1
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Casella C, Vecchiato K, Cromb D, Guo Y, Winkler AM, Hughes E, Dillon L, Green E, Colford K, Egloff A, Siddiqui A, Price A, Grande LC, Wood TC, Malik S, Teixeira RPAG, Carmichael DW, O'Muircheartaigh J. Widespread, depth-dependent cortical microstructure alterations in pediatric focal epilepsy. Epilepsia 2024; 65:739-752. [PMID: 38088235 DOI: 10.1111/epi.17861] [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: 08/18/2023] [Revised: 12/11/2023] [Accepted: 12/11/2023] [Indexed: 12/27/2023]
Abstract
OBJECTIVE Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes or treatment-related side effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilized quantitative magnetic resonance imaging (MRI), which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. METHODS To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy (age range = 4-18 years) and 46 typically developing children (age range = 2-18 years). We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically defined abnormalities (MRI positive) and healthy controls, and tested whether this could classify patients without reported radiological abnormalities (MRI negative). RESULTS We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 71.4% at 89.4% specificity on held-out MRI-negative patients. SIGNIFICANCE These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically identified abnormalities.
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Affiliation(s)
- Chiara Casella
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Yourong Guo
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Anderson M Winkler
- Department of Human Genetics, University of Texas Rio Grande Valley, Brownsville, Texas, USA
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Louise Dillon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Elaine Green
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Kathleen Colford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Ata Siddiqui
- Department of Radiology, Guy's and Saint Thomas' Hospitals NHS Trust, London, UK
| | - Anthony Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Lucilio Cordero Grande
- Department of Biomedical Engineering, King's College London, London, UK
- Biomedical Image Technologies, Telecommunication Engineering School (ETSIT), Technical University of Madrid, Bioengineering, Biomaterials and Nanomedicine Networking Biomedical Research Centre, National Institute of Health Carlos III, Madrid, Spain
| | - Tobias C Wood
- Department of Neuroimaging, King's College London, London, UK
| | - Shaihan Malik
- Department of Biomedical Engineering, King's College London, London, UK
| | | | | | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Medical Research Council (MRC) Centre for Neurodevelopmental Disorders, London, UK
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2
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Rebsamen M, Jin BZ, Klail T, De Beukelaer S, Barth R, Rezny-Kasprzak B, Ahmadli U, Vulliemoz S, Seeck M, Schindler K, Wiest R, Radojewski P, Rummel C. Clinical Evaluation of a Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis. Clin Neuroradiol 2023; 33:1045-1053. [PMID: 37358608 PMCID: PMC10654177 DOI: 10.1007/s00062-023-01308-9] [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: 03/01/2023] [Accepted: 05/09/2023] [Indexed: 06/27/2023]
Abstract
OBJECTIVE To evaluate the influence of quantitative reports (QReports) on the radiological assessment of hippocampal sclerosis (HS) from MRI of patients with epilepsy in a setting mimicking clinical reality. METHODS The study included 40 patients with epilepsy, among them 20 with structural abnormalities in the mesial temporal lobe (13 with HS). Six raters blinded to the diagnosis assessed the 3T MRI in two rounds, first using MRI only and later with both MRI and the QReport. Results were evaluated using inter-rater agreement (Fleiss' kappa [Formula: see text]) and comparison with a consensus of two radiological experts derived from clinical and imaging data, including 7T MRI. RESULTS For the primary outcome, diagnosis of HS, the mean accuracy of the raters improved from 77.5% with MRI only to 86.3% with the additional QReport (effect size [Formula: see text]). Inter-rater agreement increased from [Formula: see text] to [Formula: see text]. Five of the six raters reached higher accuracies, and all reported higher confidence when using the QReports. CONCLUSION In this pre-use clinical evaluation study, we demonstrated clinical feasibility and usefulness as well as the potential impact of a previously suggested imaging biomarker for radiological assessment of HS.
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Affiliation(s)
- Michael Rebsamen
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Baudouin Zongxin Jin
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, Bern, Switzerland
- Sleep-Wake-Epilepsy-Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Tomas Klail
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Sophie De Beukelaer
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Rike Barth
- Sleep-Wake-Epilepsy-Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Beata Rezny-Kasprzak
- University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Uzeyir Ahmadli
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, Bern, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Kaspar Schindler
- Sleep-Wake-Epilepsy-Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, Bern, Switzerland
- Swiss Institute for Translational and Entrepreneurial Medicine, sitem-insel, Bern, Switzerland
| | - Piotr Radojewski
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, Bern, Switzerland.
- Swiss Institute for Translational and Entrepreneurial Medicine, sitem-insel, Bern, Switzerland.
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse 10, 3010, Bern, Switzerland
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3
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Xiao F, Caciagli L, Wandschneider B, Sone D, Young AL, Vos SB, Winston GP, Zhang Y, Liu W, An D, Kanber B, Zhou D, Sander JW, Thom M, Duncan JS, Alexander DC, Galovic M, Koepp MJ. Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference. Brain 2023; 146:4702-4716. [PMID: 37807084 PMCID: PMC10629797 DOI: 10.1093/brain/awad284] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/30/2023] [Accepted: 08/02/2023] [Indexed: 10/10/2023] Open
Abstract
Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.
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Affiliation(s)
- Fenglai Xiao
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Britta Wandschneider
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
| | - Daichi Sone
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Psychiatry, The Jikei University School of Medicine, Tokyo, 105-8461, Japan
| | - Alexandra L Young
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Sjoerd B Vos
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Centre for Microscopy, Characterisation, and Analysis, University of Western Australia, Perth, WA 6009, Australia
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, K7L 3N6, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, K7L 3N6, Canada
| | - Yingying Zhang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Wenyu Liu
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Dongmei An
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Baris Kanber
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Dong Zhou
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Josemir W Sander
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
- Stichting Epilepsie Instellingen Nederland – (SEIN), Heemstede, 2103SW, The Netherlands
| | - Maria Thom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Marian Galovic
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, CH-8091, Switzerland
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
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Sarkar P, Sherwani P, Dev R, Tiwari A. Role of T2 relaxometry in localization of mesial temporal sclerosis and the degree of hippocampal atrophy in patients with intractable temporal lobe epilepsy: A cross sectional study. Hippocampus 2023; 33:1189-1196. [PMID: 37587770 DOI: 10.1002/hipo.23572] [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: 04/04/2023] [Revised: 07/18/2023] [Accepted: 07/30/2023] [Indexed: 08/18/2023]
Abstract
Mesial temporal lobe epilepsy is one of the most common causes of refractory epilepsy worldwide. A good percentage of patients do not have detectable hippocampal atrophy on magnetic resonance imaging (MRI). The objective of this study is to evaluate whether T2 relaxometry can identify hippocampal pathology and lateralize the epileptic focus in patients with intractable temporal lobe epilepsy (TLE). T2 relaxometry can also be used to correlate the clinical severity of the disease with the relaxometry readings in those who have hippocampal atrophy as well as those who do not. Thirty two patients having clinical and electrophysiological features of TLE were enrolled and a MRI brain with T2 relaxometry was done. Hippocampal T2 relaxometry values were calculated in the head, body, and tail of the hippocampus and average T2 relaxometry values were calculated, and a comparison was done with the controls. For patients with unilateral involvement, the contralateral side was taken as control and in cases of bilateral involvement, controls were identified from normal subjects. T2 relaxometry is found to be superior to MR visual analysis in the early detection of cases of hippocampal sclerosis where there is no atrophy on visual analysis. Nine out of 32 patients (28%) were normal on MR visual analysis; however, showed increased values on T2 relaxometry, correlating with clinical and electrophysiological diagnosis. The rest of the patients with hippocampal atrophy showed a correlation of T2 relaxometry values with the degree of atrophy. The hippocampal T2 measurement is thus more sensitive and specific. The study was clinically significant (p < .0001). There was a mild female predilection of the disease and there was no significant correlation with comorbidities. There was a strong positive correlation with patients having a history of febrile seizures in childhood. T2 relaxometry may accurately lateralize the majority of patients with persistent TLE and offers evidence of hippocampus injury in those patients who do not show evidence of atrophy on MRI and also the T2 relaxometry values correlated with the degree of atrophy. Early identification of hippocampal sclerosis is crucial for prompt management which offers better outcomes.
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Affiliation(s)
- Prasenjit Sarkar
- Department of Radiodiagnosis and Department of Neurology, All India Institute of Medical Sciences, Rishikesh, India
| | - Poonam Sherwani
- Department of Radiodiagnosis and Department of Neurology, All India Institute of Medical Sciences, Rishikesh, India
| | - Rahul Dev
- Department of Radiodiagnosis and Department of Neurology, All India Institute of Medical Sciences, Rishikesh, India
| | - Ashutosh Tiwari
- Department of Radiodiagnosis and Department of Neurology, All India Institute of Medical Sciences, Rishikesh, India
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Ben-Atya H, Freiman M. P 2T 2: A physically-primed deep-neural-network approach for robust T 2 distribution estimation from quantitative T 2-weighted MRI. Comput Med Imaging Graph 2023; 107:102240. [PMID: 37224742 DOI: 10.1016/j.compmedimag.2023.102240] [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: 01/13/2023] [Revised: 04/27/2023] [Accepted: 04/27/2023] [Indexed: 05/26/2023]
Abstract
Estimating T2 relaxation time distributions from multi-echo T2-weighted MRI (T2W) data can provide valuable biomarkers for assessing inflammation, demyelination, edema, and cartilage composition in various pathologies, including neurodegenerative disorders, osteoarthritis, and tumors. Deep neural network (DNN) based methods have been proposed to address the complex inverse problem of estimating T2 distributions from MRI data, but they are not yet robust enough for clinical data with low Signal-to-Noise ratio (SNR) and are highly sensitive to distribution shifts such as variations in echo-times (TE) used during acquisition. Consequently, their application is hindered in clinical practice and large-scale multi-institutional trials with heterogeneous acquisition protocols. We propose a physically-primed DNN approach, called P2T2, that incorporates the signal decay forward model in addition to the MRI signal into the DNN architecture to improve the accuracy and robustness of T2 distribution estimation. We evaluated our P2T2 model in comparison to both DNN-based methods and classical methods for T2 distribution estimation using 1D and 2D numerical simulations along with clinical data. Our model improved the baseline model's accuracy for low SNR levels (SNR<80) which are common in the clinical setting. Further, our model achieved a ∼35% improvement in robustness against distribution shifts in the acquisition process compared to previously proposed DNN models. Finally, Our P2T2 model produces the most detailed Myelin-Water fraction maps compared to baseline approaches when applied to real human MRI data. Our P2T2 model offers a reliable and precise means of estimating T2 distributions from MRI data and shows promise for use in large-scale multi-institutional trials with heterogeneous acquisition protocols. Our source code is available at: https://github.com/Hben-atya/P2T2-Robust-T2-estimation.git.
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Affiliation(s)
- Hadas Ben-Atya
- Faculty of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa, Israel.
| | - Moti Freiman
- Faculty of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa, Israel
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6
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Wang K, Wen Q, Wu D, Hsu YC, Heo HY, Wang W, Sun Y, Ma Y, Wu D, Zhang Y. Lateralization of temporal lobe epileptic foci with automated chemical exchange saturation transfer measurements at 3 Tesla. EBioMedicine 2023; 89:104460. [PMID: 36773347 PMCID: PMC9945641 DOI: 10.1016/j.ebiom.2023.104460] [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: 10/19/2022] [Revised: 12/17/2022] [Accepted: 01/18/2023] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND Magnetic Resonance Imaging (MRI) is an indispensable tool for the diagnosis of temporal lobe epilepsy (TLE). However, about 30% of TLE patients show no lesion on structural MRI (sMRI-negative), posing a significant challenge for presurgical evaluation. This study aimed to investigate whether chemical exchange saturation transfer (CEST) MRI at 3 Tesla can lateralize the epileptic focus of TLE and study the metabolic contributors to the CEST signal measured. METHODS Forty TLE subjects (16 males and 24 females) were included in this study. An automated data analysis pipeline was established, including segmentation of the hippocampus and amygdala (HA), calculation of four CEST metrics and quantitative relaxation times (T1 and T2), and construction of prediction models by logistic regression. Furthermore, a modified two-stage Bloch-McConnell fitting method was developed to investigate the molecular imaging mechanism of 3 T CEST in identifying epileptic foci of TLE. FINDINGS The mean CEST ratio (CESTR) metric within 2.25-3.25 ppm in the HA was the most powerful index in predicting seizure laterality, with an area under the receiver-operating characteristic curve (AUC) of 0.84. And, the combination of T2 and CESTR further increased the AUC to 0.92. Amine and guanidinium moieties were the two leading contributors to the CEST contrast between the epileptogenic HA and the normal HA. INTERPRETATION CEST at 3 Tesla is a powerful modality that can predict seizure laterality with high accuracy. This study can potentially facilitate the clinical translation of CEST MRI in identifying the epileptic foci of TLE or other localization-related epilepsies. FUNDING National Natural Science Foundation of China, Science Technology Department of Zhejiang Province, and Zhejiang University.
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Affiliation(s)
- Kang Wang
- Epilepsy Center, Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310003, China
| | - Qingqing Wen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Dengchang Wu
- Epilepsy Center, Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310003, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, 201318, China
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wenqi Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, 201318, China
| | - Yuehui Ma
- Epilepsy Center, Department of Neurosurgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310003, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, 310027, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, 310027, China.
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Adel SAA, Treit S, Abd Wahab W, Little G, Schmitt L, Wilman AH, Beaulieu C, Gross DW. Longitudinal hippocampal diffusion-weighted imaging and T2 relaxometry demonstrate regional abnormalities which are stable and predict subfield pathology in temporal lobe epilepsy. Epilepsia Open 2023; 8:100-112. [PMID: 36461649 PMCID: PMC9977756 DOI: 10.1002/epi4.12679] [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: 05/20/2022] [Accepted: 11/15/2022] [Indexed: 12/04/2022] Open
Abstract
OBJECTIVE High-resolution (1 mm isotropic) diffusion tensor imaging (DTI) of the hippocampus in temporal lobe epilepsy (TLE) patients has shown patterns of hippocampal subfield diffusion abnormalities, which were consistent with hippocampal sclerosis (HS) subtype on surgical histology. The objectives of this longitudinal imaging study were to determine the stability of focal hippocampus diffusion changes over time in TLE patients, compare diffusion and quantitative T2 abnormalities of the sclerotic hippocampus, and correlate presurgical mean diffusivity (MD) and T2 maps with postsurgical histology. METHODS Nineteen TLE patients and 19 controls underwent two high-resolution (1 mm isotropic) DTI and 1.1 × 1.1 × 1 mm3 T2 relaxometry scans (in a subset of 16 TLE patients and 9 controls) of the hippocampus at 3T, with a 2.6 ± 0.8 year inter-scan interval. Within-participant hippocampal volume, MD and T2 were compared between the scans. Contralateral hippocampal changes 2.3 ± 1.0 years after surgery and ipsilateral preoperative MD maps versus postoperative subfield histopathology were evaluated in eight patients who underwent surgical resection of the hippocampus. RESULTS Reduced volume and elevated MD and T2 of sclerotic hippocampi remained unchanged between longitudinal scans. Focal regions of elevated MD and T2 in bilateral hippocampi of HS TLE were detected consistently at both scans. Regions of high MD and T2 correlated and remained consistent over time. Volume, MD, and T2 remained unchanged in postoperative contralateral hippocampus. Regional elevations of MD identified subfield neuron loss on postsurgical histology with 88% sensitivity and 88% specificity. Focal T2 elevations identified subfield neuron loss with 75% sensitivity and 88% specificity. SIGNIFICANCE Diffusion and T2 abnormalities in ipsilateral and contralateral hippocampi remained unchanged between the scans suggesting permanent microstructural alterations. MD and T2 demonstrated good sensitivity and specificity to detect hippocampal subfield neuron loss on postsurgical histology, supporting the potential that high-resolution hippocampal DTI and T2 could be used to diagnose HS subtype before surgery.
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Affiliation(s)
- Seyed Amir Ali Adel
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Sarah Treit
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Wasan Abd Wahab
- Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
| | - Graham Little
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.,Department of Computer Science, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Laura Schmitt
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Donald W Gross
- Division of Neurology, University of Alberta, Edmonton, Alberta, Canada
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Mohanty D, Quach M. The Noninvasive Evaluation for Minimally Invasive Pediatric Epilepsy Surgery (MIPES): A Multimodal Exploration of the Localization-Based Hypothesis. JOURNAL OF PEDIATRIC EPILEPSY 2022. [DOI: 10.1055/s-0042-1760104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
AbstractMinimally invasive pediatric epilepsy surgery (MIPES) is a rising technique in the management of focal-onset drug-refractory epilepsy. Minimally invasive surgical techniques are based on small, focal interventions (such as parenchymal ablation or localized neuromodulation) leading to elimination of the seizure onset zone or interruption of the larger epileptic network. Precise localization of the seizure onset zone, demarcation of eloquent cortex, and mapping of the network leading to seizure propagation are required to achieve optimal outcomes. The toolbox for presurgical, noninvasive evaluation of focal epilepsy continues to expand rapidly, with a variety of options based on advanced imaging and electrophysiology. In this article, we will examine several of these diagnostic modalities from the standpoint of MIPES and discuss how each can contribute to the development of a localization-based hypothesis for potential surgical targets.
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Affiliation(s)
- Deepankar Mohanty
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Michael Quach
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
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9
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Iqbal S, Leon-Rojas JE, Galovic M, Vos SB, Hammers A, de Tisi J, Koepp MJ, Duncan JS. Volumetric analysis of the piriform cortex in temporal lobe epilepsy. Epilepsy Res 2022; 185:106971. [PMID: 35810570 PMCID: PMC10510027 DOI: 10.1016/j.eplepsyres.2022.106971] [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: 08/31/2021] [Revised: 05/13/2022] [Accepted: 06/22/2022] [Indexed: 11/03/2022]
Abstract
The piriform cortex, at the confluence of the temporal and frontal lobes, generates seizures in response to chemical convulsants and electrical stimulation. Resection of more than 50% of the piriform cortex in anterior temporal lobe resection for refractory temporal lobe epilepsy (TLE) was associated with a 16-fold higher chance of seizure freedom. The objectives of the current study were to implement a robust protocol to measure piriform cortex volumes and to quantify the correlation of these volumes with clinical characteristics of TLE. Sixty individuals with unilateral TLE (33 left) and 20 healthy controls had volumetric analysis of left and right piriform cortex and hippocampi. A protocol for segmenting and measuring the volumes of the piriform cortices was implemented, with good inter-rater and test-retest reliability. The right piriform cortex volume was consistently larger than the left piriform cortex in both healthy controls and patients with TLE. In controls, the mean volume of the right piriform cortex was 17.7% larger than the left, and the right piriform cortex extended a mean of 6 mm (Range: -4 to 12) more anteriorly than the left. This asymmetry was also seen in left and right TLE. In TLE patients overall, the piriform cortices were not significantly smaller than in controls. Hippocampal sclerosis was associated with decreased ipsilateral and contralateral piriform cortex volumes. The piriform cortex volumes, both ipsilateral and contralateral to the epileptic temporal lobe, were smaller with a longer duration of epilepsy. There was no significant association between piriform cortex volumes and the frequency of focal seizures with impaired awareness or the number of anti-seizure medications taken. Implementation of robust segmentation will enable consistent neurosurgical resection in anterior temporal lobe surgery for refractory TLE..
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Affiliation(s)
- Sabahat Iqbal
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom
| | - Jose E Leon-Rojas
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom; Facultad de Ciencias Médicas de la Salud y de la Vida, Escuela de Medicina, Universidad Internacional del Ecuador, Quito, Ecuador
| | - Marian Galovic
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom; Department of Neurology, Zurich University Hospital, Zurich, Switzerland
| | - Sjoerd B Vos
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, United Kingdom; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, Kings College, London, United Kingdom; Kings College London & Guys and St Thomas' PET Centre at St. Thomas' Hospital, United Kingdom
| | - Jane de Tisi
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Matthias J Koepp
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom
| | - John S Duncan
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom.
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10
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Del Signore F, Vignoli M, Della Salda L, Tamburro R, Paolini A, Cerasoli I, Chincarini M, Rossi E, Ferri N, Romanucci M, Falerno I, de Pasquale F. A Magnetic Resonance-Relaxometry-Based Technique to Identify Blood Products in Brain Parenchyma: An Experimental Study on a Rabbit Model. Front Vet Sci 2022; 9:802272. [PMID: 35711807 PMCID: PMC9195168 DOI: 10.3389/fvets.2022.802272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/11/2022] [Indexed: 11/13/2022] Open
Abstract
Magnetic resonance relaxometry is a quantitative technique that estimates T1/T2 tissue relaxation times. This has been proven to increase MRI diagnostic accuracy of brain disorders in human medicine. However, literature in the veterinary field is scarce. In this work, a T1 and T2-based relaxometry approach has been developed. The aim is to investigate its performance in characterizing subtle brain lesions obtained with autologous blood injections in rabbits. This study was performed with a low-field scanner, typically present in veterinary clinics. The approach consisted of a semi-automatic hierarchical classification of different regions, selected from a T2 map. The classification was driven according to the relaxometry properties extracted from a set of regions selected by the radiologist to compare the suspected lesion with the healthy parenchyma. Histopathological analyses were performed to estimate the performance of the proposed classifier through receiver operating characteristic curve analyses. The classifier resulted in moderate accuracy in terms of lesion characterization.
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Affiliation(s)
- Francesca Del Signore
- Veterinary Faculty, University of Teramo, Teramo, Italy
- *Correspondence: Francesca Del Signore
| | | | | | | | | | | | | | - Emanuela Rossi
- Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise Giuseppe Caporale, Teramo, Italy
| | - Nicola Ferri
- Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise Giuseppe Caporale, Teramo, Italy
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11
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Konopka-Filippow M, Sierko E, Hempel D, Maksim R, Samołyk-Kogaczewska N, Filipowski T, Rożkowska E, Jelski S, Kasprowicz B, Karbowska E, Szymański K, Szczecina K. The Learning Curve and Inter-Observer Variability in Contouring the Hippocampus under the Hippocampal Sparing Guidelines of Radiation Therapy Oncology Group 0933. Curr Oncol 2022; 29:2564-2574. [PMID: 35448184 PMCID: PMC9027685 DOI: 10.3390/curroncol29040210] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 04/04/2022] [Indexed: 11/23/2022] Open
Abstract
Hippocampal-sparing brain radiotherapy (HS-BRT) in cancer patients results in preservation of neurocognitive function after brain RT which can contribute to patients’ quality of life (QoL). The crucial element in HS-BRT treatment planning is appropriate contouring of the hippocampus. Ten doctors delineated the left and right hippocampus (LH and RH, respectively) on 10 patients’ virtual axial images of brain CT fused with T1-enhanced MRI (1 mm) according to the RTOG 0933 atlas recommendations. Variations in the spatial localization of the structure were described in three directions: right–left (X), cranio-caudal (Y), and forward–backward (Z). Discrepancies concerned three-dimensional localization, shape, volume and size of the hippocampus. The largest differences were observed in the first three delineated cases which were characterized by larger hippocampal volumes than the remaining seven cases. The volumes of LH of more than half of hippocampus contours were marginally bigger than those of RH. Most differences in delineation of the hippocampus were observed in the area of the posterior horn of the lateral ventricle. Conversely, a large number of hippocampal contours overlapped near the brainstem and the anterior horn of the lateral ventricle. The most problematic area of hippocampal contouring is the posterior horn of the lateral ventricle. Training in the manual contouring of the hippocampus during HS-BRT treatment planning under the supervision of experienced radiation oncologists is necessary to achieve optimal outcomes. This would result in superior outcomes of HS-BRT treatment and improvement in QoL of patients compared to without HS-BRT procedure. Correct delineation of the hippocampus is problematic. This study demonstrates difficulties in HS-BRT treatment planning and highlights critical points during hippocampus delineation.
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Affiliation(s)
- Monika Konopka-Filippow
- Department of Oncology, Medical University of Bialystok, 15-089 Białystok, Poland; (M.K.-F.); (D.H.)
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
| | - Ewa Sierko
- Department of Oncology, Medical University of Bialystok, 15-089 Białystok, Poland; (M.K.-F.); (D.H.)
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
- Correspondence: ; Tel.: +48-85-6646734; Fax: +48-6646783
| | - Dominika Hempel
- Department of Oncology, Medical University of Bialystok, 15-089 Białystok, Poland; (M.K.-F.); (D.H.)
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
| | - Rafał Maksim
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
| | - Natalia Samołyk-Kogaczewska
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
| | - Tomasz Filipowski
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
| | - Ewa Rożkowska
- Department of Radiotherapy I, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (R.M.); (N.S.-K.); (T.F.); (E.R.)
| | - Stefan Jelski
- Department of Radiology, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (S.J.); (B.K.); (E.K.)
| | - Beata Kasprowicz
- Department of Radiology, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (S.J.); (B.K.); (E.K.)
| | - Eryka Karbowska
- Department of Radiology, Maria Sklodowska-Curie Bialystok Oncology Centre, 15-027 Białystok, Poland; (S.J.); (B.K.); (E.K.)
| | - Krzysztof Szymański
- Department of Physics, University of Bialystok, 15-245 Białystok, Poland; (K.S.); (K.S.)
| | - Kamil Szczecina
- Department of Physics, University of Bialystok, 15-245 Białystok, Poland; (K.S.); (K.S.)
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12
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Zaidan BC, Cardoso ICDS, de Campos BM, da Silva LRP, Coelho VCM, Silveira KAA, Amorim BJ, Alvim MKM, Tedeschi H, Yasuda CL, Ghizoni E, Cendes F, Rogerio F. Histopathological Correlations of Qualitative and Quantitative Temporopolar MRI Analyses in Patients With Hippocampal Sclerosis. Front Neurol 2022; 12:801195. [PMID: 35002940 PMCID: PMC8739995 DOI: 10.3389/fneur.2021.801195] [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: 10/25/2021] [Accepted: 11/29/2021] [Indexed: 11/28/2022] Open
Abstract
Hippocampal sclerosis (HS) is a common cause of pharmacoresistant focal epilepsy. Here, we (1) performed a histological approach to the anterior temporal pole of patients with HS to evaluate cortical and white matter (WM) cell populations, alteration of myelin integrity and markers of neuronal activity, and (2) correlated microscopic data with magnetic resonance imaging (MRI) findings. Our aim was to contribute with the understanding of neuroimaging and pathophysiological mechanisms of temporal lobe epilepsy (TLE) associated with HS. We examined MRIs and surgical specimens from the anterior temporal pole from TLE-HS patients (n = 9) and compared them with 10 autopsy controls. MRIs from healthy volunteers (n = 13) were used as neuroimaging controls. Histological techniques were performed to assess oligodendrocytes, heterotopic neurons, cellular proliferative index, and myeloarchitecture integrity of the WM, as well as markers of acute (c-fos) and chronic (ΔFosB) activities of neocortical neurons. Microscopic data were compared with neuroimaging findings, including T2-weighted/FLAIR MRI temporopolar blurring and values of fractional anisotropy (FA) from diffusion-weighed imaging (DWI). We found a significant increase in WM oligodendrocyte number, both in hematoxylin and eosin, and in Olig2-stained sections. The frequencies of oligodendrocytes in perivascular spaces and around heterotopic neurons were significantly higher in patients with TLE–HS compared with controls. The percentage of 2',3'-cyclic-nucleotide 3'-phosphodiesterase (CNPase; a marker of myeloarchitecture integrity) immunopositive area in the WM was significantly higher in TLE-HS, as well as the numbers of c-fos- and ΔFosB-immunostained neocortical neurons. Additionally, we demonstrated a decrease in axonal bundle integrity on neuroimaging, with a significant reduction in the FA in the anterior temporal pole. No differences were detected between individuals with and without temporopolar blurring on visual MRI analysis, considering the number of oligodendroglial cells and percentage of WM CNPase-positive areas. Also, there was no relationship between T2 relaxometry and oligodendrocyte count. In conclusion, our histopathological data support the following: (1) the hypothesis that repetitive neocortical neuronal activity could induce changes in the WM cellular constitution and myelin remodeling in the anterior temporal pole from patients with TLE-HS, (2) that oligodendroglial hyperplasia is not related to temporal blurring or T2 signal intensity on MRI, and (3) that reduced FA is a marker of increase in Olig2-immunopositive cells in superficial temporopolar WM from patients with TLE-HS.
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Affiliation(s)
- Bruna Cunha Zaidan
- Department of Pathology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | | | - Brunno Machado de Campos
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | | | - Vanessa C Mendes Coelho
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | | | - Bárbara Juarez Amorim
- Department of Anesthesiology, Oncology and Radiology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | | | - Helder Tedeschi
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Clarissa Lin Yasuda
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Enrico Ghizoni
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Fernando Cendes
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Fabio Rogerio
- Department of Pathology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
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13
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Zhang M, Huang H, Liu W, Tang L, Li Q, Wang J, Huang X, Lin X, Meng H, Wang J, Zhan S, Li B, Luo J. Combined quantitative T2 mapping and [ 18F]FDG PET could improve lateralization of mesial temporal lobe epilepsy. Eur Radiol 2022; 32:6108-6117. [PMID: 35347363 PMCID: PMC9381472 DOI: 10.1007/s00330-022-08707-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 02/15/2022] [Accepted: 03/01/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVES To investigate whether quantitative T2 mapping is complementary to [18F]FDG PET in epileptogenic zone detection, thus improving the lateralization accuracy for drug-resistant mesial temporal lobe epilepsy (MTLE) using hybrid PET/MR. METHODS We acquired routine structural MRI, T2-weighted FLAIR, whole brain T2 mapping, and [18F]FDG PET in 46 MTLE patients and healthy controls on a hybrid PET/MR scanner, followed with computing voxel-based z-score maps of patients in reference to healthy controls. Asymmetry indexes of the hippocampus were calculated for each imaging modality, which then enter logistic regression models as univariate or multivariate for lateralization. Stereoelectroencephalography (SEEG) recordings and clinical decisions were collected as gold standard. RESULTS Routine structural MRI and T2w-FLAIR lateralized 47.8% (22/46) of MTLE patients, and FDG PET lateralized 84.8% (39/46). T2 mapping combined with [18F]FDG PET improved the lateralization accuracy by correctly lateralizing 95.6% (44/46) of MTLE patients. The asymmetry indexes of hippocampal T2 relaxometry and PET exhibit complementary tendency in detecting individual laterality, especially for MR-negative patients. In the quantitative analysis of z-score maps, the ipsilateral hippocampus had significantly lower SUVR (LTLE, p < 0.001; RTLE, p < 0.001) and higher T2 value (LTLE, p < 0.001; RTLE, p = 0.001) compared to the contralateral hippocampus. In logistic regression models, PET/T2 combination resulted in the highest AUC of 0.943 in predicting lateralization for MR-negative patients, followed by PET (AUC = 0.857) and T2 (AUC = 0.843). CONCLUSIONS The combination of quantitative T2 mapping and [18F]FDG PET could improve lateralization for temporal lobe epilepsy. KEY POINTS • Quantitative T2 mapping and18F-FDG PET are complementary in the characterization of hippocampal alterations of MR-negative temporal lobe epilepsy patients. • The combination of quantitative T2 and18F-FDG PET obtained from hybrid PET/MR could improve lateralization for temporal lobe epilepsy.
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Affiliation(s)
- Miao Zhang
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Hui Huang
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Wei Liu
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Lihong Tang
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Qikang Li
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Jia Wang
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Xinyun Huang
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Xiaozhu Lin
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Hongping Meng
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Jin Wang
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Shikun Zhan
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Biao Li
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China ,Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Ruijin Center, Shanghai, 200025 China
| | - Jie Luo
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
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14
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Gleichgerrcht E, Munsell B, Keller SS, Drane DL, Jensen JH, Spampinato MV, Pedersen NP, Weber B, Kuzniecky R, McDonald C, Bonilha L. Radiological identification of temporal lobe epilepsy using artificial intelligence: a feasibility study. Brain Commun 2021; 4:fcab284. [PMID: 35243343 PMCID: PMC8887904 DOI: 10.1093/braincomms/fcab284] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 09/29/2021] [Accepted: 10/04/2021] [Indexed: 12/15/2022] Open
Abstract
Temporal lobe epilepsy is associated with MRI findings reflecting underlying mesial temporal sclerosis. Identifying these MRI features is critical for the diagnosis and management of temporal lobe epilepsy. To date, this process relies on visual assessment by highly trained human experts (e.g. neuroradiologists, epileptologists). Artificial intelligence is increasingly recognized as a promising aid in the radiological evaluation of neurological diseases, yet its applications in temporal lobe epilepsy have been limited. Here, we applied a convolutional neural network to assess the classification accuracy of temporal lobe epilepsy based on structural MRI. We demonstrate that convoluted neural networks can achieve high accuracy in the identification of unilateral temporal lobe epilepsy cases even when the MRI had been originally interpreted as normal by experts. We show that accuracy can be potentiated by employing smoothed grey matter maps and a direct acyclic graphs approach. We further discuss the foundations for the development of computer-aided tools to assist with the diagnosis of epilepsy.
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Affiliation(s)
- Ezequiel Gleichgerrcht
- Department of Neurology, Medical University of South
Carolina, Charleston, SC 29425, USA
| | - Brent Munsell
- Department of Computer Science, University of North
Carolina, Chapel Hill, NC 27599, USA
- Department of Psychiatry, University of North
Carolina, Chapel Hill, NC 27599, USA
| | - Simon S Keller
- Institute of Systems, Molecular and Integrative
Biology, University of Liverpool, Liverpool L69 7BE, UK
- The Walton Centre NHS Foundation
Trust, Liverpool L9 7LJ, UK
| | - Daniel L Drane
- Department of Neurology, Emory
University, Atlanta, GA 30322, USA
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of
South Carolina, Charleston, SC 29425, USA
| | - M Vittoria Spampinato
- Department of Radiology, Medical University of South
Carolina, Charleston, SC 29425, USA
| | - Nigel P Pedersen
- Department of Neurology, Emory
University, Atlanta, GA 30322, USA
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition
Research, University of Bonn, Bonn 53113, Germany
| | - Ruben Kuzniecky
- Department of Neurology, Hofstra
University/Northwell, New York, NY 10075, USA
| | - Carrie McDonald
- Department of Psychiatry, University of California
San Diego, La Jolla, CA 92093, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South
Carolina, Charleston, SC 29425, USA
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15
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Andrews AE, Perumpalath N, Puthiyakam J, Mekkattukunnel A. Hippocampal magnetic resonance imaging in focal onset seizure with impaired awareness—descriptive study from tertiary care centre in southern part of India. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2021. [DOI: 10.1186/s41983-021-00347-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Temporal lobe epilepsy is the most common type of focal onset seizure. Focal onset seizure with impaired awareness, previously known as complex partial seizure (CPS), account for 18–40% of all seizure types. Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy, which produces focal onset seizure with impaired awareness. It may be detected in MRI visually, but bilateral abnormalities are better identified using volumetric analysis.
We aimed to compare hippocampal volume in patients with focal onset seizure with impaired awareness visually and quantitatively.
Methodology
This cross-sectional study includes clinically diagnosed cases of 56 focal onset seizure with impaired awareness undergoing MRI at a tertiary teaching hospital in the southern part of India for a duration of 18 months from February 2018 to August 2019.
Results
Out of 53 patients studied using 1.5 T MRI brain with seizure protocols, hippocampal atrophy was identified visually in 13 (24.5%) on the right side, 9 (16.98%) on the left side, and in 6 (11.32%) bilaterally. However, with volumetry, hippocampal atrophy (not taking T2 signal change) was detected in 15 (28.30%) on the right side, 10 (18.86%) on the left side, and in 7 (13.20%) bilaterally. Hippocampal volumes between ipsilateral and contralateral seizure focus were found to have no significant difference (p-0.84).
Conclusions
Though visual analysis is efficient in the diagnosis of pathology, MR volumetry may be used as an expert eye in cases of subtle volume loss.
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16
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Long-term changes in neuroimaging markers, cognitive function and psychiatric symptoms in an experimental model of Gulf War Illness. Life Sci 2021; 285:119971. [PMID: 34560085 DOI: 10.1016/j.lfs.2021.119971] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 09/05/2021] [Accepted: 09/16/2021] [Indexed: 11/23/2022]
Abstract
AIMS Gulf War Illness (GWI) is a multi-symptom disease with debilitating cognitive and emotional impairments in veterans. GWI, like epilepsy, is caused by chemical neurotoxicity and manifests from disturbances in neuronal excitability. However, the mechanisms underlying such devastating neurological and psychiatric symptoms remain unclear. Here we investigated the long-term changes in neural behavior and brain structural abnormalities in a rat model of GWI. GWI is linked to exposure to GWI-related organophosphate chemicals (pyridostigmine bromide or PB and insecticide DEET, permethrin) during the stressful Gulf war. METHODS To mimic GWI, we generated an experimental GWI prototype in rats by daily exposure to GWI-related chemicals with restraint stress (GWIR-CS) for 4 weeks. Changes in MRI scan and cognitive function were assessed at 5- and 10- months post-exposure. KEY FINDINGS In MRI scans, rats displayed significant increases in lateral ventricle T2 relaxation times at both 5- and 10-months after GWIR-CS, indicating alterations in the cerebrospinal fluid (CSF) density. Furthermore, at 10 months, there were significant decreases in the volumes of the hippocampus and thalamus and an increase in the lateral ventricle volume. At both time points, they exhibited impairments in multiple neurobehavioral tests, confirming substantial deficits in memory and mood function. GWI-CS rats also displayed aggressive behavior and a marked decrease in social interaction and forced swimming, indicating depression. CONCLUSIONS These results confirm that chronic GWIR-CS exposure led to cognitive and psychiatric symptoms with concurrent neuroimaging abnormalities in CSF, with morphological neural lesions, demonstrating the role of divergent etiological mechanisms in GWI and its comorbidities.
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Caldairou B, Foit NA, Mutti C, Fadaie F, Gill R, Lee HM, Demerath T, Urbach H, Schulze-Bonhage A, Bernasconi A, Bernasconi N. MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy. Neurology 2021; 97:e1583-e1593. [PMID: 34475125 DOI: 10.1212/wnl.0000000000012699] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 07/30/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND AND OBJECTIVES MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of covert hippocampal pathology in TLE. METHODS We trained a surface-based linear discriminant classifier that uses T1-weighted (morphology) and T2-weighted and fluid-attenuated inversion recovery (FLAIR)/T1 (intensity) features. The classifier was trained on 60 patients with TLE (mean age 35.6 years, 58% female) with histologically verified hippocampal sclerosis (HS). Images were deemed to be MRI negative in 42% of cases on the basis of neuroradiologic reading (40% based on hippocampal volumetry). The predictive model automatically labeled patients as having left or right TLE. Lateralization accuracy was compared to electroclinical data, including side of surgery. Accuracy of the classifier was further assessed in 2 independent TLE cohorts with similar demographics and electroclinical characteristics (n = 57, 58% MRI negative). RESULTS The overall lateralization accuracy was 93% (95% confidence interval 92%-94%), regardless of HS visibility. In MRI-negative TLE, the combination of T2 and FLAIR/T1 intensities provided the highest accuracy in both the training (84%, area under the curve [AUC] 0.95 ± 0.02) and validation (cohort 1 90%, AUC 0.99; cohort 2 76%, AUC 0.94) cohorts. DISCUSSION This prediction model for TLE lateralization operates on readily available conventional MRI contrasts and offers gain in accuracy over visual radiologic assessment. The combined contribution of decreased T1- and increased T2-weighted intensities makes the synthetic FLAIR/T1 contrast particularly effective in MRI-negative HS, setting the basis for broad clinical translation. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in people with TLE and MRI-negative HS, an automated MRI-based classifier accurately determines the side of pathology.
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Affiliation(s)
- Benoit Caldairou
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Niels A Foit
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Carlotta Mutti
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Fatemeh Fadaie
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Ravnoor Gill
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Hyo Min Lee
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Theo Demerath
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Horst Urbach
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Andreas Schulze-Bonhage
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany
| | - Andrea Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany.
| | - Neda Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (B.C., N.A.F., C.M., F.F., R.G., H.M.L., A.B., N.B.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Quebec, Canada; and Departments of Neurosurgery (N.A.F.) and Neuroradiology (T.D., H.U.), Freiburg Medical Center, and Department of Neurology (A.S.-B.), University of Freiburg, Germany.
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Zhao L, Zhang X, Luo Y, Hu J, Liang C, Wang L, Gao J, Qi X, Zhai F, Shi L, Zhu M. Automated detection of hippocampal sclerosis: Comparison of a composite MRI-based index with conventional MRI measures. Epilepsy Res 2021; 174:106638. [PMID: 33964793 DOI: 10.1016/j.eplepsyres.2021.106638] [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: 12/21/2020] [Revised: 04/01/2021] [Accepted: 04/06/2021] [Indexed: 11/27/2022]
Abstract
PURPOSE This study aims to compare the performance of an MRI-based composite index (HSI) with conventional MRI-based measures in hippocampal sclerosis (HS) detection and postoperative outcome estimation. METHODS Seventy-two temporal lobe epilepsy (TLE) patients with pathologically confirmed HS and fifteen TLE patients without HS were included retrospectively. The T1-weighted and FLAIR images of these patients were processed with AccuBrain to quantify the hippocampal volume (HV) and the hippocampal FLAIR signal. The HSI index that considered both HV and hippocampal FLAIR signal was also calculated. Two experienced neuropathologists rated the HS severity with the resected tissue and reached an agreement for all cases. The asymmetry indices of the MRI measures were used to lateralize the sclerotic side, and the original MRI measures were applied to detect HS vs. normal hippocampi. Operating characteristic curve (ROC) analyses were performed for these predictions. We also investigated the sensitivity of the ipsilateral MRI measures in characterizing the pathological severity of HS and the associations of the MRI measures with postoperative outcomes (Engel class categories). RESULTS With the optimal cutoffs, the asymmetry indices of HSI and HV both achieved excellent performance in differentiating left vs. right HS (accuracy = 100 %), and the absolute value of the asymmetry index of HSI performed best in differentiating unilateral vs. bilateral HS (accuracy = 91.7 %). Regarding the detection of HS, HSI performed better in sensitivity (94.4 % vs. 87.5 %) while HV performed better in specificity (93.6 % vs. 89.4 %) when the contralateral site of unilateral HS and both sides of non-HS patients were considered as the normal reference, and HSI performed even better than HV when only both sides of non-HS patients were considered as the normal reference (AUC: 0.956 vs. 0.934, p = 0.038). The ipsilateral HSI presented the strongest association with the pathological rating of HS severity (r = 0.405, p < 0.001). None of the ipsilateral or contralateral MRI measures was associated with the postoperative outcomes. Among the asymmetry indices, only the absolute value of the asymmetry index of HV presented a significant association with the Engel classifications for the Year 2∼3 visit (r = -0.466, p = 0.004) or the latest visit with >1 year follow-up (r = -0.374, p = 0.003) while controlling for disease duration and follow-up duration. CONCLUSION The HSI index and HV presented comparable good performance in HS detection, and HSI may have better sensitivity than HV in differentiating pathological HS severity. Higher magnitude of HV dissymmetry may indicate better post-surgical outcomes for HS patients.
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Affiliation(s)
- Lei Zhao
- BrainNow Research Institute, Shenzhen, China
| | - Xufei Zhang
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Yishan Luo
- BrainNow Research Institute, Shenzhen, China
| | - Jianxin Hu
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Chenyang Liang
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Lining Wang
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Jie Gao
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China
| | - Xueling Qi
- Department of Pathology, Sanbo Brain Hospital, Capital Medical University, China
| | - Feng Zhai
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, China; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
| | - Mingwang Zhu
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, China.
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Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility. Brain Struct Funct 2020; 226:137-150. [PMID: 33231744 PMCID: PMC7817563 DOI: 10.1007/s00429-020-02172-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 11/09/2020] [Indexed: 12/18/2022]
Abstract
Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test-retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal ("long_T1s" and "long_T1s_FLAIR") and one cross-sectional ("long_T1s_FLAIR_crossT2"). Volume reproducibility was quantified in magnitude (reproducibility error-RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4-3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1-7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm3 had better RE (1-2%) and DICE (0.7-0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements.
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Riederer F, Seiger R, Lanzenberger R, Pataraia E, Kasprian G, Michels L, Beiersdorf J, Kollias S, Czech T, Hainfellner J, Baumgartner C. Voxel-Based Morphometry-from Hype to Hope. A Study on Hippocampal Atrophy in Mesial Temporal Lobe Epilepsy. AJNR Am J Neuroradiol 2020; 41:987-993. [PMID: 32522839 DOI: 10.3174/ajnr.a6545] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 03/18/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND AND PURPOSE Automated volumetry of the hippocampus is considered useful to assist the diagnosis of hippocampal sclerosis in temporal lobe epilepsy. However, voxel-based morphometry is rarely used for individual subjects because of high rates of false-positives. We investigated whether an approach with high dimensional warping to the template and nonparametric statistics would be useful to detect hippocampal atrophy in patients with hippocampal sclerosis. MATERIALS AND METHODS We performed single-subject voxel-based morphometry with nonparametric statistics within the framework of Statistical Parametric Mapping to compare MRI from 26 well-characterized patients with temporal lobe epilepsy individually against a group of 110 healthy controls. The following statistical threshold was used: P < .05 corrected for multiple comparisons with family-wise error over the region of interest right and left hippocampus. RESULTS The sensitivity for the detection of atrophy related to hippocampal sclerosis was 0.92 (95% CI, 0.67-0.99) for the right hippocampus and 0.60 (0.31-0.83) for the left, and the specificity for volume changes was 0.98 (0.93-0.99). All clusters of decreased hippocampal volumes were correctly lateralized to the seizure focus. Hippocampal volume decrease was in accordance with neuronal cell loss on histology reports. CONCLUSIONS Nonparametric voxel-based morphometry is sensitive and specific for hippocampal atrophy in patients with mesial temporal lobe epilepsy and may be useful in clinical practice.
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Affiliation(s)
- F Riederer
- From the Hietzing Hospital with Neurological Center Rosenhügel & Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology (F.R., J.B., C.B.), Vienna, Austria .,Faculty of Medicine (F.R.), University of Zurich, Zurich, Switzerland
| | - R Seiger
- Neuroimaging Labs, Department of Psychiatry and Psychotherapy (R.S., R.L.)
| | - R Lanzenberger
- Neuroimaging Labs, Department of Psychiatry and Psychotherapy (R.S., R.L.)
| | | | | | - L Michels
- Clinic of Neuroradiology (L.M., S.K.), University Hospital Zurich, Zurich, Switzerland
| | - J Beiersdorf
- From the Hietzing Hospital with Neurological Center Rosenhügel & Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology (F.R., J.B., C.B.), Vienna, Austria
| | - S Kollias
- Clinic of Neuroradiology (L.M., S.K.), University Hospital Zurich, Zurich, Switzerland
| | | | - J Hainfellner
- and Institute of Neurology (J.H.), Medical University of Vienna, Vienna, Austria
| | - C Baumgartner
- From the Hietzing Hospital with Neurological Center Rosenhügel & Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology (F.R., J.B., C.B.), Vienna, Austria.,Medical Faculty (C.B.), Sigmund Freud Private University, Vienna, Austria
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21
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Fatemi Y, Danyali H, Helfroush MS, Amiri H. Fast T 2 mapping using multi-echo spin-echo MRI: A linear order approach. Magn Reson Med 2020; 84:2815-2830. [PMID: 32430979 PMCID: PMC7402028 DOI: 10.1002/mrm.28309] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 04/13/2020] [Accepted: 04/15/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE Multi-echo spin-echo sequence is commonly used for T2 mapping. The estimated values using conventional exponential fit, however, are hampered by stimulated and indirect echoes leading to overestimation of T2 . Here, we present fast analysis of multi-echo spin-echo (FAMESE) as a novel approach to decrease the complexity of the search space, which leads to accelerated measurement of T2 . METHODS We developed FAMESE based on mathematical analysis of the Bloch equations in which the search space dimension decreased to only one. Then, we tested it in both phantom and human brain. Bland-Altman plot was used to assess the agreement between the estimated T2 values from FAMESE and the ones estimated from single-echo spin-echo sequence. The reliability of FAMESE was assessed by intraclass correlation coefficients. In addition, we investigated the noise stability of the method in synthetic and experimental data. RESULTS In both phantom and healthy participants, FAMESE provided accelerated and SNR-resistant T2 maps. The FAMESE had a very good agreement with the single-echo spin echo for the whole range of T2 values. The intraclass correlation coefficient values for FAMESE were excellent (ie, 0.9998 and 0.9860 < intraclass correlation coefficient < 0.9942 for the phantom and humans, respectively). CONCLUSION Our developed method FAMESE could be considered as a candidate for rapid T2 mapping with a clinically feasible scan time.
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Affiliation(s)
- Yaghoub Fatemi
- Department of Electrical and Electronics EngineeringShiraz University of TechnologyShirazIran
| | - Habibollah Danyali
- Department of Electrical and Electronics EngineeringShiraz University of TechnologyShirazIran
| | | | - Houshang Amiri
- Neuroscience Research CenterInstitute of NeuropharmacologyKerman University of Medical SciencesKermanIran
- Department of Radiology and Nuclear MedicineVU University Medical CenterAmsterdamthe Netherlands
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Reddy SD, Wu X, Kuruba R, Sridhar V, Reddy DS. Magnetic resonance imaging analysis of long-term neuropathology after exposure to the nerve agent soman: correlation with histopathology and neurological dysfunction. Ann N Y Acad Sci 2020; 1480:116-135. [PMID: 32671850 PMCID: PMC7708405 DOI: 10.1111/nyas.14431] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Revised: 05/09/2020] [Accepted: 06/17/2020] [Indexed: 12/14/2022]
Abstract
Nerve agents (NAs) produce acute and long-term brain injury and dysfunction, as evident from the Japan and Syria incidents. Magnetic resonance imaging (MRI) is a versatile technique to examine such chronic anatomical, functional, and neuronal damage in the brain. The objective of this study was to investigate long-term structural and neuronal lesion abnormalities in rats exposed to acute soman intoxication. T2-weighted MRI images of 10 control and 17 soman-exposed rats were acquired using a Siemens MRI system at 90 days after soman exposure. Quantification of brain tissue volumes and T2 signal intensity was conducted using the Inveon Research Workplace software and the extent of damage was correlated with histopathology and cognitive function. Soman-exposed rats showed drastic hippocampal atrophy with neuronal loss and reduced hippocampal volume (HV), indicating severe damage, but had similar T2 relaxation times to the control group, suggesting limited scarring and fluid density changes despite the volume decrease. Conversely, soman-exposed rats displayed significant increases in lateral ventricle volumes and T2 times, signifying strong cerebrospinal fluid expansion in compensation for tissue atrophy. The total brain volume, thalamic volume, and thalamic T2 time were similar in both groups, however, suggesting that some brain regions remained more intact long-term after soman intoxication. The MRI neuronal lesions were positively correlated with the histological markers of neurodegeneration and neuroinflammation 90 days after soman exposure. The predominant MRI hippocampal atrophy (25%) was highly consistent with massive reduction (35%) of neuronal nuclear antigen-positive (NeuN+ ) principal neurons and parvalbumin-positive (PV+ ) inhibitory interneurons within this brain region. The HV was significantly correlated with both inflammatory markers of GFAP+ astrogliosis and IBA1+ microgliosis. The reduced HV was also directly correlated with significant memory deficits in the soman-exposed cohort, confirming a possible neurobiological basis for neurological dysfunction. Together, these findings provide powerful insight on long-term region-specific neurodegenerative patterns after soman exposure and demonstrate the feasibility of in vivo neuroimaging to monitor neuropathology, predict the risk of neurological deficits, and evaluate response to medical countermeasures for NAs.
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Affiliation(s)
- Sandesh D Reddy
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, Texas
- Biomedical Engineering, College of Engineering, Texas A&M University, College Station, Texas
| | - Xin Wu
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, Texas
| | - Ramkumar Kuruba
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, Texas
| | - Vidya Sridhar
- Texas A&M Institute for Preclinical Studies, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas
| | - Doodipala Samba Reddy
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, Texas
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Diagnosis of Hippocampal Sclerosis in Children: Comparison of Automated Brain MRI Volumetry and Readers of Varying Experience. AJR Am J Roentgenol 2020; 217:223-234. [PMID: 32903057 DOI: 10.2214/ajr.20.23990] [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] [Indexed: 01/18/2023]
Abstract
BACKGROUND. Hippocampal sclerosis (HS) is a leading cause of medically refractory temporal lobe epilepsy in children. The diagnosis is clinically important because most patients with HS have good postsurgical outcomes. OBJECTIVE. This study aimed to compare the performance of a fully automated brain MRI volumetric tool and readers of varying experience in the diagnosis of pediatric HS. METHODS. This retrospective study included 22 children with HS diagnosed between January 2009 and January 2020 who underwent surgery and an age- and sex-matched control group of 44 patients with normal MRI findings and extratemporal epilepsy diagnosed between January 2009 and January 2020. Regional brain MRI volumes were calculated from a high-resolution 3D T1-weighted sequence using an automated volumetric tool. Four readers (two pediatric radiologists [experienced] and two radiology residents [inexperienced]) visually assessed each MRI examination to score the likelihood of HS. One inexperienced reader repeated the evaluations using the volumetric tool. The area under the ROC curve (AUROC), sensitivity, and specificity for HS were computed for the volumetric tool and the readers. Diagnostic performances were compared using McNemar tests. RESULTS. In the HS group, the hippocampal volume (affected vs unaffected, 3.54 vs 4.59 cm3) and temporal lobe volume (affected vs unaffected, 5.66 vs 6.89 cm3) on the affected side were significantly lower than on the unaffected side (p < .001) using the volu-metric tool. AUROCs of the volumetric tool were 0.813-0.842 in patients with left HS and 0.857-0.980 in patients with right HS (sensitivity, 81.8-90.9%; specificity, 70.5-95.5%). No significant difference (p = .63 to > .99) was observed between the performance of the volumetric tool and the performance of the two experienced readers as well as one inexperienced reader (AUROCs for these three readers, 0.968-0.999; sensitivity, 86.4-90.9%; specificity, 100.0%). The volumetric tool had better performance (p < .001) than the other inexperienced reader (AUROC, 0.806; sensitivity, 81.8%; specificity, 47.7%). With subsequent use of the tool, this inexperienced reader showed a nonsignificant increase (p = .10) in AUROC (0.912) as well as in sensitivity (86.4%) and specificity (84.1%). CONCLUSION. A fully automated volumetric brain MRI tool outperformed one of two inexperienced readers and performed as well as two experienced readers in identifying and lateralizing HS in pediatric patients. The tool improved the performance of an inexperienced reader. CLINICAL IMPACT. A fully automated volumetric tool facilitates diagnosis of HS in pediatric patients, especially for an inexperienced reader.
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Goodkin O, Pemberton HG, Vos SB, Prados F, Das RK, Moggridge J, De Blasi B, Bartlett P, Williams E, Campion T, Haider L, Pearce K, Bargallό N, Sanchez E, Bisdas S, White M, Ourselin S, Winston GP, Duncan JS, Cardoso J, Thornton JS, Yousry TA, Barkhof F. Clinical evaluation of automated quantitative MRI reports for assessment of hippocampal sclerosis. Eur Radiol 2020; 31:34-44. [PMID: 32749588 PMCID: PMC7755617 DOI: 10.1007/s00330-020-07075-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 05/07/2020] [Accepted: 07/15/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVES Hippocampal sclerosis (HS) is a common cause of temporal lobe epilepsy. Neuroradiological practice relies on visual assessment, but quantification of HS imaging biomarkers-hippocampal volume loss and T2 elevation-could improve detection. We tested whether quantitative measures, contextualised with normative data, improve rater accuracy and confidence. METHODS Quantitative reports (QReports) were generated for 43 individuals with epilepsy (mean age ± SD 40.0 ± 14.8 years, 22 men; 15 histologically unilateral HS; 5 bilateral; 23 MR-negative). Normative data was generated from 111 healthy individuals (age 40.0 ± 12.8 years, 52 men). Nine raters with different experience (neuroradiologists, trainees, and image analysts) assessed subjects' imaging with and without QReports. Raters assigned imaging normal, right, left, or bilateral HS. Confidence was rated on a 5-point scale. RESULTS Correct designation (normal/abnormal) was high and showed further trend-level improvement with QReports, from 87.5 to 92.5% (p = 0.07, effect size d = 0.69). Largest magnitude improvement (84.5 to 93.8%) was for image analysts (d = 0.87). For bilateral HS, QReports significantly improved overall accuracy, from 74.4 to 91.1% (p = 0.042, d = 0.7). Agreement with the correct diagnosis (kappa) tended to increase from 0.74 ('fair') to 0.86 ('excellent') with the report (p = 0.06, d = 0.81). Confidence increased when correctly assessing scans with the QReport (p < 0.001, η2p = 0.945). CONCLUSIONS QReports of HS imaging biomarkers can improve rater accuracy and confidence, particularly in challenging bilateral cases. Improvements were seen across all raters, with large effect sizes, greatest for image analysts. These findings may have positive implications for clinical radiology services and justify further validation in larger groups. KEY POINTS • Quantification of imaging biomarkers for hippocampal sclerosis-volume loss and raised T2 signal-could improve clinical radiological detection in challenging cases. • Quantitative reports for individual patients, contextualised with normative reference data, improved diagnostic accuracy and confidence in a group of nine raters, in particular for bilateral HS cases. • We present a pre-use clinical validation of an automated imaging assessment tool to assist clinical radiology reporting of hippocampal sclerosis, which improves detection accuracy.
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Affiliation(s)
- Olivia Goodkin
- Centre for Medical Image Computing (CMIC), University College London, London, UK. .,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Hugh G Pemberton
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sjoerd B Vos
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Epilepsy Society MRI Unit, Chalfont St Peter, UK
| | - Ferran Prados
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Universitat Oberta de Catalunya, Barcelona, Spain
| | - Ravi K Das
- Clinical, Educational and Health Psychology, University College London, London, UK
| | - James Moggridge
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Bianca De Blasi
- Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Philippa Bartlett
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Elaine Williams
- Wellcome Trust Centre for Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas Campion
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Lukas Haider
- Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria.,NMR Research Unit, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Kirsten Pearce
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Nuria Bargallό
- Radiology Department, Hospital Clínic de Barcelona and Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Esther Sanchez
- Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Sotirios Bisdas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Mark White
- Digital Services, University College London Hospital, London, UK
| | - Sebastien Ourselin
- Department of Medical Physics and Bioengineering, University College London, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Gavin P Winston
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK.,Department of Medicine, Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - John S Duncan
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Tarek A Yousry
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK.,Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
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25
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Ahmad R, Maiworm M, Nöth U, Seiler A, Hattingen E, Steinmetz H, Rosenow F, Deichmann R, Wagner M, Gracien RM. Cortical Changes in Epilepsy Patients With Focal Cortical Dysplasia: New Insights With T 2 Mapping. J Magn Reson Imaging 2020; 52:1783-1789. [PMID: 32383241 DOI: 10.1002/jmri.27184] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 04/17/2020] [Accepted: 04/17/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND In epilepsy patients with focal cortical dysplasia (FCD) as the epileptogenic focus, global cortical signal changes are generally not visible on conventional MRI. However, epileptic seizures or antiepileptic medication might affect normal-appearing cerebral cortex and lead to subtle damage. PURPOSE To investigate cortical properties outside FCD regions with T2 -relaxometry. STUDY TYPE Prospective study. SUBJECTS Sixteen patients with epilepsy and FCD and 16 age-/sex-matched healthy controls. FIELD STRENGTH/SEQUENCE 3T, fast spin-echo T2 -mapping, fluid-attenuated inversion recovery (FLAIR), and synthetic T1 -weighted magnetization-prepared rapid acquisition of gradient-echoes (MP-RAGE) datasets derived from T1 -maps. ASSESSMENT Reconstruction of the white matter and cortical surfaces based on MP-RAGE structural images was performed to extract cortical T2 values, excluding lesion areas. Three independent raters confirmed that morphological cortical/juxtacortical changes in the conventional FLAIR datasets outside the FCD areas were definitely absent for all patients. Averaged global cortical T2 values were compared between groups. Furthermore, group comparisons of regional cortical T2 values were performed using a surface-based approach. Tests for correlations with clinical parameters were carried out. STATISTICAL TESTS General linear model analysis, permutation simulations, paired and unpaired t-tests, and Pearson correlations. RESULTS Cortical T2 values were increased outside FCD regions in patients (83.4 ± 2.1 msec, control group 81.4 ± 2.1 msec, P = 0.01). T2 increases were widespread, affecting mainly frontal, but also parietal and temporal regions of both hemispheres. Significant correlations were not observed (P ≥ 0.55) between cortical T2 values in the patient group and the number of seizures in the last 3 months or the number of anticonvulsive drugs in the medical history. DATA CONCLUSION Widespread increases in cortical T2 in FCD-associated epilepsy patients were found, suggesting that structural epilepsy in patients with FCD is not only a symptom of a focal cerebral lesion, but also leads to global cortical damage not visible on conventional MRI. EVIDENCE LEVEL 21 TECHNICAL EFFICACY STAGE: 3 J. MAGN. RESON. IMAGING 2020;52:1783-1789.
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Affiliation(s)
- Rida Ahmad
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - Michelle Maiworm
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - Alexander Seiler
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - Helmuth Steinmetz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - Felix Rosenow
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany.,Epilepsy Center Frankfurt Rhine-Main, Center of Neurology and Neurosurgery, Goethe University, Frankfurt/Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - Marlies Wagner
- Department of Neuroradiology, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Germany
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26
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Dou W, Zhao L, Su C, Lu Q, Liu Q, Guo J, Zhao Y, Luo Y, Shi L, Zhang Y, Wang R, Feng F. A quantitative MRI index for assessing the severity of hippocampal sclerosis in temporal lobe epilepsy. BMC Med Imaging 2020; 20:42. [PMID: 32334546 PMCID: PMC7183666 DOI: 10.1186/s12880-020-00440-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Accepted: 04/06/2020] [Indexed: 12/12/2022] Open
Abstract
Background Hippocampal sclerosis (HS) is associated with post-surgery outcome in patients with temporal lobe epilepsy (TLE), and an automated method that quantifies HS severity is still lacking. Here, we aim to propose an MRI-based HS index (HSI) that integrates hippocampal volume and FLAIR signal to measure the severity of HS. Methods Forty-two pre-surgery TLE patients were included retrospectively, with T1-weighted (T1W) and FLAIR images acquired from each subject. Two experienced neurosurgeons (W.D. and C.S.) and one neurologist (Q.L.) rated HS severity with a four-class grading scale (normal, mild, moderate and severe) based on both hippocampal volume loss and increased FLAIR signal. A consensus of HS severity for each subject was made by voting among the three visual rating results. Regarding the automatic quantification, the hippocampal volume was quantified by AccuBrain on T1W image, and the FLAIR signal of hippocampus was calculated as the mean intensity of hippocampal region on the FLAIR image (normalized by the mean intensity of gray matter). To fit the HSI from visual rating, we applied ordinal regression with the voted visual rating as the dependent variable, and hippocampal volume and FLAIR signal as the independent variables. The HSI was calculated by weighting the predicted probabilities of the four-class grading scales from ordinal regression. Results The intra-class correlation coefficient (single measure) of the three raters was 0.806. The generated HSI was significantly correlated with the visual rating scales of the three raters (W.D.: 0.823, Q.L.: 0.817, C.S.: 0.717). HSI scores well differentiated the different HS categories as defined by the agreed HS visual rating (normal vs. mild: p < 0.001, mild vs. moderate: p < 0.001, moderate vs. severe: p = 0.001). Conclusions The proposed HSI was consistent with visual rating scales from epileptologists and sensitive to HS severity. This MRI-based index may help to evaluate HS severity in clinical practice. Further validations are needed to associate HSI with post-surgery outcomes.
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Affiliation(s)
- Wanchen Dou
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China
| | - Lei Zhao
- BrainNow Research Institute, Shenzhen, Guangdong Province, China
| | - Changbao Su
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China
| | - Qiang Lu
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Qi Liu
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China
| | - Jinzhu Guo
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China
| | - Yuming Zhao
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China
| | - Yishan Luo
- BrainNow Research Institute, Shenzhen, Guangdong Province, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, Guangdong Province, China.,Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Yiwei Zhang
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
| | - Renzhi Wang
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, China.
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
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27
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Investigatory pathway and principles of patient selection for epilepsy surgery candidates: a systematic review. BMC Neurol 2020; 20:100. [PMID: 32183734 PMCID: PMC7079385 DOI: 10.1186/s12883-020-01680-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 03/10/2020] [Indexed: 01/20/2023] Open
Abstract
Background The predominant treatment for epilepsy is pharmacotherapy, yet 20–40% do not respond to anti-epileptic drugs. After becoming pharmacoresistant, some patients are worked-up to determine candidacy for epilepsy surgery. Despite the 2009 American Epilepsy Society guidelines, there is no broadly accepted criteria for the investigatory pathway and principles of patient selection for epilepsy surgery candidates. The objective of this systematic review is to elucidate what diagnostic pathways clinicians globally utilize. Methods Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and the Cochrane Handbook of Systemic Reviews of Interventions, we conducted a systematic review through MEDLINE, Embase, and CENTRAL. Results From 2092 screened articles, 14 met inclusion criteria for qualitative synthesis. Structural MRI was required in all investigatory pathways. All but two articles required neuropsychological assessment. Six required neuropsychiatric assessment. Two protocols mentioned assessing the patient’s support network. Three other protocols mentioned discussing expectations with patients. One also motioned conducing an occupational evaluation and making all surgery decisions in a multidisciplinary management conference. fMRI and the Wada test were required assessments in seven of the protocols. [18F]FDG-PET and SPECT were ancillary for all but three articles (where they were required). MEG and intracranial EEG were only mentioned as ancillary. Magnetic resonance (MR) spectroscopy was required at two institutes. With regards to the actual indication for selecting patients to begin the investigatory pathway, seven of the articles used a variation of the International League Against Epilepsy definition of refectory epilepsy, while one incorporated patient social history. Conclusions Despite attempts to standardize patient selection and investigatory pathways, no two protocols were identical. Scalp video/EEG telemetry, structural MRI, and neuropsychological assessment were the only assessments utilized in nearly all protocols. Socioeconomic restrictions appear to play a role in determining which tests are utilized in the investigatory pathway—not just for developing countries. However, cost-effective assessments, such as assessing patient support network and providing realistic expectation of outcomes, were only utilized in few protocols. In addition, no advanced imaging technologies (i.e., qMRI, 3D-MMI) were utilized. Overall, even amongst expert examiners there is significant variation throughout epilepsy centers globally, in selecting candidates and working up patients.
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28
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Lee YJ. Advanced neuroimaging techniques for evaluating pediatric epilepsy. Clin Exp Pediatr 2020; 63:88-95. [PMID: 32024331 PMCID: PMC7073377 DOI: 10.3345/kjp.2019.00871] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2019] [Accepted: 11/06/2019] [Indexed: 01/11/2023] Open
Abstract
Accurate localization of the seizure onset zone is important for better seizure outcomes and preventing deficits following epilepsy surgery. Recent advances in neuroimaging techniques have increased our understanding of the underlying etiology and improved our ability to noninvasively identify the seizure onset zone. Using epilepsy-specific magnetic resonance imaging (MRI) protocols, structural MRI allows better detection of the seizure onset zone, particularly when it is interpreted by experienced neuroradiologists. Ultra-high-field imaging and postprocessing analysis with automated machine learning algorithms can detect subtle structural abnormalities in MRI-negative patients. Tractography derived from diffusion tensor imaging can delineate white matter connections associated with epilepsy or eloquent function, thus, preventing deficits after epilepsy surgery. Arterial spin-labeling perfusion MRI, simultaneous electroencephalography (EEG)-functional MRI (fMRI), and magnetoencephalography (MEG) are noinvasive imaging modalities that can be used to localize the epileptogenic foci and assist in planning epilepsy surgery with positron emission tomography, ictal single-photon emission computed tomography, and intracranial EEG monitoring. MEG and fMRI can localize and lateralize the area of the cortex that is essential for language, motor, and memory function and identify its relationship with planned surgical resection sites to reduce the risk of neurological impairments. These advanced structural and functional imaging modalities can be combined with postprocessing methods to better understand the epileptic network and obtain valuable clinical information for predicting long-term outcomes in pediatric epilepsy.
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Affiliation(s)
- Yun Jeong Lee
- Department of Pediatrics, Kyungpook National University Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
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29
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Microstructural imaging in temporal lobe epilepsy: Diffusion imaging changes relate to reduced neurite density. NEUROIMAGE-CLINICAL 2020; 26:102231. [PMID: 32146320 PMCID: PMC7063236 DOI: 10.1016/j.nicl.2020.102231] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 02/27/2020] [Accepted: 02/27/2020] [Indexed: 01/06/2023]
Abstract
PURPOSE Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics. METHODS 20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured. RESULTS In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF. CONCLUSIONS Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study.
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30
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Vos SB, Winston GP, Goodkin O, Pemberton HG, Barkhof F, Prados F, Galovic M, Koepp M, Ourselin S, Cardoso MJ, Duncan JS. Hippocampal profiling: Localized magnetic resonance imaging volumetry and T2 relaxometry for hippocampal sclerosis. Epilepsia 2019; 61:297-309. [PMID: 31872873 PMCID: PMC7065164 DOI: 10.1111/epi.16416] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 12/02/2019] [Accepted: 12/02/2019] [Indexed: 12/13/2022]
Abstract
Objective Hippocampal sclerosis (HS) is the most common cause of drug‐resistant temporal lobe epilepsy, and its accurate detection is important to guide epilepsy surgery. Radiological features of HS include hippocampal volume loss and increased T2 signal, which can both be quantified to help improve detection. In this work, we extend these quantitative methods to generate cross‐sectional area and T2 profiles along the hippocampal long axis to improve the localization of hippocampal abnormalities. Methods T1‐weighted and T2 relaxometry data from 69 HS patients (32 left, 32 right, 5 bilateral) and 111 healthy controls were acquired on a 3‐T magnetic resonance imaging (MRI) scanner. Automated hippocampal segmentation and T2 relaxometry were performed and used to calculate whole‐hippocampal volumes and to estimate quantitative T2 (qT2) values. By generating a group template from the controls, and aligning this so that the hippocampal long axes were along the anterior‐posterior axis, we were able to calculate hippocampal cross‐sectional area and qT2 by a slicewise method to localize any volume loss or T2 hyperintensity. Individual patient profiles were compared with normative data generated from the healthy controls. Results Profiling of hippocampal volumetric and qT2 data could be performed automatically and reproducibly. HS patients commonly showed widespread decreases in volume and increases in T2 along the length of the affected hippocampus, and focal changes may also be identified. Patterns of atrophy and T2 increase in the left hippocampus were similar between left, right, and bilateral HS. These profiles have potential to distinguish between sclerosis affecting volume and qT2 in the whole or parts of the hippocampus, and may aid the radiological diagnosis in uncertain cases or cases with subtle or focal abnormalities where standard whole‐hippocampal measurements yield normal values. Significance Hippocampal profiling of volumetry and qT2 values can help spatially localize hippocampal MRI abnormalities and work toward improved sensitivity of subtle focal lesions.
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Affiliation(s)
- Sjoerd B Vos
- Centre for Medical Image Computing, University College London, London, UK.,Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Gavin P Winston
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK.,Division of Neurology, Department of Medicine, Queen's University, Kingston, Canada
| | - Olivia Goodkin
- Centre for Medical Image Computing, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Hugh G Pemberton
- Centre for Medical Image Computing, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- Centre for Medical Image Computing, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, National Health Service Foundation Trust, London, UK.,Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Faculty of Brain Sciences, UCL Queen Square Institute of Neurology, University College London, London, UK.,Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Ferran Prados
- Centre for Medical Image Computing, University College London, London, UK.,Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, Faculty of Brain Sciences, UCL Queen Square Institute of Neurology, University College London, London, UK.,eHealth Center, Open University of Catalonia, Barcelona, Spain
| | - Marian Galovic
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK.,Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Matthias Koepp
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - John S Duncan
- Epilepsy Society MRI Unit, Chalfont St Peter, UK.,Department of Clinical and Experimental Epilepsy, University College London, London, UK
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31
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Ono SE, de Carvalho Neto A, Joaquim MJM, Dos Santos GR, de Paola L, Silvado CES. Mesial temporal lobe epilepsy: Revisiting the relation of hippocampal volumetry with memory deficits. Epilepsy Behav 2019; 100:106516. [PMID: 31574430 DOI: 10.1016/j.yebeh.2019.106516] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/12/2019] [Accepted: 08/23/2019] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Neuropsychological tests can infer the lateralization of the epileptogenic focus, associating verbal memory to mesial structures in the left temporal lobe and visual or nonverbal memory to the right side. High-field magnetic resonance imaging (MRI) with high-resolution protocols allows acquisitions suitable for advanced postprocessing with precise volumetry of brain structures, and functional MRI demonstrates evidence that epilepsy should be seen as a network pathology, involving several structures in the brain. Since the literature showing associations between the volumetry of brain structures in left and right mesial temporal lobe epilepsy (MTLE) and verbal and visual memory performance on neuropsychological tests is conflicting, we revisited these relationships, considering the hippocampal volumetry of patients with unilateral MTLE. METHODS Automatized hippocampal volumes were obtained using FreeSurfer software from MRI exams of 35 patients with unilateral MTLE and hippocampal atrophy and homolateral ictal onset zone defined by video electroencephalography concordant to the side of hippocampal volume reduction (15 on the left side). Verbal memory was assessed using the Rey Auditory-Verbal Learning Test (RAVLT), and visual memory tests employed the Rey-Osterrieth Complex Figure Test (ROCFT). The statistical analysis explored relationships between hippocampal volumetry, lateralization, and performance on memory tests. RESULTS In general, we observed deficits in both verbal and visual memory for patients with left and right hippocampal volume reduction. Patients with left hippocampal volume reduction had poorer performance on verbal memory tests compared with those with right hippocampal atrophy (t = -3.813, p < 0.001). Visual memory deficits were seen on both left and right MTLE without a statistically significant difference (t = 0.074, p = 0.942). The correlation between the Hippocampal Asymmetry Index (HAI) and visual and verbal Z-scores was significant only for visual Z-score in right MTLE (R = -0.45, p = 0.048). CONCLUSIONS Verbal memory deficit seems to be more consistent in patients with left hippocampal volume reduction. Although it had only a moderate correlation to HAI, visual memory deficit is suggested as a poorer indicator for right MTLE. Considering that verbal and visual memory deficits are seen on both right and left MTLE, MTLE should not be regarded as a unilateral, focal, or local insult but as a multifactorial and network pathology, possibly involving several brain structures.
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Affiliation(s)
- Sergio Eiji Ono
- Clínica Diagnóstico Avançado por Imagem - DAPI, Curitiba, PR, Brazil.
| | - Arnolfo de Carvalho Neto
- Clínica Diagnóstico Avançado por Imagem - DAPI, Curitiba, PR, Brazil; Epilepsy and EEG Service, Hospital de Clínicas, Federal University of Paraná, Curitiba, PR, Brazil
| | | | | | - Luciano de Paola
- Epilepsy and EEG Service, Hospital de Clínicas, Federal University of Paraná, Curitiba, PR, Brazil
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Avakyan GN, Blinov DV, Alikhanov AA, Perepelova EM, Perepelov VA, Burd SG, Lebedeva AV, Avakyan GG. Recommendations of the Russian League Against Epilepsy (RLAE) on the use of magnetic resonance imaging in the diagnosis of epilepsy. ACTA ACUST UNITED AC 2019. [DOI: 10.17749/2077-8333.2019.11.3.208-232] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Introduction. The MRI method has revolutionized the diagnosis of epilepsy. However, the widespread adoption of MRI in clinical practice is slowed by an insufficient number of high-field MRI scanners, a shortage of trained specialists, and the lack of standard examination protocols. The aim of this article is to present the Recommendations of the Russian League Against Epilepsy (RLAE) on the use of magnetic resonance imaging in the diagnosis of epilepsy.Materials and methods. As a structural element of the International League Against Epilepsy (ILAE), the RLAE considers it important to adapt the Protocol developed by ILAE for specialists in Russia and EAEU countries. The working group analyzed and generalized the clinical practice existing in the Russian Federation, the Republic of Kazakhstan, the Republic of Belarus and the Republic of Uzbekistan. These recommendations are intended for doctors in specialized centers of epilepsy surgery, and for doctors in general medical centers. The recommendations are applicable primarily to adult patients, but the general principles are relevant to children as well.Results. In all patients with convulsive seizures shortly after the first seizure, or patients diagnosed with epilepsy who have an unexplained increase in the frequency of seizures, rapid decrease in cognitive functions or the appearance / worsening of neuropsychiatric symptoms, the RLAE recommends using a unified MR protocol for the neuroimaging of structural sequences in epilepsy with three-dimensional pulse sequences T1 and T2 FLAIR with isotropic voxel 1 × 1 × 1 mm3 and two-dimensional T2- weighted pulse sequences with a pixel size of 1 × 1 mm2 or less. The MRI examination should be combined with EEG or EEG-video monitoring. Using this protocol allows one to set a unified standard for examining patients with epilepsy in order to detect (with high sensitivity) brain lesions playing a key role in the occurrence of seizures. Here, all 13 recommendations are presented.Conclusion. Implementation of these recommendations in clinical practice will improve the access to high-tech medical care and optimize health care costs.
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Affiliation(s)
- G. N. Avakyan
- Pirogov Russian National Research Medical University
| | - D. V. Blinov
- Institute for Preventive and Social Medicine;
Moscow Haass Medical – Social Institute;
Lapino Clinic Hospital, MD Medical Group
| | | | | | | | - S. G. Burd
- Pirogov Russian National Research Medical University
| | | | - G. G. Avakyan
- Pirogov Russian National Research Medical University
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Wang K, Cao X, Wu D, Liao C, Zhang J, Ji C, Zhong J, He H, Chen Y. Magnetic resonance fingerprinting of temporal lobe white matter in mesial temporal lobe epilepsy. Ann Clin Transl Neurol 2019; 6:1639-1646. [PMID: 31359636 PMCID: PMC6764497 DOI: 10.1002/acn3.50851] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 05/21/2019] [Accepted: 07/02/2019] [Indexed: 12/15/2022] Open
Abstract
Objective Mesial temporal lobe epilepsy (MTLE) is a network disorder. We aimed to quantify the white matter alterations in the temporal lobe of MTLE patients with hippocampal sclerosis (MTLE‐HS) by using magnetic resonance fingerprinting (MRF), a novel imaging technique, which allows simultaneous measurements of multiple parameters with a single acquisition. Methods We consecutively recruited 27 unilateral MTLE‐HS patients and 22 healthy controls. Measurements including T1, T2, and PD values in the temporopolar white matter and temporal stem were recorded and analyzed. Results We found increased T2 value in both sides, and increased T1 value in the ipsilateral temporopolar white matter of MTLE‐HS patients, as compared with healthy controls. The T1 and T2 values were higher in the ipsilateral than the contralateral side. In the temporal stem, increased T1 and T2 values in the ipsilateral side of the MTLE‐HS patients were also observed. Only increased T2 values were observed in the contralateral temporal stem. No significant differences in PD values were observed in either the temporopolar white matter or temporal stem of the MTLE‐HS patients. Correlation analysis revealed that T1 and T2 values in the ipsilateral temporopolar white matter were negatively correlated with the age at epilepsy onset. Interpretation By using MRF, we were able to assess the alterations of T1 and T2 in the temporal lobe white matter of MTLE‐HS patients. MRF could be a promising imaging technique in identifying mild changes in MTLE patients, which might optimize the pre‐surgical evaluation and therapeutic interventions in these patients.
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Affiliation(s)
- Kang Wang
- Department of Neurology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiaozhi Cao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Dengchang Wu
- Department of Neurology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Congyu Liao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Jianfang Zhang
- Department of Neurology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Caihong Ji
- Department of Neurology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China.,Department of Imaging Sciences, University of Rochester, Rochester, New York
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
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Bernasconi A, Cendes F, Theodore WH, Gill RS, Koepp MJ, Hogan RE, Jackson GD, Federico P, Labate A, Vaudano AE, Blümcke I, Ryvlin P, Bernasconi N. Recommendations for the use of structural magnetic resonance imaging in the care of patients with epilepsy: A consensus report from the International League Against Epilepsy Neuroimaging Task Force. Epilepsia 2019; 60:1054-1068. [PMID: 31135062 DOI: 10.1111/epi.15612] [Citation(s) in RCA: 118] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 04/23/2019] [Accepted: 04/24/2019] [Indexed: 01/01/2023]
Abstract
Structural magnetic resonance imaging (MRI) is of fundamental importance to the diagnosis and treatment of epilepsy, particularly when surgery is being considered. Despite previous recommendations and guidelines, practices for the use of MRI are variable worldwide and may not harness the full potential of recent technological advances for the benefit of people with epilepsy. The International League Against Epilepsy Diagnostic Methods Commission has thus charged the 2013-2017 Neuroimaging Task Force to develop a set of recommendations addressing the following questions: (1) Who should have an MRI? (2) What are the minimum requirements for an MRI epilepsy protocol? (3) How should magnetic resonance (MR) images be evaluated? (4) How to optimize lesion detection? These recommendations target clinicians in established epilepsy centers and neurologists in general/district hospitals. They endorse routine structural imaging in new onset generalized and focal epilepsy alike and describe the range of situations when detailed assessment is indicated. The Neuroimaging Task Force identified a set of sequences, with three-dimensional acquisitions at its core, the harmonized neuroimaging of epilepsy structural sequences-HARNESS-MRI protocol. As these sequences are available on most MR scanners, the HARNESS-MRI protocol is generalizable, regardless of the clinical setting and country. The Neuroimaging Task Force also endorses the use of computer-aided image postprocessing methods to provide an objective account of an individual's brain anatomy and pathology. By discussing the breadth and depth of scope of MRI, this report emphasizes the unique role of this noninvasive investigation in the care of people with epilepsy.
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Affiliation(s)
- Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Fernando Cendes
- Department of Neurology, University of Campinas, Campinas, Brazil
| | - William H Theodore
- Clinical Epilepsy Section, National Institutes of Health, Bethesda, Maryland
| | - Ravnoor S Gill
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | | | - Robert Edward Hogan
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg, Victoria, Australia
| | - Paolo Federico
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Angelo Labate
- Institute of Neurology, University of Catanzaro, Catanzaro, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero Universitaria, University of Modena and Reggio Emilia, Modena, Italy
| | - Ingmar Blümcke
- Department of Neuropathology, University Hospital Erlangen, Erlangen, Germany
| | - Philippe Ryvlin
- Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Abstract
PURPOSE OF REVIEW MRI has a crucial position in the diagnostic routine of epilepsy patients. It relevantly contributes to etiological diagnostics and is indispensable in presurgical evaluation. As modern MRI research has been a boon to clinical neuroscience in general, it also holds the promise of enhancing diagnostics of epilepsy patients; i.e. increasing the diagnostic yield while decreasing the number of MRI-negative patients. Its rapid progress, however, has caused uncertainty about which of its latest developments already are of clinical interest and which still are of academic interest. It is the purpose of this review to clarify what, to the authors' mind, good practice of MRI in epilepsy patient care is today and what it might be tomorrow. RECENT FINDINGS Progress of diagnostic MRI in epilepsy patients is driven by development of scanner hardware, scanner sequence and data postprocessing. Ultra high-field MRI and elaborate sequences provide datasets of novel quality which can be fed into postprocessing programs extracting pathognomonic features of structural or functional anatomy. The integration of these features by means of computerized classifiers yield previously unsurpassed diagnostic validity. Enthusiasm about Diffusion Tensor Imaging and functional MRI in the evaluation before epilepsy surgery is quelled. SUMMARY The application of an epilepsy tailored MRI protocol at 3 Tesla followed by meticulous expert evaluation early after the onset of epilepsy is most crucial. It is hoped that future research will result in MRI workups more standardized than today and widely used postprocessing routines analyzing co-registered three-dimensional volumes from different modalities.
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Vos SB, Micallef C, Barkhof F, Hill A, Winston GP, Ourselin S, Duncan JS. Evaluation of prospective motion correction of high-resolution 3D-T2-FLAIR acquisitions in epilepsy patients. J Neuroradiol 2018; 45:368-373. [PMID: 29505841 PMCID: PMC6180279 DOI: 10.1016/j.neurad.2018.02.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 12/11/2017] [Accepted: 02/03/2018] [Indexed: 12/28/2022]
Abstract
T2-FLAIR is the single most sensitive MRI contrast to detect lesions underlying focal epilepsies but 3D sequences used to obtain isotropic high-resolution images are susceptible to motion artefacts. Prospective motion correction (PMC) - demonstrated to improve 3D-T1 image quality in a pediatric population - was applied to high-resolution 3D-T2-FLAIR scans in adult epilepsy patients to evaluate its clinical benefit. Coronal 3D-T2-FLAIR scans were acquired with a 1mm isotropic resolution on a 3T MRI scanner. Two expert neuroradiologists reviewed 40 scans without PMC and 40 with navigator-based PMC. Visual assessment addressed six criteria of image quality (resolution, SNR, WM-GM contrast, intensity homogeneity, lesion conspicuity, diagnostic confidence) on a seven-point Likert scale (from non-diagnostic to outstanding). SNR was also objectively quantified within the white matter. PMC scans had near-identical scores on the criteria of image quality to non-PMC scans, with the notable exception that intensity homogeneity was generally worse. Using PMC, the percentage of scans with bad image quality was substantially lower than without PMC (3.25% vs. 12.5%) on the other five criteria. Quantitative SNR estimates revealed that PMC and non-PMC had no significant difference in SNR (P=0.07). Application of prospective motion correction to 3D-T2-FLAIR sequences decreased the percentage of low-quality scans, reducing the number of scans that need to be repeated to obtain clinically useful data.
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Affiliation(s)
- Sjoerd B Vos
- Translational Imaging Group, CMIC, University College London, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, United Kingdom.
| | - Caroline Micallef
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, United Kingdom
| | - Frederik Barkhof
- Translational Imaging Group, CMIC, University College London, London, United Kingdom; Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, United Kingdom; Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Andrea Hill
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom
| | - Gavin P Winston
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom; Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Sebastien Ourselin
- Translational Imaging Group, CMIC, University College London, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom; Dementia Research Centre, UCL Institute of Neurology, London, United Kingdom
| | - John S Duncan
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom
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Quantitative volume-based morphometry in focal cortical dysplasia: A pilot study for lesion localization at the individual level. Eur J Radiol 2018; 105:240-245. [DOI: 10.1016/j.ejrad.2018.06.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 06/16/2018] [Accepted: 06/21/2018] [Indexed: 12/27/2022]
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