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Huang J, Qi X, Cheng X, Wang M, Ju H, Ding W, Zhang D. MMF-NNs: Multi-modal Multi-granularity Fusion Neural Networks for brain networks and its application to epilepsy identification. Artif Intell Med 2024; 157:102990. [PMID: 39369635 DOI: 10.1016/j.artmed.2024.102990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 07/08/2024] [Accepted: 09/26/2024] [Indexed: 10/08/2024]
Abstract
Structural and functional brain networks are generated from two scan sequences of magnetic resonance imaging data, which can provide different perspectives for describing pathological changes caused by brain diseases. Recent studies found that fusing these two types of brain networks improves performance in brain disease identification. However, traditional fusion models combine these brain networks at a single granularity, ignoring the natural multi-granularity structure of brain networks that can be divided into the edge, node, and graph levels. To this end, this paper proposes a Multi-modal Multi-granularity Fusion Neural Networks (MMF-NNs) framework for brain networks, which integrates the features of the multi-modal brain network from global (i.e., graph-level) and local (i.e., edge-level and node-level) granularities to take full advantage of the topological information. Specifically, we design an interactive feature learning module at the local granularity to learn feature maps of structural and functional brain networks at the edge-level and the node-level, respectively. In that way, these two types of brain networks are fused during the feature learning process. At the global granularity, a multi-modal decomposition bilinear pooling module is designed to learn the graph-level joint representation of these brain networks. Experiments on real epilepsy datasets demonstrate that MMF-NNs are superior to several state-of-the-art methods in epilepsy identification.
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Affiliation(s)
- Jiashuang Huang
- School of Artificial Intelligence and Computer Science, Nantong University, Nantong, 226019, China
| | - Xiaoyu Qi
- School of Artificial Intelligence and Computer Science, Nantong University, Nantong, 226019, China
| | - Xueyun Cheng
- School of Artificial Intelligence and Computer Science, Nantong University, Nantong, 226019, China
| | - Mingliang Wang
- School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Hengrong Ju
- School of Artificial Intelligence and Computer Science, Nantong University, Nantong, 226019, China
| | - Weiping Ding
- School of Artificial Intelligence and Computer Science, Nantong University, Nantong, 226019, China
| | - Daoqiang Zhang
- College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
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2
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Qu B, Tan H, Xiao M, Liu D, Wang S, Zhang Y, Chen R, Zheng G, Yang Y, Yan G, Qu X. Evaluation of the diagnostic utility on 1.5T and 3.0T 1H magnetic resonance spectroscopy for temporal lobe epilepsy. BMC Med Imaging 2023; 23:185. [PMID: 37964218 PMCID: PMC10644657 DOI: 10.1186/s12880-023-01136-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 10/24/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND 1H magnetic resonance spectroscopy (1H-MRS) can be used to study neurological disorders because it can be utilized to examine the concentrations of related metabolites. However, the diagnostic utility of different field strengths for temporal lobe epilepsy (TLE) remains unclear. The purpose of this study is to make quantitative comparisons of metabolites of TLE at 1.5T and 3.0T and evaluate their efficacy. METHODS Our retrospective collections included the single-voxel 1H-MRS of 23 TLE patients and 17 healthy control volunteers (HCs) with a 1.5T scanner, as well as 29 TLE patients and 17 HCs with a 3.0T scanner. Particularly, HCs were involved both the scans with 1.5T and 3.0T scanners, respectively. The metabolites, including the N-acetylaspartate (NAA), creatine (Cr), and choline (Cho), were measured in the left or right temporal pole of brain. To analyze the ratio of brain metabolites, including NAA/Cr, NAA/Cho, NAA/(Cho + Cr) and Cho/Cr, four controlled experiments were designed to evaluate the diagnostic utility of TLE on 1.5T and 3.0T MRS, included: (1) 1.5T TLE group vs. 1.5T HCs by the Mann-Whitney U Test, (2) 3.0T TLE group vs. 3.0T HCs by the Mann-Whitney U Test, (3) the power analysis for the 1.5T and 3.0T scanner, and (4) 3.0T HCs vs. 1.5T HCs by Paired T-Test. RESULTS Three metabolite ratios (NAA/Cr, NAA/Cho, and NAA/(Cho + Cr) showed the same statistical difference (p < 0.05) in distinguishing the TLE from HCs in the bilateral temporal poles when using 1.5T or 3.0T scanners. Similarly, the power analysis demonstrated that four metabolite ratios (NAA/Cr, NAA/Cho, NAA/(Cho + Cr), Cho/Cr) had similar distinction abilities between 1.5T and 3.0T scanner, denoting both 1.5T and 3.0T scanners were provided with similar sensitivities and reproducibilities for metabolites detection. Moreover, the metabolite ratios of the same healthy volunteers were not statistically different between 1.5T and 3.0T scanners, except for NAA/Cho (p < 0.05). CONCLUSIONS 1.5T and 3.0T scanners may have comparable diagnostic potential when 1H-MRS was used to diagnose patients with TLE.
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Affiliation(s)
- Biao Qu
- Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China
| | - Hejuan Tan
- Institute of Artificial Intelligence, Xiamen University, Xiamen, China
| | - Min Xiao
- Institute of Artificial Intelligence, Xiamen University, Xiamen, China
| | - Dongbao Liu
- Biomedical Intelligent Cloud R&D Center, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Department of Electronic Science, Xiamen University, Xiamen, China
| | - Shijin Wang
- Department of Information & Computational Mathematics, Xiamen University, Xiamen, China
| | - Yiwen Zhang
- Department of Neurology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China
| | - Runhan Chen
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Gaofeng Zheng
- Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China
| | - Yonggui Yang
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China.
| | - Gen Yan
- Department of Radiology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China.
| | - Xiaobo Qu
- Biomedical Intelligent Cloud R&D Center, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Department of Electronic Science, Xiamen University, Xiamen, China.
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3
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Veeraiah P, Jansen JFA. Multinuclear Magnetic Resonance Spectroscopy at Ultra-High-Field: Assessing Human Cerebral Metabolism in Healthy and Diseased States. Metabolites 2023; 13:metabo13040577. [PMID: 37110235 PMCID: PMC10143499 DOI: 10.3390/metabo13040577] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/06/2023] [Accepted: 04/17/2023] [Indexed: 04/29/2023] Open
Abstract
The brain is a highly energetic organ. Although the brain can consume metabolic substrates, such as lactate, glycogen, and ketone bodies, the energy metabolism in a healthy adult brain mainly relies on glucose provided via blood. The cerebral metabolism of glucose produces energy and a wide variety of intermediate metabolites. Since cerebral metabolic alterations have been repeatedly implicated in several brain disorders, understanding changes in metabolite levels and corresponding cell-specific neurotransmitter fluxes through different substrate utilization may highlight the underlying mechanisms that can be exploited to diagnose or treat various brain disorders. Magnetic resonance spectroscopy (MRS) is a noninvasive tool to measure tissue metabolism in vivo. 1H-MRS is widely applied in research at clinical field strengths (≤3T) to measure mostly high abundant metabolites. In addition, X-nuclei MRS including, 13C, 2H, 17O, and 31P, are also very promising. Exploiting the higher sensitivity at ultra-high-field (>4T; UHF) strengths enables obtaining unique insights into different aspects of the substrate metabolism towards measuring cell-specific metabolic fluxes in vivo. This review provides an overview about the potential role of multinuclear MRS (1H, 13C, 2H, 17O, and 31P) at UHF to assess the cerebral metabolism and the metabolic insights obtained by applying these techniques in both healthy and diseased states.
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Affiliation(s)
- Pandichelvam Veeraiah
- Scannexus (Ultra-High-Field MRI Center), 6229 EV Maastricht, The Netherlands
- Faculty of Health Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6229 HX Maastricht, The Netherlands
- School for Mental Health and Neuroscience, Maastricht University, 6229 ER Maastricht, The Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands
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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.
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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.
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Lucas A, Nanga RPR, Hadar P, Chen S, Gibson A, Oechsel K, Elliott MA, Stein JM, Das S, Reddy R, Detre JA, Davis KA. Mapping hippocampal glutamate in mesial temporal lobe epilepsy with glutamate weighted CEST (GluCEST) imaging. Hum Brain Mapp 2022; 44:549-558. [PMID: 36173151 PMCID: PMC9842879 DOI: 10.1002/hbm.26083] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 08/18/2022] [Accepted: 08/29/2022] [Indexed: 01/25/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is one of the most common subtypes of focal epilepsy, with mesial temporal sclerosis (MTS) being a common radiological and histopathological finding. Accurate identification of MTS during presurgical evaluation confers an increased chance of good surgical outcome. Here we propose the use of glutamate-weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) at 7 Tesla for mapping hippocampal glutamate distribution in epilepsy, allowing to differentiate lesional from non-lesional mesial TLE. We demonstrate that a directional asymmetry index, which quantifies the relative difference between GluCEST contrast in hippocampi ipsilateral and contralateral to the seizure onset zone, can differentiate between sclerotic and non-sclerotic hippocampi, even in instances where traditional presurgical MRI assessments did not provide evidence of sclerosis. Overall, our results suggest that hippocampal glutamate mapping through GluCEST imaging is a valuable addition to the presurgical epilepsy evaluation toolbox.
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Affiliation(s)
- Alfredo Lucas
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA,University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Ravi Prakash Reddy Nanga
- Center for Advanced Metabolic Imaging in Precision MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Peter Hadar
- University of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA,Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Stephanie Chen
- Department of Neurology (work conducted while at the University of Pennsylvania)University of Maryland School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Adam Gibson
- Virginia Commonwealth University School of Medicine (work conducted while at the University of Pennsylvania)PhiladelphiaPennsylvaniaUSA
| | - Kelly Oechsel
- Wake Forest University School of Medicine (work conducted while at the University of Pennsylvania)PhiladelphiaPennsylvaniaUSA
| | - Mark A. Elliott
- Center for Advanced Metabolic Imaging in Precision MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Joel M. Stein
- Department of RadiologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Sandhitsu Das
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - John A. Detre
- Center for Advanced Metabolic Imaging in Precision MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA,Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA,Department of RadiologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Kathryn A. Davis
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA,Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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7
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Abstract
PURPOSE OF REVIEW We review significant advances in epilepsy imaging in recent years. RECENT FINDINGS Structural MRI at 7T with optimization of acquisition and postacquisition image processing increases the diagnostic yield but artefactual findings remain a challenge. MRI analysis from multiple sites indicates different atrophy patterns and white matter diffusion abnormalities in temporal lobe and generalized epilepsies, with greater abnormalities close to the presumed seizure source. Structural and functional connectivity relate to seizure spread and generalization; longitudinal studies are needed to clarify the causal relationship of these associations. Diffusion MRI may help predict surgical outcome and network abnormalities extending beyond the epileptogenic zone. Three-dimensional multimodal imaging can increase the precision of epilepsy surgery, improve seizure outcome and reduce complications. Language and memory fMRI are useful predictors of postoperative deficits, and lead to risk minimization. FDG PET is useful for clinical studies and specific ligands probe the pathophysiology of neurochemical fluxes and receptor abnormalities. SUMMARY Improved structural MRI increases detection of abnormalities that may underlie epilepsy. Diffusion, structural and functional MRI indicate the widespread associations of epilepsy syndromes. These can assist stratification of surgical outcome and minimize risk. PET has continued utility clinically and for research into the pathophysiology of epilepsies.
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Affiliation(s)
- John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Karin Trimmel
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
- Department of Neurology, Medical University of Vienna, Vienna, Austria
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8
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Advances regarding Neuroinflammation Biomarkers with Noninvasive Techniques in Epilepsy. Behav Neurol 2022; 2021:7946252. [PMID: 34976232 PMCID: PMC8716206 DOI: 10.1155/2021/7946252] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 12/23/2022] Open
Abstract
A rapidly growing body of evidence supports that neuroinflammation plays a major role in epileptogenesis and disease progression. The capacity to identify pathological neuroinflammation in individuals with epilepsy is a crucial step on the timing of anti-inflammatory intervention and patient selection, which will be challenging aspects in future clinical studies. The discovery of noninvasive biomarkers that are accessible in the blood or molecular neuroimaging would facilitate clinical translation of experimental findings into humans. These innovative and noninvasive approaches have the advantage of monitoring the dynamic changes of neuroinflammation in epilepsy. Here, we will review the available evidence for the measurement of neuroinflammation in patients with epilepsy using noninvasive techniques and critically analyze the major scientific challenges of noninvasive methods. Finally, we propose the potential for use in clinical applications.
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Guo R, Zhao Y, Jin H, Jian J, Wang H, Jin S, Ren H. Abnormal hubs in global network as neuroimaging biomarker in right temporal lobe epilepsy at rest. Front Psychiatry 2022; 13:981728. [PMID: 35966487 PMCID: PMC9363580 DOI: 10.3389/fpsyt.2022.981728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
While abnormal neuroimaging features have been reported in patients suffering from right temporal lobe epilepsy (rTLE), the value of altered degree centrality (DC) as a diagnostic biomarker for rTLE has yet to be established. As such, the present study was designed to examine DC abnormalities in rTLE patients in order to gauge the diagnostic utility of these neuroimaging features. In total, 68 patients with rTLE and 73 healthy controls (HCs) participated in this study. Imaging data were analyzed using DC and receiver operating characteristic (ROC) methods. Ultimately, rTLE patients were found to exhibit reduced right caudate DC and increased left middle temporal gyrus, superior parietal gyrus, superior frontal gyrus, right precuneus, frontal gyrus Inferior gyrus, middle-superior frontal gyrus, and inferior parietal gyrus DC relative to HC. ROC analyses indicated that DC values in the right caudate nucleus could be used to differentiate between rTLE patients and HCs with a high degree of sensitivity and specificity. Together, these results thus suggest that rTLE is associated with abnormal DC values in the right caudate nucleus, underscoring the relevance of further studies of the underlying pathophysiology of this debilitating condition.
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Affiliation(s)
- Ruimin Guo
- Department of Medical Imaging, Tianyou Hospital of Wuhan University of Science and Technology, Wuhan, China.,Key Laboratory of Occupational Hazards and Identification, Wuhan University of Science and Technology, Wuhan, China
| | - Yunfei Zhao
- Department of Neurosurgery, Tianyou Hospital of Wuhan University of Science and Technology, Wuhan, China
| | - Honghua Jin
- Department of Medical Imaging, Tianyou Hospital of Wuhan University of Science and Technology, Wuhan, China
| | - Jihua Jian
- Department of Medical Imaging, Tianyou Hospital of Wuhan University of Science and Technology, Wuhan, China
| | - Haibo Wang
- Department of Medical Imaging, Renmin Hospital of Wuhan University, Wuhan, China
| | - Shengxi Jin
- Department of Neurosurgery, Tianyou Hospital of Wuhan University of Science and Technology, Wuhan, China
| | - Hongwei Ren
- Department of Medical Imaging, Tianyou Hospital of Wuhan University of Science and Technology, Wuhan, China
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10
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Hangel G, Spurny‐Dworak B, Lazen P, Cadrien C, Sharma S, Hingerl L, Hečková E, Strasser B, Motyka S, Lipka A, Gruber S, Brandner C, Lanzenberger R, Rössler K, Trattnig S, Bogner W. Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T. NMR IN BIOMEDICINE 2021; 34:e4596. [PMID: 34382280 PMCID: PMC11475238 DOI: 10.1002/nbm.4596] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/14/2021] [Accepted: 07/14/2021] [Indexed: 05/13/2023]
Abstract
PURPOSE Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach. METHODS We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs. RESULTS Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate. DISCUSSION We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.
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Affiliation(s)
- Gilbert Hangel
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Benjamin Spurny‐Dworak
- Division of General Psychiatry, Department of Psychiatry and PsychotherapyMedical University of ViennaViennaAustria
| | - Philipp Lazen
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Cornelius Cadrien
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Sukrit Sharma
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Lukas Hingerl
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Eva Hečková
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Bernhard Strasser
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Stanislav Motyka
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Alexandra Lipka
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Institute for Clinical Molecular MRIKarl Landsteiner SocietySt. PöltenAustria
| | - Stephan Gruber
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Christoph Brandner
- High‐field MR Center, Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
| | - Rupert Lanzenberger
- Division of General Psychiatry, Department of Psychiatry and PsychotherapyMedical University of ViennaViennaAustria
| | - Karl Rössler
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Siegfried Trattnig
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Institute for Clinical Molecular MRIKarl Landsteiner SocietySt. PöltenAustria
| | - Wolfgang Bogner
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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11
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Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy. Brain Topogr 2021; 34:731-744. [PMID: 34652579 DOI: 10.1007/s10548-021-00875-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 09/28/2021] [Indexed: 10/20/2022]
Abstract
To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.
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12
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Yan R, Zhang H, Wang J, Zheng Y, Luo Z, Zhang X, Xu Z. Application value of molecular imaging technology in epilepsy. IBRAIN 2021; 7:200-210. [PMID: 37786793 PMCID: PMC10528966 DOI: 10.1002/j.2769-2795.2021.tb00084.x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/16/2021] [Accepted: 09/02/2021] [Indexed: 10/04/2023]
Abstract
Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.
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Affiliation(s)
- Rong Yan
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Hai‐Qing Zhang
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Jing Wang
- Prevention and Health Care, The Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Yong‐Su Zheng
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Zhong Luo
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Xia Zhang
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Zu‐Cai Xu
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
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13
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Bottino F, Lucignani M, Napolitano A, Dellepiane F, Visconti E, Rossi Espagnet MC, Pasquini L. In Vivo Brain GSH: MRS Methods and Clinical Applications. Antioxidants (Basel) 2021; 10:antiox10091407. [PMID: 34573039 PMCID: PMC8468877 DOI: 10.3390/antiox10091407] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 08/22/2021] [Accepted: 08/30/2021] [Indexed: 01/31/2023] Open
Abstract
Glutathione (GSH) is an important antioxidant implicated in several physiological functions, including the oxidation−reduction reaction balance and brain antioxidant defense against endogenous and exogenous toxic agents. Altered brain GSH levels may reflect inflammatory processes associated with several neurologic disorders. An accurate and reliable estimation of cerebral GSH concentrations could give a clear and thorough understanding of its metabolism within the brain, thus providing a valuable benchmark for clinical applications. In this context, we aimed to provide an overview of the different magnetic resonance spectroscopy (MRS) technologies introduced for in vivo human brain GSH quantification both in healthy control (HC) volunteers and in subjects affected by different neurological disorders (e.g., brain tumors, and psychiatric and degenerative disorders). Additionally, we aimed to provide an exhaustive list of normal GSH concentrations within different brain areas. The definition of standard reference values for different brain areas could lead to a better interpretation of the altered GSH levels recorded in subjects with neurological disorders, with insights into the possible role of GSH as a biomarker and therapeutic target.
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Affiliation(s)
- Francesca Bottino
- Medical Physics Department, Bambino Gesù Children’s Hospital IRCCS, 00165 Rome, Italy; (F.B.); (M.L.)
| | - Martina Lucignani
- Medical Physics Department, Bambino Gesù Children’s Hospital IRCCS, 00165 Rome, Italy; (F.B.); (M.L.)
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children’s Hospital IRCCS, 00165 Rome, Italy; (F.B.); (M.L.)
- Correspondence: ; Tel.: +39-333-3214614
| | - Francesco Dellepiane
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, 00189 Rome, Italy; (F.D.); (M.C.R.E.); (L.P.)
| | - Emiliano Visconti
- Neuroradiology Unit, Surgery and Trauma Department, Maurizio Bufalini Hospital, 47521 Cesena, Italy;
| | - Maria Camilla Rossi Espagnet
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, 00189 Rome, Italy; (F.D.); (M.C.R.E.); (L.P.)
- Neuroradiology Unit, Bambino Gesù Children’s Hospital IRCCS, 00165 Rome, Italy
| | - Luca Pasquini
- Neuroradiology Unit, NESMOS Department, Sant’Andrea Hospital, La Sapienza University, 00189 Rome, Italy; (F.D.); (M.C.R.E.); (L.P.)
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
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14
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Zhang L, Huang J, Zhang Z, Cao Z. Altered Metabolites in the Occipital Lobe in Migraine Without Aura During the Attack and the Interictal Period. Front Neurol 2021; 12:656349. [PMID: 34093404 PMCID: PMC8172811 DOI: 10.3389/fneur.2021.656349] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 04/01/2021] [Indexed: 01/03/2023] Open
Abstract
Background: Although there have been many magnetic resonance spectroscopy (MRS) studies of migraine, few have focused on migraines during an attack. Here, we aimed to assess metabolite changes in the brain of patients with migraine, both during an attack and in the interictal phase. Methods: Six patients (one man and five women, mean age: 39 ± 10 years) with migraine without aura during the attack (MWoA-DA), 13 patients (three men and 10 women, mean age: 31 ± 9 years) with migraine without aura during the interictal period (MWoA-DI), and 13 healthy controls (HC) (four men and nine women, mean age: 31 ± 9 years) were studied. All subjects underwent an MRS examination focusing on the occipital lobe. Metabolite changes were investigated among three groups. Results: The MWoA-DA patients had lower glutathione/total creatine ratio (GSH/tCr) than the MWoA-DI patients and HC. Furthermore, MWoA-DI patients showed lower total choline/total creatine ratio (tCho/tCr) than those in the other two groups. The GSH/tCr ratio was positively correlated with attack frequency in the MWoA-DI group. The tCho/tCr ratio was positively correlated with attack frequency and Migraine Disability Assessment Scale (MIDAS) scores in the MWoA-DA group. Conclusion: The present study suggests the existence of distinct pathophysiological states between the MWoA-DA and MWoA-DI groups. Neuronal dysfunction is a possible predisposing factor for migraine attack onset, along with oxidative stress and inflammation.
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Affiliation(s)
- Luping Zhang
- Department of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China
| | - Jinwen Huang
- The First Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhengxiang Zhang
- Department of Neurology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhijian Cao
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
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15
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Mitochondrial and metabolic dysfunction in Friedreich ataxia: update on pathophysiological relevance and clinical interventions. Neuronal Signal 2021; 5:NS20200093. [PMID: 34046211 PMCID: PMC8132591 DOI: 10.1042/ns20200093] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 04/29/2021] [Accepted: 04/30/2021] [Indexed: 02/07/2023] Open
Abstract
Friedreich ataxia (FRDA) is a recessive disorder resulting from relative deficiency of the mitochondrial protein frataxin. Frataxin functions in the process of iron–sulfur (Fe–S) cluster synthesis. In this review, we update some of the processes downstream of frataxin deficiency that may mediate the pathophysiology. Based on cellular models, in vivo models and observations of patients, ferroptosis may play a major role in the pathogenesis of FRDA along with depletion of antioxidant reserves and abnormalities of mitochondrial biogenesis. Ongoing clinical trials with ferroptosis inhibitors and nuclear factor erythroid 2-related factor 2 (Nrf2) activators are now targeting each of the processes. In addition, better understanding of the mitochondrial events in FRDA may allow the development of improved imaging methodology for assessing the disorder. Though not technologically feasible at present, metabolic imaging approaches may provide a direct methodology to understand the mitochondrial changes occurring in FRDA and provide a methodology to monitor upcoming trials of frataxin restoration.
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16
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Wiers CE, Vendruscolo LF, van der Veen JW, Manza P, Shokri-Kojori E, Kroll DS, Feldman DE, McPherson KL, Biesecker CL, Zhang R, Herman K, Elvig SK, Vendruscolo JCM, Turner SA, Yang S, Schwandt M, Tomasi D, Cervenka MC, Fink-Jensen A, Benveniste H, Diazgranados N, Wang GJ, Koob GF, Volkow ND. Ketogenic diet reduces alcohol withdrawal symptoms in humans and alcohol intake in rodents. SCIENCE ADVANCES 2021; 7:7/15/eabf6780. [PMID: 33837086 PMCID: PMC8034849 DOI: 10.1126/sciadv.abf6780] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/19/2021] [Indexed: 05/15/2023]
Abstract
Individuals with alcohol use disorder (AUD) show elevated brain metabolism of acetate at the expense of glucose. We hypothesized that a shift in energy substrates during withdrawal may contribute to withdrawal severity and neurotoxicity in AUD and that a ketogenic diet (KD) may mitigate these effects. We found that inpatients with AUD randomized to receive KD (n = 19) required fewer benzodiazepines during the first week of detoxification, in comparison to those receiving a standard American (SA) diet (n = 14). Over a 3-week treatment, KD compared to SA showed lower "wanting" and increased dorsal anterior cingulate cortex (dACC) reactivity to alcohol cues and altered dACC bioenergetics (i.e., elevated ketones and glutamate and lower neuroinflammatory markers). In a rat model of alcohol dependence, a history of KD reduced alcohol consumption. We provide clinical and preclinical evidence for beneficial effects of KD on managing alcohol withdrawal and on reducing alcohol drinking.
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Affiliation(s)
- Corinde E Wiers
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA.
- University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | | | - Peter Manza
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | | | - Danielle S Kroll
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Dana E Feldman
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | | | | | - Rui Zhang
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Kimberly Herman
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Sophie K Elvig
- National Institute on Drug Abuse, Baltimore, MD 21224, USA
| | | | - Sara A Turner
- Clinical Center Nutrition Department, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shanna Yang
- Clinical Center Nutrition Department, National Institutes of Health, Bethesda, MD 20892, USA
| | - Melanie Schwandt
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Dardo Tomasi
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | | | - Anders Fink-Jensen
- Psychiatric Centre Copenhagen, University Hospital of Copenhagen, Copenhagen, Denmark
| | - Helene Benveniste
- Department of Anesthesiology, Yale University, New Haven, CT 06519, USA
| | - Nancy Diazgranados
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Gene-Jack Wang
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - George F Koob
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
- National Institute on Drug Abuse, Baltimore, MD 21224, USA
| | - Nora D Volkow
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA.
- National Institute on Drug Abuse, Baltimore, MD 21224, USA
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17
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Mahajan VR, Elvig SK, Vendruscolo LF, Koob GF, Darcey VL, King MT, Kranzler HR, Volkow ND, Wiers CE. Nutritional Ketosis as a Potential Treatment for Alcohol Use Disorder. Front Psychiatry 2021; 12:781668. [PMID: 34916977 PMCID: PMC8670944 DOI: 10.3389/fpsyt.2021.781668] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 11/08/2021] [Indexed: 12/28/2022] Open
Abstract
Alcohol use disorder (AUD) is a chronic, relapsing brain disorder, characterized by compulsive alcohol seeking and disrupted brain function. In individuals with AUD, abstinence from alcohol often precipitates withdrawal symptoms than can be life threatening. Here, we review evidence for nutritional ketosis as a potential means to reduce withdrawal and alcohol craving. We also review the underlying mechanisms of action of ketosis. Several findings suggest that during alcohol intoxication there is a shift from glucose to acetate metabolism that is enhanced in individuals with AUD. During withdrawal, there is a decline in acetate levels that can result in an energy deficit and could contribute to neurotoxicity. A ketogenic diet or ingestion of a ketone ester elevates ketone bodies (acetoacetate, β-hydroxybutyrate and acetone) in plasma and brain, resulting in nutritional ketosis. These effects have been shown to reduce alcohol withdrawal symptoms, alcohol craving, and alcohol consumption in both preclinical and clinical studies. Thus, nutritional ketosis may represent a unique treatment option for AUD: namely, a nutritional intervention that could be used alone or to augment the effects of medications.
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Affiliation(s)
- Vikrant R Mahajan
- Department of Pharmacology, Vanderbilt University, Nashville, TN, United States
| | - Sophie K Elvig
- Integrative Neuroscience Research Branch, National Institute on Drug Abuse, Baltimore, MD, United States
| | - Leandro F Vendruscolo
- Integrative Neuroscience Research Branch, National Institute on Drug Abuse, Baltimore, MD, United States
| | - George F Koob
- Integrative Neuroscience Research Branch, National Institute on Drug Abuse, Baltimore, MD, United States
| | - Valerie L Darcey
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, United States
| | - M Todd King
- National Institute on Alcohol Abuse and Alcoholism, Rockville, MD, United States
| | - Henry R Kranzler
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Nora D Volkow
- National Institute on Alcohol Abuse and Alcoholism, Rockville, MD, United States
| | - Corinde E Wiers
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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