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Tourell M, Jin J, Bachrata B, Stewart A, Ropele S, Enzinger C, Bollmann S, Bollmann S, Robinson SD, O'Brien K, Barth M. Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T. Magn Reson Med 2024; 92:997-1010. [PMID: 38778631 DOI: 10.1002/mrm.30101] [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: 10/03/2023] [Revised: 03/14/2024] [Accepted: 03/16/2024] [Indexed: 05/25/2024]
Abstract
PURPOSE QSM provides insight into healthy brain aging and neuropathologies such as multiple sclerosis (MS), traumatic brain injuries, brain tumors, and neurodegenerative diseases. Phase data for QSM are usually acquired from 3D gradient-echo (3D GRE) scans with long acquisition times that are detrimental to patient comfort and susceptible to patient motion. This is particularly true for scans requiring whole-brain coverage and submillimeter resolutions. In this work, we use a multishot 3D echo plannar imaging (3D EPI) sequence with shot-selective 2D CAIPIRIHANA to acquire high-resolution, whole-brain data for QSM with minimal distortion and blurring. METHODS To test clinical viability, the 3D EPI sequence was used to image a cohort of MS patients at 1-mm isotropic resolution at 3 T. Additionally, 3D EPI data of healthy subjects were acquired at 1-mm, 0.78-mm, and 0.65-mm isotropic resolution with varying echo train lengths (ETLs) and compared with a reference 3D GRE acquisition. RESULTS The appearance of the susceptibility maps and the susceptibility values for segmented regions of interest were comparable between 3D EPI and 3D GRE acquisitions for both healthy and MS participants. Additionally, all lesions visible in the MS patients on the 3D GRE susceptibility maps were also visible on the 3D EPI susceptibility maps. The interplay among acquisition time, resolution, echo train length, and the effect of distortion on the calculated susceptibility maps was investigated. CONCLUSION We demonstrate that the 3D EPI sequence is capable of rapidly acquiring submillimeter resolutions and providing high-quality, clinically relevant susceptibility maps.
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Affiliation(s)
- Monique Tourell
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
| | - Jin Jin
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
- Siemens Healthineers Pty Ltd, Bowen Hills, Queensland, Australia
| | - Beata Bachrata
- High Field MR Center, 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
- Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria
| | - Ashley Stewart
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Saskia Bollmann
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
| | - Steffen Bollmann
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
| | - Simon Daniel Robinson
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, Department for Biomedical Imaging and Image-Guided Therapy, University of Vienna, Vienna, Austria
| | - Kieran O'Brien
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
- Siemens Healthineers Pty Ltd, Bowen Hills, Queensland, Australia
| | - Markus Barth
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
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Fushimi Y, Nakajima S, Sakata A, Okuchi S, Otani S, Nakamoto Y. Value of Quantitative Susceptibility Mapping in Clinical Neuroradiology. J Magn Reson Imaging 2024; 59:1914-1929. [PMID: 37681441 DOI: 10.1002/jmri.29010] [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: 05/31/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/09/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) is a unique technique for providing quantitative information on tissue magnetic susceptibility using phase image data. QSM can provide valuable information regarding physiological and pathological processes such as iron deposition, hemorrhage, calcification, and myelin. QSM has been considered for use as an imaging biomarker to investigate physiological status and pathological changes. Although various studies have investigated the clinical applications of QSM, particularly regarding the use of QSM in clinical practice, have not been examined well. This review provides on an overview of the basics of QSM and its clinical applications in neuroradiology. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoshi Nakajima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Sachi Okuchi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Sayo Otani
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Bilgic B, Costagli M, Chan KS, Duyn J, Langkammer C, Lee J, Li X, Liu C, Marques JP, Milovic C, Robinson SD, Schweser F, Shmueli K, Spincemaille P, Straub S, van Zijl P, Wang Y. Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group. Magn Reson Med 2024; 91:1834-1862. [PMID: 38247051 PMCID: PMC10950544 DOI: 10.1002/mrm.30006] [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: 07/11/2023] [Revised: 10/31/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.
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Affiliation(s)
- Berkin Bilgic
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Mauro Costagli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Kwok-Shing Chan
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jeff Duyn
- Advanced MRI Section, NINDS, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Xu Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Carlos Milovic
- School of Electrical Engineering (EIE), Pontificia Universidad Catolica de Valparaiso, Valparaiso, Chile
| | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, Buffalo, New York, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute at the University at Buffalo, Buffalo, New York, USA
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Pascal Spincemaille
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Sina Straub
- Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA
| | - Peter van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yi Wang
- MRI Research Institute, Departments of Radiology and Biomedical Engineering, Cornell University, New York, New York, USA
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Naji N, Wilman A. Thin slab quantitative susceptibility mapping. Magn Reson Med 2023; 90:2290-2305. [PMID: 37526029 DOI: 10.1002/mrm.29800] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/27/2023] [Accepted: 06/30/2023] [Indexed: 08/02/2023]
Abstract
PURPOSE Susceptibility maps reconstructed from thin slabs may suffer underestimation due to background-field removal imperfections near slab boundaries and the increased difficulty of solving a 3D-inversion problem with reduced support, particularly in the direction of the main magnetic field. Reliable QSM reconstruction from thin slabs would enable focal acquisitions in a much-reduced scan time. METHODS This work proposes using additional rapid low-resolution data of extended spatial coverage to improve background-field estimation and regularize the inversion-to-susceptibility process for high resolution, thin slab data. The new method was tested using simulated and in-vivo brain data of high resolution (0.33 × 0.33 × 0.33 mm3 and 0.54 × 0.54 × 0.65 mm3 , respectively) at 3T, and compared to the standard large volume approach. RESULTS Using the proposed method, in-vivo high-resolution QSM at 3T was obtained from slabs of width as small as 10.4 mm, aided by a lower-resolution dataset of 24 times coarser voxels. Simulations showed that the proposed method produced more consistent measurements from slabs of at least eight slices. Reducing the mean ROI error to 5% required the low-resolution data to cover ˜60 mm in the direction of the main field, have at least 2-mm isotropic resolution that is not coarser than the high-resolution data by more than four-fold in any direction. CONCLUSION Applying the proposed method enabled focal QSM acquisitions at sub-millimeter resolution within reasonable acquisition time.
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Affiliation(s)
- Nashwan Naji
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Alan Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
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Li J, Guan X, Wu Q, He C, Zhang W, Lin X, Liu C, Wei H, Xu X, Zhang Y. Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method. Hum Brain Mapp 2023; 44:3781-3794. [PMID: 37186095 DOI: 10.1002/hbm.26311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/24/2023] [Accepted: 03/30/2023] [Indexed: 05/17/2023] Open
Abstract
The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.
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Affiliation(s)
- Jun Li
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qing Wu
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Chenyu He
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Weimin Zhang
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Xiyue Lin
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, California, USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, California, USA
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuyao Zhang
- School of Information Science and Technology, ShanghaiTech University, Shanghai, China
- Ihuman Institute, ShanghaiTech University, Shanghai, China
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Zhao W, Wang Y, Zhou F, Li G, Wang Z, Zhong H, Song Y, Gillen KM, Wang Y, Yang G, Li J. Automated Segmentation of Midbrain Structures in High-Resolution Susceptibility Maps Based on Convolutional Neural Network and Transfer Learning. Front Neurosci 2022; 16:801618. [PMID: 35221900 PMCID: PMC8866960 DOI: 10.3389/fnins.2022.801618] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 01/17/2022] [Indexed: 11/23/2022] Open
Abstract
Background Accurate delineation of the midbrain nuclei, the red nucleus (RN), substantia nigra (SN) and subthalamic nucleus (STN), is important in neuroimaging studies of neurodegenerative and other diseases. This study aims to segment midbrain structures in high-resolution susceptibility maps using a method based on a convolutional neural network (CNN). Methods The susceptibility maps of 75 subjects were acquired with a voxel size of 0.83 × 0.83 × 0.80 mm3 on a 3T MRI system to distinguish the RN, SN, and STN. A deeply supervised attention U-net was pre-trained with a dataset of 100 subjects containing susceptibility maps with a voxel size of 0.63 × 0.63 × 2.00 mm3 to provide initial weights for the target network. Five-fold cross-validation over the training cohort was used for all the models’ training and selection. The same test cohort was used for the final evaluation of all the models. Dice coefficients were used to assess spatial overlap agreement between manual delineations (ground truth) and automated segmentation. Volume and magnetic susceptibility values in the nuclei extracted with automated CNN delineation were compared to those extracted by manual tracing. Consistencies of volume and magnetic susceptibility values by different extraction strategies were assessed by Pearson correlation coefficients and Bland-Altman analyses. Results The automated CNN segmentation method achieved mean Dice scores of 0.903, 0.864, and 0.777 for the RN, SN, and STN, respectively. There were no significant differences between the achieved Dice scores and the inter-rater Dice scores (p > 0.05 for each nucleus). The overall volume and magnetic susceptibility values of the nuclei extracted by the automatic CNN method were significantly correlated with those by manual delineation (p < 0.01). Conclusion Midbrain structures can be precisely segmented in high-resolution susceptibility maps using a CNN-based method.
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Affiliation(s)
- Weiwei Zhao
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Yida Wang
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Fangfang Zhou
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Gaiying Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Zhichao Wang
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Haodong Zhong
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Yang Song
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Kelly M. Gillen
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
- *Correspondence: Guang Yang,
| | - Jianqi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
- Jianqi Li,
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Jin Z, Wang Y, Jokar M, Li Y, Cheng Z, Liu Y, Tang R, Shi X, Zhang Y, Min J, Liu F, He N, Yan F, Haacke EM. Automatic detection of neuromelanin and iron in the midbrain nuclei using a
magnetic resonance imaging
‐based brain template. Hum Brain Mapp 2022; 43:2011-2025. [PMID: 35072301 PMCID: PMC8933249 DOI: 10.1002/hbm.25770] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/01/2021] [Accepted: 12/22/2021] [Indexed: 12/17/2022] Open
Abstract
Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in‐vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC‐GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC‐GRE sequence was used to find the NM‐rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45–81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine‐tuned the boundaries in the original space using a dynamic programming algorithm to match the details of each individual's NM and iron features. A dual mapping approach was used to improve the performance of the morphological mapping of the midbrain of any given individual to the template space. A threshold approach was used in the NM‐rich region and susceptibility maps to optimize the DICE similarity coefficients and the volume ratios. The results for the NM of the SN as well as the iron containing SN, STN, and RN all indicate a strong agreement with manually drawn structures. The DICE similarity coefficients and volume ratios for these structures were 0.85, 0.87, 0.75, and 0.92 and 0.93, 0.95, 0.89, 1.05, respectively, before applying any threshold on the data. Using this fully automatic template‐based deep gray matter mapping approach, it is possible to accurately measure the tissue properties such as volumes, iron content, and NM content of the midbrain nuclei.
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Affiliation(s)
- Zhijia Jin
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Ying Wang
- SpinTech MRI, Inc. Detroit Michigan USA
- Department of Radiology Wayne State University Detroit Michigan USA
| | | | - Yan Li
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Zenghui Cheng
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Yu Liu
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Rongbiao Tang
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Xiaofeng Shi
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Youmin Zhang
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Jihua Min
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Fangtao Liu
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Naying He
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Ewart Mark Haacke
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
- SpinTech MRI, Inc. Detroit Michigan USA
- Department of Radiology Wayne State University Detroit Michigan USA
- Department of Biomedical Engineering Wayne State University Detroit Michigan USA
- Department of Neurology Wayne State University Detroit Michigan USA
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Asriyants SV, Tomskiy AA, Gamaleya AA, Pronin IN. [Deep brain stimulation of the subthalamic nucleus for parkinson's disease: awake vs asleep]. ZHURNAL VOPROSY NEĬROKHIRURGII IMENI N. N. BURDENKO 2021; 85:117-121. [PMID: 34714012 DOI: 10.17116/neiro202185051117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is known to be an effective and safe neurosurgical procedure for Parkinson's disease (PD). Traditionally, awake implantation of stimulation system is carried out using microelectrode registration and intraoperative stimulation. Development of neuroimaging technologies enables direct STN imaging. Therefore, asleep surgery without additional intraoperative verification is possible. This approach reduces surgery time and can potentially decrease the incidence of hemorrhagic and infectious complications. The advantages of one method or another are being discussed. OBJECTIVE To assess the benefits and limitations of various methods for DBS system implantation for bilateral STN stimulation, to study the issues of stereotaxic accuracy, efficiency and safety of asleep and awake electrode implantation into STN. MATERIAL AND METHODS We reviewed the articles published in the PubMed database. Searching algorithm included the following keywords: «asleep DBS», «Parkinson's disease», «subthalamic nucleus», «3T MRI», «SWI», «SWAN». RESULTS There were 31 articles devoted to asleep DBS of STN including 4 meta-analyses, 3 prospective controlled studies, 13 retrospective controlled studies and 11 studies without a control group. CONCLUSION Asleep implantation of electrodes for DBS of STN can be performed only after a clear imaging of STN boundaries with high-quality MRI.
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Affiliation(s)
| | - A A Tomskiy
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - I N Pronin
- Burdenko Neurosurgical Center, Moscow, Russia
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Visualization of iron-rich subcortical structures in non-human primates in vivo by quantitative susceptibility mapping at 3T MRI. Neuroimage 2021; 241:118429. [PMID: 34311068 DOI: 10.1016/j.neuroimage.2021.118429] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/13/2021] [Accepted: 07/22/2021] [Indexed: 02/06/2023] Open
Abstract
Magnetic resonance imaging (MRI) is now an essential tool in the field of neuroscience involving non-human primates (NHP). Structural MRI scanning using T1-weighted (T1w) or T2-weighted (T2w) images provides anatomical information, particularly for experiments involving deep structures such as the basal ganglia and cerebellum. However, for certain subcortical structures, T1w and T2w image contrasts are insufficient for their detection of important anatomical details. To better visualize such structures in the macaque brain, we applied a relatively new method called quantitative susceptibility mapping (QSM), which enhances tissue contrast based on the local tissue magnetic susceptibility. The QSM significantly improved the visualization of important structures, including the ventral pallidum (VP), globus pallidus external and internal segments (GPe and GPi), substantia nigra (SN), subthalamic nucleus (STN) in the basal ganglia and the dentate nucleus (DN) in the cerebellum. We quantified this the contrast enhancement by systematically comparing of contrast-to-noise ratios (CNRs) of QSM images relative to the corresponding T1w and T2w images. In addition, QSM values of some structures were correlated to the age of the macaque subjects. These results identify the QSM method as a straightforward and useful tool for clearly visualizing details of subcortical structures that are invisible with more traditional scanning sequences.
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10
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Yu K, Ren Z, Yu T, Wang X, Hu Y, Guo S, Li J, Li Y. Direct Targeting of the Anterior Nucleus of the Thalamus via 3 T Quantitative Susceptibility Mapping. Front Neurosci 2021; 15:685050. [PMID: 34290583 PMCID: PMC8287058 DOI: 10.3389/fnins.2021.685050] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 05/17/2021] [Indexed: 12/18/2022] Open
Abstract
Objective: Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a potentially effective, minimally invasive, and reversible method for treating epilepsy. The goal of this study was to explore whether 3 T quantitative susceptibility mapping (QSM) could delineate the ANT from surrounding structures, which is important for the direct targeting of DBS surgery. Methods: We obtained 3 T QSM, T1-weighted (T1w), and T2-weighted (T2w) images from 11 patients with Parkinson’s disease or dystonia who received subthalamic nucleus (STN) or globus pallidus interna (GPi) DBS surgery in our center. The ANT and its surrounding white matter structures on QSM were compared with available atlases. The contrast-to-noise ratios (CNRs) of ANT relative to the external medullary lamina (eml) were compared across the three imaging modalities. Additionally, the morphology and location of the ANT were depicted in the anterior commissure (AC)-posterior commissure (PC)-based system. Results: ANT can be clearly distinguished from the surrounding white matter laminas and appeared hyperintense on QSM. The CNRs of the ANT-eml on QSM, T1w, and T2w images were 10.20 ± 4.23, 1.71 ± 1.03, and 1.35 ± 0.70, respectively. One-way analysis of variance (ANOVA) indicated significant differences in CNRs among QSM, T1w, and T2w imaging modalities [F(2) = 85.28, p < 0.0001]. In addition, both the morphology and location of the ANT were highly variable between patients in the AC–PC-based system. Conclusion: The potential utility of QSM for the visualization of ANTs in clinical imaging is promising and may be suitable for targeting the ANT for DBS to treat epilepsy.
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Affiliation(s)
- Kaijia Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Zhiwei Ren
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Xueyuan Wang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yongsheng Hu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Song Guo
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Jianyu Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yongjie Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital of Capital Medical University, Beijing, China
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11
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Huang W, Ogbuji R, Zhou L, Guo L, Wang Y, Kopell BH. Motoric impairment versus iron deposition gradient in the subthalamic nucleus in Parkinson's disease. J Neurosurg 2021; 135:284-290. [PMID: 32764171 DOI: 10.3171/2020.5.jns201163] [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: 04/09/2020] [Accepted: 05/12/2020] [Indexed: 01/27/2023]
Abstract
OBJECTIVE The objective of this study was to investigate the correlation between the quantitative susceptibility mapping (QSM) signal gradient of the subthalamic nucleus (STN) and motor impairment in patients with Parkinson's disease (PD). METHODS All PD patients who had undergone QSM MRI for presurgical deep brain stimulation (DBS) planning were eligible for inclusion in this study. The entire STN and its three functional subdivisions, as well as the adjacent white matter (WM), were segmented and measured. The QSM value difference between the entire STN and adjacent WM (STN-WM), between the limbic and associative regions of the STN (L-A), and between the associative and motor regions of the STN (A-M) were obtained as measures of gradient and were input into an unsupervised k-means clustering algorithm to automatically categorize the overall boundary distinctness between the STN and adjacent WM and between STN subdivisions (gradient blur [GB] and gradient sharp [GS] groups). Statistical tests were performed to compare clinical and image measurements for discrimination between GB and GS groups. RESULTS Of the 39 study patients, 19 were categorized into the GB group and 20 into the GS group, based on quantitative cluster analysis. The GB group had a significantly higher presurgical off-medication Unified Parkinson's Disease Rating Scale Part III score (51.289 ± 20.741) than the GS group (38.5 ± 16.028; p = 0.037). The GB group had significantly higher QSM values for the STN and its three subdivisions and adjacent WM than those for the GS group (p < 0.01). The GB group also demonstrated a significantly higher STN-WM gradient in the right STN (p = 0.01). The GB group demonstrated a significantly lower L-A gradient in both the left and the right STN (p < 0.02). CONCLUSIONS Advancing PD with more severe motor impairment leads to more iron deposition in the STN and adjacent WM, as shown in the QSM signal. Loss of the STN inner QSM signal gradient should be considered as an image marker for more severe motor impairment in PD patients.
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Affiliation(s)
- Weiyuan Huang
- 1Department of Radiology, Weill Medical College of Cornell University, New York
- 7Department of Radiology, Hainan General Hospital (Affiliated Hainan Hospital of Hainan Medical University), Haikou City, People's Republic of China
| | | | - Liangdong Zhou
- 1Department of Radiology, Weill Medical College of Cornell University, New York
| | - Lingfei Guo
- 1Department of Radiology, Weill Medical College of Cornell University, New York
| | - Yi Wang
- 1Department of Radiology, Weill Medical College of Cornell University, New York
- 6Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York; and
| | - Brian H Kopell
- Departments of2Neurosurgery
- 3Neurology
- 4Psychiatry, and
- 5Neuroscience, Icahn School of Medicine at Mount Sinai, New York
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12
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Wen Y, Spincemaille P, Nguyen T, Cho J, Kovanlikaya I, Anderson J, Wu G, Yang B, Fung M, Li K, Kelley D, Benhamo N, Wang Y. Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping. Magn Reson Med 2021; 86:2165-2178. [PMID: 34028868 DOI: 10.1002/mrm.28814] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 02/20/2021] [Accepted: 03/28/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE Typical quantitative susceptibility mapping (QSM) reconstruction steps consist of first estimating the magnetization field from the gradient-echo images, and then reconstructing the susceptibility map from the estimated field. The errors from the field-estimation steps may propagate into the final QSM map, and the noise in the estimated field map may no longer be zero-mean Gaussian noise, thus, causing streaking artifacts in the resulting QSM. A multiecho complex total field inversion (mcTFI) method was developed to compute the susceptibility map directly from the multiecho gradient echo images using an improved signal model that retains the Gaussian noise property in the complex domain. It showed improvements in QSM reconstruction over the conventional field-to-source inversion. METHODS The proposed mcTFI method was compared with the nonlinear total field inversion (nTFI) method in a numerical brain with hemorrhage and calcification, the numerical brains provided by the QSM Challenge 2.0, 18 brains with intracerebral hemorrhage scanned at 3T, and 6 healthy brains scanned at 7T. RESULTS Compared with nTFI, the proposed mcTFI showed more accurate QSM reconstruction around the lesions in the numerical simulations. The mcTFI reconstructed QSM also showed the best image quality with the least artifacts in the brains with intracerebral hemorrhage scanned at 3T and healthy brains scanned at 7T. CONCLUSION The proposed multiecho complex total field inversion improved QSM reconstruction over traditional field-to-source inversion through better signal modeling.
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Affiliation(s)
- Yan Wen
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | | | - Thanh Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Junghun Cho
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | | | - Gaohong Wu
- General Electrical Healthcare, Waukesha, Wisconsin, USA
| | - Baolian Yang
- General Electrical Healthcare, Waukesha, Wisconsin, USA
| | - Maggie Fung
- General Electrical Healthcare, Waukesha, Wisconsin, USA
| | - Ke Li
- General Electrical Healthcare, Waukesha, Wisconsin, USA
| | | | | | - Yi Wang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.,Department of Radiology, Weill Cornell Medicine, New York, New York, USA
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13
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Direct visualization of deep brain stimulation targets in patients with Parkinson's disease via 3-T quantitative susceptibility mapping. Acta Neurochir (Wien) 2021; 163:1335-1345. [PMID: 33576911 DOI: 10.1007/s00701-021-04715-4] [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: 10/22/2020] [Accepted: 01/11/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND The direct visualization of brain nuclei on magnetic resonance (MR) images is important for target localization during deep brain stimulation (DBS) in patients with Parkinson's disease (PD). We demonstrated the superiority of 3-T high-resolution submillimeter voxel size quantitative susceptibility mapping (QSM) for delineating the subthalamic nucleus (STN) and the globus pallidus internus (GPi). METHODS Preoperative 3-T QSM and T2 weighted (T2w) images were obtained from ten patients with PD. Qualitative visualization scores were analyzed by two neurosurgeons on both images using a 4-point and 5-point scale, respectively. Images were also compared with regard to contrast-to-noise ratios (CNRs) and edge detection power for the STN and GPi. The Wilcoxon rank-sum test and the signed-rank test were used to compare measurements between the two images. RESULTS Visualization scores for the STN and GPi, the mean CNR of the STN relative to the zona incerta (ZI) and the substantia nigra, and the mean CNR of the GPi relative to the internal capsule (IC) and the globus pallidum externum, were significantly higher on QSM images than on T2w images (P < 0.01). The edge detection powers of the STN-ZI and GPi-IC on QSM were significantly larger (by 2.6- and 3.8-fold, respectively) than those on T2w images (P < 0.01). QSM detected asymmetry of the STN in two patients. CONCLUSIONS QSM images provided improved delineation ability for the STN and GPi when compared to T2w images. Our findings are important for patients with PD who undergo DBS surgery, particularly those with asymmetric bilateral nuclei.
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14
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Cho SJ, Bae YJ, Kim JM, Kim HJ, Baik SH, Sunwoo L, Choi BS, Jung C, Kim JH. Iron-sensitive magnetic resonance imaging in Parkinson's disease: a systematic review and meta-analysis. J Neurol 2021; 268:4721-4736. [PMID: 33914142 DOI: 10.1007/s00415-021-10582-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 04/23/2021] [Accepted: 04/24/2021] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To evaluate the diagnostic performance of iron-sensitive sequences targeting the substantia nigra for distinguishing patients with Parkinson's disease from control participants and to identify factors causing heterogeneity. METHODS A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies reporting the relevant topic before March 6, 2020. The pooled sensitivity and specificity values with their 95% confidence intervals were calculated using bivariate random-effects modeling. Subgroup and meta-regression analyses were also performed to determine factors influencing heterogeneity affecting the diagnostic performance among the clinical, MRI, and analytic characteristics. RESULTS A total of 22 articles including 1126 patients with Parkinson's disease and 933 control participants were enrolled in this systematic review and meta-analysis. Of those, 12 studies used objective analyses of quantitative susceptibility measurements, and 10 visually assessed the nigrosome-1 in subjective analyses. Iron-sensitive nigral magnetic resonance imaging showed a pooled sensitivity of 92% (95% confidence interval 88-95%) and a pooled specificity of 90% (95% confidence interval 81-95%). According to subgroup and meta-regression analyses, a longer mean disease duration in patients with Parkinson's disease (≥ 5 years), subjective analysis, a smaller size of pixel (< 0.6 mm2), a larger flip angle (> 15°), a smaller slice thickness (≤ 1 mm), and specific targeting of the substantia nigra pars compacta improved the diagnostic performance. CONCLUSION Iron-sensitive nigral magnetic resonance imaging had a favorable diagnostic performance in discriminating patients with Parkinson's disease from control participants. Subjective analytic methods remain superior to objective approaches. Further improvements of the spatial resolution and contrast-to-noise ratio to specifically target the nigrosome-1 with objective analytic methods will be needed.
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Affiliation(s)
- Se Jin Cho
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam, Gyeonggi, 13620, Republic of Korea
| | - 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, Gyeonggi, 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, Gyeonggi, 13620, Republic of Korea
| | - Hyun Jin Kim
- Department of Radiology, Daejin Medical Center, Bundang Jesaeng General Hospital, Seongnam, Gyeonggi, Republic of Korea
| | - Sung Hyun Baik
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam, Gyeonggi, 13620, Republic of Korea
| | - Leonard Sunwoo
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam, Gyeonggi, 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, Gyeonggi, 13620, Republic of Korea
| | - Cheolkyu Jung
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam, Gyeonggi, 13620, 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, Gyeonggi, 13620, Republic of Korea
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15
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Gillen KM, Mubarak M, Park C, Ponath G, Zhang S, Dimov A, Levine‐Ritterman M, Toro S, Huang W, Amici S, Kaunzner UW, Gauthier SA, Guerau‐de‐Arellano M, Wang Y, Nguyen TD, Pitt D. QSM is an imaging biomarker for chronic glial activation in multiple sclerosis lesions. Ann Clin Transl Neurol 2021; 8:877-886. [PMID: 33704933 PMCID: PMC8045922 DOI: 10.1002/acn3.51338] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 02/18/2021] [Accepted: 02/22/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Inflammation in chronic active lesions occurs behind a closed blood-brain barrier and cannot be detected with MRI. Activated microglia are highly enriched for iron and can be visualized with quantitative susceptibility mapping (QSM), an MRI technique used to delineate iron. OBJECTIVE To characterize the histopathological correlates of different QSM hyperintensity patterns in MS lesions. METHODS MS brain slabs were imaged with MRI and QSM, and processed for histology. Immunolabeled cells were quantified in the lesion rim, center, and adjacent normal-appearing white matter (NAWM). Iron+ myeloid cell densities at the rims were correlated with susceptibilities. Human-induced pluripotent stem cell (iPSC)-derived microglia were used to determine the effect of iron on the production of reactive oxygen species (ROS) and pro-inflammatory cytokines. RESULTS QSM hyperintensity at the lesion perimeter correlated with activated iron+ myeloid cells in the rim and NAWM. Lesions with high punctate or homogenous QSM signal contained no or minimally activated iron- myeloid cells. In vitro, iron accumulation was highest in M1-polarized human iPSC-derived microglia, but it did not enhance ROS or cytokine production. CONCLUSION A high QSM signal outlining the lesion rim but not punctate signal in the center is a biomarker for chronic inflammation in white matter lesions.
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Affiliation(s)
- Kelly M. Gillen
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Mayyan Mubarak
- Department of NeurologyYale School of MedicineNew HavenConnecticutUSA
| | - Calvin Park
- Department of NeurologyYale School of MedicineNew HavenConnecticutUSA
| | - Gerald Ponath
- Department of NeurologyYale School of MedicineNew HavenConnecticutUSA
| | - Shun Zhang
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Alexey Dimov
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | | | - Steven Toro
- Department of NeurologyYale School of MedicineNew HavenConnecticutUSA
| | - Weiyuan Huang
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Stephanie Amici
- Department of NeuroscienceThe Ohio State UniversityColumbusOhioUSA
| | | | - Susan A. Gauthier
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA,Department of NeurologyWeill Cornell MedicineNew YorkNew YorkUSA
| | | | - Yi Wang
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Thanh D. Nguyen
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - David Pitt
- Department of NeurologyYale School of MedicineNew HavenConnecticutUSA
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16
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Wei H, Zhang C, Wang T, He N, Li D, Zhang Y, Liu C, Yan F, Sun B. Precise targeting of the globus pallidus internus with quantitative susceptibility mapping for deep brain stimulation surgery. J Neurosurg 2020; 133:1605-1611. [PMID: 31604332 DOI: 10.3171/2019.7.jns191254] [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: 05/07/2019] [Accepted: 07/09/2019] [Indexed: 01/02/2023]
Abstract
OBJECTIVE The goal of this study was to demonstrate the use of quantitative susceptibility mapping (QSM)-based images to precisely localize the globus pallidus internus (GPi) for deep brain stimulation (DBS) planning and to enhance postsurgical visualization of the DBS lead positions. METHODS Presurgical T1-weighted (T1w), T2-weighted (T2w), and QSM images as well as postsurgical CT images were obtained in 29 patients with Parkinson's disease. To enhance the contrast within the GP, a hybrid contrast was created by linearly combining T1w and QSM images. Contrast-to-noise ratios (CNRs) of the GPi on T1w, T2w, QSM, and hybrid images were compared. The CNR differences were tested using the 1-way ANOVA method. The visualization of the DBS lead position was demonstrated by merging the postsurgical CT with presurgical MR images. RESULTS The hybrid images yield the best CNRs for GPi depiction and the visualization of the postsurgical DBS lead position was significantly improved. CONCLUSIONS QSM-based images allow for confident localization of borders of the GPi that is superior to T1w and T2w images. High-contrast hybrid images can be used for precisely directed DBS targeting, e.g., GPi DBS for the treatment of advanced Parkinson's disease.
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Affiliation(s)
- Hongjiang Wei
- 1Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University
| | - Chencheng Zhang
- 2Department of Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University
| | - Tao Wang
- 2Department of Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University
| | - Naying He
- 3Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University
| | - Dianyou Li
- 2Department of Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University
| | - Yuyao Zhang
- 4School of Information and Science and Technology, Shanghai Tech University, Shanghai, China
| | - Chunlei Liu
- 5Department of Electrical Engineering and Computer Sciences, University of California, Berkeley; and
- 6Helen Wills Neuroscience Institute, University of California, Berkeley, California
| | - Fuhua Yan
- 3Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University
| | - Bomin Sun
- 2Department of Functional Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University
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17
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Magnetic resonance-guided focused ultrasound for movement disorders: clinical and neuroimaging advances. Curr Opin Neurol 2020; 33:488-497. [DOI: 10.1097/wco.0000000000000840] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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18
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Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery. Curr Neurol Neurosci Rep 2019; 19:42. [DOI: 10.1007/s11910-019-0961-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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