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Taleb S, Varela-Mattatall G, Allen A, Haast R, Khan AR, Kalia V, Howard JL, MacDonald SJ, Menon RS, Lanting BA, Teeter MG. Assessing brain integrity in patients with long-term and well-functioning metal-based hip implants. J Orthop Res 2024; 42:1292-1302. [PMID: 38235918 DOI: 10.1002/jor.25785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/08/2023] [Accepted: 01/03/2024] [Indexed: 01/19/2024]
Abstract
Production of metal debris from implant wear and corrosion processes is now a well understood occurrence following hip arthroplasty. Evidence has shown that metal ions can enter the bloodstream and travel to distant organs including the brain, and in extreme cases, can induce sensorial and neurological diseases. Our objective was tosimultaneously analyze brain anatomy and physiology in patients with long-term and well-functioning implants. Included were subjects who had received total hip or hip resurfacing arthroplastywith an implantation time of a minimum of 7 years (n = 28) and age- and sex-matched controls (n = 32). Blood samples were obtained to measure ion concentrations of cobalt and chromium, and the Montreal Cognitive Assessment was performed. 3T MRI brain scans were completed with an MPRAGE sequence for ROI segmentation and multiecho gradient echo sequences to generate QSM and R2* maps. Mean QSM and R2* values were recorded for five deep brain and four middle and cortical brain structures on both hemispheres: pallidum, putamen, caudate, amygdala, hippocampus, anterior cingulate, inferior temporal, and cerebellum. No differences in QSM or R2* or cognition scores were found between both groups (p > 0.6654). No correlation was found between susceptibility and blood ion levels for cobalt or chromium in any region of the brain. No correlation was found between blood ion levels and cognition scores. Clinical significance: Results suggest that metal ions released by long-term and well-functioning implants do not affect brain integrity.
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Affiliation(s)
- Shahnaz Taleb
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Gabriel Varela-Mattatall
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Abbigail Allen
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Roy Haast
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Ali R Khan
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Vishal Kalia
- Department of Medical Imaging, Schulich School of Medicine & Dentistry, Division of Musculoskeletal Imaging, Western University, London, Ontario, Canada
| | - James L Howard
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Steven J MacDonald
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Ravi S Menon
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Brent A Lanting
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Matthew G Teeter
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
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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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Martinez JA, Yu VY, Tringale KR, Otazo R, Cohen O. Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain. Magn Reson Imaging 2024; 109:147-157. [PMID: 38513790 PMCID: PMC11042874 DOI: 10.1016/j.mri.2024.03.023] [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: 12/01/2023] [Revised: 03/15/2024] [Accepted: 03/16/2024] [Indexed: 03/23/2024]
Abstract
INTRODUCTION This study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM). METHODS Data were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences. RESULTS Total scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values. CONCLUSION The PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.
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Affiliation(s)
- Jessica A Martinez
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065, NY, USA.
| | - Victoria Y Yu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065, NY, USA
| | - Kathryn R Tringale
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York 10065, NY, USA
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065, NY, USA
| | - Ouri Cohen
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065, NY, USA
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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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Paluru N, Susan Mathew R, Yalavarthy PK. DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain. NMR IN BIOMEDICINE 2024:e5163. [PMID: 38649140 DOI: 10.1002/nbm.5163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/22/2024] [Accepted: 03/11/2024] [Indexed: 04/25/2024]
Abstract
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susceptibility distribution from the measured local field obtained from the MR phase. Although existing deep learning based QSM methods can produce high-quality reconstruction, they are highly biased toward training data distribution with less scope for generalizability. This work proposes a hybrid two-step reconstruction approach to improve deep learning based QSM reconstruction. The susceptibility map prediction obtained from the deep learning methods has been refined in the framework developed in this work to ensure consistency with the measured local field. The developed method was validated on existing deep learning and model-based deep learning methods for susceptibility mapping of the brain. The developed method resulted in improved reconstruction for MRI volumes obtained with different acquisition settings, including deep learning models trained on constrained (limited) data settings.
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Affiliation(s)
- Naveen Paluru
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, India
| | - Raji Susan Mathew
- School of Data Science, Indian Institute of Science Education and Research, Thiruvananthapuram, Kerala, India
| | - Phaneendra K Yalavarthy
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, India
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Ebrahimpour A, Khoobi M, Riyahi Alam N, Masoumbeigi M, Tirgar F, Ebrahimi T. Reliable differentiation of necrosis and active metabolically contours of glioblastoma multiforme using susceptibility-based imaging. Heliyon 2024; 10:e28355. [PMID: 38571593 PMCID: PMC10987993 DOI: 10.1016/j.heliyon.2024.e28355] [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: 09/27/2023] [Revised: 03/16/2024] [Accepted: 03/17/2024] [Indexed: 04/05/2024] Open
Abstract
Purpose Gadolinium-enhancing necrosis in glioblastoma multiforme (GBM), as an occasionally occurring false positive in contrast enhancement (CE) imaging, leads to trouble for segmentation of GBM and treatment. Therefore, the investigation of complementary detection way to identify the metabolically active volume of the tumor with high reliability is very worth to be addressed. Here, we reported on a case of GBM with gadolinium-enhancing necrosis in an experimental CE imaging study in mice and evaluated the discrimination of the necrosis and metabolically active parts of the GBM using conventional and state-of-the-art susceptibility-based MRI. Methods In this study, following 5-aminolevulinic acid (ALA) and iron supplements (FAC, 6 h after ALA, intra-tumoral injection) to animal, T2*-W imaging and quantitative susceptibility mapping (QSM) were performed, and compared with CE imaging. Results The signal intensity (SI) of the active and necrosis areas of the case in the CE image demonstrated no significant difference while the SI on the T2*-W images and susceptibility value in QSM changed 24 and 150%, respectively. Conclusion The preclinical case report provides valuable insights into the potential of susceptibility-based MRI using ALA + FAC to apply as a robust discriminator between necrotic and viable tumors.
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Affiliation(s)
- Anita Ebrahimpour
- Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mehdi Khoobi
- Department of Medicinal Chemistry, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
| | - Nader Riyahi Alam
- Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahboubeh Masoumbeigi
- Department of Radiology, Faculty of Para-Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Fatemeh Tirgar
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Tayyebeh Ebrahimi
- Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
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7
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Mohammadi S, Ghaderi S. Parkinson's disease and Parkinsonism syndromes: Evaluating iron deposition in the putamen using magnetic susceptibility MRI techniques - A systematic review and literature analysis. Heliyon 2024; 10:e27950. [PMID: 38689949 PMCID: PMC11059419 DOI: 10.1016/j.heliyon.2024.e27950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 02/29/2024] [Accepted: 03/08/2024] [Indexed: 05/02/2024] Open
Abstract
Magnetic resonance imaging (MRI) techniques, such as quantitative susceptibility mapping (QSM) and susceptibility-weighted imaging (SWI), can detect iron deposition in the brain. Iron accumulation in the putamen (PUT) can contribute to the pathogenesis of Parkinson's disease (PD) and atypical Parkinsonian disorders. This systematic review aimed to synthesize evidence on iron deposition in the PUT assessed by MRI susceptibility techniques in PD and Parkinsonism syndromes. The PubMed and Scopus databases were searched for relevant studies. Thirty-four studies from January 2007 to October 2023 that used QSM, SWI, or other MRI susceptibility methods to measure putaminal iron in PD, progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and healthy controls (HCs) were included. Most studies have found increased putaminal iron levels in PD patients versus HCs based on higher quantitative susceptibility. Putaminal iron accumulation correlates with worse motor scores and cognitive decline in patients with PD. Evidence regarding differences in susceptibility between PD and atypical Parkinsonism is emerging, with several studies showing greater putaminal iron deposition in PSP and MSA than in PD patients. Alterations in putaminal iron levels help to distinguish these disorders from PD. Increased putaminal iron levels appear to be associated with increased disease severity and progression. Thus, magnetic susceptibility MRI techniques can detect abnormal iron accumulation in the PUT of patients with Parkinsonism. Moreover, quantifying putaminal susceptibility may serve as an MRI biomarker to monitor motor and cognitive changes in PD and aid in the differential diagnosis of Parkinsonian disorders.
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Affiliation(s)
- Sana Mohammadi
- Department of Medical Sciences, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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8
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Yang J, Lv M, Han L, Li Y, Liu Y, Guo H, Feng H, Wu Y, Zhong J. Evaluation of brain iron deposition in different cerebral arteries of acute ischaemic stroke patients using quantitative susceptibility mapping. Clin Radiol 2024; 79:e592-e598. [PMID: 38320942 DOI: 10.1016/j.crad.2024.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 12/05/2023] [Accepted: 01/03/2024] [Indexed: 02/08/2024]
Abstract
AIM To investigate differences in iron deposition between infarct and normal cerebral arterial regions in acute ischaemic stroke (AIS) patients using quantitative susceptibility mapping (QSM). MATERIALS AND METHODS Forty healthy controls and 40 AIS patients were recruited, and their QSM images were obtained. There were seven regions of interest (ROIs) in AIS patients, including the infarct regions of responsible arteries (R1), the non-infarct regions of responsible arteries (R2), the contralateral symmetrical sites of lesions (R3), and the non-responsible cerebral arterial regions (R4, R5, R6, R7). For the healthy controls, the cerebral arterial regions corresponding to the AIS patient group were selected as ROIs. The differences in corresponding ROI susceptibilities between AIS patients and healthy controls and the differences in susceptibilities between infarcted and non-infarct regions in AIS patients were compared. RESULTS The susceptibilities of infarct regions in AIS patients were significantly higher than those in healthy controls (p<0.0001). There was no significant difference in non-infarct regions between the two groups (p>0.05). The susceptibility of the infarct regions in AIS patients was significantly higher than those of the non-infarct region of responsible artery and non-responsible cerebral arterial regions (p<0.01). CONCLUSIONS Abnormal iron deposition detected by QSM in the infarct regions of AIS patients may not affect iron levels in the non-infarct regions of responsible arteries and normal cerebral arteries, which may open the door for potential new diagnostic and treatment strategies.
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Affiliation(s)
- J Yang
- Department of Radiology, Zigong First People's Hospital, Zigong, China
| | - M Lv
- Department of Radiology, Zigong First People's Hospital, Zigong, China
| | - L Han
- North Sichuan Medical College, Nanchong, China
| | - Y Li
- Department of Radiology, Zigong First People's Hospital, Zigong, China
| | - Y Liu
- Department of Radiology, Zigong First People's Hospital, Zigong, China
| | - H Guo
- Department of Radiology, Zigong First People's Hospital, Zigong, China
| | - H Feng
- Department of Radiology, Zigong First People's Hospital, Zigong, China
| | - Y Wu
- MR Scientific Marketing, SIEMENS Healthineers Ltd., Shanghai, China
| | - J Zhong
- Department of Radiology, Zigong First People's Hospital, Zigong, China.
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9
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Roberts AG, Romano DJ, Şişman M, Dimov AV, Nguyen TD, Kovanlikaya I, Gauthier SA, Wang Y, Spincemaille P. Maximum spherical mean value filtering for whole-brain QSM. Magn Reson Med 2024; 91:1586-1597. [PMID: 38169132 DOI: 10.1002/mrm.29963] [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: 04/21/2023] [Revised: 10/30/2023] [Accepted: 11/19/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To develop a tissue field-filtering algorithm, called maximum spherical mean value (mSMV), for reducing shadow artifacts in QSM of the brain without requiring brain-tissue erosion. THEORY AND METHODS Residual background field is a major source of shadow artifacts in QSM. The mSMV algorithm filters large field-magnitude values near the border, where the maximum value of the harmonic background field is located. The effectiveness of mSMV for artifact removal was evaluated by comparing existing QSM algorithms in numerical brain simulation as well as using in vivo human data acquired from 11 healthy volunteers and 93 patients. RESULTS Numerical simulation showed that mSMV reduces shadow artifacts and improves QSM accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter and higher QSM image quality score, was also observed in healthy subjects and in patients with hemorrhages, stroke, and multiple sclerosis. CONCLUSION The mSMV algorithm allows QSM maps that are substantially equivalent to those obtained using SMV-filtered dipole inversion without eroding the volume of interest.
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Affiliation(s)
- Alexandra G Roberts
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Dominick J Romano
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Mert Şişman
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Alexey V Dimov
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Susan A Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Yi Wang
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
- Department of Radiology, Weill Cornell Medicine, New York, New York, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA
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De A, Grenier J, Wilman AH. Simultaneous time-of-flight MR angiography and quantitative susceptibility mapping with key time-of-flight features. NMR IN BIOMEDICINE 2024; 37:e5079. [PMID: 38054247 DOI: 10.1002/nbm.5079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 10/30/2023] [Accepted: 11/05/2023] [Indexed: 12/07/2023]
Abstract
A technique for combined time-of-flight (TOF) MR angiography (MRA) and quantitative susceptibility mapping (QSM) was developed with key features of standard three-dimensional (3D) TOF acquisitions, including multiple overlapping thin slab acquisition (MOTSA), ramped RF excitation, and venous saturation. The developed triple-echo 3D TOF-QSM sequence enabled TOF-MRA, susceptibility-weighted imaging (SWI), QSM, and R2* mapping. The effects of ramped RF, resolution, flip angle, venous saturation, and MOTSA were studied on QSM. Six volunteers were scanned at 3 T with the developed sequence, conventional TOF-MRA, and conventional SWI. Quantitative comparison of susceptibility values on QSM and normalized arterial and venous vessel-to-background contrasts on TOF and SWI were performed. The ramped RF excitation created an inherent phase variation in the raw phase. A generic correction factor was computed to remove the phase variation to obtain QSM without artifacts from the TOF-QSM sequence. No statistically significant difference was observed between the developed and standard QSM sequence for susceptibility values. However, maintaining standard TOF features led to compromises in signal-to-noise ratio for QSM and SWI, arising from the use of MOTSA rather than one large 3D slab, higher TOF spatial resolution, increased TOF background suppression due to larger flip angles, and reduced venous signal from venous saturation. In terms of vessel contrast, veins showed higher normalized contrast on SWI derived from TOF-QSM than the standard SWI sequence. While fast flowing arteries had reduced contrast compared with standard TOF-MRA, no statistical difference was observed for slow flowing arteries. Arterial contrast differences largely arise from the longer TR used in TOF-QSM over standard TOF-MRA to accommodate additional later echoes for SWI. In conclusion, although the sequence has a longer TR and slightly lower arterial contrast, provided an adequate correction is made for ramped RF excitation effects on phase, QSM may be performed from a multiecho sequence that includes all key TOF features, thus enabling simultaneous TOF-MRA, SWI, QSM, and R2* map computation.
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Affiliation(s)
- Ashmita De
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Justin Grenier
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Canada
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Liu M, Zhao S, Chen Z. Interscanner reproducibility of volumetric quantitative susceptibility mapping about cerebral subcortical gray nuclei at different MR vendors with the same magnetic strength. Brain Behav 2024; 14:e3473. [PMID: 38594225 PMCID: PMC11004039 DOI: 10.1002/brb3.3473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 03/05/2024] [Accepted: 03/16/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND AND PURPOSE Quantitative susceptibility mapping (QSM) technique was a new quantitative magnetic resonance imaging technique to evaluate the cerebral iron deposition in clinical practice. The current study was aimed to investigate the reproducibility of the volumetric susceptibility value of the subcortical gray nuclei at two different MR vendor with the same magnetic strength. METHODS Cerebral magnitude and phase images of 21 normal subjects were acquired from a 3D multiecho enhanced gradient recalled echo sequence at two different 3.0T MR scanner, and then the magnetic susceptibility images were generated by STI software. The brain structural images were coregistered with magnitude images and generated the normalized parameters, and then generated the normalized susceptibility images. The subcortical gray nuclei template was applied to extract the volumetric susceptibility value of the target nuclei. RESULTS ICC value (95% CI) of the caudate, putamen and GP were 0.847 (0.660-0.935), 0.848 (0.663-0.935) and 0.838 (0.643-0.931), respectively. The ICC value of the thalamus was 0.474 (0.064-0.747). Ninety-five point two percent (20/21) of the difference points of the susceptibility located between the 95% LA for the caudate at the two different 3.0T MR scanner, while the less than 95% of the difference points of the susceptibility value located between the 95% LA for the putamen, globus pallidus and thalamus. CONCLUSION The current study identified that the caudate had the stable reproducibility of the magnetic susceptibility value, and the other basal ganglion nuclei should be cautious for the quantitative evaluation of the magnetic susceptibility value at different 3.0T MR scanner.
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Affiliation(s)
- Mengqi Liu
- Department of RadiologyHainan Hospital of PLA General HospitalSanyaChina
- Department of RadiologyFirst Medical Center of PLA General HospitalBeijingChina
| | - Shuqiang Zhao
- Department of RadiologyHainan Hospital of PLA General HospitalSanyaChina
| | - Zhiye Chen
- Department of RadiologyHainan Hospital of PLA General HospitalSanyaChina
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12
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Silva NA, Barrios-Martinez J, Yeh FC, Hodaie M, Roque D, Boerwinkle VL, Krishna V. Diffusion and functional MRI in surgical neuromodulation. Neurotherapeutics 2024; 21:e00364. [PMID: 38669936 PMCID: PMC11064589 DOI: 10.1016/j.neurot.2024.e00364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Surgical neuromodulation has witnessed significant progress in recent decades. Notably, deep brain stimulation (DBS), delivered precisely within therapeutic targets, has revolutionized the treatment of medication-refractory movement disorders and is now expanding for refractory psychiatric disorders, refractory epilepsy, and post-stroke motor recovery. In parallel, the advent of incisionless treatment with focused ultrasound ablation (FUSA) can offer patients life-changing symptomatic relief. Recent research has underscored the potential to further optimize DBS and FUSA outcomes by conceptualizing the therapeutic targets as critical nodes embedded within specific brain networks instead of strictly anatomical structures. This paradigm shift was facilitated by integrating two imaging modalities used regularly in brain connectomics research: diffusion MRI (dMRI) and functional MRI (fMRI). These advanced imaging techniques have helped optimize the targeting and programming techniques of surgical neuromodulation, all while holding immense promise for investigations into treating other neurological and psychiatric conditions. This review aims to provide a fundamental background of advanced imaging for clinicians and scientists, exploring the synergy between current and future approaches to neuromodulation as they relate to dMRI and fMRI capabilities. Focused research in this area is required to optimize existing, functional neurosurgical treatments while serving to build an investigative infrastructure to unlock novel targets to alleviate the burden of other neurological and psychiatric disorders.
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Affiliation(s)
- Nicole A Silva
- Department of Neurological Surgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA
| | | | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mojgan Hodaie
- Division of Neurosurgery, University of Toronto, Toronto, Canada
| | - Daniel Roque
- Department of Neurology, University of North Carolina in Chapel Hill, NC, USA
| | - Varina L Boerwinkle
- Department of Neurology, University of North Carolina in Chapel Hill, NC, USA
| | - Vibhor Krishna
- Department of Neurological Surgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.
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13
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Wang M, Yang X, Liu D, Dang P, Huang X, Zheng J, Ding F, Ding X, Wang X. Altered brain iron deposition in patients with minimal hepatic encephalopathy: an MRI quantitative susceptibility mapping study. Clin Radiol 2024; 79:e369-e375. [PMID: 38071103 DOI: 10.1016/j.crad.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/08/2023] [Accepted: 11/06/2023] [Indexed: 02/15/2024]
Abstract
AIM To explore the use of quantitative susceptibility mapping (QSM) in assessing changes in brain iron deposits and their association with cognitive function in patients with minimal hepatic encephalopathy (MHE). MATERIALS AND METHODS The study cohort comprised 27 cases with hepatitis B-associated cirrhosis with MHE (MHE group), 25 with hepatitis B-associated cirrhosis without MHE (NMHE group), and 25 healthy controls (HC group). Iron deposits in the bilateral frontal white matter, caudate nucleus (CN), putamen, globus pallidus, thalamus, red nucleus, substantia nigra (SN), hippocampus, and dentate nucleus were measured by QSM. The associations between iron deposition with the time taken to complete number connection tests A (NCT-A) and the score on digital-symbol test (DST) were analysed. RESULTS Susceptibility values differed significantly in the bilateral CN, left thalamus, right SN, and left hippocampus in the MHE group compared with the other groups and were positively associated with the times taken to complete the NCT-A in the bilateral CN, left thalamus, and right SN and negatively associated with DST scores in the bilateral CN, left TH, and left HP. CONCLUSION Reduced cognitive function in MHE patients was significantly associated with abnormally increased iron deposition in certain brain areas. The quantification of brain iron deposition by QSM may thus be an objective and accurate means of evaluating MHE.
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Affiliation(s)
- M Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - X Yang
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, China
| | - D Liu
- Department of Traditional Chinese Medicine Orthopedics and Traumatology, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - P Dang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - X Huang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - J Zheng
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, China
| | - F Ding
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - X Ding
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - X Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750004, China.
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14
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Northall A, Doehler J, Weber M, Tellez I, Petri S, Prudlo J, Vielhaber S, Schreiber S, Kuehn E. Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis. Brain 2024; 147:1087-1099. [PMID: 37815224 PMCID: PMC10907094 DOI: 10.1093/brain/awad351] [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: 06/28/2023] [Revised: 09/01/2023] [Accepted: 09/24/2023] [Indexed: 10/11/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.
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Affiliation(s)
- Alicia Northall
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - Miriam Weber
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
| | - Igor Tellez
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
| | - Susanne Petri
- Department of Neurology, Hannover Medical School (MHH), Hanover 30625, Germany
| | - Johannes Prudlo
- Department of Neurology, Rostock University Medical Centre, Rostock 18147, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock 18147, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
- Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg 39120, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen 72076, Germany
- Hertie Institute for Clinical Brain Research (HIH), Tübingen 72076, Germany
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15
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Ghaderi S, Mohammadi S, Nezhad NJ, Karami S, Sayehmiri F. Iron quantification in basal ganglia: quantitative susceptibility mapping as a potential biomarker for Alzheimer's disease - a systematic review and meta-analysis. Front Neurosci 2024; 18:1338891. [PMID: 38469572 PMCID: PMC10925682 DOI: 10.3389/fnins.2024.1338891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 02/13/2024] [Indexed: 03/13/2024] Open
Abstract
Introduction Alzheimer's disease (AD), characterized by distinctive pathologies such as amyloid-β plaques and tau tangles, also involves deregulation of iron homeostasis, which may accelerate neurodegeneration. This meta-analysis evaluated the use of quantitative susceptibility mapping (QSM) to detect iron accumulation in the deep gray matter (DGM) of the basal ganglia in AD, contributing to a better understanding of AD progression, and potentially leading to new diagnostic and therapeutic approaches. Methods Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the PubMed, Scopus, Web of Sciences, and Google Scholar databases up to October 2023 for studies employing QSM in AD research. Eligibility criteria were based on the PECO framework, and we included studies assessing alterations in magnetic susceptibility indicative of iron accumulation in the DGM of patients with AD. After initial screening and quality assessment using the Newcastle-Ottawa Scale, a meta-analysis was conducted to compare iron levels between patients with AD and healthy controls (HCs) using a random-effects model. Results The meta-analysis included nine studies comprising 267 patients with AD and 272 HCs. There were significantly higher QSM values, indicating greater iron deposition, in the putamen (standardized mean difference (SMD) = 1.23; 95% CI: 0.62 to 1.84; p = 0.00), globus pallidus (SMD = 0.79; 95% CI: 0.07 to 1.52; p = 0.03), and caudate nucleus (SMD = 0.72; 95% CI: 0.39 to 1.06; p = 0.00) of AD patients compared to HCs. However, no significant differences were found in the thalamus (SMD = 1.00; 95% CI: -0.42 to 2.43; p = 0.17). The sensitivity analysis indicated that no single study impacted the overall results. Age was identified as a major contributor to heterogeneity across all basal ganglia nuclei in subgroup analysis. Older age (>69 years) and lower male percentage (≤30%) were associated with greater putamen iron increase in patients with AD. Conclusion The study suggests that excessive iron deposition is linked to the basal ganglia in AD, especially the putamen. The study underscores the complex nature of AD pathology and the accumulation of iron, influenced by age, sex, and regional differences, necessitating further research for a comprehensive understanding.
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Affiliation(s)
- Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Sana Mohammadi
- Department of Medical Sciences, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Nahid Jashire Nezhad
- The Persian Gulf Tropical Medicine Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Shaghayegh Karami
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Sayehmiri
- Skull Base Research Center, Loghman Hakim Hospital, Shahid Beheshti University of Medical Science, Tehran, Iran
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16
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Domínguez D JF, Stewart A, Burmester A, Akhlaghi H, O'Brien K, Bollmann S, Caeyenberghs K. Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level. Z Med Phys 2024:S0939-3889(24)00001-1. [PMID: 38336583 DOI: 10.1016/j.zemedi.2024.01.001] [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: 06/02/2023] [Revised: 12/19/2023] [Accepted: 01/07/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Emerging evidence suggests that traumatic brain injury (TBI) is a major risk factor for developing neurodegenerative disease later in life. Quantitative susceptibility mapping (QSM) has been used by an increasing number of studies in investigations of pathophysiological changes in TBI. However, generating artefact-free quantitative susceptibility maps in brains with large focal lesions, as in the case of moderate-to-severe TBI (ms-TBI), is particularly challenging. To address this issue, we utilized a novel two-pass masking technique and reconstruction procedure (two-pass QSM) to generate quantitative susceptibility maps (QSMxT; Stewart et al., 2022, Magn Reson Med.) in combination with the recently developed virtual brain grafting (VBG) procedure for brain repair (Radwan et al., 2021, NeuroImage) to improve automated delineation of brain areas. We used QSMxT and VBG to generate personalised QSM profiles of individual patients with reference to a sample of healthy controls. METHODS Chronic ms-TBI patients (N = 8) and healthy controls (N = 12) underwent (multi-echo) GRE, and anatomical MRI (MPRAGE) on a 3T Siemens PRISMA scanner. We reconstructed the magnetic susceptibility maps using two-pass QSM from QSMxT. We then extracted values of magnetic susceptibility in grey matter (GM) regions (following brain repair via VBG) across the whole brain and determined if they deviate from a reference healthy control group [Z-score < -3.43 or > 3.43, relative to the control mean], with the aim of obtaining personalised QSM profiles. RESULTS Using two-pass QSM, we achieved susceptibility maps with a substantial increase in quality and reduction in artefacts irrespective of the presence of large focal lesions, compared to single-pass QSM. In addition, VBG minimised the loss of GM regions and exclusion of patients due to failures in the region delineation step. Our findings revealed deviations in magnetic susceptibility measures from the HC group that differed across individual TBI patients. These changes included both increases and decreases in magnetic susceptibility values in multiple GM regions across the brain. CONCLUSIONS We illustrate how to obtain magnetic susceptibility values at the individual level and to build personalised QSM profiles in ms-TBI patients. Our approach opens the door for QSM investigations in more severely injured patients. Such profiles are also critical to overcome the inherent heterogeneity of clinical populations, such as ms-TBI, and to characterize the underlying mechanisms of neurodegeneration at the individual level more precisely. Moreover, this new personalised QSM profiling could in the future assist clinicians in assessing recovery and formulating a neuroscience-guided integrative rehabilitation program tailored to individual TBI patients.
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Affiliation(s)
- Juan F Domínguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Ashley Stewart
- School of Information Technology and Electrical Engineering, Faculty of Engineering, Architecture, and Information Technology, The University of Queensland, Brisbane, Australia
| | - Alex Burmester
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Hamed Akhlaghi
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Emergency Medicine, St. Vincent's Hospital, Melbourne, Australia
| | - Kieran O'Brien
- Siemens Healthcare Pty Ltd, Brisbane, Queensland, Australia
| | - Steffen Bollmann
- School of Information Technology and Electrical Engineering, Faculty of Engineering, Architecture, and Information Technology, The University of Queensland, Brisbane, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
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17
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Sandgaard AD, Kiselev VG, Henriques RN, Shemesh N, Jespersen SN. Incorporating the effect of white matter microstructure in the estimation of magnetic susceptibility in ex vivo mouse brain. Magn Reson Med 2024; 91:699-715. [PMID: 37772624 DOI: 10.1002/mrm.29867] [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: 02/01/2023] [Revised: 08/07/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023]
Abstract
PURPOSE To extend quantitative susceptibility mapping to account for microstructure of white matter (WM) and demonstrate its effect on ex vivo mouse brain at 16.4T. THEORY AND METHODS Previous studies have shown that the MRI measured Larmor frequency also depends on local magnetic microstructure at the mesoscopic scale. Here, we include effects from WM microstructure using our previous results for the mesoscopic Larmor frequencyΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ of cylinders with arbitrary orientations. We scrutinize the validity of our model and QSM in a digital brain phantom includingΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from a WM susceptibility tensor and biologically stored iron with scalar susceptibility. We also apply susceptibility tensor imaging to the phantom and investigate how the fitted tensors are biased fromΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ . Last, we demonstrate how to combine multi-gradient echo and diffusion MRI images of ex vivo mouse brains acquired at 16.4T to estimate an apparent scalar susceptibility without sample rotations. RESULTS Our new model improves susceptibility estimation compared to QSM for the brain phantom. Applying susceptibility tensor imaging to the phantom withΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from WM axons with scalar susceptibility produces a highly anisotropic susceptibility tensor that mimics results from previous susceptibility tensor imaging studies. For the ex vivo mouse brain we find theΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ due to WM microstructure to be substantial, changing susceptibility in WM up to 25% root-mean-squared-difference. CONCLUSION Ω ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ impacts susceptibility estimates and biases susceptibility tensor imaging fitting substantially. Hence, it should not be neglected when imaging structurally anisotropic tissue such as brain WM.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Valerij G Kiselev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | | | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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Zhang X, Zhou B, Chen Y, Cai Z, Guo Y, Wei Z, Li S, Feng Y, Sedaghat S, Jang H. Evaluation of gadolinium deposition in cortical bone using three-dimensional ultrashort echo time quantitative susceptibility mapping: A preliminary study. NMR IN BIOMEDICINE 2024; 37:e5035. [PMID: 37721094 PMCID: PMC10726698 DOI: 10.1002/nbm.5035] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 08/15/2023] [Accepted: 08/17/2023] [Indexed: 09/19/2023]
Abstract
The aim of the current study was to investigate the feasibility of three-dimensional ultrashort echo time quantitative susceptibility mapping (3D UTE-QSM) for the assessment of gadolinium (Gd) deposition in cortical bone. To this end, 40 tibial bovine cortical bone specimens were divided into five groups then soaked in phosphate-buffered saline (PBS) solutions with five different Gd concentrations of 0, 0.4, 0.8, 1.2, and 1.6 mmol/L for 48 h. Additionally, eight rabbits were randomly allocated into three groups, consisting of a normal-dose macrocyclic gadolinium-based contrast agent (GBCA) group (n = 3), a high-dose macrocyclic GBCA group (n = 3), and a control group (n = 2). All bovine and rabbit tibial bone samples underwent magnetic resonance imaging (MRI) on a 3-T clinical MR system. A 3D UTE-Cones sequence was utilized to acquire images with five different echo times (i.e., 0.032, 0.2, 0.4, 0.8, and 1.2 ms). The UTE images were subsequently processed with the morphology-enabled dipole inversion algorithm to yield a susceptibility map. The average susceptibility was calculated in three regions of interest in the middle of each specimen, and the Pearson's correlation between the estimated susceptibility and Gd concentration was calculated. The bone samples soaked in PBS with higher Gd concentrations exhibited elevated susceptibility values. A mean susceptibility value of -2.47 ± 0.23 ppm was observed for bovine bone soaked in regular PBS, while the mean QSM value increased to -1.75 ± 0.24 ppm for bone soaked in PBS with the highest Gd concentration of 1.6 mmol/L. A strong positive correlation was observed between Gd concentrations and QSM values. The mean susceptibility values of rabbit tibial specimens in the control group, normal-dose GBCA group, and high-dose GBCA group were -4.11 ± 1.52, -3.85 ± 1.33, and -3.39 ± 1.35 ppm, respectively. In conclusion, a significant linear correlation between Gd in cortical bone and QSM values was observed. The preliminary results suggest that 3D UTE-QSM may provide sensitive noninvasive assessment of Gd deposition in cortical bone.
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Affiliation(s)
- Xiaodong Zhang
- Department of Radiology, Third Affiliated Hospital of Southern Medical University, Guangzhou, China
- University of California, San Diego, San Diego, CA, United States
| | - Beibei Zhou
- The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Yanjun Chen
- Department of Radiology, Third Affiliated Hospital of Southern Medical University, Guangzhou, China
- University of California, San Diego, San Diego, CA, United States
| | - Zhenyu Cai
- University of California, San Diego, San Diego, CA, United States
| | - Yihao Guo
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Zhao Wei
- University of California, San Diego, San Diego, CA, United States
| | - Shisi Li
- Department of Radiology, Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, China
| | - Sam Sedaghat
- University of California, San Diego, San Diego, CA, United States
| | - Hyungseok Jang
- University of California, San Diego, San Diego, CA, United States
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19
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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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Lee SY, Paolillo EW, Saloner R, Cobigo Y, Diaz VE, Gontrum EQ, VandeBunte A, Chatterjee A, Tucker M, Kramer JH, Casaletto KB. Moderating role of physical activity on hippocampal iron deposition and memory outcomes in typically aging older adults. Neurobiol Aging 2023; 131:124-131. [PMID: 37633118 DOI: 10.1016/j.neurobiolaging.2023.07.026] [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: 01/18/2023] [Revised: 06/23/2023] [Accepted: 07/26/2023] [Indexed: 08/28/2023]
Abstract
Physical activity (PA) is linked to better cognitive and brain health, though its mechanisms are unknown. While brain iron is essential for normal function, levels increase with age and, when excessive, can cause detrimental neural effects. We examined how objectively measured PA relates to cerebral iron deposition and memory functioning in normal older adults. Sixty-eight cognitively unimpaired older adults from the UCSF Memory and Aging Center completed neuropsychological testing and brain magnetic resonance imaging, followed by 30-day Fitbit monitoring. Magnetic resonance imaging quantitative susceptibility mapping (QSM) quantified iron deposition. PA was operationalized as average daily steps. Linear regression models examined memory as a function of hippocampal QSM, PA, and their interaction. Higher bilateral hippocampal iron deposition correlated with worse memory but was not strongly related to PA. Covarying for demographics, PA moderated the relationship between bilateral hippocampal iron deposition and memory such that the negative effect of hippocampal QSM on memory performances was no longer significant above 9120 daily steps. PA may mitigate adverse iron-related pathways for memory health.
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Affiliation(s)
- Shannon Y Lee
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Emily W Paolillo
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Rowan Saloner
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Yann Cobigo
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Valentina E Diaz
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Eva Q Gontrum
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Anna VandeBunte
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Ankita Chatterjee
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Miwa Tucker
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Kaitlin B Casaletto
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
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21
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Kiersnowski OC, Winston GP, Caciagli L, Biondetti E, Elbadri M, Buck S, Duncan JS, Thornton JS, Shmueli K, Vos SB. Quantitative susceptibility mapping identifies hippocampal and other subcortical grey matter tissue composition changes in temporal lobe epilepsy. Hum Brain Mapp 2023; 44:5047-5064. [PMID: 37493334 PMCID: PMC10502681 DOI: 10.1002/hbm.26432] [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: 01/31/2023] [Revised: 07/04/2023] [Accepted: 07/07/2023] [Indexed: 07/27/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is associated with widespread brain alterations. Using quantitative susceptibility mapping (QSM) alongside transverse relaxation rate (R 2 * ), we investigated regional brain susceptibility changes in 36 patients with left-sided (LTLE) or right-sided TLE (RTLE) secondary to hippocampal sclerosis, and 27 healthy controls (HC). We compared three susceptibility calculation methods to ensure image quality. Correlations of susceptibility andR 2 * with age of epilepsy onset, frequency of focal-to-bilateral tonic-clonic seizures (FBTCS), and neuropsychological test scores were examined. Weak-harmonic QSM (WH-QSM) successfully reduced noise and removed residual background field artefacts. Significant susceptibility increases were identified in the left putamen in the RTLE group compared to the LTLE group, the right putamen and right thalamus in the RTLE group compared to HC, and a significant susceptibility decrease in the left hippocampus in LTLE versus HC. LTLE patients who underwent epilepsy surgery showed significantly lower left-versus-right hippocampal susceptibility. SignificantR 2 * changes were found between TLE and HC groups in the amygdala, putamen, thalamus, and in the hippocampus. Specifically, decreased R2 * was found in the left and right hippocampus in LTLE and RTLE, respectively, compared to HC. Susceptibility andR 2 * were significantly correlated with cognitive test scores in the hippocampus, globus pallidus, and thalamus. FBTCS frequency correlated positively with ipsilateral thalamic and contralateral putamen susceptibility and withR 2 * in bilateral globi pallidi. Age of onset was correlated with susceptibility in the hippocampus and putamen, and withR 2 * in the caudate. Susceptibility andR 2 * changes observed in TLE groups suggest selective loss of low-myelinated neurons alongside iron redistribution in the hippocampi, predominantly ipsilaterally, indicating QSM's sensitivity to local pathology. Increased susceptibility andR 2 * in the thalamus and putamen suggest increased iron content and reflect disease severity.
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Affiliation(s)
- Oliver C. Kiersnowski
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Gavin P. Winston
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- Department of Medicine, Division of NeurologyQueen's UniversityKingstonCanada
| | - Lorenzo Caciagli
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Emma Biondetti
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Department of Neuroscience, Imaging and Clinical SciencesInstitute for Advanced Biomedical Technologies, “D'Annunzio” University of Chieti‐PescaraChietiItaly
| | - Maha Elbadri
- Department of NeurologyQueen Elizabeth HospitalBirminghamUK
| | - Sarah Buck
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
| | - John S. Duncan
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
| | - John S. Thornton
- Neuroradiological Academic UnitUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | - Karin Shmueli
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Sjoerd B. Vos
- Neuroradiological Academic UnitUCL Queen Square Institute of Neurology, University College LondonLondonUK
- Centre for Microscopy, Characterisation, and AnalysisThe University of Western AustraliaNedlandsAustralia
- Centre for Medical Image Computing, Computer Science departmentUniversity College LondonLondonUK
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22
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Seada SA, van der Eerden AW, Boon AJW, Hernandez-Tamames JA. Quantitative MRI protocol and decision model for a 'one stop shop' early-stage Parkinsonism diagnosis: Study design. Neuroimage Clin 2023; 39:103506. [PMID: 37696098 PMCID: PMC10500558 DOI: 10.1016/j.nicl.2023.103506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/21/2023] [Accepted: 09/04/2023] [Indexed: 09/13/2023]
Abstract
Differentiating among early-stage parkinsonisms is a challenge in clinical practice. Quantitative MRI can aid the diagnostic process, but studies with singular MRI techniques have had limited success thus far. Our objective is to develop a multi-modal MRI method for this purpose. In this review we describe existing methods and present a dedicated quantitative MRI protocol, a decision model and a study design to validate our approach ahead of a pilot study. We present example imaging data from patients and a healthy control, which resemble related literature.
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Affiliation(s)
- Samy Abo Seada
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Anke W van der Eerden
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Agnita J W Boon
- Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands; Department of Imaging Physics, TU Delft, The Netherlands.
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23
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Yu JJ, Li C, Qian ZM, Liu Y. Brain iron deposition is positively correlated with cognitive impairment in patients with chronic cerebral hypoperfusion: a MRI susceptibility mapping study. Clin Radiol 2023; 78:601-607. [PMID: 37003892 DOI: 10.1016/j.crad.2023.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 02/14/2023] [Accepted: 02/27/2023] [Indexed: 04/03/2023]
Abstract
AIM To investigate the relationship of brain iron deposition with cognitive impairment in patients with chronic cerebral hypoperfusion (CHP). MATERIALS AND METHODS Brain iron deposition was detected using quantitative susceptibility mapping (QSM), and cognitive function by neuropsychological tests including the Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADLs), and verbal fluency tests in a total of 40 participants, 23 with CHP and 17 age- and sex-matched healthy participants without CHP (controls). RESULTS The neuropsychological tests revealed that cognitive impairment (p<0.05) and susceptibility values (p<0.05) of the bilateral hippocampus (HP) and substantia nigra (SN) in CHP patients were significantly higher than those of the controls. The susceptibility values of bilateral HP and left putamen correlated closely with the scores of neuropsychological tests in the CHP patients (p<0.05, r2>0.1). The susceptibility values in the left putamen and bilateral HP were significantly higher in CHP patients with mild cognitive impairment (MCI; n=8) than those of CHP patients without MCI (n=15; p<0.05). CONCLUSIONS The present findings indicated that brain iron deposition in specific areas may be responsible for the cognitive impairment in CHP patients, and that QSM is a useful tool to determine brain iron, predicting cognitive impairment in CHP patients.
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Affiliation(s)
- J-J Yu
- Department of Pain and Rehabilitation, The Second Affiliated (Xinqiao) Hospital, The Army (Third Military) Medical University, Chongqing 400038, China
| | - C Li
- Department of Medical Imaging, Chongqing University Central Hospital, Chongqing, China
| | - Z-M Qian
- Institute of Translational & Precision Medicine, Nantong University, 19 Qi Xiu Road, Nantong, JS 226019, China.
| | - Y Liu
- Department of Pain and Rehabilitation, The Second Affiliated (Xinqiao) Hospital, The Army (Third Military) Medical University, Chongqing 400038, China.
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24
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Biondetti E, Cho J, Lee H. Cerebral oxygen metabolism from MRI susceptibility. Neuroimage 2023; 276:120189. [PMID: 37230206 PMCID: PMC10335841 DOI: 10.1016/j.neuroimage.2023.120189] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/26/2023] [Accepted: 05/23/2023] [Indexed: 05/27/2023] Open
Abstract
This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.
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Affiliation(s)
- Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Junghun Cho
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, New York, USA
| | - Hyunyeol Lee
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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25
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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 S, 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. ARXIV 2023:arXiv:2307.02306v1. [PMID: 37461418 PMCID: PMC10350101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM 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 give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask 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 whole brain as a region of interest in the analysis, and QSM results should be reported with - as a minimum - the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in 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, MA, United States
| | - 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
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Jeff Duyn
- Advanced MRI Section, NINDS, National Institutes of Health, Bethesda, MD, United States
| | | | - 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, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - 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 Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, Buffalo, NY, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute at the University at Buffalo, Buffalo, NY, United States
| | - 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, NY, United States
| | - Sina Straub
- Department of Radiology, Mayo Clinic, Jacksonville, FL, United States
| | - Peter van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yi Wang
- MRI Research Institute, Departments of Radiology and Biomedical Engineering, Cornell University, New York, NY, United States
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26
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van de Zande NA, Bulk M, Najac C, van der Weerd L, de Bresser J, Lewerenz J, Ronen I, de Bot ST. Study protocol of IMAGINE-HD: Imaging iron accumulation and neuroinflammation with 7T-MRI + CSF in Huntington's disease. Neuroimage Clin 2023; 39:103450. [PMID: 37327706 PMCID: PMC10509525 DOI: 10.1016/j.nicl.2023.103450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 06/01/2023] [Accepted: 06/05/2023] [Indexed: 06/18/2023]
Abstract
INTRODUCTION Strong evidence suggests a significant role for iron accumulation in the brain in addition to the well-documented neurodegenerative aspects of Huntington's disease (HD). The putative mechanisms by which iron is linked to the HD pathogenesis are multiple, including oxidative stress, ferroptosis and neuroinflammation. However, no previous study in a neurodegenerative disease has linked the observed increase of brain iron accumulation as measured by MRI with well-established cerebrospinal fluid (CSF) and blood biomarkers for iron accumulation, or with associated processes such as neuroinflammation. This study is designed to link quantitative data from iron levels and neuroinflammation metabolites obtained from 7T MRI of HD patients, with specific and well-known clinical biofluid markers for iron accumulation, neurodegeneration and neuroinflammation. Biofluid markers will provide quantitative measures of overall iron accumulation, neurodegeneration and neuroinflammation, while MRI measurements on the other hand will provide quantitative spatial information on brain pathology, neuroinflammation and brain iron accumulation, which will be linked to clinical outcome measures. METHODS This is an observational cross-sectional study, IMAGINE-HD, in HD gene expansion carriers and healthy controls. We include premanifest HD gene expansion carriers and patients with manifest HD in an early or moderate stage. The study includes a 7T MRI scan of the brain, clinical evaluation, motor, functional, and neuropsychological assessments, and sampling of CSF and blood for the detection of iron, neurodegenerative and inflammatory markers. Quantitative Susceptibility Maps will be reconstructed using T2* weighted images to quantify brain iron levels and Magnetic Resonance Spectroscopy will be used to obtain information about neuroinflammation by measuring cell-specific intracellular metabolites' level and diffusion. Age and sex matched healthy subjects are included as a control group. DISCUSSION Results from this study will provide an important basis for the evaluation of brain iron levels and neuroinflammation metabolites as an imaging biomarker for disease stage in HD and their relationship with the salient pathomechanisms of the disease on the one hand, and with clinical outcome on the other.
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Affiliation(s)
| | - Marjolein Bulk
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.
| | - Chloé Najac
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.
| | - Louise van der Weerd
- Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands; Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands.
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.
| | - Jan Lewerenz
- Department of Neurology, University of Ulm, Ulm, Baden-Württemberg, Germany.
| | - Itamar Ronen
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton, United Kingdom.
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27
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Mashriqi F, Mishra BB, Giliberto L, Franceschi AM. 18 F-FDG Brain PET/MRI in Amyotrophic Lateral Sclerosis- Frontotemporal Spectrum Disorder (ALS-FTSD). World J Nucl Med 2023; 22:135-139. [PMID: 37223625 PMCID: PMC10202568 DOI: 10.1055/s-0043-1760762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal and progressive neurodegenerative disorder involving both upper and lower motor neurons. Interestingly, 15 to 41% of patients with ALS have concomitant frontotemporal dementia (FTD). Approximately, 50% of patients with ALS can copresent with a broader set of neuropsychological pathologies that do not meet FTD diagnostic criteria. This association resulted in revised and expanded criteria establishing the ALS-frontotemporal spectrum disorder (FTSD). In this case report, we review background information, epidemiology, pathophysiology, and structural and molecular imaging features of ALS-FTSD.
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Affiliation(s)
- Faizullah Mashriqi
- Neuroradiology Division, Department of Radiology, Northwell Health/Donald and Barbara Zucker School of Medicine, Lenox Hill Hospital, New York, United States
| | - Bibhuti B. Mishra
- Department of Neurology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, The Feinstein Institutes for Medical Research. Manhasset, New York, United States
| | - Luca Giliberto
- Department of Neurology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, The Feinstein Institutes for Medical Research. Manhasset, New York, United States
| | - Ana M. Franceschi
- Neuroradiology Division, Department of Radiology, Northwell Health/Donald and Barbara Zucker School of Medicine, Lenox Hill Hospital, New York, United States
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28
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Cogswell PM, Fan AP. Multimodal comparisons of QSM and PET in neurodegeneration and aging. Neuroimage 2023; 273:120068. [PMID: 37003447 PMCID: PMC10947478 DOI: 10.1016/j.neuroimage.2023.120068] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/17/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) has been used to study susceptibility changes that may occur based on tissue composition and mineral deposition. Iron is a primary contributor to changes in magnetic susceptibility and of particular interest in applications of QSM to neurodegeneration and aging. Iron can contribute to neurodegeneration through inflammatory processes and via interaction with aggregation of disease-related proteins. To better understand the local susceptibility changes observed on QSM, its signal has been studied in association with other imaging metrics such as positron emission tomography (PET). The associations of QSM and PET may provide insight into the pathophysiology of disease processes, such as the role of iron in aging and neurodegeneration, and help to determine the diagnostic utility of QSM as an indirect indicator of disease processes typically evaluated with PET. In this review we discuss the proposed mechanisms and summarize prior studies of the associations of QSM and amyloid PET, tau PET, TSPO PET, FDG-PET, 15O-PET, and F-DOPA PET in evaluation of neurologic diseases with a focus on aging and neurodegeneration.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Audrey P Fan
- Department of Biomedical Engineering and Department of Neurology, University of California, Davis, 1590 Drew Avenue, Davis, CA 95618, USA
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29
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Rui W, Zhang S, Shi H, Sheng Y, Zhu F, Yao Y, Chen X, Cheng H, Zhang Y, Aili A, Yao Z, Zhang XY, Ren Y. Deep Learning-Assisted Quantitative Susceptibility Mapping as a Tool for Grading and Molecular Subtyping of Gliomas. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:243-254. [PMID: 37325712 PMCID: PMC10260708 DOI: 10.1007/s43657-022-00087-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 11/16/2022] [Accepted: 11/20/2022] [Indexed: 06/17/2023]
Abstract
This study aimed to explore the value of deep learning (DL)-assisted quantitative susceptibility mapping (QSM) in glioma grading and molecular subtyping. Forty-two patients with gliomas, who underwent preoperative T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1-weighted imaging (T1WI + C), and QSM scanning at 3.0T magnetic resonance imaging (MRI) were included in this study. Histopathology and immunohistochemistry staining were used to determine glioma grades, and isocitrate dehydrogenase (IDH) 1 and alpha thalassemia/mental retardation syndrome X-linked gene (ATRX) subtypes. Tumor segmentation was performed manually using Insight Toolkit-SNAP program (www.itksnap.org). An inception convolutional neural network (CNN) with a subsequent linear layer was employed as the training encoder to capture multi-scale features from MRI slices. Fivefold cross-validation was utilized as the training strategy (seven samples for each fold), and the ratio of sample size of the training, validation, and test dataset was 4:1:1. The performance was evaluated by the accuracy and area under the curve (AUC). With the inception CNN, single modal of QSM showed better performance in differentiating glioblastomas (GBM) and other grade gliomas (OGG, grade II-III), and predicting IDH1 mutation and ATRX loss (accuracy: 0.80, 0.77, 0.60) than either T2 FLAIR (0.69, 0.57, 0.54) or T1WI + C (0.74, 0.57, 0.46). When combining three modalities, compared with any single modality, the best AUC/accuracy/F1-scores were reached in grading gliomas (OGG and GBM: 0.91/0.89/0.87, low-grade and high-grade gliomas: 0.83/0.86/0.81), predicting IDH1 mutation (0.88/0.89/0.85), and predicting ATRX loss (0.78/0.71/0.67). As a supplement to conventional MRI, DL-assisted QSM is a promising molecular imaging method to evaluate glioma grades, IDH1 mutation, and ATRX loss. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-022-00087-6.
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Affiliation(s)
- Wenting Rui
- Department of Radiology, Huashan Hospital, Fudan University, Mid 12 Wulumuqi Road, Shanghai, 200040 China
| | - Shengjie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433 China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433 China
| | - Huidong Shi
- Department of Radiology, Huashan Hospital, Fudan University, Mid 12 Wulumuqi Road, Shanghai, 200040 China
| | - Yaru Sheng
- Department of Radiology, Huashan Hospital, Fudan University, Mid 12 Wulumuqi Road, Shanghai, 200040 China
| | - Fengping Zhu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - YiDi Yao
- Department of Radiology, Huashan Hospital, Fudan University, Mid 12 Wulumuqi Road, Shanghai, 200040 China
| | - Xiang Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433 China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433 China
| | - Haixia Cheng
- Department of Neuropathology, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Yong Zhang
- GE Healthcare, MR Research, Huatuo Road, Shanghai, 201203 China
| | - Ababikere Aili
- Department of Radiology, Kuqa County People’s Hospital, Xinjiang, 842000 China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Mid 12 Wulumuqi Road, Shanghai, 200040 China
| | - Xiao-Yong Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433 China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433 China
| | - Yan Ren
- Department of Radiology, Huashan Hospital, Fudan University, Mid 12 Wulumuqi Road, Shanghai, 200040 China
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Huang C, Li J, Liu C, Zhang Y, Tang Q, Lv X, Ruan M, Deng K. Investigation of brain iron levels in Chinese patients with Alzheimer's disease. Front Aging Neurosci 2023; 15:1168845. [PMID: 37284016 PMCID: PMC10239950 DOI: 10.3389/fnagi.2023.1168845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 05/05/2023] [Indexed: 06/08/2023] Open
Abstract
Introduction We aimed (i) to explore the diagnostic value of deep gray matter magnetic susceptibility in Alzheimer's disease (AD) in China and (ii) to analyze its correlation with neuropsychiatric scales. Moreover, we conducted subgroup analysis based on the presence of the APOE-ε4 gene to improve the diagnosis of AD. Methods From the prospective studies of the China Aging and Neurodegenerative Initiative (CANDI), a total of 93 subjects who could undergo complete quantitative magnetic susceptibility imaging and APOE-ε4 gene detection were selected. Differences in quantitative susceptibility mapping (QSM) values between and within groups, including AD patients, individuals with mild cognitive impairment (MCI), and healthy controls (HCs), both APOE-ε4 carriers and non-carriers, were analyzed. Results In primary analysis, the magnetic susceptibility values of the bilateral caudate nucleus and right putamen in the AD group and of the right caudate nucleus in the MCI group were significantly higher than those in the HCs group (P < 0.05). In APOE-ε4 non-carriers, there were significant differences in more regions between the AD, MCI, and HCs groups, such as the left putamen and the right globus pallidus (P < 0.05). In subgroup analysis, the correlation between QSM values in some brain regions and neuropsychiatric scales was even stronger. Discussion Exploration of the correlation between deep gray matter iron levels and AD may provide insight into the pathogenesis of AD and facilitate early diagnosis in elderly Chinese. Further subgroup analysis based on the presence of the APOE-ε4 gene may further improve the diagnostic efficiency and sensitivity.
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Affiliation(s)
- Chuanbin Huang
- The First Affiliated Hospital of University of Science and Technology of China Anhui Provincial Hospital, Hefei, China
- Fuyang Hospital of TCM, Fuyang, Anhui, China
| | - Jing Li
- Fuyang Hospital of Anhui Medical University, Fuyang, Anhui, China
| | - Chang Liu
- The First Affiliated Hospital of University of Science and Technology of China Anhui Provincial Hospital, Hefei, China
| | | | - Qiqiang Tang
- The First Affiliated Hospital of University of Science and Technology of China Anhui Provincial Hospital, Hefei, China
| | - Xinyi Lv
- The First Affiliated Hospital of University of Science and Technology of China Anhui Provincial Hospital, Hefei, China
| | - Mengyue Ruan
- The First Affiliated Hospital of University of Science and Technology of China Anhui Provincial Hospital, Hefei, China
| | - Kexue Deng
- The First Affiliated Hospital of University of Science and Technology of China Anhui Provincial Hospital, Hefei, China
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Northall A, Doehler J, Weber M, Vielhaber S, Schreiber S, Kuehn E. Layer-specific vulnerability is a mechanism of topographic map aging. Neurobiol Aging 2023; 128:17-32. [PMID: 37141729 DOI: 10.1016/j.neurobiolaging.2023.04.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 03/29/2023] [Accepted: 04/02/2023] [Indexed: 05/06/2023]
Abstract
Topographic maps form a critical feature of cortical organization, yet are poorly described with respect to their microstructure in the living aging brain. We acquired quantitative structural and functional 7T-MRI data from younger and older adults to characterize layer-wise topographic maps of the primary motor cortex (M1). Using parcellation-inspired techniques, we show that quantitative T1 and Quantitative Susceptibility Maps values of the hand, face, and foot areas differ significantly, revealing microstructurally distinct cortical fields in M1. We show that these fields are distinct in older adults and that myelin borders between them do not degenerate. We further show that the output layer 5 of M1 shows a particular vulnerability to age-related increased iron, while layer 5 and the superficial layer show increased diamagnetic substance, likely reflecting calcifications. Taken together, we provide a novel 3D model of M1 microstructure, where body parts form distinct structural units, but layers show specific vulnerability toward increased iron and calcium in older adults. Our findings have implications for understanding sensorimotor organization and aging, in addition to topographic disease spread.
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Affiliation(s)
- Alicia Northall
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany.
| | - Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany
| | - Miriam Weber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Stefanie Schreiber
- Department of Neurology, Otto-von-Guericke University Magdeburg, Magdeburg, Saxony-Anhalt, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Saxony-Anhalt, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, Saxony-Anhalt, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Saxony-Anhalt, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Saxony-Anhalt, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, Saxony-Anhalt, Germany; Hertie Institute for Clinical Brain Research, Tübingen, Germany
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32
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Satoh R, Arani A, Senjem ML, Duffy JR, Clark HM, Utianski RL, Botha H, Machulda MM, Jack CR, Whitwell JL, Josephs KA. Spatial patterns of elevated magnetic susceptibility in progressive apraxia of speech. Neuroimage Clin 2023; 38:103394. [PMID: 37003130 PMCID: PMC10102559 DOI: 10.1016/j.nicl.2023.103394] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023]
Abstract
PURPOSE Progressive apraxia of speech (PAOS) is a neurodegenerative disorder affecting the planning or programming of speech. Little is known about its magnetic susceptibility profiles indicative of biological processes such as iron deposition and demyelination. This study aims to clarify (1) the pattern of susceptibility in PAOS patients, (2) the susceptibility differences between the phonetic (characterized by predominance of distorted sound substitutions and additions) and prosodic (characterized by predominance of slow speech rate and segmentation) subtypes of PAOS, and (3) the relationships between susceptibility and symptom severity. METHODS Twenty patients with PAOS (nine phonetic and eleven prosodic subtypes) were prospectively recruited and underwent a 3 Tesla MRI scan. They also underwent detailed speech, language, and neurological evaluations. Quantitative susceptibility maps (QSM) were reconstructed from multi-echo gradient echo MRI images. Region of interest analysis was conducted to estimate susceptibility coefficients in several subcortical and frontal regions. We compared susceptibility values between PAOS and an age-matched control group and performed a correlation analysis between susceptibilities and an apraxia of speech rating scale (ASRS) phonetic and prosodic feature ratings. RESULTS The magnetic susceptibility of PAOS was statistically greater than that of controls in subcortical regions (left putamen, left red nucleus, and right dentate nucleus) (p < 0.01, also survived FDR correction) and in the left white-matter precentral gyrus (p < 0.05, but not survived FDR correction). The prosodic patients showed greater susceptibilities than controls in these subcortical and precentral regions. The susceptibility in the left red nucleus and in the left precentral gyrus correlated with the prosodic sub-score of the ASRS. CONCLUSION Magnetic susceptibility in PAOS patients was greater than controls mainly in the subcortical regions. While larger samples are needed before QSM is considered ready for clinical differential diagnosis, the present study contributes to our understanding of magnetic susceptibility changes and the pathophysiology of PAOS.
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Affiliation(s)
- Ryota Satoh
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Arvin Arani
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA; Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Joseph R Duffy
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
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Perosa V, Rotta J, Yakupov R, Kuijf HJ, Schreiber F, Oltmer JT, Mattern H, Heinze HJ, Düzel E, Schreiber S. Implications of quantitative susceptibility mapping at 7 Tesla MRI for microbleeds detection in cerebral small vessel disease. Front Neurol 2023; 14:1112312. [PMID: 37006483 PMCID: PMC10050564 DOI: 10.3389/fneur.2023.1112312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/20/2023] [Indexed: 03/17/2023] Open
Abstract
BackgroundCerebral microbleeds (MBs) are a hallmark of cerebral small vessel disease (CSVD) and can be found on T2*-weighted sequences on MRI. Quantitative susceptibility mapping (QSM) is a postprocessing method that also enables MBs identification and furthermore allows to differentiate them from calcifications.AimsWe explored the implications of using QSM at submillimeter resolution for MBs detection in CSVD.MethodsBoth 3 and 7 Tesla (T) MRI were performed in elderly participants without MBs and patients with CSVD. MBs were quantified on T2*-weighted imaging and QSM. Differences in the number of MBs were assessed, and subjects were classified in CSVD subgroups or controls both on 3T T2*-weighted imaging and 7T QSM.Results48 participants [mean age (SD) 70.9 (8.8) years, 48% females] were included: 31 were healthy controls, 6 probable cerebral amyloid angiopathy (CAA), 9 mixed CSVD, and 2 were hypertensive arteriopathy [HA] patients. After accounting for the higher number of MBs detected at 7T QSM (Median = Mdn; Mdn7T−QSM = 2.5; Mdn3T−T2 = 0; z = 4.90; p < 0.001) and false positive MBs (6.1% calcifications), most healthy controls (80.6%) demonstrated at least one MB and more MBs were discovered in the CSVD group.ConclusionsOur observations suggest that QSM at submillimeter resolution improves the detection of MBs in the elderly human brain. A higher prevalence of MBs than so far known in healthy elderly was revealed.
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Affiliation(s)
- Valentina Perosa
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, United States
- *Correspondence: Valentina Perosa
| | - Johanna Rotta
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Renat Yakupov
- Institute of Cognitive Neurology and Dementia Research (IKND), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Hugo J. Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - Frank Schreiber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jan T. Oltmer
- Athinoula A. Martinos Center, Massachusetts General Hospital, Department of Radiology, Boston, MA, United States
| | - Hendrik Mattern
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Physics, Otto-von-Guericke University, Magdeburg, Germany
| | - Hans-Jochen Heinze
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research (IKND), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Stefanie Schreiber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
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Zhang J, Spincemaille P, Zhang H, Nguyen TD, Li C, Li J, Kovanlikaya I, Sabuncu MR, Wang Y. LARO: Learned acquisition and reconstruction optimization to accelerate quantitative susceptibility mapping. Neuroimage 2023; 268:119886. [PMID: 36669747 PMCID: PMC10021353 DOI: 10.1016/j.neuroimage.2023.119886] [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: 10/31/2022] [Revised: 12/12/2022] [Accepted: 01/16/2023] [Indexed: 01/19/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) involves acquisition and reconstruction of a series of images at multi-echo time points to estimate tissue field, which prolongs scan time and requires specific reconstruction technique. In this paper, we present our new framework, called Learned Acquisition and Reconstruction Optimization (LARO), which aims to accelerate the multi-echo gradient echo (mGRE) pulse sequence for QSM. Our approach involves optimizing a Cartesian multi-echo k-space sampling pattern with a deep reconstruction network. Next, this optimized sampling pattern was implemented in an mGRE sequence using Cartesian fan-beam k-space segmenting and ordering for prospective scans. Furthermore, we propose to insert a recurrent temporal feature fusion module into the reconstruction network to capture signal redundancies along echo time. Our ablation studies show that both the optimized sampling pattern and proposed reconstruction strategy help improve the quality of the multi-echo image reconstructions. Generalization experiments show that LARO is robust on the test data with new pathologies and different sequence parameters. Our code is available at https://github.com/Jinwei1209/LARO-QSM.git.
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Affiliation(s)
- Jinwei Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Hang Zhang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
| | - Thanh D Nguyen
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Chao Li
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA; Department of Applied Physics, Cornell University, Ithaca, NY, USA
| | - Jiahao Li
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Mert R Sabuncu
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA; Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
| | - Yi Wang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
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Wang Z, Mak HKF, Cao P. Deep learning-regularized, single-step quantitative susceptibility mapping quantification. NMR IN BIOMEDICINE 2023; 36:e4849. [PMID: 36259729 DOI: 10.1002/nbm.4849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 09/26/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
The purpose of the current study was to develop deep learning-regularized, single-step quantitative susceptibility mapping (QSM) quantification, directly generating QSM from the total phase map. A deep learning-regularized, single-step QSM quantification model, named SS-POCSnet, was trained with datasets created using the QSM synthesis approach in QSM reconstruction challenge 2.0. In SS-POCSnet, a data fidelity term based on a single-step model was iteratively applied that combined the spherical mean value kernel and dipole model. Meanwhile, SS-POCSnet regularized susceptibility maps, avoiding underestimating susceptibility values. We evaluated the SS-POCSnet on 10 synthetic datasets, 24 clinical datasets with lesions of cerebral microbleed (CMB) and calcification, and 10 datasets with multiple sclerosis (MS).On synthetic datasets, SS-POCSnet showed the best performance among the methods evaluated, with a normalized root mean squared error of 37.3% ± 4.2%, susceptibility-tuned structured similarity index measure of 0.823 ± 0.02, high-frequency error norm of 37.0 ± 5.7, and peak signal-to-noise ratio of 42.8 ± 1.1. SS-POCSnet also reduced the underestimations of susceptibility values in deep brain nuclei compared with those from the other models evaluated. Furthermore, SS-POCSnet was sensitive to CMB/calcification and MS lesions, demonstrating its clinical applicability. Our method also supported variable imaging parameters, including matrix size and resolution. It was concluded that deep learning-regularized, single-step QSM quantification can mitigate underestimating susceptibility values in deep brain nuclei.
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Affiliation(s)
- Zuojun Wang
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
| | - Peng Cao
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China
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Cognolato F, O'Brien K, Jin J, Robinson S, Laun FB, Barth M, Bollmann S. NeXtQSM-A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data. Med Image Anal 2023; 84:102700. [PMID: 36529002 DOI: 10.1016/j.media.2022.102700] [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: 07/16/2021] [Revised: 09/16/2022] [Accepted: 11/21/2022] [Indexed: 11/24/2022]
Abstract
Deep learning based Quantitative Susceptibility Mapping (QSM) has shown great potential in recent years, obtaining similar results to established non-learning approaches. Many current deep learning approaches are not data consistent, require in vivo training data or solve the QSM problem in consecutive steps resulting in the propagation of errors. Here we aim to overcome these limitations and developed a framework to solve the QSM processing steps jointly. We developed a new hybrid training data generation method that enables the end-to-end training for solving background field correction and dipole inversion in a data-consistent fashion using a variational network that combines the QSM model term and a learned regularizer. We demonstrate that NeXtQSM overcomes the limitations of previous deep learning methods. NeXtQSM offers a new deep learning based pipeline for computing quantitative susceptibility maps that integrates each processing step into the training and provides results that are robust and fast.
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Affiliation(s)
- Francesco Cognolato
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia
| | - Kieran O'Brien
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia; Siemens Healthcare Pty Ltd, Brisbane, Queensland, Australia
| | - Jin Jin
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia; Siemens Healthcare Pty Ltd, Brisbane, Queensland, Australia
| | - Simon Robinson
- Centre for Advanced Imaging, The University of Queensland, Brisbane, 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; Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Steffen Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia.
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Incerti I, Fusco M, Contarino VE, Siggillino S, Conte G, Lanfranconi S, Bertani GA, Gaudino C, d'Orio P, Pallini R, D'Alessandris QG, Meessen JMTA, Nicolis EB, Vasamì A, Dejana E, Bianchi AM, Triulzi FM, Latini R, Scola E. Magnetic susceptibility as a 1-year predictor of outcome in familial cerebral cavernous malformations: a pilot study. Eur Radiol 2023; 33:4158-4166. [PMID: 36602570 DOI: 10.1007/s00330-022-09366-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 10/24/2022] [Accepted: 12/05/2022] [Indexed: 01/06/2023]
Abstract
OBJECTIVES To test whether quantitative susceptibility mapping (QSM) of cerebral cavernous malformations (CCMs) assessed at baseline may predict the presence or absence of haemorrhagic signs at 1-year follow-up. METHODS Familial CCM patients were enrolled in the longitudinal multicentre study Treat-CCM. The 3-T MRI scan allowed performing a semi-automatic segmentation of CCMs and computing the maximum susceptibility in each segmented CCM (QSMmax) at baseline. CCMs were classified as haemorrhagic and non-haemorrhagic at baseline and then subclassified according to the 1-year (t1) evolution. Between-group differences were tested, and the diagnostic accuracy of QSMmax in predicting the presence or absence of haemorrhagic signs in CCMs was calculated with ROC analyses. RESULTS Thirty-three patients were included in the analysis, and a total of 1126 CCMs were segmented. QSMmax was higher in haemorrhagic CCMs than in non-haemorrhagic CCMs (p < 0.001). In haemorrhagic CCMs at baseline, the accuracy of QSMmax in differentiating CCMs that were still haemorrhagic from CCMs that recovered from haemorrhage at t1 calculated as area under the curve (AUC) was 0.78 with sensitivity 62.69%, specificity 82.35%, positive predictive value (PPV) 93.3% and negative predictive value (NPV) 35.9% (QSMmax cut-off ≥ 1462.95 ppb). In non-haemorrhagic CCMs at baseline, AUC was 0.91 in differentiating CCMs that bled at t1 from stable CCMs with sensitivity 100%, specificity 81.9%, PPV 5.1%, and NPV 100% (QSMmax cut-off ≥ 776.29 ppb). CONCLUSIONS The QSMmax in CCMs at baseline showed high accuracy in predicting the presence or absence of haemorrhagic signs at 1-year follow-up. Further effort is required to test the role of QSM in follow-up assessment and therapeutic trials in multicentre CCM studies. KEY POINTS • QSM in semi-automatically segmented CCM was feasible. • The maximum magnetic susceptibility in a single CCM at baseline may predict the presence or absence of haemorrhagic signs at 1-year follow-up. • Multicentric studies are needed to enforce the role of QSM in predicting the CCMs' haemorrhagic evolution in patients affected by familial and sporadic forms.
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Affiliation(s)
- Irene Incerti
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy
| | - Massimo Fusco
- Department of Neuroradiology, ASST Grande Ospedale Metropolitano Niguarda, Piazza dell'Ospedale Maggiore 3, 20162, Milan, Italy
| | - Valeria Elisa Contarino
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.
| | - Silvia Siggillino
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy
| | - Giorgio Conte
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.,Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Silvia Lanfranconi
- Department of Neurology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy
| | - Giulio Andrea Bertani
- Department of Neurosurgery, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy
| | - Chiara Gaudino
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.,Department of Neuroradiology, Azienda Ospedaliero-Universitaria Policlinico Umberto I, Viale del Policlinico 155, 00161, Rome, Italy
| | - Piergiorgio d'Orio
- "Claudio Munari" Epilepsy Surgery Centre, ASST Grande Ospedale Metropolitano Niguarda, Piazza dell'Ospedale Maggiore 3, 20162, Milan, Italy
| | - Roberto Pallini
- Department of Neurosurgery, Università Cattolica del Sacro Cuore, Fondazione IRCCS Policlinico A. Gemelli, Largo Francesco Vito 1, 00168, Rome, Italy
| | - Quintino Giorgio D'Alessandris
- Department of Neurosurgery, Università Cattolica del Sacro Cuore, Fondazione IRCCS Policlinico A. Gemelli, Largo Francesco Vito 1, 00168, Rome, Italy
| | | | - Enrico Bjorn Nicolis
- Department of Cardiovascular Medicine, Institute for Pharmacological Research Mario Negri IRCCS, Via Mario Negri, 2, 20156, Milan, Italy
| | - Antonella Vasamì
- Department of Cardiovascular Medicine, Institute for Pharmacological Research Mario Negri IRCCS, Via Mario Negri, 2, 20156, Milan, Italy
| | - Elisabetta Dejana
- Laboratory of Vascular Biology, IFOM, Firc Institute for Molecular Oncology, Via Adamello 16, 20139, Milan, Italy
| | - Anna Maria Bianchi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Fabio Maria Triulzi
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.,Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Roberto Latini
- Department of Cardiovascular Medicine, Institute for Pharmacological Research Mario Negri IRCCS, Via Mario Negri, 2, 20156, Milan, Italy
| | - Elisa Scola
- Department of Neuroradiology, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.,Department of Neuroradiology, Careggi University Hospital, Largo Piero Palagi 1, Florence, Italy
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Tinaz S. Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes. Front Neurol 2023; 14:1082060. [PMID: 36816565 PMCID: PMC9932598 DOI: 10.3389/fneur.2023.1082060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.
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Affiliation(s)
- Sule Tinaz
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Clinical Neurosciences Imaging Center, Yale School of Medicine, New Haven, CT, United States
- *Correspondence: Sule Tinaz ✉
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39
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Zhang J, Xie L, Yang X, Xu L, Chen K, Luo Y, Yu C. Higher magnetic susceptibility of globus pallidus in patients after macrocyclic GBCAs: assessment using quantitative susceptibility mapping. Acta Radiol 2022:2841851221147618. [PMID: 36567675 DOI: 10.1177/02841851221147618] [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: 12/27/2022]
Abstract
BACKGROUND As previous studies reported, gadolinium deposits in globus pallidus (GP) and dentate nucleus (DN) after repeated administrations of gadolinium-based contrast agents (GBCAs) and a signal intensity (SI) increase on T1-weighted images were related to linear GBCAs, not macrocyclic GBCAs. PURPOSE To identify whether quantitative susceptibility mapping (QSM) could measure a subtle increase in magnetic susceptibility in DN and GP in patients after repeated administrations of gadoteric acid meglumine (Gd-DOTA). MATERIAL AND METHODS In this study, 50 patients with cerebral tumors who had received at least three injections of Gd-DOTA (GBCA group) and 50 individuals without a history of GBCA injections (non-GBCA group) were included. The image data for QSM and T1-weighted images were reviewed. Spearman rank correlation was used to estimate the associations between the values (magnetic susceptibility of QSM and SI ratios of T1-weighted images) and the number of Gd-DOTA injections. RESULTS The mean magnetic susceptibility of GP in GBCA group was 0.136 ± 0.031 ppm, which was significantly higher than that in control group (0.114 ± 0.030 ppm) (P = 0.001). In the GBCA group (n = 50), we found a substantial positive correlation between magnetic susceptibility of GP and the number of Gd-DOTA injections according to Spearman rank correlation coefficient (ρ = 0.673, P = 0.0001). There was a modest but significant correlation between magnetic susceptibility of DN and the number of Gd-DOTA injections (ρ = 0.311, P = 0.028). CONCLUSION In comparison to the control group, the magnetic susceptibility of GP in the GBCA group was significantly higher and had a substantial positive association with the number of Gd-DOTA injections.
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Affiliation(s)
- Jing Zhang
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
| | - Lisi Xie
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
| | - Xiaoling Yang
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
| | - Liang Xu
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
| | - Kewei Chen
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
| | - Yuqing Luo
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
| | - Chengxin Yu
- Department of Radiology, 159371Yichang Central People's Hospital, the first Clinical Medical College of Three Gorges University, Yichang, Hubei Province, PR China
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40
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Quantitative Susceptibility Mapping in Cognitive Decline: A Review of Technical Aspects and Applications. Cognit Comput 2022. [DOI: 10.1007/s12559-022-10095-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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41
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Kamesh Iyer S, Moon BF, Josselyn N, Kurtz RM, Song JW, Ware JB, Nabavizadeh SA, Witschey WR. Quantitative susceptibility mapping using plug-and-play alternating direction method of multipliers. Sci Rep 2022; 12:21679. [PMID: 36522372 PMCID: PMC9755132 DOI: 10.1038/s41598-022-22778-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 10/19/2022] [Indexed: 12/23/2022] Open
Abstract
Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R2 = 0.98, p < 0.05) with COSMOS and no significant bias (bias = 0.007 ± 0.012). PnP-BM4D QSM achieved excellent quality when assessed using structural similarity index metric (SSIM = 0.860), high frequency error norm (HFEN = 58.5), cross correlation (CC = 0.804), and mutual information (MI = 0.475) and also maintained good conspicuity of fine features. In glioblastoma datasets, PnP-BM4D QSM showed higher performance (IQGrade = 2.4 ± 0.4, ISGrade = 2.7 ± 0.3, IQRank = 3.7 ± 0.3, ISRank = 3.9 ± 0.3) compared to MEDI (IQGrade = 2.1 ± 0.5, ISGrade = 2.1 ± 0.6, IQRank = 2.4 ± 0.6, ISRank = 2.9 ± 0.2) and FANSI-TGV (IQGrade = 2.2 ± 0.6, ISGrade = 2.1 ± 0.6, IQRank = 2.7 ± 0.3, ISRank = 2.2 ± 0.2). We illustrated the modularity of PnP QSM by interchanging two additional patch-based denoisers. PnP QSM reconstruction was feasible, and its flexibility was shown using several patch-based denoisers. This technique may allow rapid prototyping and validation of new denoisers for QSM reconstruction for an array of useful clinical applications.
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Affiliation(s)
- Srikant Kamesh Iyer
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
- Perelman Center for Advanced Medicine, South Pavilion, Rm 11-155, Philadelphia, PA, USA.
| | - Brianna F Moon
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas Josselyn
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Robert M Kurtz
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jae W Song
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey B Ware
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - S Ali Nabavizadeh
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Walter R Witschey
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
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42
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Ni MH, Li ZY, Sun Q, Yu Y, Yang Y, Hu B, Ma T, Xie H, Li SN, Tao LQ, Yuan DX, Zhu JL, Yan LF, Cui GB. Neurovascular decoupling measured with quantitative susceptibility mapping is associated with cognitive decline in patients with type 2 diabetes. Cereb Cortex 2022; 33:5336-5346. [PMID: 36310091 DOI: 10.1093/cercor/bhac422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/26/2022] [Accepted: 09/28/2022] [Indexed: 01/10/2023] Open
Abstract
Abstract
Disturbance of neurovascular coupling (NVC) is suggested to be one potential mechanism in type 2 diabetes mellitus (T2DM) associated mild cognitive impairment (MCI). However, NVC evidence derived from functional magnetic resonance imaging ignores the relationship of neuronal activity with vascular injury. Twenty-seven T2DM patients without MCI and thirty healthy controls were prospectively enrolled. Brain regions with changed susceptibility detected by quantitative susceptibility mapping (QSM) were used as seeds for functional connectivity (FC) analysis. NVC coefficients were estimated using combined degree centrality (DC) with susceptibility or cerebral blood flow (CBF). Partial correlations between neuroimaging indicators and cognitive decline were investigated. In T2DM group, higher susceptibility values in right hippocampal gyrus (R.PHG) were found and were negatively correlated with Naming Ability of Montreal Cognitive Assessment. FC increased remarkably between R.PHG and right middle temporal gyrus (R.MTG), right calcarine gyrus (R.CAL). Both NVC coefficients (DC-QSM and DC-CBF) reduced in R.PHG and increased in R.MTG and R.CAL. Both NVC coefficients in R.PHG and R.MTG increased with the improvement of cognitive ability, especially for executive function. These demonstrated that QSM and DC-QSM coefficients can be promising biomarkers for early evaluation of cognitive decline in T2DM patients and help to better understand the mechanism of NVC.
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Affiliation(s)
- Min-Hua Ni
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
- Faculty of Medical Technology, Shaanxi University of Chinese Medicine , 1 Middle Section of Shiji Road, Xian yang, Shaanxi 712046 , China
| | - Ze-Yang Li
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Qian Sun
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Ying Yu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Yang Yang
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Bo Hu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Teng Ma
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Hao Xie
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Si-Ning Li
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
- Faculty of Medical Technology, Xi’an Medical University , 1 Xinwang Road, Xi'an, Shaanxi 710016 , China
| | - Lan-Qiu Tao
- Student Brigade, Fourth Military Medical University , 169 Changle Road, Xi'an, Shaanxi 710032 , China
| | - Ding-Xin Yuan
- Student Brigade, Fourth Military Medical University , 169 Changle Road, Xi'an, Shaanxi 710032 , China
| | - Jun-Ling Zhu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Lin-Feng Yan
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Guang-Bin Cui
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
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43
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Reduced basal ganglia tissue-iron concentration in school-age children with attention-deficit/hyperactivity disorder is localized to limbic circuitry. Exp Brain Res 2022; 240:3271-3288. [PMID: 36301336 DOI: 10.1007/s00221-022-06484-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 10/10/2022] [Indexed: 11/04/2022]
Abstract
Dopamine-related abnormalities in the basal ganglia have been implicated in attention-deficit/hyperactivity disorder (ADHD). Iron plays a critical role in supporting dopaminergic function, and reduced brain iron and serum ferritin levels have been linked to ADHD symptom severity in children. Furthermore, the basal ganglia is a central brain region implicated in ADHD psychopathology and involved in motor and reward functions as well as emotional responding. The present study repurposed diffusion tensor imaging (DTI) to examine effects of an ADHD diagnosis and sex on iron deposition within the basal ganglia in children ages 8-12 years. We further explored associations between brain iron levels and ADHD symptom severity and affective symptoms. We observed reduced iron levels in children with ADHD in the bilateral limbic region of the striatum, as well as reduced levels of iron-deposition in males in the sensorimotor striatal subregion, regardless of diagnosis. Across the whole sample, iron-deposition increased with age in all regions. Brain-behavior analyses revealed that, across diagnostic groups, lower tissue-iron levels in bilateral limbic striatum correlated with greater ADHD symptom severity, whereas lower tissue-iron levels in the left limbic striatum only correlated with anxious, depressive and affective symptom severity. This study sheds light on the neurobiological underpinnings of ADHD, specifically highlighting the localization of tissue-iron deficiency in limbic regions, and providing support for repurposing DTI for brain iron analyses. Our findings highlight the need for further investigation of iron as a biomarker in the diagnosis and treatment of ADHD and sex differences.
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Pinky NN, Debert CT, Dukelow SP, Benson BW, Harris AD, Yeates KO, Emery CA, Goodyear BG. Multimodal magnetic resonance imaging of youth sport-related concussion reveals acute changes in the cerebellum, basal ganglia, and corpus callosum that resolve with recovery. Front Hum Neurosci 2022; 16:976013. [PMID: 36337852 PMCID: PMC9626521 DOI: 10.3389/fnhum.2022.976013] [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: 06/22/2022] [Accepted: 09/23/2022] [Indexed: 11/28/2022] Open
Abstract
Magnetic resonance imaging (MRI) can provide a number of measurements relevant to sport-related concussion (SRC) symptoms; however, most studies to date have used a single MRI modality and whole-brain exploratory analyses in attempts to localize concussion injury. This has resulted in highly variable findings across studies due to wide ranging symptomology, severity and nature of injury within studies. A multimodal MRI, symptom-guided region-of-interest (ROI) approach is likely to yield more consistent results. The functions of the cerebellum and basal ganglia transcend many common concussion symptoms, and thus these regions, plus the white matter tracts that connect or project from them, constitute plausible ROIs for MRI analysis. We performed diffusion tensor imaging (DTI), resting-state functional MRI, quantitative susceptibility mapping (QSM), and cerebral blood flow (CBF) imaging using arterial spin labeling (ASL), in youth aged 12-18 years following SRC, with a focus on the cerebellum, basal ganglia and white matter tracts. Compared to controls similar in age, sex and sport (N = 20), recent SRC youth (N = 29; MRI at 8 ± 3 days post injury) exhibited increased susceptibility in the cerebellum (p = 0.032), decreased functional connectivity between the caudate and each of the pallidum (p = 0.035) and thalamus (p = 0.021), and decreased diffusivity in the mid-posterior corpus callosum (p < 0.038); no changes were observed in recovered asymptomatic youth (N = 16; 41 ± 16 days post injury). For recent symptomatic-only SRC youth (N = 24), symptom severity was associated with increased susceptibility in the superior cerebellar peduncles (p = 0.011) and reduced activity in the cerebellum (p = 0.013). Fewer days between injury and MRI were associated with reduced cerebellar-parietal functional connectivity (p < 0.014), reduced activity of the pallidum (p = 0.002), increased CBF in the caudate (p = 0.005), and reduced diffusivity in the central corpus callosum (p < 0.05). Youth SRC is associated with acute cerebellar inflammation accompanied by reduced cerebellar activity and cerebellar-parietal connectivity, as well as structural changes of the middle regions of the corpus callosum accompanied by functional changes of the caudate, all of which resolve with recovery. Early MRI post-injury is important to establish objective MRI-based indicators for concussion diagnosis, recovery assessment and prediction of outcome.
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Affiliation(s)
- Najratun Nayem Pinky
- Department of Biomedical Engineering, University of Calgary, Calgary, AB, Canada
| | - Chantel T. Debert
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Sean P. Dukelow
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Brian W. Benson
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Canadian Sport Institute Calgary, University of Calgary, Calgary, AB, Canada
- Benson Concussion Institute, University of Calgary, Calgary, AB, Canada
| | - Ashley D. Harris
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Keith O. Yeates
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Department of Psychology, University of Calgary, Calgary, AB, Canada
| | - Carolyn A. Emery
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics, University of Calgary, Calgary, AB, Canada
- Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada
- Sports Injury Prevention Research Centre, University of Calgary, Calgary, AB, Canada
| | - Bradley G. Goodyear
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
- Seaman Family MR Research Centre, University of Calgary, Calgary, AB, Canada
- *Correspondence: Bradley G. Goodyear,
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Zachariou V, Bauer CE, Pappas C, Gold BT. High cortical iron is associated with the disruption of white matter tracts supporting cognitive function in healthy older adults. Cereb Cortex 2022; 33:4815-4828. [PMID: 36182267 PMCID: PMC10110441 DOI: 10.1093/cercor/bhac382] [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: 07/11/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 01/25/2023] Open
Abstract
Aging is associated with brain iron accumulation, which has been linked to cognitive decline. However, how brain iron affects the structure and function of cognitive brain networks remains unclear. Here, we explored the possibility that iron load in gray matter is associated with disruption of white matter (WM) microstructure within a network supporting cognitive function, in a cohort of 95 cognitively normal older adults (age range: 60-86). Functional magnetic resonance imaging was used to localize a set of brain regions involved in working memory and diffusion tensor imaging based probabilistic tractography was used to identify a network of WM tracts connecting the functionally defined regions. Brain iron concentration within these regions was evaluated using quantitative susceptibility mapping and microstructural properties were assessed within the identified tracts using neurite orientation dispersion and density imaging. Results indicated that high brain iron concentration was associated with low neurite density (ND) within the task-relevant WM network. Further, regional associations were observed such that brain iron in cortical regions was linked with lower ND in neighboring but not distant WM tracts. Our results provide novel evidence suggesting that age-related increases in brain iron concentration are associated with the disruption of WM tracts supporting cognitive function in normal aging.
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Affiliation(s)
- Valentinos Zachariou
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Christopher E Bauer
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Colleen Pappas
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States
| | - Brian T Gold
- Department of Neuroscience, University of Kentucky, Lexington, KY 40536-0298, United States.,College of Medicine, University of Kentucky, Lexington, KY 40536-0298, United States.,Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536-0298, United States.,Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY 40536-0298, United States
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46
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Chiang GC. The Blood-Cerebrospinal Fluid Barrier May Play a Role in Alzheimer Disease Pathogenesis. Radiology 2022; 304:646-647. [PMID: 35579527 PMCID: PMC9434809 DOI: 10.1148/radiol.220740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 11/11/2022]
Affiliation(s)
- Gloria C. Chiang
- From the Division of Neuroradiology, Department of Radiology, Weill Cornell Medical College, NewYork-Presbyterian Hospital, 525 E 68th St, Starr Pavilion, Box 141, New York, NY 10065
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Duan X, Xie Y, Zhu X, Chen L, Li F, Feng G, Li L. Quantitative Susceptibility Mapping of Brain Iron Deposition in Patients With Recurrent Depression. Psychiatry Investig 2022; 19:668-675. [PMID: 36059056 PMCID: PMC9441458 DOI: 10.30773/pi.2022.0110] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/08/2022] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE Recurrence is the most significant feature of depression and the relationship between iron and recurrent depression is still lack of direct evidence in vivo. METHODS Twenty-one patients with depression and twenty control subjects were included. Gradient-recalled echo, T1 and T2 images were acquired using a 3.0T MRI system. After quantitative susceptibility mapping were reconstructed and standardized, a whole-brain and the regions of interest were respectively analyzed. RESULTS Significant increases in susceptibility were found in multiple recurrent depression patients, which involved several brain regions (frontal lobes, temporal lobe structures, occipital lobes hippocampal regions, putamen, thalamus, cingulum, and cerebellum). Interestingly, no susceptibility changes after treatment compared to pre-treatment (all p>0.05) and no significant correlation between susceptibility and Hamilton Depression Rating Scale were found. Besides, it was close to significance that those with a higher relapse frequency or a longer mean duration of single episode had a higher susceptibility in the putamen, thalamus, and hippocampus. Further studies showed susceptibility across the putamen (ρ2=0.27, p<0.001), thalamus (ρ2=0.21, p<0.001), and hippocampus (ρ2=0.19, p<0.001) were strongly correlated with total course of disease onset. CONCLUSION Brain iron deposition is related to the total course of disease onset, but not the severity of depression, which suggest that brain iron deposition may be a sign of brain damage in multiple recurrent depression.
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Affiliation(s)
- Xinxiu Duan
- Department of Radiology, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Yuhang Xie
- Department of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Xiufang Zhu
- Department of Radiology, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Lei Chen
- Department of Radiology, The First People's Hospital of Lianyungang, Lianyungang, China
| | - Feng Li
- Department of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Guoquan Feng
- Department of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Lei Li
- Department of Radiology, The First People's Hospital of Lianyungang, Lianyungang, China
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Distribution Indices of Magnetic Susceptibility Values in the Primary Motor Cortex Enable to Classify Patients with Amyotrophic Lateral Sclerosis. Brain Sci 2022; 12:brainsci12070942. [PMID: 35884748 PMCID: PMC9313208 DOI: 10.3390/brainsci12070942] [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: 06/22/2022] [Revised: 07/14/2022] [Accepted: 07/15/2022] [Indexed: 12/10/2022] Open
Abstract
Quantitative Susceptibility Mapping (QSM) can measure iron concentration increase in the primary motor cortex (M1) of patients with Amyotrophic Lateral Sclerosis (ALS). However, such alteration is confined to only specific regions interested by upper motor neuron pathology; therefore, mean QSM values in the entire M1 have limited diagnostic accuracy in discriminating between ALS patients and control subjects. This study investigates the diagnostic accuracy of a broader set of M1 QSM distribution indices in classifying ALS patients and controls. Mean, standard deviation, skewness and kurtosis of M1 QSM values were used either individually or as combined predictors in support vector machines. The classification performance was compared to that obtained by the radiological assessment of T2* signal hypo-intensity of M1 in susceptibility-weighted MRI. The least informative index for the classification of ALS patients and controls was the subject’s mean QSM value in M1. The highest diagnostic performance was obtained when all the distribution indices of positive QSM values in M1 were considered, which yielded a diagnostic accuracy of 0.90, with sensitivity = 0.89 and specificity = 1. The radiological assessment of M1 yielded a diagnostic accuracy of 0.79, with sensitivity = 0.76 and specificity = 0.90. The joint evaluation of QSM distribution indices could support the clinical examination in ALS diagnosis and patient monitoring.
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Zhang ZY, Jiang HR, Sun XR, Wang XC, Niu Q, Meng HX, Du JF, Yang GQ, Zhang H, Tan Y. Monitoring mild cognitive impairment of workers exposed to occupational aluminium based on quantitative susceptibility mapping. Clin Radiol 2022; 77:840-847. [PMID: 35817609 DOI: 10.1016/j.crad.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 05/28/2022] [Accepted: 06/08/2022] [Indexed: 11/19/2022]
Abstract
AIM To investigate the diagnostic value of quantitative susceptibility mapping (QSM) in mild cognitive impairment (MCI) of aluminium (Al) workers. MATERIALS AND METHODS The basic data of 53 workers in an Al factory were collected and divided into the MCI group and normal control (NC) group by Montreal Cognitive Assessment (MoCA) scores. All participants were tested for plasma Al concentration and had magnetic resonance imaging (MRI). The QSM values of many areas of the brain were delineated and measured. Independent two-sample t-tests or non-parametric tests were used to compare the parameter values between the two groups. Spearman's correlation analysis was performed between QSM values, MoCA scores, and plasma Al concentration. The receiver operating characteristic curve and z test were performed to assess diagnostic efficacy and the best parameter. RESULTS There was no difference in age and educational level. Plasma Al concentration of the MCI group was higher than that of NC group (p=0.057). QSM values of the left hippocampus, left dentate nucleus, right substantia nigra, and left putamen in MCI group were higher than that of NC group (p<0.05), and the left hippocampus had the best diagnostic efficacy. QSM values correlated negatively with MoCA scores. No correlation was found between QSM values and plasma Al concentration (p>0.05). CONCLUSION QSM might be a neuroimaging marker for the diagnosis of MCI. The left hippocampus showed the best diagnostic efficacy. Plasma Al concentration of the MCI group was higher than that of the NC group. A correlation between QSM and plasma Al concentration was not found.
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Affiliation(s)
- Z Y Zhang
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
| | - H R Jiang
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
| | - X R Sun
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
| | - X C Wang
- Department of Radiology, First Clinical Medical Hospital, Shanxi Medical University, 85 Jiefang South Road, Taiyuan 030001, Shanxi Province, China
| | - Q Niu
- School of Public Health, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
| | - H X Meng
- School of Public Health, Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
| | - J F Du
- Department of Radiology, First Clinical Medical Hospital, Shanxi Medical University, 85 Jiefang South Road, Taiyuan 030001, Shanxi Province, China
| | - G Q Yang
- Department of Radiology, First Clinical Medical Hospital, Shanxi Medical University, 85 Jiefang South Road, Taiyuan 030001, Shanxi Province, China
| | - H Zhang
- Department of Radiology, First Clinical Medical Hospital, Shanxi Medical University, 85 Jiefang South Road, Taiyuan 030001, Shanxi Province, China.
| | - Y Tan
- Department of Radiology, First Clinical Medical Hospital, Shanxi Medical University, 85 Jiefang South Road, Taiyuan 030001, Shanxi Province, China.
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Harada T, Kudo K, Fujima N, Yoshikawa M, Ikebe Y, Sato R, Shirai T, Bito Y, Uwano I, Miyata M. Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications. Radiographics 2022; 42:1161-1176. [PMID: 35522577 DOI: 10.1148/rg.210054] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic susceptibility. Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and is a substance-specific value. Recently, QSM has been widely used to estimate various levels of substances in the brain, including iron, hemosiderin, and deoxyhemoglobin (paramagnetism), as well as calcification (diamagnetism). By visualizing iron distribution in the brain, it is possible to identify anatomic structures that are not evident on conventional images and to evaluate various neurodegenerative diseases. It has been challenging to apply QSM in areas outside the brain because of motion artifacts from respiration and heartbeats, as well as the presence of fat, which has a different frequency to the proton. In this review, the authors provide a brief overview of the theoretical background and analyze methods of converting MRI phase images to QSM. Moreover, we provide an overview of the current clinical applications of QSM. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Taisuke Harada
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Kohsuke Kudo
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Noriyuki Fujima
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Masato Yoshikawa
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Yohei Ikebe
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Ryota Sato
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Toru Shirai
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Yoshitaka Bito
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Ikuko Uwano
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Mari Miyata
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
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