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Andersson Forsman O, Sjöström H, Svenningsson P, Granberg T. Combined MR quantitative susceptibility mapping and multi-shell diffusion in Parkinson's disease. J Neuroimaging 2024. [PMID: 39004781 DOI: 10.1111/jon.13222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 07/05/2024] [Accepted: 07/05/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND AND PURPOSE Quantitative susceptibility mapping (QSM), neurite orientation dispersion and density imaging (NODDI), and the g-ratio have separately shown differences between Parkinson's disease (PD) and healthy controls. The g-ratio has, however, not been studied in PD in the substantia nigra (SN) and the putamen. A combination of these methods could also potentially be a complementary imaging biomarker for PD. This study aimed to assess the diagnostic performance of QSM, NODDI, the g-ratio, and a combined QSM-NODDI imaging marker in the SN and putamen of PD patients. METHODS In this prospective study, the diagnostic performance of median region of interest values was compared in a cohort of 15 participants with PD and 14 healthy controls after manual segmentation. The diagnostic performance was assessed using the area under curve (AUC) for the receiving operator characteristic. RESULTS Median QSM in the contralateral SN identified PD with AUC 0.77, and median isotropic volume fraction identified PD in the ipsilateral SN with AUC 0.68. A combined NODDI-QSM marker improved diagnostic performance (AUC 0.80). No significant differences were found in the g-ratio. CONCLUSION A combination of median QSM and median isotropic volume fraction improves the differentiation of PD from healthy controls and is a potential biomarker in the diagnostics of PD. This confirms previously reported results indicating that combining QSM and NODDI modestly improves differentiation of PD.
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Affiliation(s)
| | - Henrik Sjöström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Neurology, Academic Specialist Center, Stockholm, Sweden
| | - Per Svenningsson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Neurology, Academic Specialist Center, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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2
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Zarkali A, Thomas GEC, Zetterberg H, Weil RS. Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions. Nat Commun 2024; 15:5661. [PMID: 38969680 PMCID: PMC11226684 DOI: 10.1038/s41467-024-49949-9] [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: 07/26/2023] [Accepted: 06/19/2024] [Indexed: 07/07/2024] Open
Abstract
A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.
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Affiliation(s)
- Angeliki Zarkali
- Dementia Research Centre, Institute of Neurology, UCL, London, UK.
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Rimona S Weil
- Dementia Research Centre, Institute of Neurology, UCL, London, UK
- Department of Advanced Neuroimaging, UCL, London, UK
- Movement Disorders Centre, UCL, London, UK
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3
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Drenthen GS, Elschot EP, van der Knaap N, Uher D, Voorter PHM, Backes WH, Jansen JFA, van der Thiel MM. Imaging Interstitial Fluid With MRI: A Narrative Review on the Associations of Altered Interstitial Fluid With Vascular and Neurodegenerative Abnormalities. J Magn Reson Imaging 2024; 60:40-53. [PMID: 37823526 DOI: 10.1002/jmri.29056] [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: 07/14/2023] [Revised: 09/27/2023] [Accepted: 09/27/2023] [Indexed: 10/13/2023] Open
Abstract
Interstitial fluid (ISF) refers to the fluid between the parenchymal cells and along the perivascular spaces (PVS). ISF plays a crucial role in delivering nutrients and clearing waste products from the brain. This narrative review focuses on the use of MRI techniques to measure various ISF characteristics in humans. The complementary value of contrast-enhanced and noncontrast-enhanced techniques is highlighted. While contrast-enhanced MRI methods allow measurement of ISF transport and flow, they lack quantitative assessment of ISF properties. Noninvasive MRI techniques, including multi-b-value diffusion imaging, free-water-imaging, T2-decay imaging, and DTI along the PVS, offer promising alternatives to derive ISF measures, such as ISF volume and diffusivity. The emerging role of these MRI techniques in investigating ISF alterations in neurodegenerative diseases (eg, Alzheimer's disease and Parkinson's disease) and cerebrovascular diseases (eg, cerebral small vessel disease and stroke) is discussed. This review also emphasizes current challenges of ISF imaging, such as the microscopic scale at which ISF has to be measured, and discusses potential focus points for future research to overcome these challenges, for example, the use of high-resolution imaging techniques. Noninvasive MRI methods for measuring ISF characteristics hold significant potential and may have a high clinical impact in understanding the pathophysiology of neurodegenerative and cerebrovascular disorders, as well as in evaluating the efficacy of ISF-targeted therapies in clinical trials. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gerhard S Drenthen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Elles P Elschot
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Noa van der Knaap
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Daniel Uher
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Paulien H M Voorter
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Walter H Backes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Merel M van der Thiel
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
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Jin J, Su D, Zhang J, Lam JST, Zhou J, Feng T. Iron deposition in subcortical nuclei of Parkinson's disease: A meta-analysis of quantitative iron-sensitive magnetic resonance imaging studies. Chin Med J (Engl) 2024:00029330-990000000-01086. [PMID: 38809051 DOI: 10.1097/cm9.0000000000003167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Iron deposition plays a crucial role in the pathophysiology of Parkinson's disease (PD), yet the distribution pattern of iron deposition in the subcortical nuclei has been inconsistent across previous studies. We aimed to assess the difference patterns of iron deposition detected by quantitative iron-sensitive magnetic resonance imaging (MRI) between patients with PD and patients with atypical parkinsonian syndromes (APSs), and between patients with PD and healthy controls (HCs). METHODS A systematic literature search was conducted on PubMed, Embase, and Web of Science databases to identify studies investigating the iron content in PD patients using the iron-sensitive MRI techniques (R2* and quantitative susceptibility mapping [QSM]), up until May 1, 2023. The quality assessment of case-control and cohort studies was performed using the Newcastle-Ottawa Scale, whereas diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. Standardized mean differences and summary estimates of sensitivity, specificity, and area under the curve (AUC) were calculated for iron content, using a random effects model. We also conducted the subgroup-analysis based on the MRI sequence and meta-regression. RESULTS Seventy-seven studies with 3192 PD, 209 multiple system atrophy (MSA), 174 progressive supranuclear palsy (PSP), and 2447 HCs were included. Elevated iron content in substantia nigra (SN) pars reticulata (P <0.001) and compacta (P <0.001), SN (P <0.001), red nucleus (RN, P <0.001), globus pallidus (P <0.001), putamen (PUT, P = 0.009), and thalamus (P = 0.046) were found in PD patients compared with HCs. PD patients showed lower iron content in PUT (P <0.001), RN (P = 0.003), SN (P = 0.017), and caudate nucleus (P = 0.027) than MSA patients, and lower iron content in RN (P = 0.001), PUT (P <0.001), globus pallidus (P = 0.004), SN (P = 0.015), and caudate nucleus (P = 0.001) than PSP patients. The highest diagnostic accuracy distinguishing PD from HCs was observed in SN (AUC: 0.85), and that distinguishing PD from MSA was found in PUT (AUC: 0.90). In addition, the best diagnostic performance was achieved in the RN for distinguishing PD from PSP (AUC: 0.84). CONCLUSION Quantitative iron-sensitive MRI could quantitatively detect the iron content of subcortical nuclei in PD and APSs, while it may be insufficient to accurately diagnose PD. Future studies are needed to explore the role of multimodal MRI in the diagnosis of PD. REGISTRISION PROSPERO; CRD42022344413.
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Affiliation(s)
- Jianing Jin
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Dongning Su
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Junjiao Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Joyce S T Lam
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA 02131, United States
- Harvard Medical School, Boston, MA 02210, United States
| | - Tao Feng
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
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Guan X, Lancione M, Ayton S, Dusek P, Langkammer C, Zhang M. Neuroimaging of Parkinson's disease by quantitative susceptibility mapping. Neuroimage 2024; 289:120547. [PMID: 38373677 DOI: 10.1016/j.neuroimage.2024.120547] [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: 07/30/2023] [Revised: 02/02/2024] [Accepted: 02/17/2024] [Indexed: 02/21/2024] Open
Abstract
Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.
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Affiliation(s)
- Xiaojun Guan
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Joint Laboratory of Clinical Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31009, China
| | - Marta Lancione
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Scott Ayton
- Florey Institute, The University of Melbourne, Australia
| | - Petr Dusek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czechia; Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Auenbruggerplatz 22, Prague 8036, Czechia
| | | | - Minming Zhang
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Joint Laboratory of Clinical Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31009, China.
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Wang X, Zhu Z, Sun J, Jia L, Cai L, Chen Q, Yang W, Wang Y, Zhang Y, Guo S, Liu W, Yang Z, Zhao P, Wang Z, Lv H. Changes in iron load in specific brain areas lead to neurodegenerative diseases of the central nervous system. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110903. [PMID: 38036035 DOI: 10.1016/j.pnpbp.2023.110903] [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: 07/30/2023] [Revised: 11/24/2023] [Accepted: 11/24/2023] [Indexed: 12/02/2023]
Abstract
The causes of neurodegenerative diseases remain largely elusive, increasing their personal and societal impacts. To reveal the causal effects of iron load on Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis and multiple sclerosis, we used Mendelian randomisation and brain imaging data from a UK Biobank genome-wide association study of 39,691 brain imaging samples (predominantly of European origin). Using susceptibility-weighted images, which reflect iron load, we analysed genetically significant brain regions. Inverse variance weighting was used as the main estimate, while MR Egger and weighted median were used to detect heterogeneity and pleiotropy. Nine clear associations were obtained. For AD and PD, an increased iron load was causative: the right pallidum for AD and the right caudate, left caudate and right accumbens for PD. However, a reduced iron load was identified in the right and left caudate for multiple sclerosis, the bilateral hippocampus for mixed vascular dementia and the left thalamus and bilateral accumbens for subcortical vascular dementia. Thus, changes in iron load in different brain regions have causal effects on neurodegenerative diseases. Our results are crucial for understanding the pathogenesis and investigating the treatment of these diseases.
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Affiliation(s)
- Xinghao Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Zaimin Zhu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, People's Republic of China
| | - Jing Sun
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Li Jia
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Linkun Cai
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China; School of Biological Science and Medical Engineering, Beihang University, No.37 XueYuan Road, Beijing 100191, People's Republic of China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Wenbo Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Yiling Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Yufan Zhang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Sihui Guo
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Wenjuan Liu
- Department of Radiology, Aerospace Center Hospital, Beijing, People's Republic of China; Peking University Aerospace School of Clinical Medicine, Beijing 100049, People's Republic of China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Pengfei Zhao
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China.
| | - Han Lv
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing 100050, People's Republic of China.
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Chen M, Wang Y, Zhang C, Li J, Li Z, Guan X, Bao J, Zhang Y, Cheng J, Wei H. Free water and iron content in the substantia nigra at different stages of Parkinson's disease. Eur J Radiol 2023; 167:111030. [PMID: 37579561 DOI: 10.1016/j.ejrad.2023.111030] [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: 03/29/2023] [Revised: 07/28/2023] [Accepted: 08/08/2023] [Indexed: 08/16/2023]
Abstract
PURPOSE Abnormalities in free water (FW) and susceptibility values exist in the substantia nigra (SN) of patients with Parkinson's disease (PD), but their role in characterizing the disease processes remains uncertain. This study investigated these values at various SN locations and stages of PD, and their relationship with clinical symptoms. METHOD FW and quantitative susceptibility mapping (QSM) values were evaluated in the anterior and posterior SN, along with swallow-tail-sign (STS) ratings, in patients with PD (early-stage: n = 39; middle-to-advanced-stage: n = 97) and healthy controls (n = 82). The correlation between these indices and motor and non-motor symptoms, and their capability to distinguish PD from healthy controls, were also examined. RESULTS Increased FW in the anterior and posterior SN and increased QSM values in the posterior SN were observed in both early-stage and middle-to-advanced-stage PD patients (p < 0.05). However, there was no significant difference in FW, QSM values, or STS ratings among patients at different stages. FW and QSM values correlated with motor symptoms in middle-to-advanced-stage patients (p < 0.05), while STS ratings were associated with non-motor symptoms (p < 0.05). Additionally, combining FW and QSM values in the posterior SN with STS ratings in logistic regression showed better performance in distinguishing PD (area under curve = 0.931) compared to using STS ratings alone (area under curve = 0.880). CONCLUSIONS Findings suggest elevated FW and iron content in PD at different stages, with dissociation in SN location between the two indices. Elevated signals are related to the motor symptom severity in middle-to-advanced-stage patients, and may have the potential for PD diagnosis and symptom assessment.
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Affiliation(s)
- Mingxing Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yutong Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chunyan Zhang
- Functional Magnetic Resonance and Molecular Imaging Key Laboratory of Henan Province, Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Jun Li
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China; Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhenghao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianfeng Bao
- Functional Magnetic Resonance and Molecular Imaging Key Laboratory of Henan Province, Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jingliang Cheng
- Functional Magnetic Resonance and Molecular Imaging Key Laboratory of Henan Province, Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
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