1
|
van der Pluijm M, Wengler K, Reijers PN, Cassidy CM, Tjong Tjin Joe K, de Peuter OR, Horga G, Booij J, de Haan L, van de Giessen E. Neuromelanin-Sensitive MRI as Candidate Marker for Treatment Resistance in First-Episode Schizophrenia. Am J Psychiatry 2024; 181:512-519. [PMID: 38476044 PMCID: PMC11227872 DOI: 10.1176/appi.ajp.20220780] [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] [Indexed: 03/14/2024]
Abstract
OBJECTIVE Markers for treatment resistance in schizophrenia are needed to reduce delays in effective treatment. Nigrostriatal hyperdopaminergic function plays a critical role in the pathology of schizophrenia, yet antipsychotic nonresponders do not show increased dopamine function. Neuromelanin-sensitive MRI (NM-MRI), which indirectly measures dopamine function in the substantia nigra, has potential as a noninvasive marker for nonresponders. Increased NM-MRI signal has been shown in psychosis, but has not yet been assessed in nonresponders. In this study, the authors investigated whether nonresponders show lower NM-MRI signal than responders. METHODS NM-MRI scans were acquired in 79 patients with first-episode psychosis and 20 matched healthy control subjects. Treatment response was assessed at a 6-month follow-up. An a priori voxel-wise analysis within the substantia nigra tested the relation between NM-MRI signal and treatment response in patients. RESULTS Fifteen patients were classified as nonresponders and 47 patients as responders. Seventeen patients were excluded, primarily because of medication nonadherence or change in diagnosis. Voxel-wise analysis revealed 297 significant voxels in the ventral tier of the substantia nigra that were negatively associated with treatment response. Nonresponders and healthy control subjects had significantly lower NM-MRI signal than responders. Receiver operating characteristic curve analysis showed that NM-MRI signal separated nonresponders with areas under the curve between 0.62 and 0.85. In addition, NM-MRI signal in patients did not change over 6 months. CONCLUSIONS These findings provide further evidence for dopaminergic differences between medication responders and nonresponders and support the potential of NM-MRI as a clinically applicable marker for treatment resistance in schizophrenia.
Collapse
Affiliation(s)
- Marieke van der Pluijm
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Kenneth Wengler
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Pascalle N Reijers
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Clifford M Cassidy
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Kaithlyn Tjong Tjin Joe
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Olav R de Peuter
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Guillermo Horga
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Jan Booij
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Lieuwe de Haan
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine (van der Pluijm, Reijers, Tjong Tjin Joe, Booij, van de Giessen) and Department of Psychiatry (van der Pluijm, de Haan), Amsterdam UMC, University of Amsterdam, Amsterdam; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York (Wengler, Horga); Royal's Institute of Mental Health Research, University of Ottawa, Ottawa (Cassidy); Arkin Mental Health Care, Amsterdam (de Peuter)
| |
Collapse
|
2
|
Morandini HAE, Watson PA, Barbaro P, Rao P. Brain iron concentration in childhood ADHD: A systematic review of neuroimaging studies. J Psychiatr Res 2024; 173:200-209. [PMID: 38547742 DOI: 10.1016/j.jpsychires.2024.03.035] [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: 10/31/2023] [Revised: 02/23/2024] [Accepted: 03/22/2024] [Indexed: 04/17/2024]
Abstract
Iron deficiency may play a role in the pathophysiology of Attention Deficit/Hyperactivity Disorder (ADHD). Due to its preponderant function in monoamine catecholamine and myelin synthesis, brain iron concentration may be of primary interest in the investigation of iron dysregulation in ADHD. This study reviewed current evidence of brain iron abnormalities in children and adolescents with ADHD using magnetic resonance imaging methods, such as relaxometry and quantitative susceptibility mapping, to assess brain iron estimates. The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A literature search was performed for studies published between January 1, 2008 and July 7, 2023 in Medline, Scopus and Proquest. Regions of interest, brain iron index values and phenotypical information were extracted from the relevant studies. Risk of bias was assessed using a modified version of the National Heart, Lung, and Blood Institute quality assessment tool. Seven cross-sectional studies comparing brain iron estimates in children with ADHD with neurotypical children were included. Significantly reduced brain iron content in medication-naïve children with ADHD was a consistent finding. Two studies found psychostimulant use may increase and normalize brain iron concentration in children with ADHD. The findings were consistent across the studies despite differing methodologies and may lay the early foundation for the recognition of a potential biomarker in ADHD, although longitudinal prospective neuroimaging studies using larger sample sizes are required. Lastly, the effects of iron supplementation on brain iron concentration in children with ADHD need to be elucidated.
Collapse
Affiliation(s)
- Hugo A E Morandini
- Complex Attention and Hyperactivity Disorders Service, Child and Adolescent Health Services, Perth, WA, Australia; Division of Psychiatry, UWA Medical School, Faculty of Health & Medical Sciences, The University of Western Australia, Australia.
| | - Prue A Watson
- Complex Attention and Hyperactivity Disorders Service, Child and Adolescent Health Services, Perth, WA, Australia
| | - Parma Barbaro
- Complex Attention and Hyperactivity Disorders Service, Child and Adolescent Health Services, Perth, WA, Australia
| | - Pradeep Rao
- Complex Attention and Hyperactivity Disorders Service, Child and Adolescent Health Services, Perth, WA, Australia; Division of Psychiatry, UWA Medical School, Faculty of Health & Medical Sciences, The University of Western Australia, Australia; Telethon Kids Institute, Perth, Australia
| |
Collapse
|
3
|
Yan S, Lu J, Li Y, Zhu H, Tian T, Qin Y, Zhu W. Large-scale functional network connectivity mediates the association between nigral neuromelanin hypopigmentation and motor impairment in Parkinson's disease. Brain Struct Funct 2024; 229:843-852. [PMID: 38347222 DOI: 10.1007/s00429-024-02761-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/09/2024] [Indexed: 04/10/2024]
Abstract
Neuromelanin hypopigmentation within substantia nigra pars compacta (SNc) reflects the loss of pigmented neurons, which in turn contributes to the dysfunction of the nigrostriatal and striato-cortical pathways in Parkinson's disease (PD). Our study aims to investigate the relationships between SN degeneration manifested by neuromelanin reduction, functional connectivity (FC) among large-scale brain networks, and motor impairment in PD. This study included 68 idiopathic PD patients and 32 age-, sex- and education level-matched healthy controls who underwent neuromelanin-sensitive magnetic resonance imaging (MRI), functional MRI, and motor assessments. SN integrity was measured using the subregional contrast-to-noise ratio calculated from neuromelanin-sensitive MRI. Resting-state FC maps were obtained based on the independent component analysis. Subsequently, we performed partial correlation and mediation analyses in SN degeneration, network disruption, and motor impairment for PD patients. We found significantly decreased neuromelanin within SN and widely altered inter-network FCs, mainly involved in the basal ganglia (BG), sensorimotor and frontoparietal networks in PD. In addition, decreased neuromelanin content was negatively correlated with the dorsal sensorimotor network (dSMN)-medial visual network connection (P = 0.012) and dSMN-BG connection (P = 0.004). Importantly, the effect of SN neuromelanin hypopigmentation on motor symptom severity in PD is partially mediated by the increased connectivity strength between BG and dSMN (indirect effect = - 1.358, 95% CI: - 2.997, - 0.147). Our results advanced our understanding of the interactions between neuromelanin hypopigmentation in SN and altered FCs of functional networks in PD and suggested the potential of multimodal metrics for early diagnosis and monitoring the response to therapies.
Collapse
Affiliation(s)
- Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Jun Lu
- Department of CT & MRI, The First Affiliated Hospital, College of Medicine, Shihezi University, 107 North Second Road, Shihezi, China
| | - Yuanhao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Hongquan Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Tian Tian
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, JiefangAvenue, Wuhan, 430030, China.
| |
Collapse
|
4
|
Trujillo P, Aumann MA, Claassen DO. Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function. Brain 2024; 147:337-351. [PMID: 37669320 PMCID: PMC10834262 DOI: 10.1093/brain/awad300] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/17/2023] [Accepted: 08/20/2023] [Indexed: 09/07/2023] Open
Abstract
Disruptions to dopamine and noradrenergic neurotransmission are noted in several neurodegenerative and psychiatric disorders. Neuromelanin-sensitive (NM)-MRI offers a non-invasive approach to visualize and quantify the structural and functional integrity of the substantia nigra and locus coeruleus. This method may aid in the diagnosis and quantification of longitudinal changes of disease and could provide a stratification tool for predicting treatment success of pharmacological interventions targeting the dopaminergic and noradrenergic systems. Given the growing clinical interest in NM-MRI, understanding the contrast mechanisms that generate this signal is crucial for appropriate interpretation of NM-MRI outcomes and for the continued development of quantitative MRI biomarkers that assess disease severity and progression. To date, most studies associate NM-MRI measurements to the content of the neuromelanin pigment and/or density of neuromelanin-containing neurons, while recent studies suggest that the main source of the NM-MRI contrast is not the presence of neuromelanin but the high-water content in the dopaminergic and noradrenergic neurons. In this review, we consider the biological and physical basis for the NM-MRI contrast and discuss a wide range of interpretations of NM-MRI. We describe different acquisition and image processing approaches and discuss how these methods could be improved and standardized to facilitate large-scale multisite studies and translation into clinical use. We review the potential clinical applications in neurological and psychiatric disorders and the promise of NM-MRI as a biomarker of disease, and finally, we discuss the current limitations of NM-MRI that need to be addressed before this technique can be utilized as a biomarker and translated into clinical practice and offer suggestions for future research.
Collapse
Affiliation(s)
- Paula Trujillo
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Megan A Aumann
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Daniel O Claassen
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| |
Collapse
|
5
|
Huenchuguala S, Segura-Aguilar J. On the Role of Iron in Idiopathic Parkinson's Disease. Biomedicines 2023; 11:3094. [PMID: 38002094 PMCID: PMC10669582 DOI: 10.3390/biomedicines11113094] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/04/2023] [Accepted: 11/17/2023] [Indexed: 11/26/2023] Open
Abstract
The transition metal characteristics of iron allow it to play a fundamental role in several essential aspects of human life such as the transport of oxygen through hemoglobin or the transport of electrons in the mitochondrial respiratory chain coupled to the synthesis of ATP. However, an excess or deficiency of iron is related to certain pathologies. The maintenance of iron homeostasis is essential to avoid certain pathologies related to iron excess or deficiency. The existence of iron deposits in postmortem tissues of Parkinson's patients has been interpreted as evidence that iron plays a fundamental role in the degenerative process of the nigrostriatal system in this disease. The use of iron chelators has been successful in the treatment of diseases such as transfusion-dependent thalassemia and pantothenate kinase-associated neurodegeneration. However, a clinical study with the iron chelator deferiprone in patients with Parkinson's disease has not shown positive effects but rather worsened clinical symptoms. This suggests that iron may not play a role in the degenerative process of Parkinson's disease.
Collapse
Affiliation(s)
- Sandro Huenchuguala
- Escuela de Tecnología Médica, Facultad de Salud, Universidad Santo Tomás, Santiago 8370003, Chile
| | - Juan Segura-Aguilar
- Molecular & Clinical Pharmacology, Institute of Biomedical Sciences (ICBM), Faculty of Medicine, University of Chile, Santiago 8380453, Chile
| |
Collapse
|
6
|
Hu R, Gao B, Tian S, Liu Y, Jiang Y, Li W, Li Y, Song Q, Wang W, Miao Y. Regional high iron deposition on quantitative susceptibility mapping correlates with cognitive decline in type 2 diabetes mellitus. Front Neurosci 2023; 17:1061156. [PMID: 36793541 PMCID: PMC9922715 DOI: 10.3389/fnins.2023.1061156] [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: 10/19/2022] [Accepted: 01/10/2023] [Indexed: 01/31/2023] Open
Abstract
Objective To quantitatively evaluate the iron deposition and volume changes in deep gray nuclei according to threshold-method of quantitative susceptibility mapping (QSM) acquired by strategically acquired gradient echo (STAGE) sequence, and to analyze the correlation between the magnetic susceptibility values (MSV) and cognitive scores in type 2 diabetes mellitus (T2DM) patients. Methods Twenty-nine patients with T2DM and 24 healthy controls (HC) matched by age and gender were recruited in this prospective study. QSM images were used to evaluate whole-structural volumes (Vwh), regional magnetic susceptibility values (MSVRII), and volumes (VRII) in high-iron regions in nine gray nuclei. All QSM data were compared between groups. Receiver operating characteristic (ROC) analysis was used to assess the discriminating ability between groups. The predictive model from single and combined QSM parameters was also established using logistic regression analysis. The correlation between MSVRII and cognitive scores was further analyzed. Multiple comparisons of all statistical values were corrected by false discovery rate (FDR). A statistically significant P-value was set at 0.05. Results Compared with HC group, the MSVRII of all gray matter nuclei in T2DM were increased by 5.1-14.8%, with significant differences found in bilateral head of caudate nucleus (HCN), right putamen (PUT), right globus pallidus (GP), and left dentate nucleus (DN) (P < 0.05). The Vwh of most gray nucleus in T2DM group were decreased by 1.5-16.9% except bilateral subthalamic nucleus (STN). Significant differences were found in bilateral HCN, bilateral red nucleus (RN), and bilateral substantia nigra (SN) (P < 0.05). VRII was increased in bilateral GP, bilateral PUT (P < 0.05). VRII/Vwh was also increased in bilateral GP, bilateral PUT, bilateral SN, left HCN and right STN (P < 0.05). Compared with the single QSM parameter, the combined parameter showed the largest area under curve (AUC) of 0.86, with a sensitivity of 87.5% and specificity of 75.9%. The MSVRII in the right GP was strongly associated with List A Long-delay free recall (List A LDFR) scores (r = -0.590, P = 0.009). Conclusion In T2DM patients, excessive and heterogeneous iron deposition as well as volume loss occurs in deep gray nuclei. The MSV in high iron regions can better evaluate the distribution of iron, which is related to the decline of cognitive function.
Collapse
|
7
|
Association between Beta Oscillations from Subthalamic Nucleus and Quantitative Susceptibility Mapping in Deep Gray Matter Structures in Parkinson's Disease. Brain Sci 2023; 13:brainsci13010081. [PMID: 36672062 PMCID: PMC9857066 DOI: 10.3390/brainsci13010081] [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: 10/18/2022] [Revised: 12/15/2022] [Accepted: 12/27/2022] [Indexed: 01/03/2023] Open
Abstract
This study aimed to investigate the association between beta oscillations and brain iron deposition. Beta oscillations were filtered from the microelectrode recordings of local field potentials (LFP) in the subthalamic nucleus (STN), and the ratio of the power spectral density of beta oscillations (PSDXb) to that of the LFP signals was calculated. Iron deposition in the deep gray matter (DGM) structures was indirectly assessed using quantitative susceptibility mapping (QSM). The Unified Parkinson's Disease Rating Scale (UPDRS), part III, was used to assess the severity of symptoms. Spearman correlation coefficients were applied to assess the associations of PSDXb with QSM values in the DGM structures and the severity of symptoms. PSDXb showed a significant positive correlation with the average QSM values in DGM structures, including caudate and substantia nigra (SN) (p = 0.008 and 0.044). Similarly, the PSDXb showed significant negative correlations with the severity of symptoms, including axial symptoms and the gait in the medicine-off state (p = 0.006 for both). The abnormal iron metabolism in the SN and striatum pathways may be one of the underlying mechanisms for the occurrence of abnormal beta oscillations in the STN, and beta oscillations may serve as important pathophysiological biomarkers of PD.
Collapse
|
8
|
Tessema AW, Lee H, Gong Y, Cho H, Adem HM, Lyu I, Lee JH, Cho H. Automated volumetric determination of high R 2 * regions in substantia nigra: A feasibility study of quantifying substantia nigra atrophy in progressive supranuclear palsy. NMR IN BIOMEDICINE 2022; 35:e4795. [PMID: 35775868 DOI: 10.1002/nbm.4795] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 06/26/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
The establishment of an unbiased protocol for the automated volumetric measurement of iron-rich regions in the substantia nigra (SN) is clinically important for diagnosing neurodegenerative diseases exhibiting midbrain atrophy, such as progressive supranuclear palsy (PSP). This study aimed to automatically quantify the volume and surface properties of the iron-rich 3D regions in the SN using the quantitative MRI-R2 * map. Three hundred and sixty-seven slices of R2 * map and susceptibility-weighted imaging (SWI) at 3-T MRI from healthy control (HC) individuals and Parkinson's disease (PD) patients were used to train customized U-net++ convolutional neural network based on expert-segmented masks. Age- and sex-matched participants were selected from HC, PD, and PSP groups to automate the volumetric determination of iron-rich areas in the SN. Dice similarity coefficient values between expert-segmented and detected masks from the proposed network were 0.91 ± 0.07 for R2 * maps and 0.89 ± 0.08 for SWI. Reductions in iron-rich SN volume from the R2 * map (SWI) were observed in PSP with area under the receiver operating characteristic curve values of 0.96 (0.89) and 0.98 (0.92) compared with HC and PD, respectively. The mean curvature of the PSP showed SN deformation along the side closer to the red nucleus. We demonstrated the automated volumetric measurement of iron-rich regions in the SN using deep learning can quantify the SN atrophy in PSP compared with PD and HC.
Collapse
Affiliation(s)
- Abel Worku Tessema
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
- School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia
| | - Hansol Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Yelim Gong
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Hwapyeong Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Hamdia Murad Adem
- School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia
| | - Ilwoo Lyu
- Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Jae-Hyeok Lee
- Department of Neurology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, South Korea
| | - HyungJoon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| |
Collapse
|
9
|
Gaurav R, Valabrègue R, Yahia-Chérif L, Mangone G, Narayanan S, Arnulf I, Vidailhet M, Corvol JC, Lehéricy S. NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network. Neuroimage Clin 2022; 36:103250. [PMID: 36451356 PMCID: PMC9668659 DOI: 10.1016/j.nicl.2022.103250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/15/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI. OBJECTIVE Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI. METHODS We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (Cvol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach's alpha and Bland-Altman plots were estimated to assess inter-method consistency. RESULTS Using both methods, Vol, Cvol, NSI and CNR measurements differed between PD and HV with an effect of sex for Cvol and CNR. ICC values between the methods demonstrated optimal agreement for Cvol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were -27.4 % and -17.7 % for Vol, -30.0 % and -22.2 % for Cvol, -15.8 % and -14.4 % for NSI, -17.1 % and -16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for Cvol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for Cvol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements. CONCLUSIONS We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.
Collapse
Affiliation(s)
- Rahul Gaurav
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; Movement Investigations and Therapeutics Team (MOV'IT), ICM, Paris, France; Center for NeuroImaging Research - CENIR, ICM, Paris, France.
| | - Romain Valabrègue
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; Center for NeuroImaging Research - CENIR, ICM, Paris, France
| | - Lydia Yahia-Chérif
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; Center for NeuroImaging Research - CENIR, ICM, Paris, France
| | - Graziella Mangone
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; INSERM, Clinical Investigation Center for Neurosciences (CIC), Pitié-Salpêtrière Hospital, Paris, France
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Isabelle Arnulf
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; Movement Investigations and Therapeutics Team (MOV'IT), ICM, Paris, France; Sleep Disorders Unit, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Marie Vidailhet
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; Movement Investigations and Therapeutics Team (MOV'IT), ICM, Paris, France; Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Jean-Christophe Corvol
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; INSERM, Clinical Investigation Center for Neurosciences (CIC), Pitié-Salpêtrière Hospital, Paris, France; Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Stéphane Lehéricy
- Paris Brain Institute - ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France; Movement Investigations and Therapeutics Team (MOV'IT), ICM, Paris, France; Center for NeuroImaging Research - CENIR, ICM, Paris, France; Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| |
Collapse
|
10
|
Ravanfar P, Syeda WT, Jayaram M, Rushmore RJ, Moffat B, Lin AP, Lyall AE, Merritt AH, Yaghmaie N, Laskaris L, Luza S, Opazo CM, Liberg B, Chakravarty MM, Devenyi GA, Desmond P, Cropley VL, Makris N, Shenton ME, Bush AI, Velakoulis D, Pantelis C. In Vivo 7-Tesla MRI Investigation of Brain Iron and Its Metabolic Correlates in Chronic Schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:86. [PMID: 36289238 PMCID: PMC9605948 DOI: 10.1038/s41537-022-00293-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 09/30/2022] [Indexed: 06/16/2023]
Abstract
Brain iron is central to dopaminergic neurotransmission, a key component in schizophrenia pathology. Iron can also generate oxidative stress, which is one proposed mechanism for gray matter volume reduction in schizophrenia. The role of brain iron in schizophrenia and its potential link to oxidative stress has not been previously examined. In this study, we used 7-Tesla MRI quantitative susceptibility mapping (QSM), magnetic resonance spectroscopy (MRS), and structural T1 imaging in 12 individuals with chronic schizophrenia and 14 healthy age-matched controls. In schizophrenia, there were higher QSM values in bilateral putamen and higher concentrations of phosphocreatine and lactate in caudal anterior cingulate cortex (caCC). Network-based correlation analysis of QSM across corticostriatal pathways as well as the correlation between QSM, MRS, and volume, showed distinct patterns between groups. This study introduces increased iron in the putamen in schizophrenia in addition to network-wide disturbances of iron and metabolic status.
Collapse
Affiliation(s)
- Parsa Ravanfar
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Warda T Syeda
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Mahesh Jayaram
- Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Australia
| | - R Jarrett Rushmore
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Morphometric Analysis (CMA), Massachusetts General Hospital, Charlestown, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Bradford Moffat
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC, Australia
| | - Alexander P Lin
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amanda E Lyall
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Antonia H Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Negin Yaghmaie
- Melbourne Brain Centre Imaging Unit, Department of Radiology, University of Melbourne, Parkville, VIC, Australia
- Department of Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia
| | - Liliana Laskaris
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Sandra Luza
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience & Mental Health, and The University of Melbourne, Parkville, VIC, Australia
| | - Carlos M Opazo
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience & Mental Health, and The University of Melbourne, Parkville, VIC, Australia
| | - Benny Liberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - M Mallar Chakravarty
- Cerebral Imaging Center, Douglas Research Centre, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Gabriel A Devenyi
- Cerebral Imaging Center, Douglas Research Centre, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Patricia Desmond
- Department of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Morphometric Analysis (CMA), Massachusetts General Hospital, Charlestown, MA, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ashley I Bush
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience & Mental Health, and The University of Melbourne, Parkville, VIC, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia.
| |
Collapse
|
11
|
Iron Deposition in Brain: Does Aging Matter? Int J Mol Sci 2022; 23:ijms231710018. [PMID: 36077413 PMCID: PMC9456423 DOI: 10.3390/ijms231710018] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
The alteration of iron homeostasis related to the aging process is responsible for increased iron levels, potentially leading to oxidative cellular damage. Iron is modulated in the Central Nervous System in a very sensitive manner and an abnormal accumulation of iron in the brain has been proposed as a biomarker of neurodegeneration. However, contrasting results have been presented regarding brain iron accumulation and the potential link with other factors during aging and neurodegeneration. Such uncertainties partly depend on the fact that different techniques can be used to estimate the distribution of iron in the brain, e.g., indirect (e.g., MRI) or direct (post-mortem estimation) approaches. Furthermore, recent evidence suggests that the propensity of brain cells to accumulate excessive iron as a function of aging largely depends on their anatomical location. This review aims to collect the available data on the association between iron concentration in the brain and aging, shedding light on potential mechanisms that may be helpful in the detection of physiological neurodegeneration processes and neurodegenerative diseases such as Alzheimer's disease.
Collapse
|
12
|
Brammerloh M, Kirilina E, Alkemade A, Bazin PL, Jantzen C, Jäger C, Herrler A, Pine KJ, Gowland PA, Morawski M, Forstmann BU, Weiskopf N. Swallow Tail Sign: Revisited. Radiology 2022; 305:674-677. [PMID: 35972361 DOI: 10.1148/radiol.212696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Malte Brammerloh
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Evgeniya Kirilina
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Anneke Alkemade
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Pierre-Louis Bazin
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Caroline Jantzen
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Carsten Jäger
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Andreas Herrler
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Kerrin J Pine
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Penny A Gowland
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Markus Morawski
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Birte U Forstmann
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Nikolaus Weiskopf
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| |
Collapse
|
13
|
Vroegindeweij LHP, Wielopolski PA, Boon AJW, Wilson JHP, Verdijk RM, Zheng S, Bonnet S, Bossoni L, van der Weerd L, Hernandez-Tamames JA, Langendonk JG. MR imaging for the quantitative assessment of brain iron in aceruloplasminemia: A postmortem validation study. Neuroimage 2021; 245:118752. [PMID: 34823024 DOI: 10.1016/j.neuroimage.2021.118752] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 10/15/2021] [Accepted: 11/20/2021] [Indexed: 11/18/2022] Open
Abstract
AIMS Non-invasive measures of brain iron content would be of great benefit in neurodegeneration with brain iron accumulation (NBIA) to serve as a biomarker for disease progression and evaluation of iron chelation therapy. Although magnetic resonance imaging (MRI) provides several quantitative measures of brain iron content, none of these have been validated for patients with a severely increased cerebral iron burden. We aimed to validate R2* as a quantitative measure of brain iron content in aceruloplasminemia, the most severely iron-loaded NBIA phenotype. METHODS Tissue samples from 50 gray- and white matter regions of a postmortem aceruloplasminemia brain and control subject were scanned at 1.5 T to obtain R2*, and biochemically analyzed with inductively coupled plasma mass spectrometry. For gray matter samples of the aceruloplasminemia brain, sample R2* values were compared with postmortem in situ MRI data that had been obtained from the same subject at 3 T - in situ R2*. Relationships between R2* and tissue iron concentration were determined by linear regression analyses. RESULTS Median iron concentrations throughout the whole aceruloplasminemia brain were 10 to 15 times higher than in the control subject, and R2* was linearly associated with iron concentration. For gray matter samples of the aceruloplasminemia subject with an iron concentration up to 1000 mg/kg, 91% of variation in R2* could be explained by iron, and in situ R2* at 3 T and sample R2* at 1.5 T were highly correlated. For white matter regions of the aceruloplasminemia brain, 85% of variation in R2* could be explained by iron. CONCLUSIONS R2* is highly sensitive to variations in iron concentration in the severely iron-loaded brain, and might be used as a non-invasive measure of brain iron content in aceruloplasminemia and potentially other NBIA disorders.
Collapse
Affiliation(s)
- Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Piotr A Wielopolski
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Agnita J W Boon
- Department of Neurology, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - J H Paul Wilson
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Rob M Verdijk
- Department of Pathology, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Sipeng Zheng
- Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands
| | - Sylvestre Bonnet
- Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands
| | - Lucia Bossoni
- C.J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Louise van der Weerd
- C.J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| |
Collapse
|
14
|
Bossoni L, Hegeman-Kleinn I, van Duinen SG, Bulk M, Vroegindeweij LHP, Langendonk JG, Hirschler L, Webb A, van der Weerd L. Off-resonance saturation as an MRI method to quantify mineral- iron in the post-mortem brain. Magn Reson Med 2021; 87:1276-1288. [PMID: 34655092 PMCID: PMC9293166 DOI: 10.1002/mrm.29041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 09/17/2021] [Accepted: 09/20/2021] [Indexed: 12/24/2022]
Abstract
Purpose To employ an off‐resonance saturation method to measure the mineral‐iron pool in the postmortem brain, which is an endogenous contrast agent that can give information on cellular iron status. Methods An off‐resonance saturation acquisition protocol was implemented on a 7 Tesla preclinical scanner, and the contrast maps were fitted to an established analytical model. The method was validated by correlation and Bland‐Altman analysis on a ferritin‐containing phantom. Mineral‐iron maps were obtained from postmortem tissue of patients with neurological diseases characterized by brain iron accumulation, that is, Alzheimer disease, Huntington disease, and aceruloplasminemia, and validated with histology. Transverse relaxation rate and magnetic susceptibility values were used for comparison. Results In postmortem tissue, the mineral‐iron contrast colocalizes with histological iron staining in all the cases. Iron concentrations obtained via the off‐resonance saturation method are in agreement with literature. Conclusions Off‐resonance saturation is an effective way to detect iron in gray matter structures and partially mitigate for the presence of myelin. If a reference region with little iron is available in the tissue, the method can produce quantitative iron maps. This method is applicable in the study of diseases characterized by brain iron accumulation and can complement existing iron‐sensitive parametric methods.
Collapse
Affiliation(s)
- Lucia Bossoni
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Sjoerd G van Duinen
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marjolein Bulk
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Neurology, Alzheimer Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lydiane Hirschler
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Andrew Webb
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Louise van der Weerd
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| |
Collapse
|
15
|
Arnold I, Schwendener N, Lombardo P, Jackowski C, Zech WD. 3Tesla post-mortem MRI quantification of anatomical brain structures. Forensic Sci Int 2021; 327:110984. [PMID: 34482282 DOI: 10.1016/j.forsciint.2021.110984] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 03/04/2021] [Accepted: 08/17/2021] [Indexed: 01/31/2023]
Abstract
Quantitative post-mortem magnetic resonance imaging (PMMR) allows for measurement of T1 and T2 relaxation times and proton density (PD) of brain tissue. Quantitative PMMR values may be used for advanced post-mortem neuro-imaging diagnostics such as computer aided diagnosis. So far, the quantitative T1, T2 and PD post-mortem values of regular anatomical brain structures were unknown for a 3 Tesla PMMR application. The goal of this basic research study was to evaluate the quantitative values of post-mortem brain structures for a 3 T post-mortem magnetic resonance application with regard to various corpse temperatures. In 50 forensic cases, a quantitative PMMR brain sequence was applied prior to autopsy. Measurements of T1 (in ms), T2 (in ms), and PD (in %) values of cerebrum (Group 1: frontal grey matter, frontal white matter, thalamus, caudate nucleus, globus pallidus, putamen, internal capsule) brainstem and cerebellum (Group 2: cerebral peduncle, substantia nigra, red nucleus, pons, middle cerebellar peduncle, cerebellar hemisphere, medulla oblongata) were conducted in synthetically calculated axial PMMR brain images. Assessed quantitative values were corrected for corpse temperature. Temperature dependence was observed mainly for T1 values. ANOVA testing resulted in significant differences of quantitative values between the investigated anatomical brain structures in both groups. It can be concluded that temperature corrected 3 Tesla PMMR T1, T2 and PD values are feasible for characterization and discrimination of regular anatomical brain structures. This may provide a base for future advanced diagnostics of forensically relevant brain lesions and pathology.
Collapse
Affiliation(s)
- Isabel Arnold
- Institute of Forensic Medicine, University of Bern, Switzerland
| | | | - Paolo Lombardo
- Institute of Forensic Medicine, University of Bern, Switzerland; Department of Diagnostic, Interventional and Pediatric Radiology, University of Bern, Inselspital Bern, Switzerland
| | | | - Wolf-Dieter Zech
- Institute of Forensic Medicine, University of Bern, Switzerland.
| |
Collapse
|
16
|
Gaurav R, Yahia‐Cherif L, Pyatigorskaya N, Mangone G, Biondetti E, Valabrègue R, Ewenczyk C, Hutchison RM, Cedarbaum JM, Corvol J, Vidailhet M, Lehéricy S. Longitudinal Changes in Neuromelanin MRI Signal in Parkinson's Disease: A Progression Marker. Mov Disord 2021; 36:1592-1602. [PMID: 33751655 PMCID: PMC8359265 DOI: 10.1002/mds.28531] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/07/2021] [Accepted: 01/25/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Development of reliable and accurate imaging biomarkers of dopaminergic cell neurodegeneration is necessary to facilitate therapeutic drug trials in Parkinson's disease (PD). Neuromelanin-sensitive MRI techniques have been effective in detecting neurodegeneration in the substantia nigra pars compacta (SNpc). The objective of the current study was to investigate longitudinal neuromelanin signal changes in the SNpc in PD patients. METHODS In this prospective, longitudinal, observational case-control study, we included 140 PD patients and 64 healthy volunteers divided into 2 cohorts. Cohort I included 99 early PD patients (disease duration, 1.5 ± 1.0 years) and 41 healthy volunteers analyzed at baseline (V1), where 79 PD patients and 32 healthy volunteers were rescanned after 2.0 ± 0.2 years of follow-up (V2). Cohort II included 41 progressing PD patients (disease duration, 9.3 ± 3.7 years) and 23 healthy volunteers at V1, where 30 PD patients were rescanned after 2.4 ± 0.5 years of follow-up. Subjects were scanned at 3 T MRI using 3-dimensional T1-weighted and neuromelanin-sensitive imaging. Regions of interest were delineated manually to calculate SN volumes, volumes corrected by total intracranial volume, signal-to-noise ratio, and contrast-to-noise ratio. RESULTS Results showed (1) significant reduction in volume and volume corrected by total intracranial volume between visits, greater in progressing PD than nonsignificant changes in healthy volunteers; (2) no significant effects of visit for signal intensity (signal-to-noise ratio); (3) significant interaction in volume between group and visit; (4) greater volume corrected by total intracranial volume at baseline in female patients and greater decrease in volume and increase in the contrast-to-noise ratio in progressing female PD patients compared with male patients; and (5) correlations between neuromelanin SN changes and disease severity and duration. CONCLUSIONS We observed a progressive and measurable decrease in neuromelanin-based SN signal and volume in PD, which might allow a direct noninvasive assessment of progression of SN loss and could represent a target biomarker for disease-modifying treatments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Rahul Gaurav
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
| | - Lydia Yahia‐Cherif
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
| | - Nadya Pyatigorskaya
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeuroradiologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | - Graziella Mangone
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- INSERM, Clinical Investigation Center for Neurosciences, Pitié‐Salpêtrière HospitalParisFrance
| | - Emma Biondetti
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
| | - Romain Valabrègue
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
| | - Claire Ewenczyk
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeurologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | | | | | - Jean‐Christophe Corvol
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- INSERM, Clinical Investigation Center for Neurosciences, Pitié‐Salpêtrière HospitalParisFrance
- Department of NeurologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | - Marie Vidailhet
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeurologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| | - Stéphane Lehéricy
- Paris Brain Institute– ICMCenter for NeuroImaging Research – CENIRParisFrance
- ICM, Sorbonne University, UPMC Univ Paris 06, Inserm U1127, CNRS UMRParisFrance
- ICM Team “Movement Investigations and Therapeutics” (MOV'IT)ParisFrance
- Department of NeuroradiologyPitié‐Salpêtrière Hospital, AP‐HPParisFrance
| |
Collapse
|
17
|
Brammerloh M, Morawski M, Friedrich I, Reinert T, Lange C, Pelicon P, Vavpetič P, Jankuhn S, Jäger C, Alkemade A, Balesar R, Pine K, Gavriilidis F, Trampel R, Reimer E, Arendt T, Weiskopf N, Kirilina E. Measuring the iron content of dopaminergic neurons in substantia nigra with MRI relaxometry. Neuroimage 2021; 239:118255. [PMID: 34119638 PMCID: PMC8363938 DOI: 10.1016/j.neuroimage.2021.118255] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/02/2021] [Accepted: 06/07/2021] [Indexed: 12/19/2022] Open
Abstract
Dopaminergic neurons dominate effective transverse relaxation in nigrosome 1. Ion beam microscopy reveals highest iron concentrations in dopaminergic neurons. Developed biophysical model links MRI parameters to cellular iron content. Ferritin- and neuromelanin-bound iron impact MRI parameters differently. Quantitative MRI provides a potential biomarker of iron in dopaminergic neurons.
In Parkinson’s disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 of the substantia nigra precedes motor symptoms by two decades. Methods capable of monitoring this neuronal depletion, at an early disease stage, are needed for early diagnosis and treatment monitoring. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to tissue microstructure and in particular, to iron. However, the exact mechanisms of MRI contrast in the substantia nigra are not well understood, hindering the development of powerful biomarkers. In the present report, we illuminate the contrast mechanisms in gradient and spin echo MR images in human nigrosome 1 by combining quantitative 3D iron histology and biophysical modeling with quantitative MRI on post mortem human brain tissue. We show that the dominant contribution to the effective transverse relaxation rate (R2*) in nigrosome 1 originates from iron accumulated in the neuromelanin of dopaminergic neurons. This contribution is appropriately described by a static dephasing approximation of the MRI signal. We demonstrate that the R2* contribution from dopaminergic neurons reflects the product of cell density and cellular iron concentration. These results demonstrate that the in vivo monitoring of neuronal density and iron in nigrosome 1 may be feasible with MRI and provide directions for the development of biomarkers for an early detection of dopaminergic neuron depletion in Parkinson’s disease.
Collapse
Affiliation(s)
- Malte Brammerloh
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany.
| | - Markus Morawski
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Isabel Friedrich
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Tilo Reinert
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Charlotte Lange
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Primož Pelicon
- Jožef Stefan Institute, Jamova 39, Ljubljana SI-1000, Slovenia
| | - Primož Vavpetič
- Jožef Stefan Institute, Jamova 39, Ljubljana SI-1000, Slovenia
| | - Steffen Jankuhn
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, Nieuwe Achtergracht 129B, 1001 NK Amsterdam, The Netherlands
| | - Rawien Balesar
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, Nieuwe Achtergracht 129B, 1001 NK Amsterdam, The Netherlands; The Netherlands Institute for Neuroscience, Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands
| | - Kerrin Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Filippos Gavriilidis
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Enrico Reimer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany
| | - Thomas Arendt
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, Leipzig, 04103, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Linnéstr. 5, Leipzig 04103, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, Leipzig 04103, Germany; Center for Cognitive Neuroscience Berlin, Free University Berlin, Habelschwerdter Allee 45, Berlin, 14195, Germany
| |
Collapse
|
18
|
Vroegindeweij LHP, Bossoni L, Boon AJW, Wilson JHP, Bulk M, Labra-Muñoz J, Huber M, Webb A, van der Weerd L, Langendonk JG. Quantification of different iron forms in the aceruloplasminemia brain to explore iron-related neurodegeneration. NEUROIMAGE-CLINICAL 2021; 30:102657. [PMID: 33839643 PMCID: PMC8055714 DOI: 10.1016/j.nicl.2021.102657] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/24/2021] [Accepted: 03/30/2021] [Indexed: 12/25/2022]
Abstract
Ferrihydrite-iron is the most abundant iron form in the aceruloplasminemia brain. Iron concentrations over 1 mg/g are found in deep gray matter structures. The deep gray matter contains over three times more iron than the temporal cortex. Iron-sensitive MRI contrast is primarily driven by the amount of ferrihydrite-iron. R2* is more illustrative of the pattern of iron accumulation than QSM at 7 T.
Aims Aceruloplasminemia is an ultra-rare neurodegenerative disorder associated with massive brain iron deposits, of which the molecular composition is unknown. We aimed to quantitatively determine the molecular iron forms in the aceruloplasminemia brain, and to illustrate their influence on iron-sensitive MRI metrics. Methods The inhomogeneous transverse relaxation rate (R2*) and magnetic susceptibility obtained from 7 T MRI were combined with Electron Paramagnetic Resonance (EPR) and Superconducting Quantum Interference Device (SQUID) magnetometry. The basal ganglia, thalamus, red nucleus, dentate nucleus, superior- and middle temporal gyrus and white matter of a post-mortem aceruloplasminemia brain were studied. MRI, EPR and SQUID results that had been previously obtained from the temporal cortex of healthy controls were included for comparison. Results The brain iron pool in aceruloplasminemia detected in this study consisted of EPR-detectable Fe3+ ions, magnetic Fe3+ embedded in the core of ferritin and hemosiderin (ferrihydrite-iron), and magnetic Fe3+ embedded in oxidized magnetite/maghemite minerals (maghemite-iron). Ferrihydrite-iron represented above 90% of all iron and was the main driver of iron-sensitive MRI contrast. Although deep gray matter structures were three times richer in ferrihydrite-iron than the temporal cortex, ferrihydrite-iron was already six times more abundant in the temporal cortex of the patient with aceruloplasminemia compared to the healthy situation (162 µg/g vs. 27 µg/g), on average. The concentrations of Fe3+ ions and maghemite-iron in the temporal cortex in aceruloplasminemia were within the range of those in the control subjects. Conclusions Iron-related neurodegeneration in aceruloplasminemia is primarily associated with an increase in ferrihydrite-iron, with ferrihydrite-iron being the major determinant of iron-sensitive MRI contrast.
Collapse
Affiliation(s)
- Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Lucia Bossoni
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Agnita J W Boon
- Department of Neurology, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - J H Paul Wilson
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Marjolein Bulk
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jacqueline Labra-Muñoz
- Department of Physics, Huygens-Kamerlingh Onnes Laboratory, Leiden University, Niels Bohrweg 2, 2333CA Leiden, the Netherlands; Kavli Institute of Nanoscience, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, the Netherlands
| | - Martina Huber
- Department of Physics, Huygens-Kamerlingh Onnes Laboratory, Leiden University, Niels Bohrweg 2, 2333CA Leiden, the Netherlands
| | - Andrew Webb
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Louise van der Weerd
- C. J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| |
Collapse
|
19
|
Lee TW, Chen CY, Chen K, Tso CW, Lin HH, Lai YLL, Hsu FT, Chung HW, Liu HS. Evaluation of the Swallow-Tail Sign and Correlations of Neuromelanin Signal with Susceptibility and Relaxations. ACTA ACUST UNITED AC 2021; 7:107-119. [PMID: 33801685 PMCID: PMC8103261 DOI: 10.3390/tomography7020010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 03/22/2021] [Indexed: 11/16/2022]
Abstract
The presence of a swallow-tail sign in the nigrosome-1 with hyperintense signal shown on the susceptibility-weighted imaging (SWI) has been shown to be sensitive in detecting the abnormal iron deposits in this area. A systematic evaluation in healthy subjects is required before this tool can be recommended in a widespread application. We evaluated a simple and practical SWI approach using a multiecho gradient-echo sequence with an improved contrast-to-noise ratio (CNR). We also evaluated the association of the neuromelanin imaging contrast behavior with the susceptibility and relaxation measurements. Twenty-five older and 23 young healthy adults were evaluated. The CNRs of the nigrosome-1 were compared along with method and group. Correlations of the nigrosome-1 neuromelanin signal in the neuromelanin-sensitive imaging with CNRs in the susceptibility, T1 and T2 mappings were examined. Two different coils were used to confirm the reproducibility. Compared with the single-echo, multiecho SWI can improve the CNR of the swallow-tail sign. We found significant correlations between neuromelanin signal and CNRs in the susceptibility and T2 mappings, and T1 value. The older subjects exhibited increased CNRs compared with the young adults. No significant difference was observed in the measurements between 20 and 64 channels. The multiecho technique allows the high-quality nigrosome-1 images in SWI and allows for a joint analysis of T2* and quantitative-susceptibility mapping at high spatial resolution. The correlations of neuromelanin-sensitive imaging with susceptibility and T2 imply that the iron content in the nigrosome-1 may have significant influences on the hyperintensity of neuromelanin in the magnetization transfer-related contrast.
Collapse
Affiliation(s)
- Tzu-Wei Lee
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 110, Taiwan; (T.-W.L.); (K.C.); (C.-W.T.)
| | - Cheng-Yu Chen
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei Medical University, Taipei 110, Taiwan;
- Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan
| | - Kuan Chen
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 110, Taiwan; (T.-W.L.); (K.C.); (C.-W.T.)
| | - Chao-Wei Tso
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 110, Taiwan; (T.-W.L.); (K.C.); (C.-W.T.)
| | - Hui-Hsien Lin
- CT/MR Division, Rotary Trading Co., Ltd., Taipei 115, Taiwan;
| | - Ying-Liang Larry Lai
- Ph.D. Program for Neural Regenerative Medicine, College of Medical Science and Technology, Taipei Medical University and National Health Research Institutes, Taipei 110, Taiwan;
| | - Fei-Ting Hsu
- Department of Biological Science and Technology, China Medical University, Taichung 406, Taiwan;
| | - Hsiao-Wen Chung
- Department of Electrical Engineering, National Taiwan University, Taipei 110, Taiwan;
| | - Hua-Shan Liu
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 110, Taiwan; (T.-W.L.); (K.C.); (C.-W.T.)
- International Ph.D. Program in Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 110, Taiwan
- Correspondence: ; Tel.: +886-2-6638-2736 (ext. 1363)
| |
Collapse
|
20
|
Ravanfar P, Loi SM, Syeda WT, Van Rheenen TE, Bush AI, Desmond P, Cropley VL, Lane DJR, Opazo CM, Moffat BA, Velakoulis D, Pantelis C. Systematic Review: Quantitative Susceptibility Mapping (QSM) of Brain Iron Profile in Neurodegenerative Diseases. Front Neurosci 2021; 15:618435. [PMID: 33679303 PMCID: PMC7930077 DOI: 10.3389/fnins.2021.618435] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 01/07/2021] [Indexed: 12/11/2022] Open
Abstract
Iron has been increasingly implicated in the pathology of neurodegenerative diseases. In the past decade, development of the new magnetic resonance imaging technique, quantitative susceptibility mapping (QSM), has enabled for the more comprehensive investigation of iron distribution in the brain. The aim of this systematic review was to provide a synthesis of the findings from existing QSM studies in neurodegenerative diseases. We identified 80 records by searching MEDLINE, Embase, Scopus, and PsycInfo databases. The disorders investigated in these studies included Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Wilson's disease, Huntington's disease, Friedreich's ataxia, spinocerebellar ataxia, Fabry disease, myotonic dystrophy, pantothenate-kinase-associated neurodegeneration, and mitochondrial membrane protein-associated neurodegeneration. As a general pattern, QSM revealed increased magnetic susceptibility (suggestive of increased iron content) in the brain regions associated with the pathology of each disorder, such as the amygdala and caudate nucleus in Alzheimer's disease, the substantia nigra in Parkinson's disease, motor cortex in amyotrophic lateral sclerosis, basal ganglia in Huntington's disease, and cerebellar dentate nucleus in Friedreich's ataxia. Furthermore, the increased magnetic susceptibility correlated with disease duration and severity of clinical features in some disorders. Although the number of studies is still limited in most of the neurodegenerative diseases, the existing evidence suggests that QSM can be a promising tool in the investigation of neurodegeneration.
Collapse
Affiliation(s)
- Parsa Ravanfar
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Samantha M Loi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Warda T Syeda
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Ashley I Bush
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience & Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Patricia Desmond
- Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia.,Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Centre for Mental Health, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Darius J R Lane
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience & Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Carlos M Opazo
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Bradford A Moffat
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, The University of Melbourne, Parkville, VIC, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.,Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| |
Collapse
|
21
|
He N, Ghassaban K, Huang P, Jokar M, Wang Y, Cheng Z, Jin Z, Li Y, Sethi SK, He Y, Chen Y, Gharabaghi S, Chen S, Yan F, Haacke EM. Imaging iron and neuromelanin simultaneously using a single 3D gradient echo magnetization transfer sequence: Combining neuromelanin, iron and the nigrosome-1 sign as complementary imaging biomarkers in early stage Parkinson's disease. Neuroimage 2021; 230:117810. [PMID: 33524572 DOI: 10.1016/j.neuroimage.2021.117810] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 01/15/2021] [Accepted: 01/23/2021] [Indexed: 10/22/2022] Open
Abstract
Diagnosing early stage Parkinson's disease (PD) is still a clinical challenge. Previous studies using iron, neuromelanin (NM) or the Nigrosome-1 (N1) sign in the substantia nigra (SN) by themselves have been unable to provide sufficiently high diagnostic performance for these methods to be adopted clinically. Our goal in this study was to extract the NM complex volume, iron content and volume representing the entire SN, and the N1 sign as potential complementary imaging biomarkers using a single 3D magnetization transfer contrast (MTC) gradient echo sequence and to evaluate their diagnostic performance and clinical correlations in early stage PD. A total of 40 early stage idiopathic PD subjects and 40 age- and sex-matched healthy controls (HCs) were imaged at 3T. NM boundaries (representing the SN pars compacta (SNpc) and parabrachial pigmented nucleus) and iron boundaries representing the total SN (SNpc and SN pars reticulata) were determined semi-automatically using a dynamic programming (DP) boundary detection algorithm. Receiver operating characteristic analyses were performed to evaluate the utility of these imaging biomarkers in diagnosing early stage PD. A correlation analysis was used to study the relationship between these imaging measures and the clinical scales. We also introduced the concept of NM and total iron overlap volumes to demonstrate the loss of NM relative to the iron containing SN. Furthermore, all 80 cases were evaluated for the N1 sign independently. The NM and SN volumes were lower while the iron content was higher in the SN for PD subjects compared to HCs. Interestingly, the PD subjects with bilateral loss of the N1 sign had the highest iron content. The area under the curve (AUC) values for the average of both hemispheres for single measures were: .960 for NM complex volume; .788 for total SN volume; .740 for SN iron content and .891 for the N1 sign. Combining NM complex volume with each of the following measures through binary logistic regression led to AUC values for the averaged right and left sides of: .976 for total iron content; .969 for total SN volume, .965 for overlap volume and .983 for the N1 sign. We found a negative correlation between SN volume and UPDRS-III (R2 = .22, p = .002). While the N1 sign performed well, it does not contain any information about iron content or NM quantitatively, therefore, marrying this sign with the NM and iron measures provides a better physiological explanation of what is happening when the N1 sign disappears in PD subjects. In summary, the combination of NM complex volume, SN volume, iron content and the N1 sign as derived from a single MTC sequence provides complementary information for understanding and diagnosing early stage PD.
Collapse
Affiliation(s)
- Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China.
| | - Kiarash Ghassaban
- Department of Radiology, Wayne State University, 3990 John R, Detroit, Michigan 48201, USA; Department of Biomedical Engineering, Wayne State University, 3990 John R, Detroit, Michigan 48201, USA
| | - Pei Huang
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Ying Wang
- Department of Radiology, Wayne State University, 3990 John R, Detroit, Michigan 48201, USA; SpinTech, Inc., Bingham Farms, Michigan 48025, USA
| | - Zenghui Cheng
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Zhijia Jin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Sean K Sethi
- Department of Radiology, Wayne State University, 3990 John R, Detroit, Michigan 48201, USA; SpinTech, Inc., Bingham Farms, Michigan 48025, USA
| | - Yixi He
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yongsheng Chen
- Department of Neurology, Wayne State University, 4201 St. Antoine, Detroit, Michigan 48201, USA
| | | | - Shengdi Chen
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China.
| | - E Mark Haacke
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, China; Department of Radiology, Wayne State University, 3990 John R, Detroit, Michigan 48201, USA; Department of Biomedical Engineering, Wayne State University, 3990 John R, Detroit, Michigan 48201, USA; SpinTech, Inc., Bingham Farms, Michigan 48025, USA; Department of Neurology, Wayne State University, 4201 St. Antoine, Detroit, Michigan 48201, USA
| |
Collapse
|
22
|
Angelova PR, Esteras N, Abramov AY. Mitochondria and lipid peroxidation in the mechanism of neurodegeneration: Finding ways for prevention. Med Res Rev 2020; 41:770-784. [PMID: 32656815 DOI: 10.1002/med.21712] [Citation(s) in RCA: 134] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/23/2020] [Accepted: 07/04/2020] [Indexed: 12/14/2022]
Abstract
The world's population aging progression renders age-related neurodegenerative diseases to be one of the biggest unsolved problems of modern society. Despite the progress in studying the development of pathology, finding ways for modifying neurodegenerative disorders remains a high priority. One common feature of neurodegenerative diseases is mitochondrial dysfunction and overproduction of reactive oxygen species, resulting in oxidative stress. Although lipid peroxidation is one of the markers for oxidative stress, it also plays an important role in cell physiology, including activation of phospholipases and stimulation of signaling cascades. Excessive lipid peroxidation is a hallmark for most neurodegenerative disorders including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and many other neurological conditions. The products of lipid peroxidation have been shown to be the trigger for necrotic, apoptotic, and more specifically for oxidative stress-related, that is, ferroptosis and neuronal cell death. Here we discuss the involvement of lipid peroxidation in the mechanism of neuronal loss and some novel therapeutic directions to oppose it.
Collapse
Affiliation(s)
- Plamena R Angelova
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
| | - Noemi Esteras
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
| | - Andrey Y Abramov
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
| |
Collapse
|
23
|
MRI T 2 and T 2* relaxometry to visualize neuromelanin in the dorsal substantia nigra pars compacta. Neuroimage 2020; 211:116625. [PMID: 32058001 DOI: 10.1016/j.neuroimage.2020.116625] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 02/05/2020] [Accepted: 02/06/2020] [Indexed: 12/19/2022] Open
Abstract
Visualizing gradual changes in neuromelanin distribution within the substantia nigra is an important metric used to monitor the progression of Parkinsonism. This study aimed to identify the origin of the mismatch region between magnetic resonance transverse relaxation times (T2 and T2*) in the substantia nigra and investigate its feasibility and implications for in vivo detection of neuromelanin as a clinical biomarker. The relationships between neuromelanin distribution assessed by histological staining and the area of T2 and T2* mismatch determined by high- and low-resolution magnetic resonance relaxometry at 7T were directly compared in two normal and one depigmented substantia nigra collected at postmortem. In vivo feasibility of assessing T2 and T2* mismatch, clinically, was investigated using 3T magnetic resonance imaging. In the normal postmortem substantia nigra tissue, the T2 and T2* mismatch region exhibiting a linear pattern was strongly colocalized with neuromelanin distribution along the dorsal substantia nigra pars compacta, but a negligible amount of dorsal mismatch was observed in the depigmented brain. The regions of T2 and T2* mismatch from MRI, neuromelanin pigments from histology, and elevated iron signals from mass spectrometry were spatially overlapped for a normal postmortem brain. In preliminary in vivo studies, a similar, linear T2 and T2* mismatch region was observed in the dorsal area of the substantia nigra in eight normal subjects; this mismatch was significantly obscured in eight Parkinson's disease patients. The length of the dorsal linear mismatch line based on the T2*-T2 mask was significantly shorter in the Parkinson's disease patients compared to normal controls; this result was corroborated by reduced striatal uptake of [18F] FP-CIT dopamine transporters assessed by positron emission tomography scans. In conclusion, the measurement of T2 and T2* mismatch could serve as a complementary imaging biomarker to visualize the dorsal region of the substantia nigra pars compacta, which contains large amounts of neuromelanin.
Collapse
|
24
|
Vaillancourt DE, Lehericy S. Illuminating basal ganglia and beyond in Parkinson's disease. Mov Disord 2019; 33:1373-1375. [PMID: 30311976 DOI: 10.1002/mds.27483] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 08/08/2018] [Indexed: 12/14/2022] Open
Affiliation(s)
- David E Vaillancourt
- Department of Applied Physiology and Kinesiology, Biomedical Engineering, Neurology, University of Florida, Gainesville, Florida, USA
| | - Stéphane Lehericy
- Institut du Cerveau et de la Moelle - ICM, Centre de NeuroImagerie de Recherche - CENIR, Sorbonne Universités, UPMC Univ Paris 06, Paris, France
| |
Collapse
|
25
|
De Barros A, Arribarat G, Combis J, Chaynes P, Péran P. Matching ex vivo MRI With Iron Histology: Pearls and Pitfalls. Front Neuroanat 2019; 13:68. [PMID: 31333421 PMCID: PMC6616088 DOI: 10.3389/fnana.2019.00068] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 06/19/2019] [Indexed: 12/12/2022] Open
Abstract
Iron levels in the brain can be estimated using newly developed specific magnetic resonance imaging (MRI) sequences. This technique has several applications, especially in neurodegenerative disorders like Alzheimer's disease or Parkinson's disease. Coupling ex vivo MRI with histology allows neuroscientists to better understand what they see in the images. Iron is one of the most extensively studied elements, both by MRI and using histological or physical techniques. Researchers were initially only able to make visual comparisons between MRI images and different types of iron staining, but the emergence of specific MRI sequences like R2* or quantitative susceptibility mapping meant that quantification became possible, requiring correlations with physical techniques. Today, with advances in MRI and image post-processing, it is possible to look for MRI/histology correlations by matching the two sorts of images. For the result to be acceptable, the choice of methodology is crucial, as there are hidden pitfalls every step of the way. In order to review the advantages and limitations of ex vivo MRI correlation with iron-based histology, we reviewed all the relevant articles dealing with the topic in humans. We provide separate assessments of qualitative and quantitative studies, and after summarizing the significant results, we emphasize all the pitfalls that may be encountered.
Collapse
Affiliation(s)
- Amaury De Barros
- Toulouse NeuroImaging Center, University of Toulouse Paul Sabatier-INSERM, Toulouse, France
- Department of Anatomy, Toulouse Faculty of Medicine, Toulouse, France
| | - Germain Arribarat
- Toulouse NeuroImaging Center, University of Toulouse Paul Sabatier-INSERM, Toulouse, France
| | - Jeanne Combis
- Toulouse NeuroImaging Center, University of Toulouse Paul Sabatier-INSERM, Toulouse, France
| | - Patrick Chaynes
- Department of Anatomy, Toulouse Faculty of Medicine, Toulouse, France
| | - Patrice Péran
- Toulouse NeuroImaging Center, University of Toulouse Paul Sabatier-INSERM, Toulouse, France
| |
Collapse
|
26
|
Cassidy CM, Zucca FA, Girgis RR, Baker SC, Weinstein JJ, Sharp ME, Bellei C, Valmadre A, Vanegas N, Kegeles LS, Brucato G, Kang UJ, Sulzer D, Zecca L, Abi-Dargham A, Horga G. Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain. Proc Natl Acad Sci U S A 2019; 116:5108-5117. [PMID: 30796187 PMCID: PMC6421437 DOI: 10.1073/pnas.1807983116] [Citation(s) in RCA: 128] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Neuromelanin-sensitive MRI (NM-MRI) purports to detect the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). Interindividual variability in dopamine function may result in varying levels of NM accumulation in the SN; however, the ability of NM-MRI to measure dopamine function in nonneurodegenerative conditions has not been established. Here, we validated that NM-MRI signal intensity in postmortem midbrain specimens correlated with regional NM concentration even in the absence of neurodegeneration, a prerequisite for its use as a proxy for dopamine function. We then validated a voxelwise NM-MRI approach with sufficient anatomical sensitivity to resolve SN subregions. Using this approach and a multimodal dataset of molecular PET and fMRI data, we further showed the NM-MRI signal was related to both dopamine release in the dorsal striatum and resting blood flow within the SN. These results suggest that NM-MRI signal in the SN is a proxy for function of dopamine neurons in the nigrostriatal pathway. As a proof of concept for its clinical utility, we show that the NM-MRI signal correlated to severity of psychosis in schizophrenia and individuals at risk for schizophrenia, consistent with the well-established dysfunction of the nigrostriatal pathway in psychosis. Our results indicate that noninvasive NM-MRI is a promising tool that could have diverse research and clinical applications to investigate in vivo the role of dopamine in neuropsychiatric illness.
Collapse
Affiliation(s)
- Clifford M Cassidy
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032;
- University of Ottawa Institute of Mental Health Research, affiliated with The Royal, Ottawa, ON K1Z 8N3, Canada
| | - Fabio A Zucca
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, 20090 Milan, Italy
| | - Ragy R Girgis
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
| | - Seth C Baker
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
| | - Jodi J Weinstein
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
- Department of Psychiatry, Stony Brook University, Stony Brook, NY 11794
| | - Madeleine E Sharp
- Department of Neurology, Columbia University Medical Center, New York, NY 10032
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 2B4, Canada
| | - Chiara Bellei
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, 20090 Milan, Italy
| | - Alice Valmadre
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, 20090 Milan, Italy
| | - Nora Vanegas
- Department of Neurology, Columbia University Medical Center, New York, NY 10032
| | - Lawrence S Kegeles
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
| | - Gary Brucato
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
| | - Un Jung Kang
- Department of Neurology, Columbia University Medical Center, New York, NY 10032
| | - David Sulzer
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
- Department of Neurology, Columbia University Medical Center, New York, NY 10032
| | - Luigi Zecca
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, 20090 Milan, Italy
| | - Anissa Abi-Dargham
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032
- Department of Psychiatry, Stony Brook University, Stony Brook, NY 11794
| | - Guillermo Horga
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Medical Center, New York, NY 10032;
| |
Collapse
|
27
|
Lin F, Prince MR, Spincemaille P, Wang Y. Patents on Quantitative Susceptibility Mapping (QSM) of Tissue Magnetism. Recent Pat Biotechnol 2018; 13:90-113. [PMID: 30556508 DOI: 10.2174/1872208313666181217112745] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 12/04/2018] [Accepted: 12/11/2018] [Indexed: 01/06/2023]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) depicts biodistributions of tissue magnetic susceptibility sources, including endogenous iron and calcifications, as well as exogenous paramagnetic contrast agents and probes. When comparing QSM with simple susceptibility weighted MRI, QSM eliminates blooming artifacts and shows reproducible tissue susceptibility maps independent of field strength and scanner manufacturer over a broad range of image acquisition parameters. For patient care, QSM promises to inform diagnosis, guide surgery, gauge medication, and monitor drug delivery. The Bayesian framework using MRI phase data and structural prior knowledge has made QSM sufficiently robust and accurate for routine clinical practice. OBJECTIVE To address the lack of a summary of US patents that is valuable for QSM product development and dissemination into the MRI community. METHOD We searched the USPTO Full-Text and Image Database for patents relevant to QSM technology innovation. We analyzed the claims of each patent to characterize the main invented method and we investigated data on clinical utility. RESULTS We identified 17 QSM patents; 13 were implemented clinically, covering various aspects of QSM technology, including the Bayesian framework, background field removal, numerical optimization solver, zero filling, and zero-TE phase. CONCLUSION Our patent search identified patents that enable QSM technology for imaging the brain and other tissues. QSM can be applied to study a wide range of diseases including neurological diseases, liver iron disorders, tissue ischemia, and osteoporosis. MRI manufacturers can develop QSM products for more seamless integration into existing MRI scanners to improve medical care.
Collapse
Affiliation(s)
- Feng Lin
- School of Law, City University of Hong Kong, Hong Kong, China
| | - Martin R Prince
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
| | - Pascal Spincemaille
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States.,Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| |
Collapse
|
28
|
Kau T, Hametner S, Endmayr V, Deistung A, Prihoda M, Haimburger E, Menard C, Haider T, Höftberger R, Robinson S, Reichenbach JR, Lassmann H, Traxler H, Trattnig S, Grabner G. Microvessels may Confound the “Swallow Tail Sign” in Normal Aged Midbrains: A Postmortem 7 T SW-MRI Study. J Neuroimaging 2018; 29:65-69. [DOI: 10.1111/jon.12576] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 10/21/2018] [Accepted: 10/22/2018] [Indexed: 12/25/2022] Open
Affiliation(s)
- Thomas Kau
- Department of Radiologic Technology; Carinthia University of Applied Sciences; Klagenfurt Austria
- Institute of Radiology; Villach General Hospital; Villach Austria
| | - Simon Hametner
- Center for Brain Research; Medical University of Vienna; Vienna Austria
| | - Verena Endmayr
- Center for Brain Research; Medical University of Vienna; Vienna Austria
| | - Andreas Deistung
- Medical Physics Group, Institute for Diagnostic and Interventional Radiology; Jena University Hospital-Friedrich Schiller-University; Jena Germany
- Section of Experimental Neurology, Department of Neurology; Essen University Hospital; Essen Germany
| | - Max Prihoda
- Department of Radiologic Technology; Carinthia University of Applied Sciences; Klagenfurt Austria
| | - Evelin Haimburger
- Department of Radiologic Technology; Carinthia University of Applied Sciences; Klagenfurt Austria
| | - Christian Menard
- Department of Medical Engineering; Carinthia University of Applied Sciences; Klagenfurt Austria
| | - Thomas Haider
- Department of Orthopedics and Trauma Surgery; Medical University of Vienna; Vienna Austria
| | - Romana Höftberger
- Institute of Neurology; Medical University of Vienna; Vienna Austria
| | - Simon Robinson
- Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Centre; Medical University of Vienna; Vienna Austria
| | - Jürgen R. Reichenbach
- Medical Physics Group, Institute for Diagnostic and Interventional Radiology; Jena University Hospital-Friedrich Schiller-University; Jena Germany
| | - Hans Lassmann
- Center for Brain Research; Medical University of Vienna; Vienna Austria
| | - Hannes Traxler
- Center of Anatomy and Cell Biology; Medical University of Vienna; Vienna Austria
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Centre; Medical University of Vienna; Vienna Austria
| | - Günther Grabner
- Department of Biomedical Imaging and Image-guided Therapy, High Field Magnetic Resonance Centre; Medical University of Vienna; Vienna Austria
- Institute for Applied Research on Ageing; Carinthia University of Applied Sciences; Klagenfurt Austria
| |
Collapse
|