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Li X, Liu H, Zhang T. Resting-state functional MRI study of conventional MRI-negative intractable epilepsy in children. Front Hum Neurosci 2024; 18:1337294. [PMID: 38510512 PMCID: PMC10951396 DOI: 10.3389/fnhum.2024.1337294] [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: 11/12/2023] [Accepted: 02/19/2024] [Indexed: 03/22/2024] Open
Abstract
Objective The study aimed at investigating functional connectivity strength (FCS) changes in children with MRI-negative intractable epilepsy (ITE) and evaluating correlations between aberrant FCS and both disease duration and intelligence quotient (IQ). Methods Fifteen children with ITE, 24 children with non-intractable epilepsy (nITE) and 25 matched healthy controls (HCs) were subjected to rs-fMRI. IQ was evaluated by neuropsychological assessment. Voxelwise analysis of covariance was conducted in the whole brain, and then pairwise comparisons were made across three groups using Bonferroni corrections. Results FCS was significantly different among three groups. Relative to HCs, ITE patients exhibited decreased FCS in right temporal pole of the superior temporal gyrus, middle temporal gyrus, bilateral precuneus, etc and increased FCS values in left triangular part of the inferior frontal gyrus, parahippocampal gyrus, supplementary motor area, caudate and right calcarine fissure and surrounding cortex and midbrain. The nITE patients presented decreased FCS in right orbital superior frontal gyrus, precuneus etc and increased FCS in bilateral fusiform gyri, parahippocampal gyri, etc. In comparison to nITE patients, the ITE patients presented decreased FCS in right medial superior frontal gyrus and left inferior temporal gyrus and increased FCS in right middle temporal gyrus, inferior temporal gyrus and calcarine fissure and surrounding cortex. Correlation analysis indicated that FCS in left caudate demonstrated correlation with verbal IQ (VIQ) and disease duration. Conclusion ITE patients demonstrated changed FCS values in the temporal and prefrontal cortices relative to nITE patients, which may be related to drug resistance in epilepsy. FCS in the left caudate nucleus associated with VIQ, suggesting the caudate may become a key target for improving cognitive impairment and seizures in children with ITE.
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Affiliation(s)
| | - Heng Liu
- Department of Radiology, Medical Imaging Center, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Tijiang Zhang
- Department of Radiology, Medical Imaging Center, Affiliated Hospital of Zunyi Medical University, Zunyi, China
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2
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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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3
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Kong Y, Cheng N, Qiu FJ, Yao L, Gao M, Chen AQ, Kong QX, Zhang GQ. Application value of multimodal MRI combined with PET metabolic parameters in temporal lobe epilepsy with dual pathology. Eur J Radiol 2023; 169:111171. [PMID: 38250750 DOI: 10.1016/j.ejrad.2023.111171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/03/2023] [Accepted: 10/24/2023] [Indexed: 01/23/2024]
Abstract
OBJECTIVES To investigate the application value of multimodal MRI combined with PET metabolic parameters in detecting temporal lobe epilepsy (TLE) with dual pathology (DP) and the prediction effect of post-surgical outcomes in these patients. METHODS We retrospectively reviewed 50 patients with TLE-DP who underwent surgery at our hospital between January 2016 and December 2021 and collected the demographics, clinical characteristics, video-electroencephalography (v-EEG), neuroimaging, and surgical data. Seizure outcome data were collected during a regular follow-up of at least 12 months and were graded using Engel scores. Fisher's exact test was used to compare the differences in DP detection rates of various diagnostic modalities. Univariate and multivariate analyses were performed to explore the prognostic factors for predicting seizure outcomes post-surgery. RESULTS Of the 50 patients, 20 were males. The median age was 30, the median age at first seizure was 14, and the median duration was ten years. Voxel-based morphometry-PET statistical parametric mapping-PET/MRI (VBM-PSPM-PET/MRI) had the highest detection rate, followed by PET/MRI, VBM analysis, and PET-SPM. Regardless of follow-up duration, v-EEG, PET, image post-processing methods, and VBM-PSPM-PET/MRI statistically correlated with seizure outcomes using the log-rank test in the Kaplan-Meier analysis. Multivariate analysis showed that VBM-PSPM-PET/MRI was an independent predictor of TLE-DP (hazard ratio (HR) = 15.674, 95 % CI = 0.002-0.122, P < 0.00 1). CONCLUSIONS Our study illustrates that VBM-PSPM-PET/MRI has the highest detection value in patients with TLE-DP and can provide independent prognostic information for patients who undergo surgery. This approach has the most substantial potential for the selection of candidates for patients who undergo surgical treatment and for prognostic stratification.
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Affiliation(s)
- Yu Kong
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China; College of Materials Science and Engineering, Qingdao University, Qingdao 266071, Shandong, China
| | - Nan Cheng
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - Feng-Juan Qiu
- Department of Pediatric Rehabilitation, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - Lei Yao
- Clinical Medical College, Jining Medical University, Jining 272067, Shandong, China
| | - Ming Gao
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - An-Qiang Chen
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - Qing-Xia Kong
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China.
| | - Gu-Qing Zhang
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China.
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4
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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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5
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Říha P, Doležalová I, Mareček R, Lamoš M, Bartoňová M, Kojan M, Mikl M, Gajdoš M, Vojtíšek L, Bartoň M, Strýček O, Pail M, Brázdil M, Rektor I. Multimodal combination of neuroimaging methods for localizing the epileptogenic zone in MR-negative epilepsy. Sci Rep 2022; 12:15158. [PMID: 36071087 PMCID: PMC9452535 DOI: 10.1038/s41598-022-19121-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 08/24/2022] [Indexed: 11/10/2022] Open
Abstract
The objective was to determine the optimal combination of multimodal imaging methods (IMs) for localizing the epileptogenic zone (EZ) in patients with MR-negative drug-resistant epilepsy. Data from 25 patients with MR-negative focal epilepsy (age 30 ± 10 years, 16M/9F) who underwent surgical resection of the EZ and from 110 healthy controls (age 31 ± 9 years; 56M/54F) were used to evaluate IMs based on 3T MRI, FDG-PET, HD-EEG, and SPECT. Patients with successful outcomes and/or positive histological findings were evaluated. From 38 IMs calculated per patient, 13 methods were selected by evaluating the mutual similarity of the methods and the accuracy of the EZ localization. The best results in postsurgical patients for EZ localization were found for ictal/ interictal SPECT (SISCOM), FDG-PET, arterial spin labeling (ASL), functional regional homogeneity (ReHo), gray matter volume (GMV), cortical thickness, HD electrical source imaging (ESI-HD), amplitude of low-frequency fluctuation (ALFF), diffusion tensor imaging, and kurtosis imaging. Combining IMs provides the method with the most accurate EZ identification in MR-negative epilepsy. The PET, SISCOM, and selected MRI-post-processing techniques are useful for EZ localization for surgical tailoring.
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Affiliation(s)
- Pavel Říha
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Irena Doležalová
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Radek Mareček
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Lamoš
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Michaela Bartoňová
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Kojan
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Michal Mikl
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Gajdoš
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Lubomír Vojtíšek
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Marek Bartoň
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ondřej Strýček
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Martin Pail
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Milan Brázdil
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic. .,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
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6
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Li R, Deng C, Wang X, Zou T, Biswal B, Guo D, Xiao B, Zhang X, Cheng JL, Liu D, Yang M, Chen H, Wu Q, Feng L. Interictal dynamic network transitions in mesial temporal lobe epilepsy. Epilepsia 2022; 63:2242-2255. [PMID: 35699346 DOI: 10.1111/epi.17325] [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: 03/17/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To reveal the possible routine of brain network dynamic alterations in patients with mesial temporal lobe epilepsy (mTLE) and to establish a predicted model of seizure recurrence during interictal periods. METHODS Seventy-nine unilateral mTLE patients with hippocampal sclerosis and 97 healthy controls from two centers were retrospectively enrolled. Dynamic brain configuration analyses were performed with resting-state functional magnetic resonance imaging (MRI) data to quantify the functional stability over time and the dynamic interactions between brain regions. Relationships between seizure frequency and ipsilateral hippocampal module allegiance were evaluated using a machine learning predictive model. RESULTS Compared to the healthy controls, patients with mTLE displayed an overall higher dynamic network, switching mainly in the epileptogenic regions (false discovery rate [FDR] corrected p-FDR < .05). Moreover, the dynamic network configuration in mTLE was characterized by decreased recruitment (intra-network communication), and increased integration (inter-network communication) among hippocampal systems and large-scale higher-order brain networks (p-FDR < .05). We further found that the dynamic interactions between the hippocampal system and the default-mode network (DMN) or control networks exhibited an opposite distribution pattern (p-FDR < .05). Strikingly, we showed that there was a robust association between predicted seizure frequency based on the ipsilateral hippocampal-DMN dynamics model and actual seizure frequency (p-perm < .001). SIGNIFICANCE These findings suggest that the interictal brain of mTLE is characterized by dynamical shifts toward unstable state. Our study provides novel insights into the brain dynamic network alterations and supports the potential use of DMN dynamic parameters as candidate neuroimaging markers in monitoring the seizure frequency clinically during interictal periods.
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Affiliation(s)
- Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chijun Deng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xuyang Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ting Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
| | - Danni Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jing Liang Cheng
- Department of Magnetic Resonance, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ding Liu
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Mi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qian Wu
- Department of Neurology, First Affiliated Hospital, Kunming Medical University, Kunming, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
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7
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Shih YC, Lee TH, Yu HY, Chou CC, Lee CC, Lin PT, Peng SJ. Machine Learning Quantitative Analysis of FDG PET Images of Medial Temporal Lobe Epilepsy Patients. Clin Nucl Med 2022; 47:287-293. [PMID: 35085166 PMCID: PMC8884180 DOI: 10.1097/rlu.0000000000004072] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 11/20/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE 18F-FDG PET is widely used in epilepsy surgery. We established a robust quantitative algorithm for the lateralization of epileptogenic foci and examined the value of machine learning of 18F-FDG PET data in medial temporal lobe epilepsy (MTLE) patients. PATIENTS AND METHODS We retrospectively reviewed patients who underwent surgery for MTLE. Three clinicians identified the side of MTLE epileptogenesis by visual inspection. The surgical side was set as the epileptogenic side. Two parcellation paradigms and corresponding atlases (Automated Anatomical Labeling and FreeSurfer aparc + aseg) were used to extract the normalized PET uptake of the regions of interest (ROIs). The lateralization index of the MTLE-associated regions in either hemisphere was calculated. The lateralization indices of each ROI were subjected for machine learning to establish the model for classifying the side of MTLE epileptogenesis. RESULT Ninety-three patients were enrolled for training and validation, and another 11 patients were used for testing. The hit rate of lateralization by visual analysis was 75.3%. Among the 23 patients whose MTLE side of epileptogenesis was incorrectly determined or for whom no conclusion was reached by visual analysis, the Automated Anatomical Labeling and aparc + aseg parcellated the associated ROIs on the correctly lateralized MTLE side in 100.0% and 82.6%. In the testing set, lateralization accuracy was 100% in the 2 paradigms. CONCLUSIONS Visual analysis of 18F-FDG PET to lateralize MTLE epileptogenesis showed a lower hit rate compared with machine-assisted interpretation. While reviewing 18F-FDG PET images of MTLE patients, considering the regions associated with MTLE resulted in better performance than limiting analysis to hippocampal regions.
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Affiliation(s)
- Yen-Cheng Shih
- From the Department of Neurology, Neurological Institute, Taipei Veterans General Hospital
- School of Medicine, National Yang Ming Chiao Tung University College of Medicine
- Brain Research Center, National Yang Ming Chiao Tung University
| | - Tse-Hao Lee
- School of Medicine, National Yang Ming Chiao Tung University College of Medicine
- Departments of Nuclear Medicine
| | - Hsiang-Yu Yu
- From the Department of Neurology, Neurological Institute, Taipei Veterans General Hospital
- School of Medicine, National Yang Ming Chiao Tung University College of Medicine
- Brain Research Center, National Yang Ming Chiao Tung University
| | - Chien-Chen Chou
- From the Department of Neurology, Neurological Institute, Taipei Veterans General Hospital
- School of Medicine, National Yang Ming Chiao Tung University College of Medicine
- Brain Research Center, National Yang Ming Chiao Tung University
| | - Cheng-Chia Lee
- School of Medicine, National Yang Ming Chiao Tung University College of Medicine
- Brain Research Center, National Yang Ming Chiao Tung University
- Neurosurgery, Neurological Institute, Taipei Veterans General Hospital
| | - Po-Tso Lin
- From the Department of Neurology, Neurological Institute, Taipei Veterans General Hospital
- School of Medicine, National Yang Ming Chiao Tung University College of Medicine
- Brain Research Center, National Yang Ming Chiao Tung University
| | - Syu-Jyun Peng
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
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8
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Wu D, Yang L, Gong G, Zheng Y, Jin C, Qi L, Li Y, Wu D, Cui Z, He X, Ren L. Characterizing the hyper- and hypometabolism in temporal lobe epilepsy using multivariate machine learning. J Neurosci Res 2021; 99:3035-3046. [PMID: 34498762 DOI: 10.1002/jnr.24951] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 07/21/2021] [Accepted: 08/07/2021] [Indexed: 11/08/2022]
Abstract
Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy, presenting both structural and metabolic abnormalities in the ipsilateral mesial temporal lobe. While it has been demonstrated that the metabolic abnormalities in MTLE actually extend beyond the epileptogenic zone, how such multidimensional information is associated with the diagnosis of MTLE remains to be tested. Here, we explore the whole-brain metabolic patterns in 23 patients with MTLE and 24 healthy controls using [18 F]fluorodeoxyglucose PET imaging. Based on a multivariate machine learning approach, we demonstrate that the brain metabolic patterns can discriminate patients with MTLE from controls with a superior accuracy (>95%). Importantly, voxels showing the most extreme contributing weights to the classification (i.e., the most important regional predictors) distribute across both hemispheres, involving both ipsilateral negative weights over the anterior part of lateral and medial temporal lobe, posterior insula, and lateral orbital frontal gyrus, and contralateral positive weights over the anterior frontal lobe, temporal lobe, and lingual gyrus. Through region-of-interest analyses, we verify that in patients with MTLE, the negatively weighted regions are hypometabolic, and the positively weighted regions are hypermetabolic, compared to controls. Interestingly, despite that both hypo- and hypermetabolism have mutually contributed to our model, they may reflect different pathological and/or compensative responses. For instance, patients with earlier age at epilepsy onset present greater hypometabolism in the ipsilateral inferior temporal gyrus, while we find no evidence of such association with hypermetabolism. In summary, quantitative models utilizing multidimensional brain metabolic information may provide additional assistance to presurgical workups in TLE.
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Affiliation(s)
- Dongyan Wu
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yumin Zheng
- Department of Nuclear Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Chaoling Jin
- Department of Nuclear Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Lei Qi
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yanran Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Di Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Xiaosong He
- Department of Psychology, University of Science and Technology of China, Hefei, China
| | - Liankun Ren
- Comprehensive Epilepsy Center of Beijing, The Beijing Key Laboratory of Neuromodulation, Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
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9
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Association of hypometabolic extension of 18F-FDG PET with diffusion tensor imaging indices in mesial temporal lobe epilepsy with hippocampal sclerosis. Seizure 2021; 88:130-137. [PMID: 33878604 DOI: 10.1016/j.seizure.2021.04.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/06/2021] [Accepted: 04/08/2021] [Indexed: 11/23/2022] Open
Abstract
PURPOSE To assess the association between hypometabolic extension of 18F-fluorodeoxyglucose positron emission tomography and diffusion tensor imaging indices, including mean diffusivity (MD) and fractional anisotropy (FA), in hippocampal sclerosis (HS). METHODS Thirty-six unilateral HS were retrospectively selected and stratified into two groups: broad and localized hypometabolic groups (hypometabolism beyond [n = 26] and within the temporal lobe [n = 10]). Forty-one pairs of gray matter (GM) regions of interest (ROIs) were segmented using FreeSurfer software. The GM ROIs were applied to MD maps, and median MD values within each ROI were compared between hemispheres ipsilateral and contralateral to HS using a mixed effect model. Tract-Based Spatial Statistics (TBSS) was used to evaluate FA of white matter (WM) tracts between hemispheres ipsilateral and contralateral to HS. Disease laterality was controlled for. RESULTS The MD values in the thalamus, caudate, hippocampus, amygdala, superior frontal gyrus, middle and inferior temporal gyrus, temporal pole, and isthmus cingulate gyrus were significantly higher in the HS side than the contralateral side for the broad hypometabolic group. Those in the amygdala and superior temporal sulcus were significantly higher in the HS side than the contralateral side for the localized group. The TBSS analyses showed significantly decreased FA in the WM tracts of the temporal and frontal lobes for the broad hypometabolic group, while no tracts showed significant differences for the localized group. CONCLUSION The hypometabolic extension for HS was associated with the abnormalities of MD and FA in GM and WM, respectively, with more widespread microstructural alterations for broad hypometabolic HS.
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Kojan M, Gajdoš M, Říha P, Doležalová I, Řehák Z, Rektor I. Arterial Spin Labeling is a Useful MRI Method for Presurgical Evaluation in MRI-Negative Focal Epilepsy. Brain Topogr 2021; 34:504-510. [PMID: 33783670 DOI: 10.1007/s10548-021-00833-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 03/16/2021] [Indexed: 12/25/2022]
Abstract
Arterial spin labeling (ASL) is an MRI technique measuring brain perfusion using magnetically labeled blood as a tracer. The clinical utility of ASL for presurgical evaluation in non-lesional epilepsy as compared with the quantitative analysis of interictal [18F] fluorodeoxyglucose PET (FDG-PET) was studied. In 10 patients (4 female; median age 29 years) who underwent a complete presurgical evaluation followed by surgical resection, the presurgical FDG-PET and ASL scans were compared with the resection masks using asymmetry index (AI) maps. The positive predictive value (PPV) and sensitivity (SEN), were calculated from the number of voxels inside the mask (true positive), and outside the mask (false positive). The comparison of the PPVs showed better PPV in 6 patients using ASL and in 2 patients with PET. SEN was better in 4 patients using ASL and in 5 patients with PET. According to the Wilcoxon signed rank test for PPV (p = 0.74) and for SEN (p = 0.43), these methods have similar predictive power. ASL is a useful method for presurgical evaluation in non-lesional epilepsy. The main benefits of ASL over PET are that it avoids radiation exposure for patients, and it offers lower costs, higher availability, and better time efficiency.
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Affiliation(s)
- Martin Kojan
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- CEITEC - Central European Institute of Technology, Neuroscience Center, Masaryk University, Brno, Czech Republic
| | - Martin Gajdoš
- CEITEC - Central European Institute of Technology, Neuroscience Center, Masaryk University, Brno, Czech Republic
| | - Pavel Říha
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- CEITEC - Central European Institute of Technology, Neuroscience Center, Masaryk University, Brno, Czech Republic
| | - Irena Doležalová
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Zdeněk Řehák
- Department of Nuclear Medicine, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Ivan Rektor
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic.
- CEITEC - Central European Institute of Technology, Neuroscience Center, Masaryk University, Brno, Czech Republic.
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Kuruva M, Moncayo VM, Peterson RB. PET and SPECT Imaging of Epilepsy: Technical Considerations, Pathologies, and Pitfalls. Semin Ultrasound CT MR 2020; 41:551-561. [DOI: 10.1053/j.sult.2020.08.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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Guo K, Wei Y, Yuan M, Wei L, Lu J. Identifying the characteristics of brain glucose metabolism using normal 18F-FDG PET database in patients with temporal lobe epilepsy. Neurol Sci 2020; 41:3219-3226. [PMID: 32372198 DOI: 10.1007/s10072-020-04426-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 04/13/2020] [Indexed: 11/29/2022]
Abstract
OBJECTIVES This study aimed to measure the global brain glucose metabolism of patients with temporal lobe epilepsy (TLE) using MIMneuro software based on the normal brain glucose metabolism database. METHODS In this cross-sectional study, 23 patients (11 males and 12 females, mean age 25.6 ± 10.1 years) with TLE who underwent 18F-labeled fluoro-2-deoxyglucose positron emission tomography (18F-FDG PET) were enrolled. 18F-FDG PET images were then imported into MIMneuro software, which can automatically analyze the differences in regional brain glucose metabolism between patients and a normal database, and the results of different brain regions were presented by values of Z-score. RESULTS In patients with TLE, 18F-FDG PET imaging showed that in addition to the presence of temporal lobe hypometabolism, there was hypometabolism in the ipsilateral hippocampus, parahippocampal gyrus, insula, amygdala, temporal operculum, and bilateral cerebellar hemisphere, while hypermetabolism was found in the contralateral temporal lobe, frontal lobe, parietal lobe, parietal lobule, angular gyrus, and precentral gyrus. There was no significant difference in brain areas between the left and the right temporal lobe seizures (P > 0.05). CONCLUSIONS We found that TLE has a specific characteristic in terms of brain glucose metabolism, and the underlying mechanism needs to be further studied that may be helpful to localize seizure focus.
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Affiliation(s)
- Kun Guo
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yixin Wei
- Department of Nuclear Medicine, The Second Affiliated Hospital of Air Force Medical University, Xi'an, Shanxi, China
| | - Menghui Yuan
- Department of Nuclear Medicine, The Second Affiliated Hospital of Air Force Medical University, Xi'an, Shanxi, China.
| | - Longxiao Wei
- Department of Nuclear Medicine, The Second Affiliated Hospital of Air Force Medical University, Xi'an, Shanxi, China.
| | - Jie Lu
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China. .,Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China. .,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
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Zhang Z, Zhou X, Liu J, Qin L, Ye W, Zheng J. Aberrant functional connectivity of the cingulate subregions in right-sided temporal lobe epilepsy. Exp Ther Med 2020; 19:2901-2912. [PMID: 32256775 PMCID: PMC7086282 DOI: 10.3892/etm.2020.8551] [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: 07/17/2019] [Accepted: 12/09/2019] [Indexed: 11/17/2022] Open
Abstract
Patients with temporal lobe epilepsy (TLE) have been indicated to exhibit abnormal resting-state functional connectivity (rsFC) of the cingulate cortex. However, it has remained elusive whether cingulate subregions show different connectivity patterns in TLE. The present study aimed to investigate the differences in rsFC of each cingulate subregion between patients with right-sided TLE (rTLE) and healthy controls (HCs), as well as their association with executive control performance in rTLE. A total of 27 patients with rTLE and 20 age-, sex- and education-matched healthy controls were recruited and all participants underwent resting-state functional MRI and an attention network test for the assessment executive control function. In each hemisphere, the cingulate gyrus (CG) was divided into CG-1 (dorsal area 23; A23d), CG-2 (rostroventral area 24; A24rv), CG-3 (pregenual area 32; A32p), CG-4 (ventral area 23; A23v), CG-5 (caudodorsal area 24; A24cd), CG-6 (caudal area 24; A23c) and CG-7 (subgenual area 32; A32sg). Pearson's correlation analysis was performed to assess the correlation between the altered FCs of the cingulate subregions and clinical variables. In patients with rTLE, the majority of the cingulate subregions exhibited decreased rsFC; this was primarily restricted to the right CG-2, the bilateral CG-6 and the bilateral CG-7. Increased rsFC was only detected in rTLE restricted to the left CG-1. Impairments in executive control efficiency were identified in patients with rTLE in comparison with the HCs. Significant alterations in rsFC between the cingulate subregion and the brain regions were mostly decreased (and some slightly increased), suggesting that FC may potentially have a left-side advantage in patients with rTLE. FC variations of the cingulate subregions were indicated to be specific to rTLE. In addition, increased connectivity in the left CG-1 and left superior frontal gyrus were negatively correlated with executive control performance, suggesting a compensatory mechanism on executive control deficits in pathological conditions. This information on differentially altered FC patterns of the cingulate subregions may provide a deeper understanding of the complex neurological mechanisms and executive control dysfunctions underlying rTLE.
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Affiliation(s)
- Zhao Zhang
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jinping Liu
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Lu Qin
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Wei Ye
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jinou Zheng
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
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Zhang Z, Zhou X, Liu J, Qin L, Yu L, Pang X, Ye W, Zheng J. Longitudinal assessment of resting-state fMRI in temporal lobe epilepsy: A two-year follow-up study. Epilepsy Behav 2020; 103:106858. [PMID: 31899164 DOI: 10.1016/j.yebeh.2019.106858] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 12/07/2019] [Accepted: 12/13/2019] [Indexed: 12/27/2022]
Abstract
In this study, we aimed to detect longitudinal alterations in local spontaneous brain activity and functional connectivity (FC) of the default mode network (DMN) in patients with temporal lobe epilepsy (TLE) over a two-year follow-up. We used amplitude of low-frequency fluctuation (ALFF) analysis and independent component analysis (ICA) to explore differences in local spontaneous brain activity and FC strength. In total, 33 participants (16 patients with TLE and 17 age- and gender-matched healthy controls (HCs)) were recruited in this study. All participants performed the Attention Network Test (ANT) for evaluation of the executive control function. Compared with healthy patients at baseline, patients with TLE at follow-up exhibited increased ALFF values in the left medial frontal gyrus, as well as reduced FC values in the left inferior parietal gyrus (IPG) within the DMN. Patients with TLE revealed executive dysfunction, but no progressive deterioration was observed during follow-up. This study revealed the abnormal distribution of ALFF values and Rs-FC changes over a two-year follow-up period in TLE, both of which demonstrated different reorganization trajectories and loss of efficiency.
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Affiliation(s)
- Zhao Zhang
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jinping Liu
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Lu Qin
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Lu Yu
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiaomin Pang
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wei Ye
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jinou Zheng
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
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Imaging correlates of behavioral impairments: An experimental PET study in the rat pilocarpine epilepsy model. Neurobiol Dis 2018; 118:9-21. [DOI: 10.1016/j.nbd.2018.06.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 06/05/2018] [Accepted: 06/12/2018] [Indexed: 01/04/2023] Open
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