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Strýček O, Říha P, Kojan M, Řehák Z, Brázdil M. Metabolic connectivity as a predictor of surgical outcome in mesial temporal lobe epilepsy. Epilepsia Open 2024; 9:187-199. [PMID: 37881152 PMCID: PMC10839369 DOI: 10.1002/epi4.12853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 10/20/2023] [Indexed: 10/27/2023] Open
Abstract
OBJECTIVE The study investigated metabolic connectivity (MC) differences between patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS) and healthy controls (HCs), based on [18 F]-fluorodeoxyglucose (FDG)-PET data. We focused on the MC changes dependent on the lateralization of the epileptogenic lobe and on correlations with postoperative outcomes. METHODS FDG-PET scans of 47 patients with unilateral MTLE with histopathologically proven HS and 25 HC were included in the study. All the patients underwent a standard anterior temporal lobectomy and were more than 2 years after the surgery. MC changes were compared between the two HS groups (left HS, right HS) and HC. Differences between the metabolic network of seizure-free and non-seizure-free patients after surgery were depicted afterward. Network changes were correlated with clinical characteristics. RESULTS The study showed widespread metabolic network changes in the HS patients as compared to HC. The changes were more extensive in the right HS than in the left HS. Unfavorable surgical outcomes were found in patients with decreased MC within the network including both the lesional and contralesional hippocampus, ipsilesional frontal operculum, and contralesional insula. Favorable outcomes correlated with decreased MC within the network involving both orbitofrontal cortices and the ipsilesional temporal lobe. SIGNIFICANCE There are major differences in the metabolic networks of left and right HS, with more extensive changes in right HS. The changes within the metabolic network could help predict surgical outcomes in patients with HS. MC may identify patients with potentially unfavorable outcomes and direct them to a more detailed presurgical evaluation. PLAIN LANGUAGE SUMMARY Metabolic connectivity is a promising method for metabolic network mapping. Metabolic networks in mesial temporal lobe epilepsy are dependent on lateralization of the epileptogenic lobe and could predict surgical outcomes.
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Affiliation(s)
- Ondřej Strýček
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Faculty of MedicineMasaryk University, Member of ERN‐EpiCAREBrnoCzech Republic
- Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzech Republic
| | - Pavel Říha
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Faculty of MedicineMasaryk University, Member of ERN‐EpiCAREBrnoCzech Republic
- Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzech Republic
| | - Martin Kojan
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Faculty of MedicineMasaryk University, Member of ERN‐EpiCAREBrnoCzech Republic
- Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzech Republic
| | - Zdeněk Řehák
- Department of Nuclear MedicineMasaryk Memorial Cancer InstituteBrnoCzech Republic
| | - Milan Brázdil
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Faculty of MedicineMasaryk University, Member of ERN‐EpiCAREBrnoCzech Republic
- Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzech Republic
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Kim JR, Jo H, Park B, Park YH, Chung YH, Shon YM, Seo DW, Hong SB, Hong SC, Seo SW, Joo EY. Identifying important factors for successful surgery in patients with lateral temporal lobe epilepsy. PLoS One 2023; 18:e0288054. [PMID: 37384651 PMCID: PMC10310033 DOI: 10.1371/journal.pone.0288054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 06/18/2023] [Indexed: 07/01/2023] Open
Abstract
OBJECTIVE Lateral temporal lobe epilepsy (LTLE) has been diagnosed in only a small number of patients; therefore, its surgical outcome is not as well-known as that of mesial temporal lobe epilepsy. We aimed to evaluate the long-term (5 years) and short-term (2 years) surgical outcomes and identify possible prognostic factors in patients with LTLE. METHODS This retrospective cohort study was conducted between January 1995 and December 2018 among patients who underwent resective surgery in a university-affiliated hospital. Patients were classified as LTLE if ictal onset zone was in lateral temporal area. Surgical outcomes were evaluated at 2 and 5 years. We subdivided based on outcomes and compared clinical and neuroimaging data including cortical thickness between two groups. RESULTS Sixty-four patients were included in the study. The mean follow-up duration after the surgery was 8.4 years. Five years after surgery, 45 of the 63 (71.4%) patients achieved seizure freedom. Clinically and statistically significant prognostic factors for postsurgical outcomes were the duration of epilepsy before surgery and focal cortical dysplasia on postoperative histopathology at the 5-year follow-up. Optimal cut-off point for epilepsy duration was eight years after the seizure onset (odds ratio 4.375, p-value = 0.0214). Furthermore, we propose a model for predicting seizure outcomes 5 years after surgery using the receiver operating characteristic curve and nomogram (area under the curve = 0.733; 95% confidence interval, 0.588-0.879). Cortical thinning was observed in ipsilateral cingulate gyrus and contralateral parietal lobe in poor surgical group compared to good surgical group (p-value < 0.01, uncorrected). CONCLUSIONS The identified predictors of unfavorable surgical outcomes may help in selecting optimal candidates and identifying the optimal timing for surgery among patients with LTLE. Additionally, cortical thinning was more extensive in the poor surgical group.
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Affiliation(s)
- Jae Rim Kim
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hyunjin Jo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Boram Park
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
| | - Yu Hyun Park
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Yeon Hak Chung
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Young-Min Shon
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Dae-Won Seo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seung Bong Hong
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seung-Chyul Hong
- Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Eun Yeon Joo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
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Wang X, Lin D, Zhao C, Li H, Fu L, Huang Z, Xu S. Abnormal metabolic connectivity in default mode network of right temporal lobe epilepsy. Front Neurosci 2023; 17:1011283. [PMID: 37034164 PMCID: PMC10076532 DOI: 10.3389/fnins.2023.1011283] [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: 08/04/2022] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Abstract
Aims Temporal lobe epilepsy (TLE) is a common neurological disorder associated with the dysfunction of the default mode network (DMN). Metabolic connectivity measured by 18F-fluorodeoxyglucose Positron Emission Computed Tomography (18F-FDG PET) has been widely used to assess cumulative energy consumption and provide valuable insights into the pathophysiology of TLE. However, the metabolic connectivity mechanism of DMN in TLE is far from fully elucidated. The present study investigated the metabolic connectivity mechanism of DMN in TLE using 18F-FDG PET. Method Participants included 40 TLE patients and 41 health controls (HC) who were age- and gender-matched. A weighted undirected metabolic network of each group was constructed based on 14 primary volumes of interest (VOIs) in the DMN, in which Pearson's correlation coefficients between each pair-wise of the VOIs were calculated in an inter-subject manner. Graph theoretic analysis was then performed to analyze both global (global efficiency and the characteristic path length) and regional (nodal efficiency and degree centrality) network properties. Results Metabolic connectivity in DMN showed that regionally networks changed in the TLE group, including bilateral posterior cingulate gyrus, right inferior parietal gyrus, right angular gyrus, and left precuneus. Besides, significantly decreased (P < 0.05, FDR corrected) metabolic connections of DMN in the TLE group were revealed, containing bilateral hippocampus, bilateral posterior cingulate gyrus, bilateral angular gyrus, right medial of superior frontal gyrus, and left inferior parietal gyrus. Conclusion Taken together, the present study demonstrated the abnormal metabolic connectivity in DMN of TLE, which might provide further insights into the understanding the dysfunction mechanism and promote the treatment for TLE patients.
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Affiliation(s)
- Xiaoyang Wang
- Department of Medical Imaging, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, China
- Department of Medical Imaging, Affiliated Dongfang Hospital, Xiamen University, Fuzhou, Fujian, China
| | - Dandan Lin
- Department of Clinical Medicine, Fujian Health College, Fuzhou, Fujian, China
| | - Chunlei Zhao
- Department of Medical Imaging, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, China
- Department of Medical Imaging, Affiliated Dongfang Hospital, Xiamen University, Fuzhou, Fujian, China
| | - Hui Li
- Department of Medical Imaging, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, China
| | - Liyuan Fu
- Department of Medical Imaging, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, China
- Department of Medical Imaging, Affiliated Dongfang Hospital, Xiamen University, Fuzhou, Fujian, China
| | - Zhifeng Huang
- Department of Medical Imaging, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, China
- Department of Medical Imaging, Affiliated Dongfang Hospital, Xiamen University, Fuzhou, Fujian, China
| | - Shangwen Xu
- Department of Medical Imaging, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, China
- Department of Medical Imaging, Affiliated Dongfang Hospital, Xiamen University, Fuzhou, Fujian, China
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Expression of fructose-1,6-bisphosphatase 1 is associated with [ 18F]FDG uptake and prognosis in patients with mesial temporal lobe epilepsy. Eur Radiol 2023; 33:3396-3406. [PMID: 36692596 DOI: 10.1007/s00330-023-09422-5] [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: 08/18/2022] [Revised: 12/09/2022] [Accepted: 01/02/2023] [Indexed: 01/25/2023]
Abstract
OBJECTIVES To determine whether fructose-1,6-bisphosphatase 1 (FBP1) expression is associated with [18F]FDG PET uptake and postsurgical outcomes in patients with mesial temporal lobe epilepsy (mTLE) and to investigate whether the molecular mechanism involving gamma-aminobutyric acid type A receptor (GABAAR), glucose transporter-3 (GLUT-3), and hexokinase-II (HK-II). METHODS Forty-three patients with mTLE underwent [18F]FDG PET/CT. Patients were divided into Ia (Engel class Ia) and non-Ia (Engel class Ib-IV) groups according to more than 1 year of follow-up after surgery. The maximum standard uptake value (SUVmax) and asymmetry index (AI) of hippocampus were measured. The relationship among the SUVmax, AI, prognosis, and FBP1 expression was analyzed. A lithium-pilocarpine acute mTLE rat model was subjected to [18F]FDG micro-PET/CT. Hippocampal SUVmax and FBP1, GABAAR, GLUT-3, and HK-II expression were analyzed. RESULTS SUVmax was higher in the Ia group than in the non-Ia group (7.31 ± 0.97 vs. 6.56 ± 0.96, p < 0.05) and FBP1 expression was lower in the Ia group (0.24 ± 0.03 vs. 0.27 ± 0.03, p < 0.01). FBP1 expression was negatively associated with SUVmax and AI (p < 0.01). In mTLE rats, the hippocampal FBP1 increased (0.26 ± 0.00 vs. 0.17 ± 0.00, p < 0.0001), and SUVmax, GLUT-3 and GABAAR levels decreased significantly (0.73 ± 0.12 vs. 1.46 ± 0.23, 0.20 ± 0.01 vs. 0.32 ± 0.05, 0.26 ± 0.02 vs. 0.35 ± 0.02, p < 0.05); no significant difference in HK-II levels was observed. In mTLE patients and rats, FBP1 negatively correlated with SUVmax and GLUT-3 and GABAAR levels (p < 0.05). CONCLUSION FBP1 expression was inversely associated with SUVmax in mTLE, which might inhibit [18F]FDG uptake by regulating GLUT-3 expression. High FBP1 expression was indicative of low GABAAR expression and poor prognosis. KEY POINTS • It is of paramount importance to explore the deep pathophysiological mechanisms underlying the pathogenesis of mesial temporal lobe epilepsy and find potential therapeutic targets. • [18F]FDG PET has demonstrated low metabolism in epileptic regions during the interictal period, and hypometabolism may be associated with prognosis, but the pathomechanism of this association remains uncertain. • Our results support the possibility that FBP1 might be simultaneously involved in the regulation of glucose metabolism levels and the excitability of neurons and suggest that targeting FBP1 may be a viable strategy in the diagnosis and treatment of mesial temporal lobe epilepsy.
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Bartoňová M, Tournier JD, Bartoň M, Říha P, Vojtíšek L, Mareček R, Doležalová I, Rektor I. White matter alterations in MR-negative temporal and frontal lobe epilepsy using fixel-based analysis. Sci Rep 2023; 13:19. [PMID: 36593331 PMCID: PMC9807578 DOI: 10.1038/s41598-022-27233-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/28/2022] [Indexed: 01/03/2023] Open
Abstract
This study focuses on white matter alterations in pharmacoresistant epilepsy patients with no visible lesions in the temporal and frontal lobes on clinical MRI (i.e. MR-negative) with lesions confirmed by resective surgery. The aim of the study was to extend the knowledge about group-specific neuropathology in MR-negative epilepsy. We used the fixel-based analysis (FBA) that overcomes the limitations of traditional diffusion tensor image analysis, mainly within-voxel averaging of multiple crossing fibres. Group-wise comparisons of fixel parameters between healthy controls (N = 100) and: (1) frontal lobe epilepsy (FLE) patients (N = 9); (2) temporal lobe epilepsy (TLE) patients (N = 13) were performed. A significant decrease of the cross-section area of the fixels in the superior longitudinal fasciculus was observed in the FLE. Results in TLE reflected widespread atrophy of limbic, thalamic, and cortico-striatal connections and tracts directly connected to the temporal lobe (such as the anterior commissure, inferior fronto-occipital fasciculus, uncinate fasciculus, splenium of corpus callosum, and cingulum bundle). Alterations were also observed in extratemporal connections (brainstem connection, commissural fibres, and parts of the superior longitudinal fasciculus). To our knowledge, this is the first study to use an advanced FBA method not only on the datasets of MR-negative TLE patients, but also MR-negative FLE patients, uncovering new common tract-specific alterations on the group level.
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Affiliation(s)
- Michaela Bartoňová
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, First Department of Neurology, St. Anne’s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Jacques-Donald Tournier
- grid.13097.3c0000 0001 2322 6764Centre for Medical Engineering, King’s College London, London, UK ,grid.13097.3c0000 0001 2322 6764Centre for the Developing Brain, King’s College London, London, UK
| | - Marek Bartoň
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Pavel Říha
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, First Department of Neurology, St. Anne’s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Lubomír Vojtíšek
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Radek Mareček
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Irena Doležalová
- grid.10267.320000 0001 2194 0956Brno Epilepsy Center, First Department of Neurology, St. Anne’s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, First Department of Neurology, St. Anne’s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
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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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Doyen M, Chawki MB, Heyer S, Guedj E, Roch V, Marie PY, Tyvaert L, Maillard L, Verger A. Metabolic connectivity is associated with seizure outcome in surgically treated temporal lobe epilepsies: A 18F-FDG PET seed correlation analysis. Neuroimage Clin 2022; 36:103210. [PMID: 36208546 PMCID: PMC9668618 DOI: 10.1016/j.nicl.2022.103210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/14/2022] [Accepted: 09/22/2022] [Indexed: 12/14/2022]
Abstract
18F-FDG PET provides high sensitivity for the pre-surgical assessment of drug-resistant temporal lobe epilepsy (TLE). However, little is known about the metabolic connectivity of epileptogenic networks involved. This study therefore aimed to evaluate the association between metabolic connectivity and seizure outcome in surgically treated TLE. METHODS The study included 107 right-handed patients that had undergone a presurgical interictal 18F-FDG PET assessment followed by an anterior temporal lobectomy and were classified according to seizure outcome 2 years after surgery. Metabolic connectivity was evaluated by seed correlation analysis in left and right epilepsy patients with a Class Engel IA or > IA outcome and compared to age-, sex- and handedness-matched healthy controls. RESULTS Increased metabolic connectivity was observed in the >IA compared to the IA group within the operated temporal lobe (respective clusters of 7.5 vs 3.3 cm3 and 2.6 cm3 vs 2.2 cm3 in left and right TLE), and to a lower extent with the contralateral temporal lobe (1.2 vs 0.7 cm3 and 1.7 cm3 vs 0.7 cm3 in left and right TLE). Seed correlations provided added value for the estimated individual performance of seizure outcome over the group comparisons in left TLE (AUC of 0.74 vs 0.67). CONCLUSION Metabolic connectivity is associated with outcome in surgically treated TLE with a strengthened epileptogenic connectome in patients with non-free-seizure outcomes. The added value of seed correlation analysis in left TLE underlines the importance of evaluating metabolic connectivity in network related diseases.
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Affiliation(s)
- Matthieu Doyen
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France,Université de Lorraine, IADI, INSERM U1254, F-54000 Nancy, France,Corresponding author at: Université de Lorraine, IADI - INSERM U1254, Department of Nuclear Medicine and Nancyclotep Imaging Platform, F-54000 Nancy, France.
| | - Mohammad B. Chawki
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France
| | - Sébastien Heyer
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France
| | - Eric Guedj
- Aix Marseille Univ, APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, CERIMED, Nuclear Medicine Department, F-13000 Marseille, France
| | - Véronique Roch
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France
| | - Pierre-Yves Marie
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France,Université de Lorraine, INSERM, DCAC, Nancy, France
| | - Louise Tyvaert
- Université de Lorraine, CRAN UMR 7039, Nancy, France,Department of Neurology, CHRU Nancy, National Reference Center for Rare Epilepsies, F-54000 Nancy, France
| | - Louis Maillard
- Université de Lorraine, CRAN UMR 7039, Nancy, France,Department of Neurology, CHRU Nancy, National Reference Center for Rare Epilepsies, F-54000 Nancy, France
| | - Antoine Verger
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France,Université de Lorraine, IADI, INSERM U1254, F-54000 Nancy, France
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Tang Y, Yu J, Zhou M, Li J, Long T, Li Y, Feng L, Chen D, Yang Z, Huang Y, Hu S. Cortical abnormalities of synaptic vesicle protein 2A in focal cortical dysplasia type II identified in vivo with 18F-SynVesT-1 positron emission tomography imaging. Eur J Nucl Med Mol Imaging 2022; 49:3482-3491. [PMID: 34978594 PMCID: PMC9308579 DOI: 10.1007/s00259-021-05665-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 12/19/2021] [Indexed: 11/29/2022]
Abstract
PURPOSE The loss of synaptic vesicle glycoprotein 2A (SV2A) is well established as the major correlate of epileptogenesis in focal cortical dysplasia type II (FCD II), but this has not been directly tested in vivo. In this positron emission tomography (PET) study with the new tracer 18F-SynVesT-1, we evaluated SV2A abnormalities in patients with FCD II and compared the pattern to 18F-fluorodeoxyglucose (18F-FDG). METHODS Sixteen patients with proven FCD II and 16 healthy controls were recruited. All FCD II patients underwent magnetic resonance imaging (MRI) and static PET imaging with both 18F-SynVesT-1 and 18F-FDG, while the controls underwent MRI and PET with only 18F-SynVesT-1. Visual assessment of PET images was undertaken. The standardized uptake values (SUVs) of 18F-SynVesT-1 were computed for regions of interest (ROIs), along with SUV ratio (SUVr) between ROI and centrum semiovale (white matter). Asymmetry indices (AIs) were analyzed between the lesion and the contralateral hemisphere for intersubject comparisons. RESULTS Lesions in the brains of FCD II patients had significantly reduced 18F-SynVesT-1 uptake compared with contralateral regions, and brains of the controls. 18F-SynVesT-1 PET indicated low lesion uptake in 14 patients (87.5%), corresponding to hypometabolism detected by 18F-FDG PET, with higher accuracy for lesion localization than MRI (43.8%) (P < 0.05). AI analyses demonstrated that in the lesions, SUVr for each of the radiotracers were not significantly different (P > 0.05), and 18F-SynVesT-1 SUVr correlated with that of 18F-FDG across subjects (R2 = 0.41, P = 0.008). Subsequent visual ratings indicated that 18F-SynVesT-1 uptake had a more restricted pattern of reduction than 18F-FDG uptake in FCD II lesions (P < 0.05). CONCLUSION SV2A PET with 18F-SynVesT-1 shows a higher accuracy for the localization of FCD II lesions than MRI and a more restricted pattern of abnormality than 18F-FDG PET.
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Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Jie Yu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Ming Zhou
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Tingting Long
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Yulai Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dengming Chen
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Zhiquan Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yiyun Huang
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 801 Howard Ave, P.O. Box 208048, New Haven, CT, 06520-8048, USA.
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan, China.
- National Clinical Research Center for Geriatric Disorders (Xiangya), Xiangya Hospital, Central South University, Changsha, Hunan, China.
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Tang Y, Liu P, Li W, Liu Z, Zhou M, Li J, Yuan Y, Fang L, Wang M, Shen L, Huang Y, Tang B, Wang J, Hu S. Detection of changes in synaptic density in amyotrophic lateral sclerosis patients using 18 F-SynVesT-1 positron-emission tomography. Eur J Neurol 2022; 29:2934-2943. [PMID: 35708508 DOI: 10.1111/ene.15451] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 06/13/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Synaptic loss is well established as the major correlate of characteristic and consistent pathology in amyotrophic lateral sclerosis (ALS). We aimed to assess the possible discriminant diagnostic value of 18 F-SynVesT-1 positron-emission tomography (PET) as a marker of ALS pathology and investigate whether specific synaptic density signatures are present in ALS with different subtypes. METHODS Twenty-one patients with ALS and 25 healthy controls (HCs) were recruited. All participants underwent 18 F-SynVesT-1-PET. Synaptic density between ALS and HCs and between different ALS subgroups were compared. Correlation between synaptic density and clinical features in ALS was also performed. RESULTS Low uptake distribution was found in the group comprising 21 ALS patients as compared with HCs in the right temporal lobe and the bilateral inferior frontal gyrus, anterior cingulate, and hippocampus-insula region. We also found a low uptake in the bilateral superior temporal gyrus, hippocampus-insula, anterior cingulate and left inferior frontal gyrus in ALS patients with cognitive impairment compared to HCs. Furthermore, compared to spinal-onset ALS, bulbar-onset ALS showed low uptake in the bilateral cingulate gyrus and high uptake in the bilateral superior temporal gyrus and left occipital lobe. No significant result was found in correlation analysis. CONCLUSION This approach may provide a direct measure of synaptic density, and it therefore might represent a potentially useful biomarker for ALS diagnosis, as well as for estimating the cognitive decline and site of onset in ALS. 18 F-SynVesT-1-PET is presently not justified as a routine investigation to detect evidence of brain dysfunction justifying progression in ALS.
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Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Pan Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Wanzhen Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Zhen Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Ming Zhou
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Yanchun Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Liangjuan Fang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Mengli Wang
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, P. R. China.,Center for Medical Genetics, School of Life Sciences, Central South University
| | - Yiyun Huang
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, P. R. China.,Center for Medical Genetics, School of Life Sciences, Central South University
| | - Junling Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, P. R. China.,Center for Medical Genetics, School of Life Sciences, Central South University.,Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China.,Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.,Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan, China
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Tang Y, Li W, Tao L, Li J, Long T, Li Y, Chen D, Hu S. Machine Learning-Derived Multimodal Neuroimaging of Presurgical Target Area to Predict Individual's Seizure Outcomes After Epilepsy Surgery. Front Cell Dev Biol 2022; 9:669795. [PMID: 35127691 PMCID: PMC8814443 DOI: 10.3389/fcell.2021.669795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 12/21/2021] [Indexed: 11/16/2022] Open
Abstract
Objectives: Half of the patients who have tailored resection of the suspected epileptogenic zone for drug-resistant epilepsy have recurrent postoperative seizures. Although neuroimaging has become an indispensable part of delineating the epileptogenic zone, no validated method uses neuroimaging of presurgical target area to predict an individual's post-surgery seizure outcome. We aimed to develop and validate a machine learning-powered approach incorporating multimodal neuroimaging of a presurgical target area to predict an individual's post-surgery seizure outcome in patients with drug-resistant focal epilepsy. Materials and Methods: One hundred and forty-one patients with drug-resistant focal epilepsy were classified either as having seizure-free (Engel class I) or seizure-recurrence (Engel class II through IV) at least 1 year after surgery. The presurgical magnetic resonance imaging, positron emission tomography, computed tomography, and postsurgical magnetic resonance imaging were co-registered for surgical target volume of interest (VOI) segmentation; all VOIs were decomposed into nine fixed views, then were inputted into the deep residual network (DRN) that was pretrained on Tiny-ImageNet dataset to extract and transfer deep features. A multi-kernel support vector machine (MKSVM) was used to integrate multiple views of feature sets and to predict seizure outcomes of the targeted VOIs. Leave-one-out validation was applied to develop a model for verifying the prediction. In the end, performance using this approach was assessed by calculating accuracy, sensitivity, and specificity. Receiver operating characteristic curves were generated, and the optimal area under the receiver operating characteristic curve (AUC) was calculated as a metric for classifying outcomes. Results: Application of DRN-MKSVM model based on presurgical target area neuroimaging demonstrated good performance in predicting seizure outcomes. The AUC ranged from 0.799 to 0.952. Importantly, the classification performance DRN-MKSVM model using data from multiple neuroimaging showed an accuracy of 91.5%, a sensitivity of 96.2%, a specificity of 85.5%, and AUCs of 0.95, which were significantly better than any other single-modal neuroimaging (all p ˂ 0.05). Conclusion: DRN-MKSVM, using multimodal compared with unimodal neuroimaging from the surgical target area, accurately predicted postsurgical outcomes. The preoperative individualized prediction of seizure outcomes in patients who have been judged eligible for epilepsy surgery could be conveniently facilitated. This may aid epileptologists in presurgical evaluation by providing a tool to explore various surgical options, offering complementary information to existing clinical techniques.
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Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Weikai Li
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
| | - Lue Tao
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Jian Li
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Tingting Long
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Yulai Li
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Dengming Chen
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Changsha, China
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Diseases, Xiangya Hospital, Changsha, China
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11
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Zhu Z, Zhang Z, Gao X, Feng L, Chen D, Yang Z, Hu S. Individual Brain Metabolic Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation Predicts Seizure Outcomes of Temporal Lobe Epilepsy. Front Cell Dev Biol 2022; 9:803800. [PMID: 35310541 PMCID: PMC8926031 DOI: 10.3389/fcell.2021.803800] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/15/2021] [Indexed: 01/01/2023] Open
Abstract
Objective: We aimed to use an individual metabolic connectome method, the Jensen-Shannon Divergence Similarity Estimation (JSSE), to characterize the aberrant connectivity patterns and topological alterations of the individual-level brain metabolic connectome and predict the long-term surgical outcomes in temporal lobe epilepsy (TLE). Methods: A total of 128 patients with TLE (63 females, 65 males; 25.07 ± 12.01 years) who underwent Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) imaging were enrolled. Patients were classified either as experiencing seizure recurrence (SZR) or seizure free (SZF) at least 1 year after surgery. Each individual's metabolic brain network was ascertained using the proposed JSSE method. We compared the similarity and difference in the JSSE network and its topological measurements between the two groups. The two groups were then classified by combining the information from connection and topological metrics, which was conducted by the multiple kernel support vector machine. The validation was performed using the nested leave-one-out cross-validation strategy to confirm the performance of the methods. Results: With a median follow-up of 33 months, 50% of patients achieved SZF. No relevant differences in clinical features were found between the two groups except age at onset. The proposed JSSE method showed marked degree reductions in IFGoperc.R, ROL. R, IPL. R, and SMG. R; and betweenness reductions in ORBsup.R and IOG. R; meanwhile, it found increases in the degree analysis of CAL. L and PCL. L, and in the betweenness analysis of PreCG.R, IOG. R, PoCG.R, PCL. L and PCL.R. Exploring consensus significant metabolic connections, we observed that the most involved metabolic motor networks were the INS-TPOmid.L, MTG. R-SMG. R, and MTG. R-IPL.R pathways between the two groups, and yielded another detailed individual pathological connectivity in the PHG. R-CAU.L, PHG. R-HIP.L, TPOmid.L-LING.R, TPOmid.L-DCG.R, MOG. R-MTG.R, MOG. R-ANG.R, and IPL. R-IFGoperc.L pathways. These aberrant functional network measures exhibited ideal classification performance in predicting SZF individuals from SZR ones at a sensitivity of 75.00%, a specificity of 92.79%, and an accuracy of 83.59%. Conclusion: The JSSE method indicator can identify abnormal brain networks in predicting an individual's long-term surgical outcome of TLE, thus potentially constituting a clinically applicable imaging biomarker. The results highlight the biological meaning of the estimated individual brain metabolic connectome.
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Affiliation(s)
- Zehua Zhu
- Department of Nuclear Medicine, XiangYa Hospital, Changsha, China
| | - Zhimin Zhang
- Department of Blood Transfusion, XiangYa Hospital, Changsha, China
| | - Xin Gao
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Dengming Chen
- Department of Nuclear Medicine, XiangYa Hospital, Changsha, China
| | - Zhiquan Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - Shuo Hu
- Department of Nuclear Medicine, XiangYa Hospital, Changsha, China
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, China
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