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Xiao S, Yang Z, Lin Z, Chen L, Liao W, Wang J, Gao C, Lu J, Song Y, Su S, Jiang G. Spontaneous Brain Activity Abnormalities in Patients With Temporal Lobe Epilepsy: A Meta-Analysis of 1474 Patients. J Magn Reson Imaging 2024. [PMID: 39215606 DOI: 10.1002/jmri.29568] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 07/31/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Abnormalities in resting-state functional brain activity have been detected in patients with temporal lobe epilepsy (TLE). The results of individual neuroimaging studies of TLE, however, are frequently inconsistent due to small and heterogeneous samples, analytical flexibility, and publication bias toward positive findings. PURPOSE To investigate the most consistent regions of resting-state functional brain activity abnormality in patients with TLE through a quantitative meta-analysis of published neuroimaging data. STUDY TYPE Meta-analysis. SUBJECTS Exactly 1474 TLE patients (716 males and 758 females) from 31 studies on resting-state functional brain activity were included in this study. FIELD STRENGTH/SEQUENCE Studies utilizing 1.5 T or 3 T MR scanners were included for meta-analysis. Resting-state functional MRI using gradient echo-planar imaging, T1-weighted imaging. ASSESSMENT PubMed, Web of Science, Chinese National Knowledge Infrastructure, and WanFang databases were searched to identify studies investigating amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) at the whole-brain level between patients with TLE and healthy controls (HCs). STATISTICAL TESTS Seed-based d Mapping with Permutation of Subject Images, standard randomization tests and meta-regression analysis were used. Results were significant if P < 0.05 with family-wise error corrected. RESULTS Patients with TLE displayed resting-state functional brain activity which was a significant increase in the right hippocampus, and significant decrease in the right angular gurus and right precuneus. Additionally, the meta-regression analysis demonstrated that age (P = 0.231), sex distribution (P = 0.376), and illness duration (P = 0.184), did not show significant associations with resting state functional brain activity in patients with TLE. DATA CONCLUSION Common alteration patterns of spontaneous brain activity were identified in the right hippocampus and default-model network regions in patients with TLE. These findings may contribute to understanding of the underlying mechanism for potentially effective intervention of TLE. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE Stage 2.
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Affiliation(s)
- Shu Xiao
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- Department of Radiology, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China
| | - Zibin Yang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Zitao Lin
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Liqing Chen
- Department of Catheter Intervention, Maoming Maonan District People's Hospital, Maoming, China
| | - Weiming Liao
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jurong Wang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Cuihua Gao
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jianjun Lu
- Department of Neurosurgery, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yang Song
- Siemens Healthineers Ltd, Shanghai, China
| | - Sulian Su
- Department of Radiology, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China
| | - Guihua Jiang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
- Department of Radiology, Xiamen Humanity Hospital Fujian Medical University, Xiamen, China
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Yuan S, Huang H, Cai B, Li J, Zhang M, Luo J. Altered metabolic-functional coupling in the epileptogenic network could predict surgical outcomes of mesial temporal lobe epilepsy. Front Neurosci 2023; 17:1165982. [PMID: 37360171 PMCID: PMC10286900 DOI: 10.3389/fnins.2023.1165982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 05/09/2023] [Indexed: 06/28/2023] Open
Abstract
Objective To investigate the relationship between glucose metabolism and functional activity in the epileptogenic network of patients with mesial temporal lobe epilepsy (MTLE) and to determine whether this relationship is associated with surgical outcomes. Methods 18F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed on a hybrid PET/MR scanner in 38 MTLE patients with hippocampal sclerosis (MR-HS), 35 MR-negative patients and 34 healthy controls (HC). Glucose metabolism was measured using 18F-FDG PET standardized uptake value ratio (SUVR) relative to cerebellum; Functional activity was obtained by fractional amplitude of low-frequency fluctuation (fALFF). The betweenness centrality (BC) of metabolic covariance network and functional network were calculated using graph theoretical analysis. Differences in SUVR, fALFF, BC and the spatial voxel-wise SUVR-fALFF couplings of the epileptogenic network, consisting of default mode network (DMN) and thalamus, were evaluated by Mann-Whitney U test (using the false discovery rate [FDR] for multiple comparison correction). The top ten SUVR-fALFF couplings were selected by Fisher score to predict surgical outcomes using logistic regression model. Results The results showed decreased SUVR-fALFF coupling in the bilateral middle frontal gyrus (PFDR = 0.0230, PFDR = 0.0296) in MR-HS patients compared to healthy controls. Coupling in the ipsilateral hippocampus was marginally increased (PFDR = 0.0802) in MR-HS patients along with decreased BC of metabolic covariance network and functional network (PFDR = 0.0152; PFDR = 0.0429). With Fisher score ranking, the top ten SUVR-fALFF couplings in regions from DMN and thalamic subnuclei could predict surgical outcomes with the best performance being a combination of ten SUVR-fALFF couplings with an AUC of 0.914. Conclusion These findings suggest that the altered neuroenergetic coupling in the epileptogenic network is associated with surgical outcomes of MTLE patients, which may provide insight into their pathogenesis and help with preoperative evaluation.
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Affiliation(s)
- Siyu Yuan
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hui Huang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Bingyang Cai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jiwei Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Miao Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Luo
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Uher D, Drenthen GS, Schijns OEMG, Colon AJ, Hofman PAM, van Lanen RHGJ, Hoeberigs CM, Jansen JFA, Backes WH. Advances in Image Processing for Epileptogenic Zone Detection with MRI. Radiology 2023; 307:e220927. [PMID: 37129491 DOI: 10.1148/radiol.220927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Focal epilepsy is a common and severe neurologic disorder. Neuroimaging aims to identify the epileptogenic zone (EZ), preferably as a macroscopic structural lesion. For approximately a third of patients with chronic drug-resistant focal epilepsy, the EZ cannot be precisely identified using standard 3.0-T MRI. This may be due to either the EZ being undetectable at imaging or the seizure activity being caused by a physiologic abnormality rather than a structural lesion. Computational image processing has recently been shown to aid radiologic assessments and increase the success rate of uncovering suspicious regions by enhancing their visual conspicuity. While structural image analysis is at the forefront of EZ detection, physiologic image analysis has also been shown to provide valuable information about EZ location. This narrative review summarizes and explains the current state-of-the-art computational approaches for image analysis and presents their potential for EZ detection. Current limitations of the methods and possible future directions to augment EZ detection are discussed.
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Affiliation(s)
- Daniel Uher
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Gerhard S Drenthen
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Olaf E M G Schijns
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Albert J Colon
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Paul A M Hofman
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Rick H G J van Lanen
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Christianne M Hoeberigs
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Jacobus F A Jansen
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
| | - Walter H Backes
- From the Department of Radiology and Nuclear Medicine (D.U., G.S.D., P.A.M.H., C.M.H., J.F.A.J., W.H.B.) and Department of Neurosurgery (O.E.M.G.S., R.H.G.J.v.L.), Maastricht University Medical Centre, P. Debyelaan 25, NL-6229 HX Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands (D.U., G.S.D., O.E.M.G.S., R.H.G.J.v.L., J.F.A.J., W.H.B.); Academic Center for Epileptology, Kempenhaeghe and Maastricht University Medical Centre, Heeze/Maastricht, the Netherlands (O.E.M.G.S., A.J.C., P.A.M.H., C.M.H., J.F.A.J.); and Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (J.F.A.J.)
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Shan Y, Chen Y, Gu H, Wang Y, Sun Y. Regulatory Basis of Adipokines Leptin and Adiponectin in Epilepsy: from Signaling Pathways to Glucose Metabolism. Neurochem Res 2023; 48:2017-2028. [PMID: 36797447 PMCID: PMC10181973 DOI: 10.1007/s11064-023-03891-2] [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: 12/21/2022] [Revised: 01/25/2023] [Accepted: 02/07/2023] [Indexed: 02/18/2023]
Abstract
Epilepsy is a common and severe neurological disorder in which impaired glucose metabolism leads to changes in neuronal excitability that slow or promote the development of epilepsy. Leptin and adiponectin are important mediators regulating glucose metabolism in the peripheral and central nervous systems. Many studies have reported a strong association between epilepsy and these two adipokines involved in multiple signaling cascades and glucose metabolism. Due to the complex regulatory mechanisms between them and various signal activation networks, their role in epilepsy involves many aspects, including the release of inflammatory mediators, oxidative damage, and neuronal apoptosis. This paper aims to summarize the signaling pathways involved in leptin and adiponectin and the regulation of glucose metabolism from the perspective of the pathogenesis of epilepsy. In particular, we discuss the dual effects of leptin in epilepsy and the relationship between antiepileptic drugs and changes in the levels of these two adipokines. Clinical practitioners may need to consider these factors in evaluating clinical drugs. Through this review, we can better understand the specific involvement of leptin and adiponectin in the pathogenesis of epilepsy, provide ideas for further exploration, and bring about practical significance for the treatment of epilepsy, especially for the development of personalized treatment according to individual metabolic characteristics.
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Affiliation(s)
- Yisi Shan
- Department of Neurology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, China.,Translational Medical Innovation Center, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, China
| | - Yeting Chen
- Department of Acupuncture, Zhangjiagang Second People's Hospital, Zhangjiagang, 215600, China
| | - Haiping Gu
- Department of Neurology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, China
| | - Yadong Wang
- Department of Neurology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, China
| | - Yaming Sun
- Department of Neurology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, China.
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Sukprakun C, Tepmongkol S. Nuclear imaging for localization and surgical outcome prediction in epilepsy: A review of latest discoveries and future perspectives. Front Neurol 2022; 13:1083775. [PMID: 36588897 PMCID: PMC9800996 DOI: 10.3389/fneur.2022.1083775] [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: 10/29/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022] Open
Abstract
Background Epilepsy is one of the most common neurological disorders. Approximately, one-third of patients with epilepsy have seizures refractory to antiepileptic drugs and further require surgical removal of the epileptogenic region. In the last decade, there have been many recent developments in radiopharmaceuticals, novel image analysis techniques, and new software for an epileptogenic zone (EZ) localization. Objectives Recently, we provided the latest discoveries, current challenges, and future perspectives in the field of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in epilepsy. Methods We searched for relevant articles published in MEDLINE and CENTRAL from July 2012 to July 2022. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis was conducted using the keywords "Epilepsy" and "PET or SPECT." We included both prospective and retrospective studies. Studies with preclinical subjects or not focusing on EZ localization or surgical outcome prediction using recently developed PET radiopharmaceuticals, novel image analysis techniques, and new software were excluded from the review. The remaining 162 articles were reviewed. Results We first present recent findings and developments in PET radiopharmaceuticals. Second, we present novel image analysis techniques and new software in the last decade for EZ localization. Finally, we summarize the overall findings and discuss future perspectives in the field of PET and SPECT in epilepsy. Conclusion Combining new radiopharmaceutical development, new indications, new techniques, and software improves EZ localization and provides a better understanding of epilepsy. These have proven not to only predict prognosis but also to improve the outcome of epilepsy surgery.
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Affiliation(s)
- Chanan Sukprakun
- Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Supatporn Tepmongkol
- Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand,Chulalongkorn University Biomedical Imaging Group (CUBIG), Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand,Chula Neuroscience Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand,Cognitive Impairment and Dementia Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand,*Correspondence: Supatporn Tepmongkol ✉
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Wang L, Wei L, Jin L, Li Y, Wei Y, He W, Shi L, Sun Q, Li W, Li Q, Li Y, Wu Y, Wang Y, Yuan M. Different Features of a Metabolic Connectivity Map and the Granger Causality Method in Revealing Directed Dopamine Pathways: A Study Based on Integrated PET/MR Imaging. AJNR Am J Neuroradiol 2022; 43:1770-1776. [PMID: 36357153 DOI: 10.3174/ajnr.a7707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 10/01/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND AND PURPOSE Exploring the directionality of neural information in the brain is important for understanding brain mechanisms and neurodisease development. Granger causality analysis and the metabolic connectivity map can be used to investigate directional transmission of information between brain regions, but their differences in depicting functional effective connectivity are not clear. MATERIALS AND METHODS Using the Monash rs-PET/MR imaging data set, we conducted Granger causality and metabolic connectivity map analyses of the dopamine reward circuit in the brain. The dopamine reward circuit is a well-known system consisting primarily of the bilateral orbital frontal cortex, caudate, nucleus accumbens, thalamus, and substantia nigra. We validated these circuit pathways using Granger causality and the metabolic connectivity map for identifying effective connectivities against a priori knowledge by testing the significance of directed pathways (P < .05, false discovery rate-corrected). RESULTS We found 3 types of effective connectivities in the dopamine reward circuit: long-range, neighborhood, and symmetric. Granger causality analysis revealed long-range connections in the orbital frontal cortex-caudate and orbital frontal cortex-nucleus accumbens regions. Metabolic connectivity map analysis revealed neighborhood connections in the nucleus accumbens-caudate, substantia nigra-thalamus, and thalamus-caudate regions. Metabolic connectivity map analysis also found symmetric connections in each of the bilateral nucleus accumbens, caudate, thalamus, and orbital frontal cortex-caudate regions. Different patterns in directional networks of the dopamine reward circuit were revealed by Granger causality and metabolic connectivity map analyses. CONCLUSIONS Granger causality analysis primarily identified bidirectional cortico-nucleus connections, while the metabolic connectivity map primarily identified direct connections among neighborhood and symmetric regions. The results of this study indicated that investigations of effective connectivities should use an appropriate analysis method depending on the purpose of the study.
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Affiliation(s)
- L Wang
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - L Wei
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - L Jin
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - Y Li
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - Y Wei
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - W He
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - L Shi
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
| | - Q Sun
- Department of Radiology (Q.S., Y. Wang), the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - W Li
- Radiology (W.L., Q.L.), Tangdu Hospital of Air Force Military Medical University, Xi'an, China
| | - Q Li
- Radiology (W.L., Q.L.), Tangdu Hospital of Air Force Military Medical University, Xi'an, China
| | - Y Li
- Department of Radiology (YongBin Li), the First Hospital of Xi'an, Xi'an, China; and Siemens
| | - Y Wu
- Healthineers Ltd (Y. Wu), Beijing, China
| | - Y Wang
- Department of Radiology (Q.S., Y. Wang), the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - M Yuan
- From the Departments of Nuclear Medicine (L. Wang., L. Wei, L.J., YunBo Li, Y. Wei, W.H., L.S., M.Y.)
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Berk BA, Ottka C, Hong Law T, Packer RMA, Wessmann A, Bathen-Nöthen A, Jokinen TS, Knebel A, Tipold A, Lohi H, Volk HA. Metabolic fingerprinting of dogs with idiopathic epilepsy receiving a ketogenic medium-chain triglyceride (MCT) oil. Front Vet Sci 2022; 9:935430. [PMID: 36277072 PMCID: PMC9584307 DOI: 10.3389/fvets.2022.935430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 09/15/2022] [Indexed: 11/04/2022] Open
Abstract
Consumption of medium-chain triglycerides (MCT) has been shown to improve seizure control, reduce behavioural comorbidities and improve cognitive function in epileptic dogs. However, the exact metabolic pathways affected by dietary MCT remain poorly understood. In this study, we aimed to identify changes in the metabolome and neurotransmitters levels relevant to epilepsy and behavioural comorbidities associated with the consuming of an MCT supplement (MCT-DS) in dogs with idiopathic epilepsy (IE). Metabolic alterations induced by a commercial MCT-DS in a population of 28 dogs with IE were evaluated in a 6-month multi-centre, prospective, randomised, double-blinded, controlled cross-over trial design. A metabolic energy requirement-based amount of 9% MCT or control oil was supplemented to the dogs' stable base diet for 3 months, followed by the alternative oil for another 3 months. A validated, quantitative nuclear magnetic resonance (NMR) spectroscopy platform was applied to pre- and postprandially collected serum samples to compare the metabolic profile between both DS and baseline. Furthermore, alterations in urinary neurotransmitter levels were explored. Five dogs (30%) had an overall reduction in seizure frequency of ≥50%, and were classified as MCT-responders, while 23 dogs showed a ≤50% reduction, and were defined as MCT non-responders. Amino-acid metabolism was significantly influenced by MCT consumption compared to the control oil. While the serum concentrations of total fatty acids appeared similar during both supplements, the relative concentrations of individual fatty acids differed. During MCT supplementation, the concentrations of polyunsaturated fatty acids and arachidonic acid were significantly higher than under the control oil. β-Hydroxybutyric acid levels were significantly higher under MCT supplementation. In total, four out of nine neurotransmitters were significantly altered: a significantly increased γ-aminobutyric acid (GABA) concentration was detected during the MCT-phase accompanied by a significant shift of the GABA-glutamate balance. MCT-Responders had significantly lowered urinary concentrations of histamine, glutamate, and serotonin under MCT consumption. In conclusion, these novel data highlight metabolic changes in lipid, amino-acid and ketone metabolism due to MCT supplementation. Understanding the metabolic response to MCT provides new avenues to develop better nutritional management with improved anti-seizure and neuroprotective effects for dogs with epilepsy, and other behavioural disorders.
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Affiliation(s)
- Benjamin Andreas Berk
- Department of Clinical Science and Services, Royal Veterinary College, Hatfield, United Kingdom,BrainCheck.Pet, Tierärztliche Praxis für Epilepsie, Mannheim, Germany
| | - Claudia Ottka
- Department of Veterinary Biosciences and Department of Medical and Clinical Genetics, Folkhälsan Research Center, University of Helsinki, Helsinki, Finland,PetBiomics Ltd., Helsinki, Finland
| | - Tsz Hong Law
- Department of Clinical Science and Services, Royal Veterinary College, Hatfield, United Kingdom
| | - Rowena Mary Anne Packer
- Department of Clinical Science and Services, Royal Veterinary College, Hatfield, United Kingdom
| | - Annette Wessmann
- Pride Veterinary Centre, Neurology/Neurosurgery Service, Derby, United Kingdom
| | | | - Tarja Susanna Jokinen
- Department of Equine and Small Animal Medicine, Faculty of Veterinary Medicine, Helsinki, Finland
| | - Anna Knebel
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine, Hannover, Germany
| | - Andrea Tipold
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine, Hannover, Germany
| | - Hannes Lohi
- Department of Veterinary Biosciences and Department of Medical and Clinical Genetics, Folkhälsan Research Center, University of Helsinki, Helsinki, Finland,PetBiomics Ltd., Helsinki, Finland
| | - Holger Andreas Volk
- Department of Clinical Science and Services, Royal Veterinary College, Hatfield, United Kingdom,Department of Small Animal Medicine and Surgery, University of Veterinary Medicine, Hannover, Germany,*Correspondence: Holger Andreas Volk
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8
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Hao S, Duan Y, Qi L, Li Z, Ren J, Nangale N, Yang C. A resting-state fMRI study of temporal lobe epilepsy using multivariate pattern analysis and Granger causality analysis. J Neuroimaging 2022; 32:977-990. [PMID: 35670638 DOI: 10.1111/jon.13012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 05/09/2022] [Accepted: 05/10/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND AND PURPOSE Understanding the pathogenesis of temporal lobe epilepsy (TLE) is essential for its diagnosis and treatment. The study aimed to explore regional homogeneity (ReHo) and changes in effective connectivity (EC) between brain regions in TLE patients, hoping to discover potential abnormalities in certain brain regions in TLE patients. METHODS Resting-state functional magnetic resonance data were collected from 23 TLE patients and 32 normal controls (NC). ReHo was used as a feature of multivariate pattern analysis (MVPA) to explore the ability of its alterations in identifying TLE. Based on the results of the MVPA, certain brain regions were selected as seed points to further explore alterations in EC between brain regions using Granger causality analysis. RESULTS MVPA results showed that the classification accuracy for the TLE and NC groups was 87.27%, and the right posterior cerebellum lobe, right lingual gyrus (LING_R), right cuneus (CUN_R), and left superior temporal gyrus (STG_L) provided significant contributions. Moreover, the EC from STG_L to right fusiform gyrus (FFG_R) and LING_R and the EC from CUN_R to the right occipital superior gyrus (SOG_R) and right occipital middle gyrus (MOG_R) were altered compared to the NC group. CONCLUSION The MVPA results indicated that ReHo abnormalities in brain regions may be an important feature in the identification of TLE. The enhanced EC from STG_L to FFG_R and LING_R indicates a shift in language processing to the right hemisphere, and the weakened EC from SOG_R and MOG_R to CUN_R may reveal an underlying mechanism of TLE.
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Affiliation(s)
- Siyao Hao
- Faculty of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
| | - Ying Duan
- Beijing Universal Medical Imaging Diagnostic Center, Beijing, China
| | - Lei Qi
- Beijing Universal Medical Imaging Diagnostic Center, Beijing, China
| | - Zhimei Li
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiechuan Ren
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | | | - Chunlan Yang
- Faculty of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
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9
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Shan Y, Wang Z, Song S, Xue Q, Ge Q, Yang H, Cui B, Zhang M, Zhou Y, Lu J. Integrated Positron Emission Tomography/Magnetic Resonance Imaging for Resting-State Functional and Metabolic Imaging in Human Brain: What Is Correlated and What Is Impacted. Front Neurosci 2022; 16:824152. [PMID: 35310105 PMCID: PMC8926297 DOI: 10.3389/fnins.2022.824152] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 01/24/2022] [Indexed: 12/04/2022] Open
Abstract
Integrated positron emission tomography (PET)/magnetic resonance imaging (MRI) could simultaneously obtain both functional MRI (fMRI) and 18F-fluorodeoxyglucose (FDG) PET and thus provide multiparametric information for the analysis of brain metabolism. In this study, we aimed to, for the first time, investigate the interplay of simultaneous fMRI and FDG PET scan using a randomized self-control protocol. In total, 24 healthy volunteers underwent PET/MRI scan for 30–40 min after the injection of FDG. A 22-min brain scan was separated into MRI-off mode (without fMRI pulsing) and MRI-on mode (with fMRI pulsing), with each one lasting for 11 min. We calculated the voxel-wise fMRI metrics (regional homogeneity, amplitude of low-frequency fluctuations, fractional amplitude of low-frequency fluctuations, and degree centrality), resting networks, relative standardized uptake value ratios (SUVr), SUVr slope, and regional cerebral metabolic rate of glucose (rCMRGlu) maps. Paired two-sample t-tests were applied to assess the statistical differences between SUVr, SUVr slope, correlation coefficients of fMRI metrics, and rCMRGlu between MRI-off and MRI-on modes, respectively. The voxel-wise whole-brain SUVr revealed no statistical difference (P > 0.05), while the SUVr slope was significantly elevated in sensorimotor, dorsal attention, ventral attention, control, default, and auditory networks (P < 0.05) during fMRI scan. The task-based group independent-component analysis revealed that the most active network components derived from the combined MRI-off and MRI-on static PET images were frontal pole, superior frontal gyrus, middle temporal gyrus, and occipital pole. High correlation coefficients were found among fMRI metrics with rCMRGlu in both MRI-off and MRI-on mode (P < 0.05). Our results systematically evaluated the impact of simultaneous fMRI scan on the quantification of human brain metabolism from an integrated PET/MRI system.
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Affiliation(s)
- Yi Shan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Shuangshuang Song
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Qiaoyi Xue
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Qi Ge
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Miao Zhang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yun Zhou
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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10
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Wang J, Yang H, Cui B, Shan B, Lu J. Effects of MRI protocols on brain FDG uptake in simultaneous PET/MR imaging. Eur J Nucl Med Mol Imaging 2022; 49:2812-2820. [DOI: 10.1007/s00259-022-05703-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 01/23/2022] [Indexed: 11/04/2022]
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11
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Individual [ 18F]FDG PET and functional MRI based on simultaneous PET/MRI may predict seizure recurrence after temporal lobe epilepsy surgery. Eur Radiol 2022; 32:3880-3888. [PMID: 35024947 DOI: 10.1007/s00330-021-08490-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 10/21/2021] [Accepted: 11/28/2021] [Indexed: 01/11/2023]
Abstract
OBJECTIVES To investigate the individual measures of brain glucose metabolism, neural activity obtained from simultaneous 18[F]FDG PET/MRI, and their association with surgical outcomes in medial temporal lobe epilepsy due to hippocampal sclerosis (mTLE-HS). METHODS Thirty-nine unilateral mTLE-HS patients who underwent anterior temporal lobectomy were classified as having completely seizure-free (Engel class IA; n = 22) or non-seizure-free (Engel class IB-IV; n = 17) outcomes at 1 year after surgery. Preoperative [18F]FDG PET and functional MRI (fMRI) were obtained from a simultaneous PET/MRI scanner, and individual glucose metabolism and fractional amplitude of low-frequency fluctuation (fALFF) were evaluated by standardizing these with respect to healthy controls. These abnormality measures and clinical data from each patient were incorporated into a machine learning framework (gradient boosting decision tree and logistic regression analysis) to estimate seizure recurrence. The predictive values of features were evaluated by the receiver operating characteristic (ROC) curve in the training and test cohorts. RESULTS The machine learning classification model showed [18F]FDG PET and fMRI variations in contralateral hippocampal network and age of onset identify unfavorable surgical outcomes effectively. In the validation dataset, the logistic regression model with [18F]FDG PET and fALFF obtained from simultaneous [18F]FDG PET/MRI gained the maximum area under the ROC curve of 0.905 for seizure recurrence, higher than 0.762 with 18[F]-FDG PET, and 0.810 with fALFF alone. CONCLUSION Machine learning model suggests individual [18F]FDG PET and fMRI variations in contralateral hippocampal network based on 18[F]-FDG PET/MRI could serve as a potential biomarker of unfavorable surgical outcomes. KEY POINTS • Individual [18F]FDG PET and fMRI obtained from preoperative [18F]FDG PET/MR were investigated. • Individual differences were further assessed based on a seizure propagation network. • Machine learning can classify surgical outcomes with 90.5% accuracy.
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12
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Bandopadhyay R, Singh T, Ghoneim MM, Alshehri S, Angelopoulou E, Paudel YN, Piperi C, Ahmad J, Alhakamy NA, Alfaleh MA, Mishra A. Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements. BIOLOGY 2021; 10:1097. [PMID: 34827090 PMCID: PMC8615191 DOI: 10.3390/biology10111097] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/21/2021] [Accepted: 10/21/2021] [Indexed: 12/18/2022]
Abstract
Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60-70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.
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Affiliation(s)
- Ritam Bandopadhyay
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144411, Punjab, India;
| | - Tanveer Singh
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, TX 77807, USA;
| | - Mohammed M. Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah 13713, Saudi Arabia;
| | - Sultan Alshehri
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia;
| | - Efthalia Angelopoulou
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (E.A.); (C.P.)
| | - Yam Nath Paudel
- Neuropharmacology Research Strength, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Subang Jaya 47500, Selangor, Malaysia;
| | - Christina Piperi
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (E.A.); (C.P.)
| | - Javed Ahmad
- Department of Pharmaceutics, College of Pharmacy, Najran University, Najran 11001, Saudi Arabia;
| | - Nabil A. Alhakamy
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (N.A.A.); (M.A.A.)
| | - Mohamed A. Alfaleh
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (N.A.A.); (M.A.A.)
- Vaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Awanish Mishra
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144411, Punjab, India;
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER)—Guwahati, Changsari, Guwahati 781101, Assam, India
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13
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Hybrid PET-MRI for early detection of dopaminergic dysfunction and microstructural degradation involved in Parkinson's disease. Commun Biol 2021; 4:1162. [PMID: 34621005 PMCID: PMC8497575 DOI: 10.1038/s42003-021-02705-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 09/22/2021] [Indexed: 01/10/2023] Open
Abstract
Dopamine depletion and microstructural degradation underlie the neurodegenerative processes in Parkinson’s disease (PD). To explore early alterations and underlying associations of dopamine and microstructure in PD patients utilizing the hybrid positron emission tomography (PET)-magnetic resonance imaging (MRI). Twenty-five PD patients in early stages and twenty-four matched healthy controls underwent hybrid 18F-fluorodopa (DOPA) PET-diffusion tensor imaging (DTI) scanning. The striatal standardized uptake value ratio (SUVR), DTI maps (fractional anisotropy, FA; mean diffusivity, MD) in subcortical grey matter, and deterministic tractography of the nigrostriatal pathway were processed. Values in more affected (MA) side, less affected (LA) side and mean were analysed. Correlations and mediations among PET, DTI and clinical characteristics were further analysed. PD groups exhibited asymmetric pattern of dopaminergic dysfunction in putamen, impaired integrity in the microstructures (nigral FA, putaminal MD, and FA of nigrostriatal projection). On MA side, significant associations between DTI metrics (nigral FA, putaminal MD, and FA of nigrostriatal projection) and motor performance were significantly mediated by putaminal SUVR, respectively. Early asymmetric disruptions in putaminal dopamine concentrations and nigrostriatal pathway microstructure were detected using hybrid PET-MRI. The findings further implied that molecular degeneration mediates the modulation of microstructural disorganization on motor dysfunction in the early stages of PD. To explore early alterations and underlying associations of dopamine levels and microstructure in Parkinson’s Disease (PD), Shang et al use a hybrid positron emission tomography (PET)-magnetic resonance imaging (MRI) approach in early stage patients and age-matched controls. Their data implies that molecular degeneration mediates the effects of microstructural disorganization on motor dysfunction in the early stages of PD.
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Chen Y, Zhang J. How Energy Supports Our Brain to Yield Consciousness: Insights From Neuroimaging Based on the Neuroenergetics Hypothesis. Front Syst Neurosci 2021; 15:648860. [PMID: 34295226 PMCID: PMC8291083 DOI: 10.3389/fnsys.2021.648860] [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: 01/02/2021] [Accepted: 05/26/2021] [Indexed: 11/13/2022] Open
Abstract
Consciousness is considered a result of specific neuronal processes and mechanisms in the brain. Various suggested neuronal mechanisms, including the information integration theory (IIT), global neuronal workspace theory (GNWS), and neuronal construction of time and space as in the context of the temporospatial theory of consciousness (TTC), have been laid forth. However, despite their focus on different neuronal mechanisms, these theories neglect the energetic-metabolic basis of the neuronal mechanisms that are supposed to yield consciousness. Based on the findings of physiology-induced (sleep), pharmacology-induced (general anesthesia), and pathology-induced [vegetative state/unresponsive wakeful syndrome (VS/UWS)] loss of consciousness in both human subjects and animals, we, in this study, suggest that the energetic-metabolic processes focusing on ATP, glucose, and γ-aminobutyrate/glutamate are indispensable for functional connectivity (FC) of normal brain networks that renders consciousness possible. Therefore, we describe the energetic-metabolic predispositions of consciousness (EPC) that complement the current theories focused on the neural correlates of consciousness (NCC).
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Affiliation(s)
- Yali Chen
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jun Zhang
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical college, Fudan University, Shanghai, China
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15
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The Relationship Among Glucose Metabolism, Cerebral Blood Flow, and Functional Activity: a Hybrid PET/fMRI Study. Mol Neurobiol 2021; 58:2862-2873. [PMID: 33523358 DOI: 10.1007/s12035-021-02305-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 12/20/2020] [Indexed: 10/22/2022]
Abstract
18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) estimate brain activities from different aspects, including regional glucose uptake (rGU) by 18FDG-PET, regional cerebral blood flow (rCBF) by arterial spin labeling, and dynamic changes of deoxyhemoglobin by blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI). However, the relationships between them remain incompletely understood. In the current study, twenty-four subjects (14 males, 10 females) were recruited and investigated the correlation among rGU, rCBF, and BOLD fMRI-derived metrics reflecting the neural activity, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) by hybrid PET/fMRI. Correlation analyses were performed across subject and across space at both voxel level and region level, considering partial volume effects by adjusting for gray matter volume. Each pair of metrics showed significant across-space correlations. rGU against ReHo showed the highest mean correlation coefficients. rGU had higher correlations with three resting-state (RS) fMRI metrics than did ASL-rCBF. However, the across-subject correlations were not significant among functional modalities (rGU, rCBF, and RS-fMRI BOLD data) at either voxel level or region level even with a liberal threshold, except for significant across-subject correlation between RS-fMRI metrics (ALFF, ReHo, and DC). These comprehensive findings from hybrid PET/MR might provide complementary information to reveal the underlying mechanisms of the brain activity and open new perspective to interpret pathologic conditions.
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