. Iron concentrations obtained via the off‐resonance saturation method are in agreement with literature. Conclusions Off‐resonance saturation is an effective way to detect iron in gray matter structures and partially mitigate for the presence of myelin. If a reference region with little iron is available in the tissue, the method can produce quantitative iron maps. This method is applicable in the study of diseases characterized by brain iron accumulation and can complement existing iron‐sensitive parametric methods.
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Affiliation(s)
- Lucia Bossoni
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Sjoerd G van Duinen
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marjolein Bulk
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Neurology, Alzheimer Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lydiane Hirschler
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Andrew Webb
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Louise van der Weerd
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
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128
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Jang J, Nam Y, Jung SW, Riew TR, Kim SH, Kim IB. Paradoxical paramagnetic calcifications in the globus pallidus: An ex vivo MR investigation and histological validation study. NMR IN BIOMEDICINE 2021; 34:e4571. [PMID: 34129267 DOI: 10.1002/nbm.4571] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 04/12/2021] [Accepted: 05/26/2021] [Indexed: 06/12/2023]
Abstract
MR images based on phase contrast images have gained clinical interest as an in vivo tool for assessing anatomical and histological findings. The globus pallidus is an area of major iron metabolism and storage in the brain tissue. Calcium, another important metal in the body, is frequently deposited in the globus pallidus as well. Recently, we observed dense paramagnetic deposition with paradoxical calcifications in the globus pallidus and putamen. In this work, we explore detailed MR findings on these structures, and the histological source of the related findings using ex vivo CT and MR images. Ex vivo MR was obtained with a maximum 100 μm3 isotropic resolution using a 15.2 T MR system. 3D gradient echo images and quantitative susceptibility mapping were used because of their good sensitivity to metallic deposition, high signal-to-noise ratio, and excellent contrast to iron and calcium. We found dense paramagnetic deposition along the perforating arteries in the globus pallidus. This paramagnetic deposition was hyperdense on ex vivo CT scans. Histological studies confirmed this finding, and simultaneous deposition of iron and calcium, although more iron dominant, was observed along the vessel walls of the globus pallidus. This was an exclusive finding for the penetrating arteries of the globus pallidus. Thus, our results suggest that several strong and paradoxical paramagnetic sources at the globus pallidus can be associated with vascular degeneration.
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Affiliation(s)
- Jinhee Jang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Yoonho Nam
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, South Korea
| | - Sung Won Jung
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Tae-Ryong Riew
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
- Catholic Neuroscience Institute, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Sang Hyun Kim
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - In-Beom Kim
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
- Catholic Neuroscience Institute, College of Medicine, The Catholic University of Korea, Seoul, South Korea
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Isaacs BR, Heijmans M, Kuijf ML, Kubben PL, Ackermans L, Temel Y, Keuken MC, Forstmann BU. Variability in subthalamic nucleus targeting for deep brain stimulation with 3 and 7 Tesla magnetic resonance imaging. NEUROIMAGE-CLINICAL 2021; 32:102829. [PMID: 34560531 PMCID: PMC8463907 DOI: 10.1016/j.nicl.2021.102829] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/12/2021] [Accepted: 09/12/2021] [Indexed: 12/13/2022]
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective surgical treatment for Parkinson's disease (PD). Side-effects may, however, be induced when the DBS lead is placed suboptimally. Currently, lower field magnetic resonance imaging (MRI) at 1.5 or 3 Tesla (T) is used for targeting. Ultra-high-field MRI (7 T and above) can obtain superior anatomical information and might therefore be better suited for targeting. This study aims to test whether optimized 7 T imaging protocols result in less variable targeting of the STN for DBS compared to clinically utilized 3 T images. Three DBS-experienced neurosurgeons determined the optimal STN DBS target site on three repetitions of 3 T-T2, 7 T-T2*, 7 T-R2* and 7 T-QSM images for five PD patients. The distance in millimetres between the three repetitive coordinates was used as an index of targeting variability and was compared between field strength, MRI contrast and repetition with a Bayesian ANOVA. Further, the target coordinates were registered to MNI space, and anatomical coordinates were compared between field strength, MRI contrast and repetition using a Bayesian ANOVA. The results indicate that the neurosurgeons are stable in selecting the DBS target site across MRI field strength, MRI contrast and repetitions. The analysis of the coordinates in MNI space however revealed that the actual selected location of the electrode is seemingly more ventral when using the 3 T scan compared to the 7 T scans.
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Affiliation(s)
- Bethany R Isaacs
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands; Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Margot Heijmans
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Mark L Kuijf
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Pieter L Kubben
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Linda Ackermans
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Yasin Temel
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Max C Keuken
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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Emmerich J, Bachert P, Ladd ME, Straub S. On the separation of susceptibility sources in quantitative susceptibility mapping: Theory and phantom validation with an in vivo application to multiple sclerosis lesions of different age. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 330:107033. [PMID: 34303117 DOI: 10.1016/j.jmr.2021.107033] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 06/14/2021] [Accepted: 07/08/2021] [Indexed: 06/13/2023]
Abstract
PURPOSE In biological tissue, phase contrast is determined by multiple substances such as iron, myelin or calcifications. Often, these substances occur co-located within the same measurement volume. However, quantitative susceptibility mapping can solely measure the average susceptibility per voxel. To provide new insight in disease progression and mechanisms in neurological diseases, where multiple processes such as demyelination and iron accumulation occur simultaneously in the same location, a separation of susceptibility sources is desirable to disentangle the underlying susceptibility proportions. METHODS The basic concept of separating the susceptibility effects from sources with different sign within one voxel is to include information on relaxation rate ΔR2∗ in the quantitative susceptibility mapping reconstruction pipeline. The presented reconstruction algorithm is implemented as a constrained minimization problem and solved using conjugate gradients. The algorithm is evaluated using a software phantom and validated in MRI measurements with a phantom containing mixtures of microscopic positive and negative susceptibility sources. Data from three multiple sclerosis patients are used to show in vivo feasibility. RESULTS In numerical simulations, the feasibility of disentangling susceptibility sources within the same voxel was confirmed provided the critera of the static dephasing regime were fulfilled. In phantom experiments, the magnitude decay kernel, which is an essential reconstruction parameter of the algorithm, was determined to be Dm=194.5T-1s-1ppm-1, and susceptibility sources could be separated in MRI measurement data. CONCLUSIONS In conclusion, in this study a detailed description of the implementation of an algorithm for the separation of positive and negative susceptibility sources within the same volume element as well as its limitations is presented and validated quantitatively in both simulation and phantom experiments for the first time. An application to multiple sclerosis lesions shows promising results for in vivo usability.
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Affiliation(s)
- Julian Emmerich
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany; Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | - Sina Straub
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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131
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Goel A, Roy S, Punjabi K, Mishra R, Tripathi M, Shukla D, Mandal PK. PRATEEK: Integration of Multimodal Neuroimaging Data to Facilitate Advanced Brain Research. J Alzheimers Dis 2021; 83:305-317. [PMID: 34308905 DOI: 10.3233/jad-210440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND In vivo neuroimaging modalities such as magnetic resonance imaging (MRI), functional MRI (fMRI), magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), and quantitative susceptibility mapping (QSM) are useful techniques to understand brain anatomical structure, functional activity, source localization, neurochemical profiles, and tissue susceptibility respectively. Integrating unique and distinct information from these neuroimaging modalities will further help to enhance the understanding of complex neurological diseases. OBJECTIVE To develop a processing scheme for multimodal data integration in a seamless manner on healthy young population, thus establishing a generalized framework for various clinical conditions (e.g., Alzheimer's disease). METHODS A multimodal data integration scheme has been developed to integrate the outcomes from multiple neuroimaging data (fMRI, MEG, MRS, and QSM) spatially. Furthermore, the entire scheme has been incorporated into a user-friendly toolbox- "PRATEEK". RESULTS The proposed methodology and toolbox has been tested for viability among fourteen healthy young participants. The data-integration scheme was tested for bilateral occipital cortices as the regions of interest and can also be extended to other anatomical regions. Overlap percentage from each combination of two modalities (fMRI-MRS, MEG-MRS, fMRI-QSM, and fMRI-MEG) has been computed and also been qualitatively assessed for combinations of the three (MEG-MRS-QSM) and four (fMRI-MEG-MRS-QSM) modalities. CONCLUSION This user-friendly toolbox minimizes the need of an expertise in handling different neuroimaging tools for processing and analyzing multimodal data. The proposed scheme will be beneficial for clinical studies where geometric information plays a crucial role for advance brain research.
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Affiliation(s)
- Anshika Goel
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Saurav Roy
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Khushboo Punjabi
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Ritwick Mishra
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Manjari Tripathi
- Department of Neurology, All Indian Institute of Medical Sciences, New Delhi, India
| | - Deepika Shukla
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Pravat K Mandal
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India.,Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
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132
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In vivo assessment of anisotropy of apparent magnetic susceptibility in white matter from a single orientation acquisition. Neuroimage 2021; 241:118442. [PMID: 34339831 DOI: 10.1016/j.neuroimage.2021.118442] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 06/02/2021] [Accepted: 07/29/2021] [Indexed: 11/20/2022] Open
Abstract
Multiple studies have reported a significant dependence of the effective transverse relaxation rate constant (R2*) and the phase of gradient-echo based (GRE) signal on the orientation of white matter fibres in the human brain. It has also been hypothesized that magnetic susceptibility, as obtained by single-orientation quantitative susceptibility mapping (QSM), exhibits such a dependence. In this study, we investigated this hypothesized relationship in a cohort of healthy volunteers. We show that R2* follows the predicted orientation dependence consistently across white matter regions, whereas the apparent magnetic susceptibility is related differently to fibre orientation across the brain and often in a complex non-monotonic manner. In addition, we explored the effect of fractional anisotropy measured by diffusion-weighted MRI on the strength of the orientation dependence and observed only a limited influence in many regions. However, with careful consideration of such an impact and the limitations imposed by the ill-posed nature of the dipole inversion process, it is possible to study magnetic susceptibility anisotropy in specific brain regions with a single orientation acquisition.
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133
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Zhu X, Gao Y, Liu F, Crozier S, Sun H. Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning. Z Med Phys 2021; 32:188-198. [PMID: 34312047 PMCID: PMC9948866 DOI: 10.1016/j.zemedi.2021.06.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 06/23/2021] [Accepted: 06/26/2021] [Indexed: 01/15/2023]
Abstract
INTRODUCTION Quantitative Susceptibility Mapping (QSM) is generally acquired with full brain coverage, even though many QSM brain-iron studies focus on the deep grey matter (DGM) region only. Reducing the spatial coverage to the DGM vicinity can substantially shorten the scan time or enhance the spatial resolution without increasing scan time; however, this may lead to significant DGM susceptibility underestimation. METHOD A recently proposed deep learning-based QSM method, namely xQSM, is investigated to assess the accuracy of dipole inversion on reduced brain coverages. The xQSM method is compared with two conventional dipole inversion methods using simulated and in vivo experiments from 4 healthy subjects at 3T. Pre-processed magnetic field maps are extended symmetrically from the centre of globus pallidus in the coronal plane to simulate QSM acquisitions of difference spatial coverages, ranging from 100% (∼32mm) to 400% (∼128mm) of the actual DGM physical size. RESULTS The proposed xQSM network led to the lowest DGM contrast loss in both simulated and in vivo subjects, with the smallest susceptibility variation range across all spatial coverages. For the digital brain phantom simulation, xQSM improved the DGM susceptibility underestimation more than 20% in small spatial coverages, as compared to conventional methods. For the in vivo acquisition, less than 5% DGM susceptibility error was achieved in 48mm axial slabs using the xQSM network, while a minimum of 112mm coverage was required for conventional methods. It is also shown that the background field removal process performed worse in reduced brain coverages, which further deteriorated the subsequent dipole inversion. CONCLUSION The recently proposed deep learning-based xQSM method significantly improves the accuracy of DGM QSM from small spatial coverages as compared with conventional QSM algorithms, which can shorten DGM QSM acquisition time substantially.
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Affiliation(s)
| | | | | | | | - Hongfu Sun
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia.
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134
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Gao Y, Cloos M, Liu F, Crozier S, Pike GB, Sun H. Accelerating quantitative susceptibility and R2* mapping using incoherent undersampling and deep neural network reconstruction. Neuroimage 2021; 240:118404. [PMID: 34280526 DOI: 10.1016/j.neuroimage.2021.118404] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/26/2021] [Accepted: 07/15/2021] [Indexed: 10/20/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) and R2* mapping are MRI post-processing methods that quantify tissue magnetic susceptibility and transverse relaxation rate distributions. However, QSM and R2* acquisitions are relatively slow, even with parallel imaging. Incoherent undersampling and compressed sensing reconstruction techniques have been used to accelerate traditional magnitude-based MRI acquisitions; however, most do not recover the full phase signal, as required by QSM, due to its non-convex nature. In this study, a learning-based Deep Complex Residual Network (DCRNet) is proposed to recover both the magnitude and phase images from incoherently undersampled data, enabling high acceleration of QSM and R2* acquisition. Magnitude, phase, R2*, and QSM results from DCRNet were compared with two iterative and one deep learning methods on retrospectively undersampled acquisitions from six healthy volunteers, one intracranial hemorrhage and one multiple sclerosis patients, as well as one prospectively undersampled healthy subject using a 7T scanner. Peak signal to noise ratio (PSNR), structural similarity (SSIM), root-mean-squared error (RMSE), and region-of-interest susceptibility and R2* measurements are reported for numerical comparisons. The proposed DCRNet method substantially reduced artifacts and blurring compared to the other methods and resulted in the highest PSNR, SSIM, and RMSE on the magnitude, R2*, local field, and susceptibility maps. Compared to two iterative and one deep learning methods, the DCRNet method demonstrated a 3.2% to 9.1% accuracy improvement in deep grey matter susceptibility when accelerated by a factor of four. The DCRNet also dramatically shortened the reconstruction time of single 2D brain images from 36-140 seconds using conventional approaches to only 15-70 milliseconds.
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Affiliation(s)
- Yang Gao
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Martijn Cloos
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, QLD, Australia
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Stuart Crozier
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, University of Calgary, Calgary, Canada
| | - Hongfu Sun
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia.
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Berg RC, Preibisch C, Thomas DL, Shmueli K, Biondetti E. Investigating the effect of flow compensation and quantitative susceptibility mapping method on the accuracy of venous susceptibility measurement. Neuroimage 2021; 240:118399. [PMID: 34273528 DOI: 10.1016/j.neuroimage.2021.118399] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 06/15/2021] [Accepted: 07/13/2021] [Indexed: 11/25/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is a promising non-invasive method for obtaining information relating to oxygen metabolism. However, the optimal acquisition sequence and QSM reconstruction method for reliable venous susceptibility measurements are unknown. Full flow compensation is generally recommended to correct for the influence of venous blood flow, although the effect of flow compensation on the accuracy of venous susceptibility values has not been systematically evaluated. In this study, we investigated the effect of different acquisition sequences, including different flow compensation schemes, and different QSM reconstruction methods on venous susceptibilities. Ten healthy subjects were scanned with five or six distinct QSM sequence designs using monopolar readout gradients and different flow compensation schemes. All data sets were processed using six different QSM pipelines and venous blood susceptibility was evaluated in whole-brain segmentations of the venous vasculature and single veins. The quality of vein segmentations and the accuracy of venous susceptibility values were analyzed and compared between all combinations of sequences and reconstruction methods. The influence of the QSM reconstruction method on average venous susceptibility values was found to be 2.7-11.6 times greater than the influence of the acquisition sequence, including flow compensation. The majority of the investigated QSM reconstruction methods tended to underestimate venous susceptibility values in the vein segmentations that were obtained. In summary, we found that multi-echo gradient-echo acquisition sequences without full flow compensation yielded venous susceptibility values comparable to sequences with full flow compensation. However, the QSM reconstruction method had a great influence on susceptibility values and thus needs to be selected carefully for accurate venous QSM.
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Affiliation(s)
- Ronja C Berg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany.
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaninger Str. 22, 81675 Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Clinic for Neurology, Ismaninger Str. 22, 81675 Munich, Munich, Germany.
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, United Kingdom.
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, United Kingdom.
| | - Emma Biondetti
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, United Kingdom; Institut du Cerveau - ICM, Centre de NeuroImagerie de Recherche - CENIR, Team "Movement Investigations and Therapeutics" (MOV'IT), INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France.
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136
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Marques JP, Meineke J, Milovic C, Bilgic B, Chan K, Hedouin R, van der Zwaag W, Langkammer C, Schweser F. QSM reconstruction challenge 2.0: A realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures. Magn Reson Med 2021; 86:526-542. [PMID: 33638241 PMCID: PMC8048665 DOI: 10.1002/mrm.28716] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 01/12/2021] [Accepted: 01/15/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To create a realistic in silico head phantom for the second QSM reconstruction challenge and for future evaluations of processing algorithms for QSM. METHODS We created a digital whole-head tissue property phantom by segmenting and postprocessing high-resolution (0.64 mm isotropic), multiparametric MRI data acquired at 7 T from a healthy volunteer. We simulated the steady-state magnetization at 7 T using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based processing. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the phantom in the future, such as the inclusion of pathologies as well as the simulation of a wide range of acquisition protocols. Specifically, the following parameters and effects were implemented: TR and TE, voxel size, background fields, and RF phase biases. Diffusion-weighted imaging phantom data are provided, allowing future investigations of tissue-microstructure effects in phase and QSM algorithms. RESULTS The brain part of the phantom featured realistic morphology with spatial variations in relaxation and susceptibility values similar to the in vivo setting. We demonstrated some of the phantom's properties, including the possibility of generating phase data with nonlinear evolution over TE due to partial-volume effects or complex distributions of frequency shifts within the voxel. CONCLUSION The presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative susceptibility reconstruction algorithms.
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Affiliation(s)
- José P. Marques
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
| | | | - Carlos Milovic
- Department of Electrical EngineeringPontificia Universidad Catolica de ChileSantiagoChile
- Biomedical Imaging CenterPontificia Universidad Catolica de ChileSantiagoChile
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUnited Kingdom
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical ImagingCharlestownMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Harvard‐MIT Health Sciences and TechnologyMITCambridgeMassachusettsUSA
| | - Kwok‐Shing Chan
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
| | - Renaud Hedouin
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
- Centre Inria Rennes ‐ Bretagne AtlantiqueRennesFrance
| | | | | | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis CenterDepartment of NeurologyJacobs School of Medicine and Biomedical SciencesUniversity at BuffaloThe State University of New YorkBuffaloNew YorkUSA
- Center for Biomedical Imaging, Clinical and Translational Science InstituteUniversity at BuffaloThe State University of New YorkBuffaloNew YorkUSA
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137
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RESUME N: A flexible class of multi-parameter qMRI protocols. Phys Med 2021; 88:23-36. [PMID: 34171573 DOI: 10.1016/j.ejmp.2021.04.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/16/2021] [Accepted: 04/02/2021] [Indexed: 12/30/2022] Open
Abstract
PURPOSE To introduce a class of fast 3D quantitative MRI (qMRI) schemes (RESUMEN, for N=1,…,4) that allow for a thorough characterization of microstructural properties of brain tissues. METHODS An arbitrary multi-echo GRE acquisition optimized for quantitative susceptibility mapping (QSM) is complemented with an appropriate low flip-angle GRE sequence drawn from four possible choices. The acquired signals are processed to analytically derive the longitudinal relaxation (R1) and free induction decay (R2∗) rates, as well as the proton density (PD) and QSM. A comprehensive modeling of the excitation and B1- profiles and of the RF-spoiling is included in the acquisition and processing pipeline. RESULTS The RESUMEN maps appear homogeneous throughout the field-of-view and exhibit comparable values and high SNR across the considered range of N values. CONCLUSIONS The introduced schemes represent a class of robust and flexible strategies to derive a thorough and fast qMRI study, suitable for a whole-brain acquisition with isotropic voxel resolution of 700 μm in less than 15 min.
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Callewaert B, Jones EAV, Himmelreich U, Gsell W. Non-Invasive Evaluation of Cerebral Microvasculature Using Pre-Clinical MRI: Principles, Advantages and Limitations. Diagnostics (Basel) 2021; 11:diagnostics11060926. [PMID: 34064194 PMCID: PMC8224283 DOI: 10.3390/diagnostics11060926] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 12/11/2022] Open
Abstract
Alterations to the cerebral microcirculation have been recognized to play a crucial role in the development of neurodegenerative disorders. However, the exact role of the microvascular alterations in the pathophysiological mechanisms often remains poorly understood. The early detection of changes in microcirculation and cerebral blood flow (CBF) can be used to get a better understanding of underlying disease mechanisms. This could be an important step towards the development of new treatment approaches. Animal models allow for the study of the disease mechanism at several stages of development, before the onset of clinical symptoms, and the verification with invasive imaging techniques. Specifically, pre-clinical magnetic resonance imaging (MRI) is an important tool for the development and validation of MRI sequences under clinically relevant conditions. This article reviews MRI strategies providing indirect non-invasive measurements of microvascular changes in the rodent brain that can be used for early detection and characterization of neurodegenerative disorders. The perfusion MRI techniques: Dynamic Contrast Enhanced (DCE), Dynamic Susceptibility Contrast Enhanced (DSC) and Arterial Spin Labeling (ASL), will be discussed, followed by less established imaging strategies used to analyze the cerebral microcirculation: Intravoxel Incoherent Motion (IVIM), Vascular Space Occupancy (VASO), Steady-State Susceptibility Contrast (SSC), Vessel size imaging, SAGE-based DSC, Phase Contrast Flow (PC) Quantitative Susceptibility Mapping (QSM) and quantitative Blood-Oxygenation-Level-Dependent (qBOLD). We will emphasize the advantages and limitations of each strategy, in particular on applications for high-field MRI in the rodent's brain.
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Affiliation(s)
- Bram Callewaert
- Biomedical MRI Group, University of Leuven, Herestraat 49, bus 505, 3000 Leuven, Belgium; (B.C.); (W.G.)
- CMVB, Center for Molecular and Vascular Biology, University of Leuven, Herestraat 49, bus 911, 3000 Leuven, Belgium;
| | - Elizabeth A. V. Jones
- CMVB, Center for Molecular and Vascular Biology, University of Leuven, Herestraat 49, bus 911, 3000 Leuven, Belgium;
- CARIM, Maastricht University, Universiteitssingel 50, 6200 MD Maastricht, The Netherlands
| | - Uwe Himmelreich
- Biomedical MRI Group, University of Leuven, Herestraat 49, bus 505, 3000 Leuven, Belgium; (B.C.); (W.G.)
- Correspondence:
| | - Willy Gsell
- Biomedical MRI Group, University of Leuven, Herestraat 49, bus 505, 3000 Leuven, Belgium; (B.C.); (W.G.)
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139
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Tuzzi E, Balla DZ, Loureiro JRA, Neumann M, Laske C, Pohmann R, Preische O, Scheffler K, Hagberg GE. Ultra-High Field MRI in Alzheimer's Disease: Effective Transverse Relaxation Rate and Quantitative Susceptibility Mapping of Human Brain In Vivo and Ex Vivo compared to Histology. J Alzheimers Dis 2021; 73:1481-1499. [PMID: 31958079 DOI: 10.3233/jad-190424] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia worldwide. So far, diagnosis of AD is only unequivocally defined through postmortem histology. Amyloid plaques are a classical hallmark of AD and amyloid load is currently quantified by Positron Emission tomography (PET) in vivo. Ultra-high field magnetic resonance imaging (UHF-MRI) can potentially provide a non-invasive biomarker for AD by allowing imaging of pathological processes at a very-high spatial resolution. The first aim of this work was to reproduce the characteristic cortical pattern previously observed in vivo in AD patients using weighted-imaging at 7T. We extended these findings using quantitative susceptibility mapping (QSM) and quantification of the effective transverse relaxation rate (R2*) at 9.4T. The second aim was to investigate the origin of the contrast patterns observed in vivo in the cortex of AD patients at 9.4T by comparing quantitative UHF-MRI (9.4T and 14.1T) of postmortem samples with histology. We observed a distinctive cortical pattern in vivo in patients compared to healthy controls (HC), and these findings were confirmed ex vivo. Specifically, we found a close link between the signal changes detected by QSM in the AD sample at 14.1T and the distribution pattern of amyloid plaques in the histological sections of the same specimen. Our findings showed that QSM and R2* maps can distinguish AD from HC at UHF by detecting cortical alterations directly related to amyloid plaques in AD patients. Furthermore, we provided a method to quantify amyloid plaque load in AD patients at UHF non-invasively.
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Affiliation(s)
- Elisa Tuzzi
- Department for High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department for Biomedical Magnetic Resonance, Eberhard Karl's University, Tübingen and University Hospital, Tübingen, Germany
| | - David Z Balla
- Department for Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Joana R A Loureiro
- Department for High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department for Biomedical Magnetic Resonance, Eberhard Karl's University, Tübingen and University Hospital, Tübingen, Germany.,Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, University of California, Los Angeles, CA, USA
| | - Manuela Neumann
- Department of Neuropathology, University Hospital, Tübingen, Germany.,German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Rolf Pohmann
- Department for High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Oliver Preische
- German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Klaus Scheffler
- Department for High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department for Biomedical Magnetic Resonance, Eberhard Karl's University, Tübingen and University Hospital, Tübingen, Germany
| | - Gisela E Hagberg
- Department for High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department for Biomedical Magnetic Resonance, Eberhard Karl's University, Tübingen and University Hospital, Tübingen, Germany
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140
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Vroegindeweij LHP, Bossoni L, Boon AJW, Wilson JHP, Bulk M, Labra-Muñoz J, Huber M, Webb A, van der Weerd L, Langendonk JG. Quantification of different iron forms in the aceruloplasminemia brain to explore iron-related neurodegeneration. NEUROIMAGE-CLINICAL 2021; 30:102657. [PMID: 33839643 PMCID: PMC8055714 DOI: 10.1016/j.nicl.2021.102657] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/24/2021] [Accepted: 03/30/2021] [Indexed: 12/25/2022]
Abstract
Ferrihydrite-iron is the most abundant iron form in the aceruloplasminemia brain. Iron concentrations over 1 mg/g are found in deep gray matter structures. The deep gray matter contains over three times more iron than the temporal cortex. Iron-sensitive MRI contrast is primarily driven by the amount of ferrihydrite-iron. R2* is more illustrative of the pattern of iron accumulation than QSM at 7 T.
Aims Aceruloplasminemia is an ultra-rare neurodegenerative disorder associated with massive brain iron deposits, of which the molecular composition is unknown. We aimed to quantitatively determine the molecular iron forms in the aceruloplasminemia brain, and to illustrate their influence on iron-sensitive MRI metrics. Methods The inhomogeneous transverse relaxation rate (R2*) and magnetic susceptibility obtained from 7 T MRI were combined with Electron Paramagnetic Resonance (EPR) and Superconducting Quantum Interference Device (SQUID) magnetometry. The basal ganglia, thalamus, red nucleus, dentate nucleus, superior- and middle temporal gyrus and white matter of a post-mortem aceruloplasminemia brain were studied. MRI, EPR and SQUID results that had been previously obtained from the temporal cortex of healthy controls were included for comparison. Results The brain iron pool in aceruloplasminemia detected in this study consisted of EPR-detectable Fe3+ ions, magnetic Fe3+ embedded in the core of ferritin and hemosiderin (ferrihydrite-iron), and magnetic Fe3+ embedded in oxidized magnetite/maghemite minerals (maghemite-iron). Ferrihydrite-iron represented above 90% of all iron and was the main driver of iron-sensitive MRI contrast. Although deep gray matter structures were three times richer in ferrihydrite-iron than the temporal cortex, ferrihydrite-iron was already six times more abundant in the temporal cortex of the patient with aceruloplasminemia compared to the healthy situation (162 µg/g vs. 27 µg/g), on average. The concentrations of Fe3+ ions and maghemite-iron in the temporal cortex in aceruloplasminemia were within the range of those in the control subjects. Conclusions Iron-related neurodegeneration in aceruloplasminemia is primarily associated with an increase in ferrihydrite-iron, with ferrihydrite-iron being the major determinant of iron-sensitive MRI contrast.
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Affiliation(s)
- Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Lucia Bossoni
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Agnita J W Boon
- Department of Neurology, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - J H Paul Wilson
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Marjolein Bulk
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jacqueline Labra-Muñoz
- Department of Physics, Huygens-Kamerlingh Onnes Laboratory, Leiden University, Niels Bohrweg 2, 2333CA Leiden, the Netherlands; Kavli Institute of Nanoscience, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, the Netherlands
| | - Martina Huber
- Department of Physics, Huygens-Kamerlingh Onnes Laboratory, Leiden University, Niels Bohrweg 2, 2333CA Leiden, the Netherlands
| | - Andrew Webb
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Louise van der Weerd
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
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141
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Automated assessment of the substantia nigra on susceptibility map-weighted imaging using deep convolutional neural networks for diagnosis of Idiopathic Parkinson's disease. Parkinsonism Relat Disord 2021; 85:84-90. [PMID: 33761389 DOI: 10.1016/j.parkreldis.2021.03.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 01/27/2021] [Accepted: 03/08/2021] [Indexed: 11/23/2022]
Abstract
OBJECTIVES Despite its use in determining nigrostriatal degeneration, the lack of a consistent interpretation of nigrosome 1 susceptibility map-weighted imaging (SMwI) limits its generalized applicability. To implement and evaluate a diagnostic algorithm based on convolutional neural networks for interpreting nigrosome 1 SMwI for determining nigrostriatal degeneration in idiopathic Parkinson's disease (IPD). METHODS In this retrospective study, we enrolled 267 IPD patients and 160 control subjects (125 patients with drug-induced parkinsonism and 35 healthy subjects) at our institute, and 24 IPD patients and 27 control subjects at three other institutes on approval of the local institutional review boards. Dopamine transporter imaging served as the reference standard for the presence or absence of abnormalities of nigrosome 1 on SMwI. Diagnostic performance was compared between visual assessment by an experienced neuroradiologist and the developed deep learning-based diagnostic algorithm in both internal and external datasets using a bootstrapping method with 10000 re-samples by the "pROC" package of R (version 1.16.2). RESULTS The area under the receiver operating characteristics curve (AUC) (95% confidence interval [CI]) per participant by the bootstrap method was not significantly different between visual assessment and the deep learning-based algorithm (internal validation, .9622 [0.8912-1.0000] versus 0.9534 [0.8779-0.9956], P = .1511; external validation, 0.9367 [0.8843-0.9802] versus 0.9208 [0.8634-0.9693], P = .6267), indicative of a comparable performance to visual assessment. CONCLUSIONS Our deep learning-based algorithm for assessing abnormalities of nigrosome 1 on SMwI was found to have a comparable performance to that of an experienced neuroradiologist.
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142
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Song T, Li J, Mei S, Jia X, Yang H, Ye Y, Yuan J, Zhang Y, Lu J. Nigral Iron Deposition Is Associated With Levodopa-Induced Dyskinesia in Parkinson's Disease. Front Neurosci 2021; 15:647168. [PMID: 33828454 PMCID: PMC8019898 DOI: 10.3389/fnins.2021.647168] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 02/16/2021] [Indexed: 11/29/2022] Open
Abstract
Objective To investigate iron deposition in the substantia nigra (SN) of Parkinson’s disease (PD) patients associated with levodopa-induced dyskinesia (LID). Methods Seventeen PD patients with LID, 17 PD patients without LID, and 16 healthy controls were recruited for this study. The mean QSM values of the whole, left, and right SN were compared among the three groups. A multivariate logistic regression model was constructed to determine the factors associated with increased risk of LID. The receiver operating characteristic curve of the QSM value of SN in discriminating PD with and without LID was evaluated. Results The mean QSM values of the whole and right SN in the PD with LID were higher than those in the PD without LID (∗P = 0.03, ∗P = 0.03). Multivariate logistic regression analysis revealed that the QSM value of whole, left, or right SN was a predictor of the development of LID (∗P = 0.03, ∗P = 0.04, and ∗P = 0.04). The predictive accuracy of LID in adding the QSM value of the whole, left, and right SN to LID-related clinical risk factors was 70.6, 64.7, and 67.6%, respectively. The QSM cutoff values between PD with and without LID of the whole, left, and right SN were 148.3, 165.4, and 152.7 ppb, respectively. Conclusion This study provides the evidence of higher iron deposition in the SN of PD patients with LID than those without LID, suggesting that the QSM value of the SN may be a potential early diagnostic neuroimaging biomarker for LID.
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Affiliation(s)
- Tianbin Song
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Jiping Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Shanshan Mei
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiaofei Jia
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yongquan Ye
- UIH America, Inc., Houston, TX, United States
| | - Jianmin Yuan
- Central Research Institute, UIH Group, Shanghai, China
| | - Yuqing Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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143
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Tian Y, Lim Y, Zhao Z, Byrd D, Narayanan S, Nayak KS. Aliasing artifact reduction in spiral real-time MRI. Magn Reson Med 2021; 86:916-925. [PMID: 33728700 DOI: 10.1002/mrm.28746] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 01/09/2021] [Accepted: 02/02/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE To mitigate a common artifact in spiral real-time MRI, caused by aliasing of signal outside the desired FOV. This artifact frequently occurs in midsagittal speech real-time MRI. METHODS Simulations were performed to determine the likely origin of the artifact. Two methods to mitigate the artifact are proposed. The first approach, denoted as "large FOV" (LF), keeps an FOV that is large enough to include the artifact signal source during reconstruction. The second approach, denoted as "estimation-subtraction" (ES), estimates the artifact signal source before subtracting a synthetic signal representing that source in multicoil k-space raw data. Twenty-five midsagittal speech-production real-time MRI data sets were used to evaluate both of the proposed methods. Reconstructions without and with corrections were evaluated by two expert readers using a 5-level Likert scale assessing artifact severity. Reconstruction time was also compared. RESULTS The origin of the artifact was found to be a combination of gradient nonlinearity and imperfect anti-aliasing in spiral sampling. The LF and ES methods were both able to substantially reduce the artifact, with an averaged qualitative score improvement of 1.25 and 1.35 Likert levels for LF correction and ES correction, respectively. Average reconstruction time without correction, with LF correction, and with ES correction were 160.69 ± 1.56, 526.43 ± 5.17, and 171.47 ± 1.71 ms/frame. CONCLUSION Both proposed methods were able to reduce the spiral aliasing artifacts, with the ES-reduction method being more effective and more time efficient.
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Affiliation(s)
- Ye Tian
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Yongwan Lim
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Ziwei Zhao
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Dani Byrd
- Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Shrikanth Narayanan
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA.,Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
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144
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Gao Y, Zhu X, Moffat BA, Glarin R, Wilman AH, Pike GB, Crozier S, Liu F, Sun H. xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks. NMR IN BIOMEDICINE 2021; 34:e4461. [PMID: 33368705 DOI: 10.1002/nbm.4461] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 11/25/2020] [Indexed: 06/12/2023]
Abstract
Quantitative susceptibility mapping (QSM) provides a valuable MRI contrast mechanism that has demonstrated broad clinical applications. However, the image reconstruction of QSM is challenging due to its ill-posed dipole inversion process. In this study, a new deep learning method for QSM reconstruction, namely xQSM, was designed by introducing noise regularization and modified octave convolutional layers into a U-net backbone and trained with synthetic and in vivo datasets, respectively. The xQSM method was compared with two recent deep learning (QSMnet+ and DeepQSM) and two conventional dipole inversion (MEDI and iLSQR) methods, using both digital simulations and in vivo experiments. Reconstruction error metrics, including peak signal-to-noise ratio, structural similarity, normalized root mean squared error and deep gray matter susceptibility measurements, were evaluated for comparison of the different methods. The results showed that the proposed xQSM network trained with in vivo datasets achieved the best reconstructions of all the deep learning methods. In particular, it led to, on average, 32.3%, 25.4% and 11.7% improvement in the accuracy of globus pallidus susceptibility estimation for digital simulations and 39.3%, 21.8% and 6.3% improvements for in vivo acquisitions compared with DeepQSM, QSMnet+ and iLSQR, respectively. It also exhibited the highest linearity against different susceptibility intensity scales and demonstrated the most robust generalization capability to various spatial resolutions of all the deep learning methods. In addition, the xQSM method also substantially shortened the reconstruction time from minutes using MEDI to only a few seconds.
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Affiliation(s)
- Yang Gao
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Xuanyu Zhu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Bradford A Moffat
- Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, The University of Melbourne, Parkville, Australia
| | - Rebecca Glarin
- Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, The University of Melbourne, Parkville, Australia
- Department of Radiology, Royal Melbourne Hospital, Parkville, Australia
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, University of Calgary, Calgary, Canada
| | - Stuart Crozier
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Hongfu Sun
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
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145
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Yaghmaie N, Syeda WT, Wu C, Zhang Y, Zhang TD, Burrows EL, Brodtmann A, Moffat BA, Wright DK, Glarin R, Kolbe S, Johnston LA. QSMART: Quantitative susceptibility mapping artifact reduction technique. Neuroimage 2021; 231:117701. [PMID: 33484853 DOI: 10.1016/j.neuroimage.2020.117701] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/19/2020] [Accepted: 12/21/2020] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Quantitative susceptibility mapping (QSM) is a novel MR technique that allows mapping of tissue susceptibility values from MR phase images. QSM is an ill-conditioned inverse problem, and although several methods have been proposed in the field, in the presence of a wide range of susceptibility sources, streaking artifacts appear around high susceptibility regions and contaminate the whole QSM map. QSMART is a post-processing pipeline that uses two-stage parallel inversion to reduce the streaking artifacts and remove banding artifact at the cortical surface and around the vasculature. METHOD Tissue and vein susceptibility values were separately estimated by generating a mask of vasculature driven from the magnitude data using a Frangi filter. Spatially dependent filtering was used for the background field removal step and the two susceptibility estimates were combined in the final QSM map. QSMART was compared to RESHARP/iLSQR and V-SHARP/iLSQR inversion in a numerical phantom, 7T in vivo single and multiple-orientation scans, 9.4T ex vivo mouse data, and 4.7T in vivo rat brain with induced focal ischemia. RESULTS Spatially dependent filtering showed better suppression of phase artifacts near cortex compared to RESHARP and V-SHARP, while preserving voxels located within regions of interest without brain edge erosion. QSMART showed successful reduction of streaking artifacts as well as improved contrast between different brain tissues compared to the QSM maps obtained by RESHARP/iLSQR and V-SHARP/iLSQR. CONCLUSION QSMART can reduce QSM artifacts to enable more robust estimation of susceptibility values in vivo and ex vivo.
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Affiliation(s)
- Negin Yaghmaie
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Australia; Department of Biomedical Engineering, The University of Melbourne, Australia
| | - Warda T Syeda
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Australia; Department of Medicine and Radiology, The University of Melbourne, Australia
| | - Chengchuan Wu
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Australia; Department of Biomedical Engineering, The University of Melbourne, Australia
| | - Yicheng Zhang
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Australia; Department of Biomedical Engineering, The University of Melbourne, Australia
| | - Tracy D Zhang
- Florey Institute of Neuroscience and Mental Health, Australia
| | - Emma L Burrows
- Florey Institute of Neuroscience and Mental Health, Australia
| | - Amy Brodtmann
- Florey Institute of Neuroscience and Mental Health, Australia
| | - Bradford A Moffat
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Australia; Department of Medicine and Radiology, The University of Melbourne, Australia
| | - David K Wright
- Department of Neuroscience, Central Clinical School, Monash University, Australia
| | - Rebecca Glarin
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Australia; Department of Radiology, Royal Melbourne Hospital, Australia
| | - Scott Kolbe
- Department of Medicine and Radiology, The University of Melbourne, Australia; Department of Neuroscience, Central Clinical School, Monash University, Australia; Department of Radiology, Alfred Hospital, Australia
| | - Leigh A Johnston
- Melbourne Brain Centre Imaging Unit, The University of Melbourne, Australia; Department of Biomedical Engineering, The University of Melbourne, Australia; Department of Medicine and Radiology, The University of Melbourne, Australia.
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146
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Karsa A, Punwani S, Shmueli K. An optimized and highly repeatable MRI acquisition and processing pipeline for quantitative susceptibility mapping in the head-and-neck region. Magn Reson Med 2020; 84:3206-3222. [PMID: 32621302 DOI: 10.1002/mrm.28377] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 05/06/2020] [Accepted: 05/23/2020] [Indexed: 02/11/2024]
Abstract
PURPOSE Quantitative Susceptibility Mapping (QSM) is an emerging technique sensitive to disease-related changes including oxygenation. It is extensively used in brain studies and has increasing clinical applications outside the brain. Here we present the first MRI acquisition protocol and QSM pipeline optimized for the head-and-neck region together with a repeatability analysis performed in healthy volunteers. METHODS We investigated both the intrasession and the intersession repeatability of the optimized method in 10 subjects. We also implemented two, Tikhonov-regularisation-based susceptibility calculation techniques that were found to have higher contrast-to-noise than existing methods in the head-and-neck region. Repeatability was evaluated by calculating the distributions of susceptibility differences between repeated scans and the corresponding minimum detectable effect sizes (MDEs). RESULTS Deep brain regions had higher QSM repeatability than neck regions. As expected, intrasession repeatability was generally better than intersession repeatability. Susceptibility maps calculated using projection onto dipole fields for background field removal were more repeatable than using the Laplacian boundary value method in the head-and-neck region. Small (short-axis diameter <5 mm) lymph nodes had the lowest repeatability (MDE = 0.27 ppm) as imperfect segmentation included some of the surrounding paramagnetic fatty fascia, highlighting the importance of accurate region delineation. MDEs in the larger lymph nodes (0.16 ppm), submandibular glands (0.10 ppm), and especially the parotid glands (0.06 ppm) were much lower, comparable to those of the brain regions. CONCLUSIONS The high repeatability of the acquisition and pipeline optimized for QSM will facilitate clinical studies in the head-and-neck region.
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Affiliation(s)
- Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Centre for Medical Imaging, University College London, London, United Kingdom
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, London, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Centre for Medical Imaging, University College London, London, United Kingdom
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147
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Bechler E, Stabinska J, Thiel T, Jasse J, Zukovs R, Valentin B, Wittsack HJ, Ljimani A. Feasibility of quantitative susceptibility mapping (QSM) of the human kidney. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 34:389-397. [PMID: 33230656 PMCID: PMC8492554 DOI: 10.1007/s10334-020-00895-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/03/2020] [Accepted: 11/05/2020] [Indexed: 11/28/2022]
Abstract
Objective To evaluate the feasibility of in-vivo quantitative susceptibility mapping (QSM) of the human kidney. Methods An axial single-breath-hold 3D multi-echo sequence (acquisition time 33 s) was completed on a 3 T-MRI-scanner (Magnetom Prisma, Siemens Healthineers, Erlangen, Germany) in 19 healthy volunteers. Graph-cut-based unwrapping combined with the T2*-IDEAL approach was performed to remove the chemical shift of fat and to quantify QSM of the upper abdomen. Mean susceptibility values of the entire, renal cortex and medulla in both kidneys and the liver were determined and compared. Five subjects were measured twice to examine the reproducibility. One patient with severe renal fibrosis was included in the study to evaluate the potential clinical relevance of QSM. Results QSM was successful in 17 volunteers and the patient with renal fibrosis. Anatomical structures in the abdomen were clearly distinguishable by QSM and the susceptibility values obtained in the liver were comparable to those found in the literature. The results showed a good reproducibility. Besides, the mean renal QSM values obtained in healthy volunteers (0.04 ± 0.07 ppm for the right and − 0.06 ± 0.19 ppm for the left kidney) were substantially higher than that measured in the investigated fibrotic kidney (− 0.43 ± − 0.02 ppm). Conclusion QSM of the human kidney could be a promising approach for the assessment of information about microscopic renal tissue structure. Therefore, it might further improve functional renal MR imaging. Electronic supplementary material The online version of this article (10.1007/s10334-020-00895-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Eric Bechler
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
| | - Julia Stabinska
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
| | - Thomas Thiel
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
| | - Jonas Jasse
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
| | - Romans Zukovs
- Department of Haematology, Oncology and Clinical Immunology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Birte Valentin
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
| | - Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
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Isaacs BR, Mulder MJ, Groot JM, van Berendonk N, Lute N, Bazin PL, Forstmann BU, Alkemade A. 3 versus 7 Tesla magnetic resonance imaging for parcellations of subcortical brain structures in clinical settings. PLoS One 2020; 15:e0236208. [PMID: 33232325 PMCID: PMC7685480 DOI: 10.1371/journal.pone.0236208] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022] Open
Abstract
7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa. These parcellations were created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. The clinical 3T MRI scans did not allow delineation of an anatomically plausible structure due to its limited spatial resolution. o3T and 7T parcellations were directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results showed a higher consistency for structure volumes for 7T compared to optimized 3T which illustrates the importance of the use of isotropic voxels for 3D visualization of the surgical target area. Together these results indicate that 7T outperforms c3T as well as o3T given the constraints of a clinical setting.
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Affiliation(s)
- Bethany R. Isaacs
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Department of Experimental Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Martijn J. Mulder
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Psychology and Social Sciences, University of Utrecht, Utrecht, The Netherlands
| | - Josephine M. Groot
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nikita van Berendonk
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nicky Lute
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Clinical Neuropsychology, Vrije University, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Max Planck Institute for Human, Cognitive and Brain Sciences, Leipzig, Germany
| | - Birte U. Forstmann
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
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149
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Bae YJ, Song YS, Choi BS, Kim JM, Nam Y, Kim JH. Comparison of susceptibility-weighted imaging and susceptibility map-weighted imaging for the diagnosis of Parkinsonism with nigral hyperintensity. Eur J Radiol 2020; 134:109398. [PMID: 33264728 DOI: 10.1016/j.ejrad.2020.109398] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 10/22/2020] [Accepted: 11/01/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVE To determine whether susceptibility map-weighted imaging (SMWI) was superior to conventional susceptibility-weighted imaging (SWI) in the diagnosis of Parkinson's disease (PD) and in its correlation with 123I-2bcarbomethoxy-3b-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane single photon emission computerized tomography (123I-FP-CIT SPECT). METHODS Between May 2017 and February 2018, 125 consecutive patients diagnosed with idiopathic PD, vascular pseudoparkinsonism, essential tremor, or drug-induced parkinsonism and who underwent 123I-FP-CIT SPECT imaging and 3 T SWI on the same day or within 3 months were included in this retrospective study. In all patients, SMWI images were generated from SWI images. On both MRIs, two neuroradiologists independently evaluated the status of nigral hyperintensity on each side of substantia nigra. Inter-observer agreements for the nigral hyperintensity were tested. Using consensus reading, concordance between SWI, SMWI, and 123I-FP-CIT SPECT were evaluated, and the diagnostic performance between SWI and SMWI for PD was compared. RESULTS Inter-observer agreement for the nigral hyperintensity was higher for SMWI (right, κ = 0.919; left, κ = 0.984) than for SWI (right, κ = 0.918; left, κ = 0.902). SMWI (right 67.2 %, left 68.0 %) showed a higher concordance rate with the results of 123I-FP-CIT SPECT than SWI (right 60.0 %, left 59.2 %). SMWI (area under curve [AUC], 0.791) provided significantly higher diagnostic performance for PD than SWI (AUC, 0.720; P = 0.0005). CONCLUSION SMWI may be a superior assessment tool for nigral hyperintensity than SWI and may be an improved diagnostic imaging modality for patients with suspected PD.
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Affiliation(s)
- Yun Jung Bae
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam-si, 13620, Republic of Korea.
| | - Yoo Sung Song
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam-si, 13620, Republic of Korea.
| | - Byung Se Choi
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam-si, 13620, Republic of Korea.
| | - Jong-Min Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam-si, 13620, Republic of Korea.
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, 81, Oedae-ro, Mohyeon-eup, Cheoin-gu, Yongin-si, Gyeonggi-do, 17035, Republic of Korea.
| | - Jae Hyoung Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam-si, 13620, Republic of Korea.
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150
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Wang N, Liu XL, Li L, Zuo CT, Wang J, Wu PY, Zhang Y, Liu F, Li Y. Screening for Early-Stage Parkinson's Disease: Swallow Tail Sign on MRI Susceptibility Map-Weighted Images Compared With PET. J Magn Reson Imaging 2020; 53:722-730. [PMID: 33096586 DOI: 10.1002/jmri.27386] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 09/19/2020] [Accepted: 09/22/2020] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Swallow tail sign (STS) on MRI is presumed to be an imaging biomarker of nigrosome-1, which may exhibit a similar role as positron emission tomography (PET), indicating dopaminergic degeneration. PURPOSE To investigate whether an alteration of STS could serve as an alternative screening sign compared with PET in the diagnosis of early-stage Parkinson's disease (esPD). STUDY TYPE Prospective. POPULATION Thirty-seven patients with esPD and 27 age- and sex-matched healthy controls (HCs). FIELD STRENGTH/SEQUENCE Quantitative susceptibility mapping images were collected on 3T MRI and [18 F]9-fluoropropyl-(+)-dihydrotetra-benazine PET images were acquired using a 64 rings PET/CT scanner. ASSESSMENT Alterations of STS and striatal uptake in each hemisphere were visually rated on a 0-2 points scale. Point 2: normal appearance of STS/normal striatal uptake; Point 1: partial loss of STS/uptake reduction confined to the putamen; Point 0: total loss of STS/uptake reduction extended to the caudate nucleus. The concordance rate of STS rating and ipsilateral striatal binding was calculated at the nuclei level. At the participant level, an evaluation rating was calculated by adding the STS ratings from both hemispheres to distinguish esPD from HCs. STATISTICAL TESTS The intra- and interobserver agreement were tested using Cohen's kappa and the intraclass correlation coefficient. Hotelling's T-squared test was used to compare the difference of rating points. Receiver operating characteristic analysis was performed to evaluate the diagnostic power. RESULTS The intra- and interobserver agreement for STS and striatal uptake rating was over 0.75. There was no significant difference of rating point distribution (P = 0.084). The concordance rate was 94.3% for the right side and 91.4% for the left. Using bilateral partial loss of STS as the threshold, the achieved sensitivity and specificity for discriminating esPD from HCs were 94.59% and 92.49%, respectively. DATA CONCLUSION STS alterations corresponded well with striatal uptake on PET in esPD, and our proposed evaluation scale of STS had satisfactory diagnostic performance in discriminating the disease. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Na Wang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Xue-Ling Liu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ling Li
- Department of PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Chuan-Tao Zuo
- Department of PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jian Wang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | | | | | - Fengtao Liu
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - YuXin Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
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