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Zhang X, Zhang Y, Wang C, Li L, Zhu F, Sun Y, Mo T, Hu Q, Xu J, Cao D. Focal cortical dysplasia lesion segmentation using multiscale transformer. Insights Imaging 2024; 15:222. [PMID: 39266782 PMCID: PMC11393231 DOI: 10.1186/s13244-024-01803-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Accepted: 08/27/2024] [Indexed: 09/14/2024] Open
Abstract
OBJECTIVES Accurate segmentation of focal cortical dysplasia (FCD) lesions from MR images plays an important role in surgical planning and decision but is still challenging for radiologists and clinicians. In this study, we introduce a novel transformer-based model, designed for the end-to-end segmentation of FCD lesions from multi-channel MR images. METHODS The core innovation of our proposed model is the integration of a convolutional neural network-based encoder-decoder structure with a multiscale transformer to augment the feature representation of lesions in the global field of view. Transformer pathways, composed of memory- and computation-efficient dual-self-attention modules, leverage feature maps from varying depths of the encoder to discern long-range interdependencies among feature positions and channels, thereby emphasizing areas and channels relevant to lesions. The proposed model was trained and evaluated on a public-open dataset including MR images of 85 patients using both subject-level and voxel-level metrics. RESULTS Experimental results indicate that our model offers superior performance both quantitatively and qualitatively. It successfully identified lesions in 82.4% of patients, with a low false-positive lesion cluster rate of 0.176 ± 0.381 per patient. Furthermore, the model achieved an average Dice coefficient of 0.410 ± 0.288, outperforming five established methods. CONCLUSION Integration of the transformer could enhance the feature presentation and segmentation performance of FCD lesions. The proposed model has the potential to serve as a valuable assistive tool for physicians, enabling rapid and accurate identification of FCD lesions. The source code and pre-trained model weights are available at https://github.com/zhangxd0530/MS-DSA-NET . CRITICAL RELEVANCE STATEMENT This multiscale transformer-based model performs segmentation of focal cortical dysplasia lesions, aiming to help radiologists and clinicians make accurate and efficient preoperative evaluations of focal cortical dysplasia patients from MR images. KEY POINTS The first transformer-based model was built to explore focal cortical dysplasia lesion segmentation. Integration of global and local features enhances the segmentation performance of lesions. A valuable benchmark for model development and comparative analyses was provided.
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Affiliation(s)
- Xiaodong Zhang
- Shenzhen Children's Hospital, Shenzhen, 518000, Guangdong, China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518000, Guangdong, China
| | - Yongquan Zhang
- Zhejiang University of Finance and Economics, Hangzhou, 310000, Zhejiang, China
| | - Changmiao Wang
- Shenzhen Research Institute of Big Data, Shenzhen, 518000, Guangdong, China
| | - Lin Li
- Shenzhen Children's Hospital, Shenzhen, 518000, Guangdong, China
| | - Fengjun Zhu
- Shenzhen Children's Hospital, Shenzhen, 518000, Guangdong, China
| | - Yang Sun
- Shenzhen Children's Hospital, Shenzhen, 518000, Guangdong, China
| | - Tong Mo
- Shenzhen Children's Hospital, Shenzhen, 518000, Guangdong, China
| | - Qingmao Hu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518000, Guangdong, China
| | - Jinping Xu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518000, Guangdong, China.
| | - Dezhi Cao
- Shenzhen Children's Hospital, Shenzhen, 518000, Guangdong, China.
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Bustros S, Kaur M, Ritchey E, Szaflarski JP, McGwin GJ, Riley KO, Bentley JN, Memon AA, Jaisani Z. Non-lesional epilepsy does not necessarily convey poor outcomes after invasive monitoring followed by resection or thermal ablation. Neurol Res 2024; 46:653-661. [PMID: 38602305 DOI: 10.1080/01616412.2024.2340879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 04/03/2024] [Indexed: 04/12/2024]
Abstract
OBJECTIVE We aimed to compare outcomes including seizure-free status at the last follow-up in adult patients with medically refractory focal epilepsy identified as lesional vs. non-lesional based on their magnetic resonance imaging (MRI) findings who underwent invasive evaluation followed by subsequent resection or thermal ablation (LiTT). METHODS We identified 88 adult patients who underwent intracranial monitoring between 2014 and 2021. Of those, 40 received resection or LiTT, and they were dichotomized based on MRI findings, as lesional (N = 28) and non-lesional (N = 12). Patient demographics, seizure characteristics, non-invasive interventions, intracranial monitoring, and surgical variables were compared between the groups. Postsurgical seizure outcome at the last follow-up was rated according to the Engel classification, and postoperative seizure freedom was determined by Kaplan-Meyer survival analysis. Statistical analyses employed Fisher's exact test to compare categorical variables, while a t-test was used for continuous variables. RESULTS There were no differences in baseline characteristics between groups except for more often noted PET abnormality in the lesional group (p = 0.0003). 64% of the lesional group and 57% of the non-lesional group received surgical resection or LiTT (p = 0.78). At the last follow-up, 78.5% of the patients with lesional MRI findings achieved Engel I outcomes compared to 66.7% of non-lesional patients (p = 0.45). Kaplan-Meier curves did not show a significant difference in seizure-free duration between both groups after surgical intervention (p = 0.49). SIGNIFICANCE In our sample, the absence of lesion on brain MRI was not associated with worse seizure outcomes in adult patients who underwent invasive intracranial monitoring followed by resection or thermal ablation.
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Affiliation(s)
- Stephanie Bustros
- Division of Epilepsy, Department of Neurology, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
- Department of Neurology, University of Missouri, Columbia, MO, USA
| | - Manmeet Kaur
- Division of Neurocritical Care, Department of Neurology, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - Elizabeth Ritchey
- Division of Epilepsy, Department of Neurology, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - Jerzy P Szaflarski
- Division of Epilepsy, Department of Neurology, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
- Division of Neurocritical Care, Department of Neurology, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - Gerald Jr McGwin
- Department of Epidemiology, School of Public Health, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Kristen O Riley
- Department of Neurosurgery, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - J Nicole Bentley
- Department of Neurosurgery, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - Adeel A Memon
- Department of Neurology, West Virginia University, Morgantown, WV, USA
| | - Zeenat Jaisani
- Division of Epilepsy, Department of Neurology, The University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
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Clay JL, Mirza FA, Hulou KD, Raslau FD. Value and potential pitfalls of morphometric analysis of magnetic resonance imaging in epilepsy. Epilepsia 2024. [PMID: 39031775 DOI: 10.1111/epi.18049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/22/2024]
Affiliation(s)
- Jordan L Clay
- Comprehensive Epilepsy Program, Department of Neurology, University of Kentucky College of Medicine, Lexington, Kentucky, USA
| | - Farhan A Mirza
- Comprehensive Epilepsy Program, Department of Neurological Surgery, University of Kentucky College of Medicine, Lexington, Kentucky, USA
| | - Kamar D Hulou
- Comprehensive Epilepsy Program, Department of Radiology, University of Kentucky College of Medicine, Lexington, Kentucky, USA
| | - Flavius D Raslau
- Comprehensive Epilepsy Program, Department of Neurology, University of Kentucky College of Medicine, Lexington, Kentucky, USA
- Comprehensive Epilepsy Program, Department of Neurological Surgery, University of Kentucky College of Medicine, Lexington, Kentucky, USA
- Comprehensive Epilepsy Program, Department of Radiology, University of Kentucky College of Medicine, Lexington, Kentucky, USA
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4
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Ding Z, Hu S, Su TY, Choi JY, Morris S, Wang X, Sakaie K, Murakami H, Huppertz HJ, Blümcke I, Jones S, Najm I, Ma D, Wang ZI. Combining magnetic resonance fingerprinting with voxel-based morphometric analysis to reduce false positives for focal cortical dysplasia detection. Epilepsia 2024; 65:1631-1643. [PMID: 38511905 PMCID: PMC11166521 DOI: 10.1111/epi.17951] [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: 10/31/2023] [Revised: 02/09/2024] [Accepted: 03/04/2024] [Indexed: 03/22/2024]
Abstract
OBJECTIVE We aim to improve focal cortical dysplasia (FCD) detection by combining high-resolution, three-dimensional (3D) magnetic resonance fingerprinting (MRF) with voxel-based morphometric magnetic resonance imaging (MRI) analysis. METHODS We included 37 patients with pharmacoresistant focal epilepsy and FCD (10 IIa, 15 IIb, 10 mild Malformation of Cortical Development [mMCD], and 2 mMCD with oligodendroglial hyperplasia and epilepsy [MOGHE]). Fifty-nine healthy controls (HCs) were also included. 3D lesion labels were manually created. Whole-brain MRF scans were obtained with 1 mm3 isotropic resolution, from which quantitative T1 and T2 maps were reconstructed. Voxel-based MRI postprocessing, implemented with the morphometric analysis program (MAP18), was performed for FCD detection using clinical T1w images, outputting clusters with voxel-wise lesion probabilities. Average MRF T1 and T2 were calculated in each cluster from MAP18 output for gray matter (GM) and white matter (WM) separately. Normalized MRF T1 and T2 were calculated by z-scores using HCs. Clusters that overlapped with the lesion labels were considered true positives (TPs); clusters with no overlap were considered false positives (FPs). Two-sample t-tests were performed to compare MRF measures between TP/FP clusters. A neural network model was trained using MRF values and cluster volume to distinguish TP/FP clusters. Ten-fold cross-validation was used to evaluate model performance at the cluster level. Leave-one-patient-out cross-validation was used to evaluate performance at the patient level. RESULTS MRF metrics were significantly higher in TP than FP clusters, including GM T1, normalized WM T1, and normalized WM T2. The neural network model with normalized MRF measures and cluster volume as input achieved mean area under the curve (AUC) of .83, sensitivity of 82.1%, and specificity of 71.7%. This model showed superior performance over direct thresholding of MAP18 FCD probability map at both the cluster and patient levels, eliminating ≥75% FP clusters in 30% of patients and ≥50% of FP clusters in 91% of patients. SIGNIFICANCE This pilot study suggests the efficacy of MRF for reducing FPs in FCD detection, due to its quantitative values reflecting in vivo pathological changes. © 2024 International League Against Epilepsy.
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Affiliation(s)
- Zheng Ding
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
- Biomedical Engineering - Case Western Reserve University, Cleveland, Ohio
| | - Siyuan Hu
- Biomedical Engineering - Case Western Reserve University, Cleveland, Ohio
| | - Ting-Yu Su
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
- Biomedical Engineering - Case Western Reserve University, Cleveland, Ohio
| | - Joon Yul Choi
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
- Biomedical Engineering - Yonsei University, Wonju, Republic of Korea
| | - Spencer Morris
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
- Biomedical Engineering - Case Western Reserve University, Cleveland, Ohio
| | - Xiaofeng Wang
- Quantitative Health Science - Cleveland Clinic, Cleveland, Ohio
| | - Ken Sakaie
- Imaging Institute - Cleveland Clinic, Cleveland, Ohio
| | - Hiroatsu Murakami
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
| | | | - Ingmar Blümcke
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
- Neuropathology - University Hospital Erlangen, Erlangen, Germany
| | - Stephen Jones
- Imaging Institute - Cleveland Clinic, Cleveland, Ohio
| | - Imad Najm
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
| | - Dan Ma
- Biomedical Engineering - Case Western Reserve University, Cleveland, Ohio
| | - Zhong Irene Wang
- Epilepsy Center, Neurological Institute - Cleveland Clinic, Cleveland, Ohio
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5
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Chanra V, Chudzinska A, Braniewska N, Silski B, Holst B, Sauvigny T, Stodieck S, Pelzl S, House PM. Development and prospective clinical validation of a convolutional neural network for automated detection and segmentation of focal cortical dysplasias. Epilepsy Res 2024; 202:107357. [PMID: 38582073 DOI: 10.1016/j.eplepsyres.2024.107357] [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: 11/13/2023] [Revised: 02/28/2024] [Accepted: 04/01/2024] [Indexed: 04/08/2024]
Abstract
PURPOSE Focal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early detection and resection of FCDs have favorable prognostic implications for postoperative seizure freedom. Despite advancements in imaging methods, FCD detection remains challenging. House et al. (2021) introduced a convolutional neural network (CNN) for automated FCD detection and segmentation, achieving a sensitivity of 77.8%. However, its clinical applicability was limited due to a low specificity of 5.5%. The objective of this study was to improve the CNN's performance through data-driven training and algorithm optimization, followed by a prospective validation on daily-routine MRIs. MATERIAL AND METHODS A dataset of 300 3 T MRIs from daily clinical practice, including 3D T1 and FLAIR sequences, was prospectively compiled. The MRIs were visually evaluated by two neuroradiologists and underwent morphometric assessment by two epileptologists. The dataset included 30 FCD cases (11 female, mean age: 28.1 ± 10.1 years) and a control group of 150 normal cases (97 female, mean age: 32.8 ± 14.9 years), along with 120 non-FCD pathological cases (64 female, mean age: 38.4 ± 18.4 years). The dataset was divided into three subsets, each analyzed by the CNN. Subsequently, the CNN underwent a two-phase-training process, incorporating subset MRIs and expert-labeled FCD maps. This training employed both classical and continual learning techniques. The CNN's performance was validated by comparing the baseline model with the trained models at two training levels. RESULTS In prospective validation, the best model trained using continual learning achieved a sensitivity of 90.0%, specificity of 70.0%, and accuracy of 72.0%, with an average of 0.41 false positive clusters detected per MRI. For FCD segmentation, an average Dice coefficient of 0.56 was attained. The model's performance improved in each training phase while maintaining a high level of sensitivity. Continual learning outperformed classical learning in this regard. CONCLUSIONS Our study presents a promising CNN for FCD detection and segmentation, exhibiting both high sensitivity and specificity. Furthermore, the model demonstrates continuous improvement with the inclusion of more clinical MRI data. We consider our CNN a valuable tool for automated, examiner-independent FCD detection in daily clinical practice, potentially addressing the underutilization of epilepsy surgery in drug-resistant focal epilepsy and thereby improving patient outcomes.
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Affiliation(s)
- Vicky Chanra
- Hamburg Epilepsy Center, Protestant Hospital Alsterdorf, Department of Neurology and Epileptology, Hamburg, Germany
| | | | | | | | - Brigitte Holst
- University Hospital Hamburg-Eppendorf, Department of Neuroradiology, Hamburg, Germany
| | - Thomas Sauvigny
- University Hospital Hamburg-Eppendorf, Department of Neurosurgery, Hamburg, Germany
| | - Stefan Stodieck
- Hamburg Epilepsy Center, Protestant Hospital Alsterdorf, Department of Neurology and Epileptology, Hamburg, Germany
| | | | - Patrick M House
- Hamburg Epilepsy Center, Protestant Hospital Alsterdorf, Department of Neurology and Epileptology, Hamburg, Germany; theBlue.ai GmbH, Hamburg, Germany; Epileptologicum Hamburg, Specialist's Practice for Epileptology, Hamburg, Germany.
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6
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Bernasconi A, Gill RS, Bernasconi N. The use of automated and AI-driven algorithms for the detection of hippocampal sclerosis and focal cortical dysplasia. Epilepsia 2024. [PMID: 38642009 DOI: 10.1111/epi.17989] [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: 01/31/2024] [Revised: 04/08/2024] [Accepted: 04/08/2024] [Indexed: 04/22/2024]
Abstract
In drug-resistant epilepsy, magnetic resonance imaging (MRI) plays a central role in detecting lesions as it offers unmatched spatial resolution and whole-brain coverage. In addition, the last decade has witnessed continued developments in MRI-based computer-aided machine-learning techniques for improved diagnosis and prognosis. In this review, we focus on automated algorithms for the detection of hippocampal sclerosis and focal cortical dysplasia, particularly in cases deemed as MRI negative, with an emphasis on studies with histologically validated data. In addition, we discuss imaging-derived prognostic markers, including response to anti-seizure medication, post-surgical seizure outcome, and cognitive reserves. We also highlight the advantages and limitations of these approaches and discuss future directions toward person-centered care.
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Affiliation(s)
- Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Ravnoor S Gill
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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7
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Wang W, Huang Q, Zhou Q, Han J, Zhang X, Li L, Lin Y, Wang Y. Multimodal non-invasive evaluation in MRI-negative epilepsy patients. Epilepsia Open 2024; 9:765-775. [PMID: 38258486 PMCID: PMC10984307 DOI: 10.1002/epi4.12896] [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: 12/15/2022] [Revised: 12/15/2023] [Accepted: 12/24/2023] [Indexed: 01/24/2024] Open
Abstract
Presurgical evaluation is still challenging for MRI-negative epilepsy patients. As non-invasive modalities are the easiest acceptable and economic methods in determining the epileptogenic zone, we analyzed the localization value of common non-invasive methods in MRI-negative epilepsy patients. In this study, we included epilepsy patients undergoing presurgical evaluation with presurgical negative MRI. MRI post-processing was performed using a Morphometric Analysis Program (MAP) on T1-weighted volumetric MRI. The relationship between MAP, magnetoencephalography (MEG), scalp electroencephalogram (EEG), and seizure outcomes was analyzed to figure out the localization value of different non-invasive methods. Eighty-six patients were included in this study. Complete resection of the MAP-positive regions or the MEG-positive regions was positively associated with seizure freedom (p = 0.028 and 0.007, respectively). When an area is co-localized by MAP and MEG, the resection of the area was significantly associated with seizure freedom (p = 0.006). However, neither the EEG lateralization nor the EEG localization showed statistical association with the surgical outcome (p = 0.683 and 0.505, respectively). In conclusion, scalp EEG had a limited role in presurgical localization and predicting seizure outcome, combining MAP and MEG results can significantly improve the localization of epileptogenic lesions and have a positive association with seizure-free outcome. PLAIN LANGUAGE SUMMARY: Due to the lack of obvious structure abnormalities on neuroimaging examinations, the identification of epilepsy lesions in MRI-negative epilepsy patients can be difficult. In this study, we intended to use non-invasive examinations to explore the potential epileptic lesions in MRI-negative epilepsy patients and to determine the results accuracy by comparing the neuroimaging results with the epilepsy surgery outcomes. A total of 86 epilepsy patients without obvious structure lesions on MRI were included, and we found that the combinations of different non-invasive examinations and neuroimaging post-processing methods are significantly associated with the seizure freedom results of epilepsy surgery.
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Affiliation(s)
- Wei Wang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Qian Huang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Qilin Zhou
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Jiaqi Han
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xiating Zhang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Liping Li
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Yicong Lin
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Yuping Wang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of NeuromodulationBeijingChina
- Center of Epilepsy, Beijing Institute for Brain DisordersCapital Medical UniversityBeijingChina
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Qian Z, Lin J, Jiang R, Jean S, Dai Y, Deng D, Tagu PT, Shi L, Song S. Evaluation of MRI post-processing methods combined with PET in detecting focal cortical dysplasia lesions for patients with MRI-negative epilepsy. Seizure 2024; 117:275-283. [PMID: 38579502 DOI: 10.1016/j.seizure.2024.03.011] [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: 08/30/2023] [Revised: 03/15/2024] [Accepted: 03/25/2024] [Indexed: 04/07/2024] Open
Abstract
OBJECTIVE Accurate detection of focal cortical dysplasia (FCD) through magnetic resonance imaging (MRI) plays a pivotal role in the preoperative assessment of epilepsy. The integration of multimodal imaging has demonstrated substantial value in both diagnosing FCD and devising effective surgical strategies. This study aimed to enhance MRI post-processing by incorporating positron emission tomography (PET) analysis. We sought to compare the diagnostic efficacy of diverse image post-processing methodologies in patients presenting MRI-negative FCD. METHODS In this retrospective investigation, we assembled a cohort of patients with negative preoperative MRI results. T1-weighted volumetric sequences were subjected to morphometric analysis program (MAP) and composite parametric map (CPM) post-processing techniques. We independently co-registered images derived from various methods with PET scans. The alignment was subsequently evaluated, and its correlation was correlated with postoperative seizure outcomes. RESULTS A total of 41 patients were enrolled in the study. In the PET-MAP(p = 0.0189) and PET-CPM(p = 0.00041) groups, compared with the non-overlap group, the overlap group significantly associated with better postoperative outcomes. In PET(p = 0.234), CPM(p = 0.686) and MAP(p = 0.672), there is no statistical significance between overlap and seizure-free outcomes. The sensitivity of using the CPM alone outperformed the MAP (0.65 vs 0.46). The use of PET-CPM demonstrated superior sensitivity (0.96), positive predictive value (0.83), and negative predictive value (0.91), whereas the MAP displayed superior specificity (0.71). CONCLUSIONS Our findings suggested a superiority in sensitivity of CPM in detecting potential FCD lesions compared to MAP, especially when it is used in combination with PET for diagnosis of MRI-negative epilepsy patients. Moreover, we confirmed the superiority of synergizing metabolic imaging (PET) with quantitative maps derived from structural imaging (MAP or CPM) to enhance the identification of subtle epileptogenic zones (EZs). This study serves to illuminate the potential of integrated multimodal techniques in advancing our capability to pinpoint elusive pathological features in epilepsy cases.
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Affiliation(s)
- Zhe Qian
- Fujian Medical University, Fuzhou, China.
| | - Jiuluan Lin
- Department of Neurosurgery, Tsinghua University Yuquan Hospital, Fuzhou, China.
| | - Rifeng Jiang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.
| | - Stéphane Jean
- Department of Neurosurgery, Fuzhou Children's Hospital, Fuzhou, China
| | - Yihai Dai
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Donghuo Deng
- Fujian Medical University Union Hospital, Fuzhou, China.
| | | | - Lin Shi
- BrainNow Research Institute, Guangdong, China.
| | - Shiwei Song
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, China.
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Zheng R, Chen R, Chen C, Yang Y, Ge Y, Ye L, Miao P, Jin B, Li H, Zhu J, Wang S, Huang K. Automated detection of focal cortical dysplasia based on magnetic resonance imaging and positron emission tomography. Seizure 2024; 117:126-132. [PMID: 38417211 DOI: 10.1016/j.seizure.2024.02.009] [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: 10/12/2023] [Revised: 02/10/2024] [Accepted: 02/14/2024] [Indexed: 03/01/2024] Open
Abstract
PURPOSE Focal cortical dysplasia (FCD) is a common etiology of drug-resistant focal epilepsy. Visual identification of FCD is usually time-consuming and depends on personal experience. Herein, we propose an automated type II FCD detection approach utilizing multi-modal data and 3D convolutional neural network (CNN). METHODS MRI and positron emission tomography (PET) data of 82 patients with FCD were collected, including 55 (67.1%) histopathologically, and 27 (32.9%) radiologically diagnosed patients. Three types of morphometric feature maps and three types of tissue maps were extracted from the T1-weighted images. These maps, T1, and PET images formed the inputs for CNN. Five-fold cross-validations were carried out on the training set containing 62 patients, and the model behaving best was chosen to detect FCD on the test set of 20 patients. Furthermore, ablation experiments were performed to estimate the value of PET data and CNN. RESULTS On the validation set, FCD was detected in 90.3% of the cases, with an average of 1.7 possible lesions per patient. The sensitivity on the test set was 90.0%, with 1.85 possible lesions per patient. Without the PET data, the sensitivity decreased to 80.0%, and the average lesion number increased to 2.05 on the test set. If an artificial neural network replaced the CNN, the sensitivity decreased to 85.0%, and the average lesion number increased to 4.65. SIGNIFICANCE Automated detection of FCD with high sensitivity and few false-positive findings is feasible based on multi-modal data. PET data and CNN could improve the performance of automated detection.
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Affiliation(s)
- Ruifeng Zheng
- College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Ruotong Chen
- Department of Neurology and Epilepsy Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Cong Chen
- Department of Neurology and Epilepsy Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Yuyu Yang
- Department of Neurology and Epilepsy Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yi Ge
- Department of Neurology and Epilepsy Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Linqi Ye
- Department of Neurology and Epilepsy Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Pu Miao
- Department of Pediatrics, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Bo Jin
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Hong Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Junming Zhu
- Department of Neurosurgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Shuang Wang
- Department of Neurology and Epilepsy Center, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Kejie Huang
- College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
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10
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Tsalouchidou PE, Hoffmann J, Strehlau S, Linka L, Belke M, Habermehl L, Schulze M, Kemmling A, Menzler K, Knake S. Morphometric magnetic resonance imaging (MRI) postprocessing in MRI-negative patients with first unprovoked seizure. Epilepsia 2024; 65:1107-1114. [PMID: 38305932 DOI: 10.1111/epi.17909] [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: 09/27/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 02/03/2024]
Abstract
OBJECTIVE The aim of the study was to evaluate the benefits of morphometric magnetic resonance imaging (MRI) postprocessing in patients presenting with a first seizure and negative MRI results and to investigate these findings in the context of the clinical and electroencephalographic data, seizure recurrence rates, and epilepsy diagnosis in these patients. METHODS We retrospectively reviewed 97 MRI scans of patients with first unprovoked epileptic seizure and no evidence of epileptogenic lesion on clinical routine MRI. Morphometric Analysis Program (MAP; v2018), automated postprocessing software, was used to identify subtle, potentially epileptogenic lesions in the three-dimensional T1-weighted MRI data. The resulting probability maps were examined together with the conventional MRI images by a reviewer who remained blinded to the patients' clinical and electroencephalographical data. Clinical data were prospectively collected between February 2018 and May 2023. RESULTS Among the apparently MRI-negative patients, a total of 18 of 97 (18.6%) showed cortical changes suggestive of focal cortical dysplasia. Within the population with positive MAP findings (MAP+), seizure recurrence rates were 61.1% and 66.7% at 1 and 2 years after the first unprovoked seizure, respectively. Conversely, patients with negative MAP findings (MAP-) had lower seizure recurrence rates of 27.8% and 34.2% at 1 and 2 years after the first unprovoked seizure, respectively. Patients with MAP+ findings were significantly more likely to be diagnosed with epilepsy than those patients with MAP- findings (χ2 [1, n = 97] = 14.820, p < .001, odds ratio = 21.371, 95% CI = 2.710-168.531) during a mean follow-up time of 22.51 months (SD = 16.7 months, range = 1-61 months). SIGNIFICANCE MRI postprocessing can be a valuable tool for detecting subtle epileptogenic lesions in patients with a first seizure and negative MRI results. Patients with first seizure and MAP+ findings had high seizure recurrence rates, meeting the criteria for beginning epilepsy.
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Affiliation(s)
- Panagiota-Eleni Tsalouchidou
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
- Second Department of Neurology, Attikon University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Johanna Hoffmann
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
| | - Sascha Strehlau
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
| | - Louise Linka
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
| | - Marcus Belke
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-University Marburg, Marburg, Germany
| | - Lena Habermehl
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
| | - Maximilian Schulze
- Department of Neuroradiology, Philipps University Marburg, Marburg, Germany
| | - André Kemmling
- Department of Neuroradiology, Philipps University Marburg, Marburg, Germany
| | - Katja Menzler
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-University Marburg, Marburg, Germany
- Core Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Susanne Knake
- Epilepsy Center Hessen, Department of Neurology, Philipps University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Philipps-University Marburg, Marburg, Germany
- Core Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
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11
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Zhang S, Zhuang Y, Luo Y, Zhu F, Zhao W, Zeng H. Deep learning-based automated lesion segmentation on pediatric focal cortical dysplasia II preoperative MRI: a reliable approach. Insights Imaging 2024; 15:71. [PMID: 38472513 DOI: 10.1186/s13244-024-01635-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 01/27/2024] [Indexed: 03/14/2024] Open
Abstract
OBJECTIVES Focal cortical dysplasia (FCD) represents one of the most common causes of refractory epilepsy in children. Deep learning demonstrates great power in tissue discrimination by analyzing MRI data. A prediction model was built and verified using 3D full-resolution nnU-Net for automatic lesion detection and segmentation of children with FCD II. METHODS High-resolution brain MRI structure data from 65 patients, confirmed with FCD II by pathology, were retrospectively studied. Experienced neuroradiologists segmented and labeled the lesions as the ground truth. Also, we used 3D full-resolution nnU-Net to segment lesions automatically, generating detection maps. The algorithm was trained using fivefold cross-validation, with data partitioned into training (N = 200) and testing (N = 15). To evaluate performance, detection maps were compared to expert manual labels. The Dice-Sørensen coefficient (DSC) and sensitivity were used to assess the algorithm performance. RESULTS The 3D nnU-Net showed a good performance for FCD lesion detection at the voxel level, with a sensitivity of 0.73. The best segmentation model achieved a mean DSC score of 0.57 on the testing dataset. CONCLUSION This pilot study confirmed that 3D full-resolution nnU-Net can automatically segment FCD lesions with reliable outcomes. This provides a novel approach to FCD lesion detection. CRITICAL RELEVANCE STATEMENT Our fully automatic models could process the 3D T1-MPRAGE data and segment FCD II lesions with reliable outcomes. KEY POINTS • Simplified image processing promotes the DL model implemented in clinical practice. • The histopathological confirmed lesion masks enhance the clinical credibility of the AI model. • The voxel-level evaluation metrics benefit lesion detection and clinical decisions.
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Affiliation(s)
- Siqi Zhang
- Shantou University Medical College, Shantou University, 22 Xinling Road, Jinping District, Shantou, 515041, China
- Department of Radiology, Shenzhen Children's Hospital, District, 7019 Yitian Road, Futian, Shenzhen, 518038, China
| | - Yijiang Zhuang
- Department of Radiology, Shenzhen Children's Hospital, District, 7019 Yitian Road, Futian, Shenzhen, 518038, China
| | - Yi Luo
- Department of Radiology, Shenzhen Children's Hospital, District, 7019 Yitian Road, Futian, Shenzhen, 518038, China
| | - Fengjun Zhu
- Department of Epilepsy Surgical Department, Shenzhen Children's Hospital, 7019 Yitian Road, Futian District, Shenzhen, 518038, China
| | - Wen Zhao
- Shantou University Medical College, Shantou University, 22 Xinling Road, Jinping District, Shantou, 515041, China
- Department of Radiology, Shenzhen Children's Hospital, District, 7019 Yitian Road, Futian, Shenzhen, 518038, China
| | - Hongwu Zeng
- Department of Radiology, Shenzhen Children's Hospital, District, 7019 Yitian Road, Futian, Shenzhen, 518038, China.
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12
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Czarnetzki C, Spinelli L, Huppertz HJ, Schaller K, Momjian S, Lobrinus J, Vargas MI, Garibotto V, Vulliemoz S, Seeck M. Yield of non-invasive imaging in MRI-negative focal epilepsy. J Neurol 2024; 271:995-1003. [PMID: 37907727 PMCID: PMC10827933 DOI: 10.1007/s00415-023-11987-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/02/2023] [Accepted: 09/04/2023] [Indexed: 11/02/2023]
Abstract
OBJECTIVE The absence of MRI-lesion reduces considerably the probability of having an excellent outcome (International League Against Epilepsies [ILAE] class I-II) after epilepsy surgery. Surgical success in magnetic-resonance imaging (MRI)-negative cases relies therefore mainly on non-invasive techniques such as positron-emission tomography (PET), subtraction ictal/inter-ictal single-photon-emission-computed-tomography co-registered to MRI (SISCOM), electric source imaging (ESI) and morphometric MRI analysis (MAP). We were interested in identifying the optimal imaging technique or combination to achieve post-operative class I-II in patients with MRI-negative focal epilepsy. METHODS We identified 168 epileptic patients without MRI lesion. Thirty-three (19.6%) were diagnosed with unifocal epilepsy, underwent surgical resection and follow-up ⩾ 2 years. Sensitivity, specificity, predictive values, and diagnostic odds ratio (OR) were calculated for each technique individually and in combination (after co-registration). RESULTS 23/33 (70%) were free of disabling seizures (75.0% with temporal and 61.5% extratemporal lobe epilepsy). None of the individual modalities presented an OR > 1.5, except ESI if only patients with interictal epileptiform discharges (IEDs) were considered (OR 3.2). On a dual combination, SISCOM with ESI presented the highest outcome (OR = 6). MAP contributed to detecting indistinguishable focal cortical dysplasia in particular in extratemporal epilepsies with a sensitivity of 75%. Concordance of PET, ESI on interictal epileptic discharges, and SISCOM was associated with the highest chance for post-operative seizure control (OR = 11). CONCLUSION If MRI is negative, the chances to benefit from epilepsy surgery are almost as high as in lesional epilepsy, provided that multiple established non-invasive imaging tools are rigorously applied and co-registered together.
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Affiliation(s)
- Christian Czarnetzki
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
| | - Laurent Spinelli
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland
| | | | - Karl Schaller
- Department of Clinical Neurosciences, Neurosurgery Clinic, University Hospital of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Department of Clinical Neurosciences, Neurosurgery Clinic, University Hospital of Geneva, Geneva, Switzerland
| | - Johannes Lobrinus
- Department of Clinical Pathology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Maria-Isabel Vargas
- Department of Radiology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Department of Radiology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland
| | - Margitta Seeck
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
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13
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Jin B, Xu J, Wang C, Wang S, Li H, Chen C, Ye L, He C, Cheng H, Zhang L, Wang S, Wang J, Aung T. Functional profile of perilesional gray matter in focal cortical dysplasia: an fMRI study. Front Neurosci 2024; 18:1286302. [PMID: 38318464 PMCID: PMC10838983 DOI: 10.3389/fnins.2024.1286302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 01/08/2024] [Indexed: 02/07/2024] Open
Abstract
Objectives We aim to investigate the functional profiles of perilesional gray matter (GM) in epileptic patients with focal cortical dysplasia (FCD) and to correlate these profiles with FCD II subtypes, surgical outcomes, and different antiseizure medications (ASMs) treatment response patterns. Methods Nine patients with drug-responsive epilepsy and 30 patients with drug-resistant epilepsy (11 were histologically confirmed FCD type IIa, 19 were FCD type IIb) were included. Individual-specific perilesional GM and contralateral homotopic GM layer masks were generated. These masks underwent a two-voxel (2 mm) dilation from the FCD lesion and contralateral homotopic region, resulting in 10 GM layers (20 mm). Layer 1, the innermost, progressed to Layer 10, the outermost. Amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) analyses were conducted to assess the functional characteristics of ipsilateral perilesional GM and contralateral homotopic GM. Results Compared to the contralateral homotopic GM, a significant reduction of ALFF was detected at ipsilateral perilesional GM layer 1 to 6 in FCD type IIa (after Bonferroni correction p < 0.005, paired t-test), whereas a significant decrease was observed at ipsilateral perilesional GM layer 1 to 2 in FCD type IIb (after Bonferroni correction p < 0.005, paired t-test). Additionally, a significant decrease of the ReHo was detected at ipsilateral perilesional GM layer 1 compared to the CHRs in FCD type IIb. Notably, complete resection of functional perilesional GM alterations did not correlate with surgical outcomes. Compared to the contralateral homotopic GM, a decreased ALFF in the ipsilateral perilesional GM layer was detected in drug-responsive patients, whereas decreased ALFF in the ipsilateral perilesional GM layer 1-6 and decreased ReHo at ipsilateral perilesional GM layer 1 were observed in drug-resistant patients (after Bonferroni correction p < 0.005, paired t-test). Conclusion Our findings indicate distinct functional profiles of perilesional GM based on FCD histological subtypes and ASMs' response patterns. Importantly, our study illustrates that the identified functional alterations in perilesional GM may not provide sufficient evidence to determine the epileptogenic boundary required for surgical resection.
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Affiliation(s)
- Bo Jin
- Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiahui Xu
- Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Chao Wang
- Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Shan Wang
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Hong Li
- Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Cong Chen
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Linqi Ye
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Chenmin He
- Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Hui Cheng
- Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Lisan Zhang
- Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Shuang Wang
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jin Wang
- Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Thandar Aung
- Department of Neurology, Epilepsy Center, University of Pittsburgh Medical Center, Pittsburgh, PA, United States
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14
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Mann L, Rosenow F, Strzelczyk A, Hattingen E, Willems LM, Harter PN, Weber K, Mann C. The impact of referring patients with drug-resistant focal epilepsy to an epilepsy center for presurgical diagnosis. Neurol Res Pract 2023; 5:65. [PMID: 38093325 PMCID: PMC10720126 DOI: 10.1186/s42466-023-00288-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 10/13/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Epilepsy surgery is an established treatment for drug-resistant focal epilepsy (DRFE) that results in seizure freedom in about 60% of patients. Correctly identifying an epileptogenic lesion in magnetic resonance imaging (MRI) is challenging but highly relevant since it improves the likelihood of being referred for presurgical diagnosis. The epileptogenic lesion's etiology directly relates to the surgical intervention's indication and outcome. Therefore, it is vital to correctly identify epileptogenic lesions and their etiology presurgically. METHODS We compared the final histopathological diagnoses of all patients with DRFE undergoing epilepsy surgery at our center between 2015 and 2021 with their MRI diagnoses before and after presurgical diagnosis at our epilepsy center, including MRI evaluations by expert epilepsy neuroradiologists. Additionally, we analyzed the outcome of different subgroups. RESULTS This study included 132 patients. The discordance between histopathology and MRI diagnoses significantly decreased from 61.3% for non-expert MRI evaluations (NEMRIs) to 22.1% for epilepsy center MRI evaluations (ECMRIs; p < 0.0001). The MRI-sensitivity improved significantly from 68.6% for NEMRIs to 97.7% for ECMRIs (p < 0.0001). Identifying focal cortical dysplasia (FCD) and amygdala dysplasia was the most challenging for both subgroups. 65.5% of patients with negative NEMRI were seizure-free 12 months postoperatively, no patient with negative ECMRI achieved seizure-freedom. The mean duration of epilepsy until surgical intervention was 13.6 years in patients with an initial negative NEMRI and 9.5 years in patients with a recognized lesion in NEMRI. CONCLUSIONS This study provides evidence that for patients with DRFE-especially those with initial negative findings in a non-expert MRI-an early consultation at an epilepsy center, including an ECMRI, is important for identifying candidates for epilepsy surgery. NEMRI-negative findings preoperatively do not preclude seizure freedom postoperatively. Therefore, patients with DRFE that remain MRI-negative after initial NEMRI should be referred to an epilepsy center for presurgical evaluation. Nonreferral based on NEMRI negativity may harm such patients and delay surgical intervention. However, ECMRI-negative patients have a reduced chance of becoming seizure-free after epilepsy surgery. Further improvements in MRI technique and evaluation are needed and should be directed towards improving sensitivity for FCDs and amygdala dysplasias.
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Affiliation(s)
- Leonhard Mann
- Epilepsy Center Rhine-Main, Center of Neurology and Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany.
- Department of Neuroradiology, University Hospital Frankfurt, Goethe University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany.
| | - Felix Rosenow
- Epilepsy Center Rhine-Main, Center of Neurology and Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University, Frankfurt am Main, Germany
| | - Adam Strzelczyk
- Epilepsy Center Rhine-Main, Center of Neurology and Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University, Frankfurt am Main, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Frankfurt, Goethe University Frankfurt, Schleusenweg 2-16, 60528, Frankfurt am Main, Germany
| | - Laurent M Willems
- Epilepsy Center Rhine-Main, Center of Neurology and Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University, Frankfurt am Main, Germany
| | - Patrick N Harter
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
- Centre for Neuropathology and Prion-Research, Ludwig-Maximilians-Universität München, München, Germany
| | - Katharina Weber
- Neurological Institute (Edinger Institute), University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany
- Center for Tumor Diseases, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Catrin Mann
- Epilepsy Center Rhine-Main, Center of Neurology and Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University, Frankfurt am Main, Germany
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15
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Kong Y, Cheng N, Qiu FJ, Yao L, Gao M, Chen AQ, Kong QX, Zhang GQ. Application value of multimodal MRI combined with PET metabolic parameters in temporal lobe epilepsy with dual pathology. Eur J Radiol 2023; 169:111171. [PMID: 38250750 DOI: 10.1016/j.ejrad.2023.111171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/03/2023] [Accepted: 10/24/2023] [Indexed: 01/23/2024]
Abstract
OBJECTIVES To investigate the application value of multimodal MRI combined with PET metabolic parameters in detecting temporal lobe epilepsy (TLE) with dual pathology (DP) and the prediction effect of post-surgical outcomes in these patients. METHODS We retrospectively reviewed 50 patients with TLE-DP who underwent surgery at our hospital between January 2016 and December 2021 and collected the demographics, clinical characteristics, video-electroencephalography (v-EEG), neuroimaging, and surgical data. Seizure outcome data were collected during a regular follow-up of at least 12 months and were graded using Engel scores. Fisher's exact test was used to compare the differences in DP detection rates of various diagnostic modalities. Univariate and multivariate analyses were performed to explore the prognostic factors for predicting seizure outcomes post-surgery. RESULTS Of the 50 patients, 20 were males. The median age was 30, the median age at first seizure was 14, and the median duration was ten years. Voxel-based morphometry-PET statistical parametric mapping-PET/MRI (VBM-PSPM-PET/MRI) had the highest detection rate, followed by PET/MRI, VBM analysis, and PET-SPM. Regardless of follow-up duration, v-EEG, PET, image post-processing methods, and VBM-PSPM-PET/MRI statistically correlated with seizure outcomes using the log-rank test in the Kaplan-Meier analysis. Multivariate analysis showed that VBM-PSPM-PET/MRI was an independent predictor of TLE-DP (hazard ratio (HR) = 15.674, 95 % CI = 0.002-0.122, P < 0.00 1). CONCLUSIONS Our study illustrates that VBM-PSPM-PET/MRI has the highest detection value in patients with TLE-DP and can provide independent prognostic information for patients who undergo surgery. This approach has the most substantial potential for the selection of candidates for patients who undergo surgical treatment and for prognostic stratification.
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Affiliation(s)
- Yu Kong
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China; College of Materials Science and Engineering, Qingdao University, Qingdao 266071, Shandong, China
| | - Nan Cheng
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - Feng-Juan Qiu
- Department of Pediatric Rehabilitation, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - Lei Yao
- Clinical Medical College, Jining Medical University, Jining 272067, Shandong, China
| | - Ming Gao
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - An-Qiang Chen
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China
| | - Qing-Xia Kong
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China.
| | - Gu-Qing Zhang
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining 272029, Shandong, China.
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Mo J, Dong W, Sang L, Zheng Z, Guo Q, Zhou X, Zhou W, Wang H, Meng X, Yao Y, Wang F, Hu W, Zhang K, Shao X. Multimodal imaging-based diagnostic approach for MRI-negative posterior cortex epilepsy. Ther Adv Neurol Disord 2023; 16:17562864231212254. [PMID: 38021475 PMCID: PMC10657531 DOI: 10.1177/17562864231212254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 10/17/2023] [Indexed: 12/01/2023] Open
Abstract
Background Posterior cortex epilepsy (PCE) primarily comprises seizures originating from the occipital, parietal, and/or posterior edge of the temporal lobe. Electroclinical dissociation and subtle imaging representation render the diagnosis of PCE challenging. Improved methods for accurately identifying patients with PCE are necessary. Objectives To develop a novel voxel-based image postprocessing method for better visual identification of the neuroimaging abnormalities associated with PCE. Design Multicenter, retrospective study. Methods Clinical and imaging features of 165 patients with PCE were retrospectively reviewed and collected from five epilepsy centers. A total of 37 patients (32.4% female, 20.2 ± 8.9 years old) with magnetic resonance imaging (MRI)-negative PCE were finally included for analysis. Image postprocessing features were calculated over a neighborhood for each voxel in the multimodality data. The postprocessed maps comprised structural deformation, hyperintense signal, and hypometabolism. Five raters from three different centers were blinded to the clinical diagnosis and determined the neuroimaging abnormalities in the postprocessed maps. Results The average accuracy of correct identification was 55.7% (range from 43.2 to 62.2%) and correct lateralization was 74.1% (range from 64.9 to 81.1%). The Cronbach's alpha was 0.766 for the correct identification and 0.683 for the correct lateralization with similar results of the interclass correlation coefficient, thus indicating reliable agreement between the raters. Conclusion The image postprocessing method developed in this study can potentially improve the visual detection of MRI-negative PCE. The technique could lead to an increase in the number of patients with PCE who could benefit from the surgery.
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Affiliation(s)
- Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wenyu Dong
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Disease, NCRC-ND, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Zhong Zheng
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Qiang Guo
- Epilepsy Center, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Xiuming Zhou
- Epilepsy Center, Guangdong Sanjiu Brain Hospital, Guangzhou, China
| | - Wenjing Zhou
- Epilepsy Center, Tsinghua University Yuquan Hospital, Beijing, China
| | - Haixiang Wang
- Epilepsy Center, Tsinghua University Yuquan Hospital, Beijing, China
| | - Xianghong Meng
- Department of Neurosurgery, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China
| | - Yi Yao
- Department of Functional Neurosurgery, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China
| | - Fengpeng Wang
- Department of Functional Neurosurgery, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Disease, NCRC-ND, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing 100070, China
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing 100070, China
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Honke J, Hoffmann L, Coras R, Kobow K, Leu C, Pieper T, Hartlieb T, Bien CG, Woermann F, Cloppenborg T, Kalbhenn T, Gaballa A, Hamer H, Brandner S, Rössler K, Dörfler A, Rampp S, Lemke JR, Baldassari S, Baulac S, Lal D, Nürnberg P, Blümcke I. Deep histopathology genotype-phenotype analysis of focal cortical dysplasia type II differentiates between the GATOR1-altered autophagocytic subtype IIa and MTOR-altered migration deficient subtype IIb. Acta Neuropathol Commun 2023; 11:179. [PMID: 37946310 PMCID: PMC10633947 DOI: 10.1186/s40478-023-01675-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 10/21/2023] [Indexed: 11/12/2023] Open
Abstract
Focal cortical dysplasia type II (FCDII) is the most common cause of drug-resistant focal epilepsy in children. Herein, we performed a deep histopathology-based genotype-phenotype analysis to further elucidate the clinico-pathological and genetic presentation of FCDIIa compared to FCDIIb. Seventeen individuals with histopathologically confirmed diagnosis of FCD ILAE Type II and a pathogenic variant detected in brain derived DNA whole-exome sequencing or mTOR gene panel sequencing were included in this study. Clinical data were directly available from each contributing centre. Histopathological analyses were performed from formalin-fixed, paraffin-embedded tissue samples using haematoxylin-eosin and immunohistochemistry for NF-SMI32, NeuN, pS6, p62, and vimentin. Ten individuals carried loss-of-function variants in the GATOR1 complex encoding genes DEPDC5 (n = 7) and NPRL3 (n = 3), or gain-of-function variants in MTOR (n = 7). Whereas individuals with GATOR1 variants only presented with FCDIIa, i.e., lack of balloon cells, individuals with MTOR variants presented with both histopathology subtypes, FCDIIa and FCDIIb. Interestingly, 50% of GATOR1-positive cases showed a unique and predominantly vacuolizing phenotype with p62 immunofluorescent aggregates in autophagosomes. All cases with GATOR1 alterations had neurosurgery in the frontal lobe and the majority was confined to the cortical ribbon not affecting the white matter. This pattern was reflected by subtle or negative MRI findings in seven individuals with GATOR1 variants. Nonetheless, all individuals were seizure-free after surgery except four individuals carrying a DEPDC5 variant. We describe a yet underrecognized genotype-phenotype correlation of GATOR1 variants with FCDIIa in the frontal lobe. These lesions were histopathologically characterized by abnormally vacuolizing cells suggestive of an autophagy-altered phenotype. In contrast, individuals with FCDIIb and brain somatic MTOR variants showed larger lesions on MRI including the white matter, suggesting compromised neural cell migration.
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Affiliation(s)
- Jonas Honke
- Department of Neuropathology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Partner of the European Reference Network (ERN) EpiCARE, Barcelona, Spain
| | - Lucas Hoffmann
- Department of Neuropathology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Partner of the European Reference Network (ERN) EpiCARE, Barcelona, Spain
| | - Roland Coras
- Department of Neuropathology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Partner of the European Reference Network (ERN) EpiCARE, Barcelona, Spain
| | - Katja Kobow
- Department of Neuropathology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Partner of the European Reference Network (ERN) EpiCARE, Barcelona, Spain
| | - Costin Leu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, USA
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK
- Department of Neurology, McGovern Medical School, UTHealth Houston, University of Texas, Houston, USA
| | - Tom Pieper
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
| | - Till Hartlieb
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
- Research Institute for Rehabilitation, Transition, and Palliation, Paracelsus Medical University, Salzburg, Austria
| | - Christian G Bien
- Department of Epileptology (Krankenhaus Mara), Medical School, Bielefeld University, Bielefeld, Germany
| | - Friedrich Woermann
- Department of Epileptology (Krankenhaus Mara), Medical School, Bielefeld University, Bielefeld, Germany
| | - Thomas Cloppenborg
- Department of Epileptology (Krankenhaus Mara), Medical School, Bielefeld University, Bielefeld, Germany
| | - Thilo Kalbhenn
- Department of Epileptology (Krankenhaus Mara), Medical School, Bielefeld University, Bielefeld, Germany
- Department of Neurosurgery (Evangelisches Klinikum Bethel), Medical School, Bielefeld University, Bielefeld, Germany
| | - Ahmed Gaballa
- Department of Epileptology (Krankenhaus Mara), Medical School, Bielefeld University, Bielefeld, Germany
| | - Hajo Hamer
- Partner of the European Reference Network (ERN) EpiCARE, Barcelona, Spain
- Epilepsy Center, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Sebastian Brandner
- Department of Neurosurgery, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Karl Rössler
- Department of Neurosurgery, Medical University of Vienna, Vienna General Hospital, Vienna, Austria
| | - Arnd Dörfler
- Department of Neuroradiology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Stefan Rampp
- Department of Neurosurgery, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Department of Neuroradiology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Johannes R Lemke
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
- Center for Rare Diseases, University of Leipzig Medical Center, Leipzig, Germany
| | - Sara Baldassari
- Inserm, CNRS, APHP, Institut du Cerveau - Paris Brain Institute - ICM, Hôpital de La Pitié Salpêtrière, Sorbonne Université, Paris, France
| | - Stéphanie Baulac
- Inserm, CNRS, APHP, Institut du Cerveau - Paris Brain Institute - ICM, Hôpital de La Pitié Salpêtrière, Sorbonne Université, Paris, France
| | - Dennis Lal
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and M.I.T, Cambridge, MA, 02142, USA
- Cologne Center for Genomics (CCG), Medical Faculty of the University of Cologne, University Hospital of Cologne, 50931, Cologne, Germany
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK
- Department of Neurology, McGovern Medical School, UTHealth Houston, University of Texas, Houston, USA
| | - Peter Nürnberg
- Cologne Center for Genomics (CCG), Medical Faculty of the University of Cologne, University Hospital of Cologne, 50931, Cologne, Germany
| | - Ingmar Blümcke
- Department of Neuropathology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany.
- Partner of the European Reference Network (ERN) EpiCARE, Barcelona, Spain.
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and M.I.T, Cambridge, MA, 02142, USA.
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18
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Urbach H, Scheiwe C, Shah MJ, Nakagawa JM, Heers M, San Antonio-Arce MV, Altenmueller DM, Schulze-Bonhage A, Huppertz HJ, Demerath T, Doostkam S. Diagnostic Accuracy of Epilepsy-dedicated MRI with Post-processing. Clin Neuroradiol 2023; 33:709-719. [PMID: 36856785 PMCID: PMC10449992 DOI: 10.1007/s00062-023-01265-3] [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: 10/22/2022] [Accepted: 01/17/2023] [Indexed: 03/02/2023]
Abstract
PURPOSE To evaluate the diagnostic accuracy of epilepsy-dedicated 3 Tesla MRI including post-processing by correlating MRI, histopathology, and postsurgical seizure outcomes. METHODS 3 Tesla-MRI including a magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence for post-processing using the morphometric analysis program MAP was acquired in 116 consecutive patients with drug-resistant focal epilepsy undergoing resection surgery. The MRI, histopathology reports and postsurgical seizure outcomes were recorded from the patient's charts. RESULTS The MRI and histopathology were concordant in 101 and discordant in 15 patients, 3 no hippocampal sclerosis/gliosis only lesions were missed on MRI and 1 of 28 focal cortical dysplasia (FCD) type II associated with a glial scar was considered a glial scar only on MRI. In another five patients, MRI was suggestive of FCD, the histopathology was uneventful but patients were seizure-free following surgery. The MRI and histopathology were concordant in 20 of 21 glioneuronal tumors, 6 cavernomas, and 7 glial scars. Histopathology was negative in 10 patients with temporal lobe epilepsy, 4 of them had anteroinferior meningoencephaloceles. Engel class IA outcome was reached in 71% of patients. CONCLUSION The proposed MRI protocol is highly accurate. No hippocampal sclerosis/gliosis only lesions are typically MRI negative. Small MRI positive FCD can be histopathologically missed, most likely due to sampling errors resulting from insufficient harvesting of tissue.
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Affiliation(s)
- Horst Urbach
- Dept. of Neuroradiology, Medical Center, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
| | - Christian Scheiwe
- Dept. of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Muskesh J Shah
- Dept. of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Julia M Nakagawa
- Dept. of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Marcel Heers
- Dept. of Epileptology, Medical Center, University of Freiburg, Freiburg, Germany
| | | | | | | | | | - Theo Demerath
- Dept. of Neuroradiology, Medical Center, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany
| | - Soroush Doostkam
- Dept. of Neuropathology, Medical Center, University of Freiburg, Freiburg, Germany
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19
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Všianský V, Brázdil M, Rektor I, Doležalová I, Kočvarová J, Strýček O, Hemza J, Chrastina J, Brichtová E, Horák O, Mužlayová P, Hermanová M, Hendrych M, Pail M. Twenty-five years of epilepsy surgery at a Central European comprehensive epilepsy center-Trends in intervention delay and outcomes. Epilepsia Open 2023; 8:991-1001. [PMID: 37259787 PMCID: PMC10472383 DOI: 10.1002/epi4.12769] [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: 01/13/2023] [Accepted: 05/26/2023] [Indexed: 06/02/2023] Open
Abstract
OBJECTIVE We analyzed trends in patients' characteristics, outcomes, and waiting times over the last 25 years at our epilepsy surgery center situated in Central Europe to highlight possible areas of improvement in our care for patients with drug-resistant epilepsy. METHODS A total of 704 patients who underwent surgery at the Brno Epilepsy Center were included in the study, 71 of those were children. Patients were separated into three time periods, 1996-2000 (n = 95), 2001-2010 (n = 295) and 2011-2022 (n = 314) based on first evaluation at the center. RESULTS The average duration of epilepsy before surgery in adults remained high over the last 25 years (20.1 years from 1996 to 2000, 21.3 from 2001 to 2010, and 21.3 from 2011 to 2020, P = 0.718). There has been a decrease in rate of surgeries for temporal lobe epilepsy in the most recent time period (67%-70%-52%, P < 0.001). Correspondingly, extratemporal resections have become more frequent with a significant increase in surgeries for focal cortical dysplasia (2%-8%-19%, P < 0.001). For resections, better outcomes (ILAE scores 1a-2) have been achieved in extratemporal lesional (0%-21%-61%, P = 0.01, at least 2-year follow-up) patients. In temporal lesional patients, outcomes remained unchanged (at least 77% success rate). A longer duration of epilepsy predicted a less favorable outcome for resective procedures (P = 0.024) in patients with disease duration of less than 25 years. SIGNIFICANCE The spectrum of epilepsy surgery is shifting toward nonlesional and extratemporal cases. While success rates of extratemporal resections at our center are getting better, the average duration of epilepsy before surgical intervention is still very long and is not improving. This underscores the need for stronger collaboration between epileptologists and outpatient neurologists to ensure prompt and effective treatment for patients with drug-resistant epilepsy.
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Affiliation(s)
- Vít Všianský
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Milan Brázdil
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Ivan Rektor
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Irena Doležalová
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Jitka Kočvarová
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Ondřej Strýček
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Jan Hemza
- Brno Epilepsy Center, Department of Neurosurgery, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Jan Chrastina
- Brno Epilepsy Center, Department of Neurosurgery, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Eva Brichtová
- Brno Epilepsy Center, Department of Neurosurgery, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Ondřej Horák
- Brno Epilepsy Center, Department of Pediatric Neurology, Brno University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Patrícia Mužlayová
- Brno Epilepsy Center, Department of Pediatric Neurology, Brno University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
| | - Markéta Hermanová
- Department of Pathology, St. Anne's University Hospital, Faculty of MedicineMasaryk UniversityBrnoCzech Republic
| | - Michal Hendrych
- Department of Pathology, St. Anne's University Hospital, Faculty of MedicineMasaryk UniversityBrnoCzech Republic
| | - Martin Pail
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of MedicineMasaryk University, Member of the ERN EpiCAREBrnoCzech Republic
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20
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Schuch F, Walger L, Schmitz M, David B, Bauer T, Harms A, Fischbach L, Schulte F, Schidlowski M, Reiter J, Bitzer F, von Wrede R, Rácz A, Baumgartner T, Borger V, Schneider M, Flender A, Becker A, Vatter H, Weber B, Specht-Riemenschneider L, Radbruch A, Surges R, Rüber T. An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II. Sci Data 2023; 10:475. [PMID: 37474522 PMCID: PMC10359264 DOI: 10.1038/s41597-023-02386-7] [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: 11/14/2022] [Accepted: 07/13/2023] [Indexed: 07/22/2023] Open
Abstract
Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.
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Affiliation(s)
- Fabiane Schuch
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Lennart Walger
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Matthias Schmitz
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Bastian David
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Tobias Bauer
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Antonia Harms
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Laura Fischbach
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Freya Schulte
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | | | - Johannes Reiter
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Felix Bitzer
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Atilla Rácz
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | | | - Valeri Borger
- Department of Neurosurgery, University Hospital Bonn, Bonn, Germany
| | | | - Achim Flender
- Medical Faculty, University Hospital Bonn, Bonn, Germany
| | - Albert Becker
- Section of Translational Epilepsy Research, Department of Neuropathology, University Hospital Bonn, Bonn, Germany
| | - Hartmut Vatter
- Department of Neurosurgery, University Hospital Bonn, Bonn, Germany
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | | | | | - Rainer Surges
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Theodor Rüber
- Department of Epileptology, University Hospital Bonn, Bonn, Germany.
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21
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Villaseñor PJ, Cortés-Servín D, Pérez-Moriel A, Aquiles A, Luna-Munguía H, Ramirez-Manzanares A, Coronado-Leija R, Larriva-Sahd J, Concha L. Multi-tensor diffusion abnormalities of gray matter in an animal model of cortical dysplasia. Front Neurol 2023; 14:1124282. [PMID: 37342776 PMCID: PMC10278582 DOI: 10.3389/fneur.2023.1124282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/18/2023] [Indexed: 06/23/2023] Open
Abstract
Focal cortical dysplasias are a type of malformations of cortical development that are a common cause of drug-resistant focal epilepsy. Surgical treatment is a viable option for some of these patients, with their outcome being highly related to complete surgical resection of lesions visible in magnetic resonance imaging (MRI). However, subtle lesions often go undetected on conventional imaging. Several methods to analyze MRI have been proposed, with the common goal of rendering subtle cortical lesions visible. However, most image-processing methods are targeted to detect the macroscopic characteristics of cortical dysplasias, which do not always correspond to the microstructural disarrangement of these cortical malformations. Quantitative analysis of diffusion-weighted MRI (dMRI) enables the inference of tissue characteristics, and novel methods provide valuable microstructural features of complex tissue, including gray matter. We investigated the ability of advanced dMRI descriptors to detect diffusion abnormalities in an animal model of cortical dysplasia. For this purpose, we induced cortical dysplasia in 18 animals that were scanned at 30 postnatal days (along with 19 control animals). We obtained multi-shell dMRI, to which we fitted single and multi-tensor representations. Quantitative dMRI parameters derived from these methods were queried using a curvilinear coordinate system to sample the cortical mantle, providing inter-subject anatomical correspondence. We found region- and layer-specific diffusion abnormalities in experimental animals. Moreover, we were able to distinguish diffusion abnormalities related to altered intra-cortical tangential fibers from those associated with radial cortical fibers. Histological examinations revealed myelo-architectural abnormalities that explain the alterations observed through dMRI. The methods for dMRI acquisition and analysis used here are available in clinical settings and our work shows their clinical relevance to detect subtle cortical dysplasias through analysis of their microstructural properties.
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Affiliation(s)
- Paulina J. Villaseñor
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - David Cortés-Servín
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ana Aquiles
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - Hiram Luna-Munguía
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | | | - Ricardo Coronado-Leija
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Jorge Larriva-Sahd
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
| | - Luis Concha
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, Mexico
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22
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Fearns N, Birk D, Bartkiewicz J, Rémi J, Noachtar S, Vollmar C. Quantitative analysis of the morphometric analysis program MAP in patients with truly MRI-negative focal epilepsy. Epilepsy Res 2023; 192:107133. [PMID: 37001290 DOI: 10.1016/j.eplepsyres.2023.107133] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/21/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023]
Abstract
OBJECTIVE In the presurgical evaluation of epilepsy, identifying the epileptogenic zone is challenging if magnetic resonance imaging (MRI) is negative. Several studies have shown the benefit of using a morphometric analysis program (MAP) on T1-weighted MRI scans to detect subtle lesions. MAP can guide a focused re-evaluation of MRI to ultimately identify structural lesions that were previously overlooked. Data on patients where this additional review after MAP analysis did not reveal any lesions is limited. Here we evaluate the diagnostic yield of MAP in a large group of truly MRI-negative patients. METHODS We identified 68 patients with MRI-negative focal epilepsy and clear localization of the epileptogenic zone by intracranial EEG or postoperative seizure freedom. High resolution 3D T1 data of patients and 73 healthy controls were acquired on a 3 T scanner. Morphometric analysis was performed with MAP software, creating five z-score maps, reflecting different structural properties of the brain and a patient's deviation from the control population, and a neural network-based focal cortical dysplasia probability map. Ten brain regions were specified to quantify whether MAP findings were located in the correct region. Receiver operating characteristic (ROC) analyses were performed to identify the optimal thresholds for each map. RESULTS MAP-guided visual re-evaluation of the original MRI revealed overlooked lesions in three patients. The remaining 65 truly MRI-negative patients were included in the statistical analysis. At the optimal thresholds, maximum sensitivity was 84 %, with 35 % specificity. Balanced accuracy (arithmetic mean of sensitivity and specificity) of the respective maps ranged from 51 % to 60 %, creating three to six times more false positive than true positive findings. CONCLUSION This study confirms that MAP is useful in detecting previously overlooked subtle structural lesions. However, in truly MRI-negative patients, the additional diagnostic yield is very limited.
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23
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Medina-Pizarro M, Spencer DD, Damisah EC. Recent advances in epilepsy surgery. Curr Opin Neurol 2023; 36:95-101. [PMID: 36762633 DOI: 10.1097/wco.0000000000001134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
PURPOSE OF REVIEW Technological innovations in the preoperative evaluation, surgical techniques and outcome prediction in epilepsy surgery have grown exponentially over the last decade. This review highlights and emphasizes relevant updates in techniques and diagnostic tools, discussing their context within standard practice at comprehensive epilepsy centres. RECENT FINDINGS High-resolution structural imaging has set an unprecedented opportunity to detect previously unrecognized subtle abnormalities. Machine learning and computer science are impacting the methodologies to analyse presurgical and surgical outcome data, building more accurate prediction models to tailor treatment strategies. Robotic-assisted placement of depth electrodes has increased the safety and ability to sample epileptogenic nodes within deep structures, improving our understanding of the seizure networks in drug-resistant epilepsy. The current available minimally invasive techniques are reasonable surgical alternatives to ablate or disrupt epileptogenic regions, although their sustained efficacy is still an active area of research. SUMMARY Epilepsy surgery is still underutilized worldwide. Every patient who continues with seizures despite adequate trials of two well selected and tolerated antiseizure medications should be evaluated for surgical candidacy. Collaboration between academic epilepsy centres is of paramount importance to answer long-standing questions in epilepsy surgery regarding the understanding of spatio-temporal dynamics in epileptogenic networks and its impact on surgical outcomes.
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24
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Choi JY, Hu S, Su TY, Murakami H, Tang Y, Blümcke I, Najm I, Sakaie K, Jones S, Griswold M, Wang ZI, Ma D. Normative quantitative relaxation atlases for characterization of cortical regions using magnetic resonance fingerprinting. Cereb Cortex 2023; 33:3562-3574. [PMID: 35945683 PMCID: PMC10068276 DOI: 10.1093/cercor/bhac292] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/04/2022] [Accepted: 07/05/2022] [Indexed: 11/14/2022] Open
Abstract
Quantitative magnetic resonance (MR) has been used to study cyto- and myelo-architecture of the human brain non-invasively. However, analyzing brain cortex using high-resolution quantitative MR acquisition can be challenging to perform using 3T clinical scanners. MR fingerprinting (MRF) is a highly efficient and clinically feasible quantitative MR technique that simultaneously provides T1 and T2 relaxation maps. Using 3D MRF from 40 healthy subjects (mean age = 25.6 ± 4.3 years) scanned on 3T magnetic resonance imaging, we generated whole-brain gyral-based normative MR relaxation atlases and investigated cortical-region-based T1 and T2 variations. Gender and age dependency of T1 and T2 variations were additionally analyzed. The coefficient of variation of T1 and T2 for each cortical-region was 3.5% and 7.3%, respectively, supporting low variability of MRF measurements across subjects. Significant differences in T1 and T2 were identified among 34 brain regions (P < 0.001), lower in the precentral, postcentral, paracentral lobule, transverse temporal, lateral occipital, and cingulate areas, which contain sensorimotor, auditory, visual, and limbic functions. Significant correlations were identified between age and T1 and T2 values. This study established whole-brain MRF T1 and T2 atlases of healthy subjects using a clinical 3T scanner, which can provide a quantitative and region-specific baseline for future brain studies and pathology detection.
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Affiliation(s)
- Joon Yul Choi
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
| | - Siyuan Hu
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States
| | - Ting-Yu Su
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States
| | - Hiroatsu Murakami
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
| | - Yingying Tang
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
- Department of Neurology, West China Hospital of Sichuan University, 37 Guoxue Ln, Wuhou District, Chengdu, Sichuan 610041, China
| | - Ingmar Blümcke
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
- Imaging Institute, Cleveland Clinic, 1950 E 89th St U Bldg, Cleveland, OH 44195, United States
| | - Imad Najm
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
| | - Ken Sakaie
- Department of Neuropathology, University of Erlangen, Schlobplatz 4, Erlangen 91054, Germany
| | - Stephen Jones
- Department of Neuropathology, University of Erlangen, Schlobplatz 4, Erlangen 91054, Germany
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, United States
| | - Zhong Irene Wang
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44106, United States
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States
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25
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Azzony S, Moria K, Alghamdi J. Detecting Cortical Thickness Changes in Epileptogenic Lesions Using Machine Learning. Brain Sci 2023; 13:brainsci13030487. [PMID: 36979297 PMCID: PMC10046408 DOI: 10.3390/brainsci13030487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/25/2023] [Accepted: 03/07/2023] [Indexed: 03/16/2023] Open
Abstract
Epilepsy is a neurological disorder characterized by abnormal brain activity. Epileptic patients suffer from unpredictable seizures, which may cause a loss of awareness. Seizures are considered drug resistant if treatment does not affect success. This leads practitioners to calculate the cortical thickness to measure the distance between the brain’s white and grey matter surfaces at various locations to perform a surgical intervention. In this study, we introduce using machine learning as an approach to classify extracted measurements from T1-weighted magnetic resonance imaging. Data were collected from the epilepsy unit at King Abdulaziz University Hospital. We applied two trials to classify the extracted measurements from T1-weighted MRI for drug-resistant epilepsy and healthy control subjects. The preprocessing sequence on T1-weighted MRI images was performed using C++ through BrainSuite’s pipeline. The first trial was performed on seven different combinations of four commonly selected measurements. The best performance was achieved in Exp6 and Exp7, with 80.00% accuracy, 83.00% recall score, and 83.88% precision. It is noticeable that grey matter volume and white matter volume measurements are more significant than the cortical thickness measurement. The second trial applied four different machine learning classifiers after applying 10-fold cross-validation and principal component analysis on all extracted measurements as in the first trial based on the mentioned previous works. The K-nearest neighbours model outperformed the other machine learning classifiers with 97.11% accuracy, 75.00% recall score, and 75.00% precision.
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Affiliation(s)
- Sumayya Azzony
- Department of Computer Sciences, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Correspondence:
| | - Kawthar Moria
- Department of Computer Sciences, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Jamaan Alghamdi
- Diagnostic Radiology Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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26
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Su TY, Tang Y, Choi JY, Hu S, Sakaie K, Murakami H, Jones S, Blümcke I, Najm I, Ma D, Wang ZI. Evaluating whole-brain tissue-property changes in MRI-negative pharmacoresistant focal epilepsies using MR fingerprinting. Epilepsia 2023; 64:430-442. [PMID: 36507762 PMCID: PMC10107443 DOI: 10.1111/epi.17488] [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: 06/30/2022] [Revised: 12/09/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVE We aim to quantify whole-brain tissue-property changes in patients with magnetic resonance imaging (MRI)-negative pharmacoresistant focal epilepsy by three-dimensional (3D) magnetic resonance fingerprinting (MRF). METHODS We included 30 patients with pharmacoresistant focal epilepsy and negative MRI by official radiology report, as well as 40 age- and gender-matched healthy controls (HCs). MRF scans were obtained with 1 mm3 isotropic resolution. Quantitative T1 and T2 relaxometry maps were reconstructed from MRF and registered to the Montreal Neurological Institute (MNI) space. A two-sample t test was performed in Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) to evaluate significant abnormalities in patients comparing to HCs, with correction by the threshold-free cluster enhancement (TFCE) method. Subgroups analyses were performed for extra-temporal epilepsy/temporal epilepsy (ETLE/TLE), and for those with/without subtle abnormalities detected by morphometric analysis program (MAP), to investigate each subgroup's pattern of MRF changes. Correlation analyses were performed between the mean MRF values in each significant cluster and seizure-related clinical variables. RESULTS Compared to HCs, patients exhibited significant group-level T1 increase ipsilateral to the epileptic origin, in the mesial temporal gray matter (GM) and white matter (WM), temporal pole GM, orbitofrontal GM, hippocampus, and amygdala, with scattered clusters in the neocortical temporal and insular GM. No significant T2 changes were detected. The ETLE subgroup showed a T1-increase pattern similar to the overall cohort, with additional involvement of the ipsilateral anterior cingulate GM. The subgroup of MAP+ patients also showed a T1-increase pattern similar to the overall cohort, with additional cluster in the ipsilateral lateral orbitofrontal GM. Higher T1 was associated with younger seizure-onset age, longer epilepsy duration, and higher seizure frequency. SIGNIFICANCE MRF revealed group-level T1 increase in limbic/paralimbic structures ipsilateral to the epileptic origin, in patients with pharmacoresistant focal epilepsy and no apparent lesions on MRI, suggesting that these regions may be commonly affected by seizures in the epileptic brain. The significant association between T1 increase and higher seizure burden may reflect progressive tissue damage.
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Affiliation(s)
- Ting-Yu Su
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yingying Tang
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Joon Yul Choi
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Siyuan Hu
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Ken Sakaie
- Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | | | - Stephen Jones
- Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ingmar Blümcke
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Neuropathology, University of Erlangen, Erlangen, Germany
| | - Imad Najm
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Dan Ma
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
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27
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Son H, Park KI, Shin DS, Moon J, Lee ST, Jung KH, Jung KY, Chu K, Lee SK. Lesion Detection Through MRI Postprocessing in Pathology-Proven Focal Cortical Dysplasia: Experience at a Single Institution in the Republic of Korea. J Clin Neurol 2023; 19:288-295. [PMID: 37151142 PMCID: PMC10169920 DOI: 10.3988/jcn.2022.0317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/01/2022] [Accepted: 10/07/2022] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND AND PURPOSE Focal cortical dysplasia (FCD) is one of the most common causes of drug-resistant epilepsy, and necessitates a multimodal evaluation to ensure optimal surgical treatment. This study aimed to determine the supportive value of the morphometric analysis program (MAP) in detecting FCD using data from a single institution in Korea. METHODS To develop a standard reference for the MAP, normal-looking MRIs by two scanners that are frequently used in this center were chosen. Patients with drug-resistant epilepsy and FCD after surgery were candidates for the analysis. The three-dimensional T1-weighted MRI scans of the patients were analyzed as test cases using the MAP. RESULTS The MRI scans of 87 patients were included in the analysis. The radiologist detected abnormal findings correlated with FCD (RAD positive [RAD(+)]) in 34 cases (39.1%), while the MAP could detect FCD in 25.3% of cases. A combination of the MAP (MAP[+] cases) with interpretations by the radiologist increased the detection to 42.5% (37 cases). The lesion detection rate was not different according to the type of reference scanners except in one case. MAP(+)/RAD(-) presented in three cases, all of which had FCD type IIa. The detection rate was slightly higher using the same kind of scanner as a reference, but not significantly (35.0% vs. 22.4% p=0.26). CONCLUSIONS The results of postprocessing in the MAP for detecting FCD did not depend on the type of reference scanner, and the MAP was the strongest in detecting FCD IIa. We suggested that the MAP could be widely utilized without developing institutional standards and could become an effective tool for detecting FCD lesions.
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Affiliation(s)
- Hyoshin Son
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
| | - Kyung-Il Park
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
- Department of Neurology, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea
| | - Dae-Seop Shin
- Department of Neurology, Soonchunhyang University Hospital, Gumi, Korea
| | - Jangsup Moon
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Korea
| | - Soon-Tae Lee
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
| | - Keun-Hwa Jung
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
| | - Ki-Young Jung
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
| | - Kon Chu
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
| | - Sang Kun Lee
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
- Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
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28
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Spitzer H, Ripart M, Whitaker K, D’Arco F, Mankad K, Chen AA, Napolitano A, De Palma L, De Benedictis A, Foldes S, Humphreys Z, Zhang K, Hu W, Mo J, Likeman M, Davies S, Güttler C, Lenge M, Cohen NT, Tang Y, Wang S, Chari A, Tisdall M, Bargallo N, Conde-Blanco E, Pariente JC, Pascual-Diaz S, Delgado-Martínez I, Pérez-Enríquez C, Lagorio I, Abela E, Mullatti N, O’Muircheartaigh J, Vecchiato K, Liu Y, Caligiuri ME, Sinclair B, Vivash L, Willard A, Kandasamy J, McLellan A, Sokol D, Semmelroch M, Kloster AG, Opheim G, Ribeiro L, Yasuda C, Rossi-Espagnet C, Hamandi K, Tietze A, Barba C, Guerrini R, Gaillard WD, You X, Wang I, González-Ortiz S, Severino M, Striano P, Tortora D, Kälviäinen R, Gambardella A, Labate A, Desmond P, Lui E, O’Brien T, Shetty J, Jackson G, Duncan JS, Winston GP, Pinborg LH, Cendes F, Theis FJ, Shinohara RT, Cross JH, Baldeweg T, Adler S, Wagstyl K. Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study. Brain 2022; 145:3859-3871. [PMID: 35953082 PMCID: PMC9679165 DOI: 10.1093/brain/awac224] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 04/22/2022] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
Abstract
One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.
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Affiliation(s)
- Hannah Spitzer
- Institute of Computational Biology, Helmholtz Center Munich, Munich 85764, Germany
| | - Mathilde Ripart
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
| | | | - Felice D’Arco
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Kshitij Mankad
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Andrew A Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children’s Hospital, Rome 00165, Italy
| | - Luca De Palma
- Rare and Complex Epilepsies, Department of Neurosciences, Bambino Gesù Children’s Hospital, IRCCS, Rome 00165, Italy
| | - Alessandro De Benedictis
- Neurosurgery Unit, Department of Neurosciences, Bambino Gesù Children’s Hospital, IRCCS, Rome 00165, Italy
| | - Stephen Foldes
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Zachary Humphreys
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100054, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100054, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100054, China
| | - Marcus Likeman
- Bristol Royal Hospital for Children, Bristol BS2 8BJ, UK
| | - Shirin Davies
- School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff CF24 4HQ, UK
- The Welsh Epilepsy Unit, Cardiff and Vale University Health Board, University Hospital of Wales, Cardiff CF14 4XW, UK
| | | | - Matteo Lenge
- Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence 50139, Italy
| | - Nathan T Cohen
- Center for Neuroscience, Children’s National Hospital, Washington, DC 20012, USA
| | - Yingying Tang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu 610093, China
- Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Shan Wang
- Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Aswin Chari
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Martin Tisdall
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Nuria Bargallo
- Department of Neuroradiology, Hospital Clinic Barcelona and Magnetic Resonance Imaging, Core Facility, IDIBAPS, Barcelona 08036, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid 28029, Spain
| | | | | | - Saül Pascual-Diaz
- Magnetic Resonance Imaging, Core Facility, IDIBAPS, Barcelona 08036, Spain
| | | | | | | | - Eugenio Abela
- Center for Neuropsychiatry and Intellectual Disability, Psychiatrische Dienste Aargau AG, Windisch 5120, Switzerland
| | - Nandini Mullatti
- Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
| | - Jonathan O’Muircheartaigh
- Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
- Department of Perinatal Imaging and Health, St. Thomas’ Hospital, King’s College London, London SE1 7EH, UK
| | - Katy Vecchiato
- Department of Perinatal Imaging and Health, St. Thomas’ Hospital, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE5 8AF, UK
| | - Yawu Liu
- Department of Neurology, University of Eastern Finland, Kuopio 70210, Finland
| | - Maria Eugenia Caligiuri
- Department of Medical and Surgical Sciences, Magna Graecia University of Catanzaro, Catanzaro 88100, Italy
| | - Ben Sinclair
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
- Department of Neurology, Monash University, Melbourne, VIC 3004, Australia
| | - Anna Willard
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
| | - Jothy Kandasamy
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Ailsa McLellan
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Drahoslav Sokol
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Mira Semmelroch
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC 3052, Australia
| | - Ane G Kloster
- Neurobiology Research Unit, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
| | - Giske Opheim
- Neurobiology Research Unit, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
- Department of Neuroradiology, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
| | - Letícia Ribeiro
- Department of Neurology, University of Campinas, Campinas 13083-888, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas 13083-888, Brazil
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas, Campinas 13083-888, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas 13083-888, Brazil
| | | | - Khalid Hamandi
- School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff CF24 4HQ, UK
- The Welsh Epilepsy Unit, University Hospital of Wales, Cardiff CF14 4XW, UK
| | - Anna Tietze
- Charité University Hospital, Berlin 10117, Germany
| | - Carmen Barba
- Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence 50139, Italy
| | - Renzo Guerrini
- Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence 50139, Italy
| | | | - Xiaozhen You
- Center for Neuroscience, Children’s National Hospital, Washington, DC 20012, USA
| | - Irene Wang
- Epilepsy Center, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Sofía González-Ortiz
- Department of Neuroradiology, Hospital del Mar, Barcelona 08003, Spain
- Magnetic Resonance Imaging Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
| | | | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova 16147, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | | | - Reetta Kälviäinen
- Department of Neurology, University of Eastern Finland, Kuopio 70210, Finland
- Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Kuopio 70210, Finland
| | - Antonio Gambardella
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro 88100, Italy
| | - Angelo Labate
- Neurology Unit, Department of BIOMORF, University of Messina, Messina 98168, Italy
| | - Patricia Desmond
- Department of Radiology, The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC 3050, Australia
| | - Elaine Lui
- Department of Radiology, The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC 3050, Australia
| | - Terence O’Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC 3004, Australia
- Department of Medicine, The Royal Melbourne Hospital, Parkville, VIC, 3052, Australia
| | - Jay Shetty
- Royal Hospital for Children and Young People, Edinburgh EH16 4TJ, UK
| | - Graeme Jackson
- The Florey Institute of Neuroscience and Mental Health, Austin Campus, Heidelberg, VIC 3071, Australia
- Department of Neurology, Austin Health, Heidelberg, VIC 3084, Australia
| | - John S Duncan
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Gavin P Winston
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, ON, Canada K7L 3N6
| | - Lars H Pinborg
- Neurobiology Research Unit, Copenhagen University Hospital—Rigshospitalet, Copenhagen 2100, Denmark
- Epilepsy Clinic, Department of Neurology, Copenhagen University Hospital—Rigshopsitalet, Copenhagen 2100, Denmark
| | - Fernando Cendes
- Department of Neurology, University of Campinas, Campinas 13083-888, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas 13083-888, Brazil
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Center Munich, Munich 85764, Germany
- Department of Mathematics, Technical University of Munich, Garching 85748, Germany
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - J Helen Cross
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Young Epilepsy, Lingfield, Surrey RH7 6PW, UK
| | - Torsten Baldeweg
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, UK
| | - Sophie Adler
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
| | - Konrad Wagstyl
- Department of Developmental Neuroscience, UCL Great Ormond Street Institute for Child Health, London WC1N 1EH, UK
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
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29
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Hu WH, Mo JJ, Yang BW, Liu HG, Zhang C, Wang X, Qiu JJ, Zhao BT, Shao XQ, Zhang JG, Zhang K. Voxel-Based Morphometric MRI Postprocessing-Assisted Laser Interstitial Thermal Therapy for Focal Cortical Dysplasia-Suspected Lesions: Technique and Outcomes. Oper Neurosurg (Hagerstown) 2022; 23:334-341. [PMID: 36001745 DOI: 10.1227/ons.0000000000000328] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 04/25/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND MRI-guided laser interstitial thermal therapy (MRgLITT) is a novel treatment modality for focal cortical dysplasia (FCD). However, identifying the location and extent of subtle FCD by visual analysis during MRgLITT remains challenging. OBJECTIVE To introduce voxel-based morphometric MRI postprocessing into the procedure of MRgLITT for FCD-suspected lesions and assess the complementary value of the MRI postprocessing technique for the trajectory design and thermal parameter setting of MRgLITT. METHODS Junction and normalized fluid-attenuated inversion recovery signal intensity images were used to detect the gray-white matter junction blurring and cortical fluid-attenuated inversion recovery hyperintensity, respectively. According to the 2 postprocessing images, the region of interest (ROI) for ablation was drawn. The main principle of presurgical planning is that the trajectory of the laser fiber was designed as far as possible along the long axis of the ROI while the extent of planned ablation covered the entire ROI. The subsequent intraoperative procedure was performed under the guidance of the presurgical plan. RESULTS Nine patients with epilepsy with FCD-suspected lesions underwent MRgLITT with the assistance of MRI postprocessing images. Among them, 4 patients were junction positive, 2 patients were normalized fluid-attenuated inversion recovery signal intensity positive, and the remaining 3 patients were positive for both. Postsurgical MRI demonstrated that the ROIs were ablated entirely in 7 patients. Engel Ia, Ib, and IV scores were obtained at 1-year follow-up for 6, 1, and 2 patients, respectively. CONCLUSION MRI postprocessing provides complementary information for designing the laser fiber trajectory and subsequent ablation for FCDs.
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Affiliation(s)
- Wen-Han Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jia-Jie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bo-Wen Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huan-Guang Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jia-Ji Qiu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bao-Tian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiao-Qiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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30
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Říha P, Doležalová I, Mareček R, Lamoš M, Bartoňová M, Kojan M, Mikl M, Gajdoš M, Vojtíšek L, Bartoň M, Strýček O, Pail M, Brázdil M, Rektor I. Multimodal combination of neuroimaging methods for localizing the epileptogenic zone in MR-negative epilepsy. Sci Rep 2022; 12:15158. [PMID: 36071087 PMCID: PMC9452535 DOI: 10.1038/s41598-022-19121-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 08/24/2022] [Indexed: 11/10/2022] Open
Abstract
The objective was to determine the optimal combination of multimodal imaging methods (IMs) for localizing the epileptogenic zone (EZ) in patients with MR-negative drug-resistant epilepsy. Data from 25 patients with MR-negative focal epilepsy (age 30 ± 10 years, 16M/9F) who underwent surgical resection of the EZ and from 110 healthy controls (age 31 ± 9 years; 56M/54F) were used to evaluate IMs based on 3T MRI, FDG-PET, HD-EEG, and SPECT. Patients with successful outcomes and/or positive histological findings were evaluated. From 38 IMs calculated per patient, 13 methods were selected by evaluating the mutual similarity of the methods and the accuracy of the EZ localization. The best results in postsurgical patients for EZ localization were found for ictal/ interictal SPECT (SISCOM), FDG-PET, arterial spin labeling (ASL), functional regional homogeneity (ReHo), gray matter volume (GMV), cortical thickness, HD electrical source imaging (ESI-HD), amplitude of low-frequency fluctuation (ALFF), diffusion tensor imaging, and kurtosis imaging. Combining IMs provides the method with the most accurate EZ identification in MR-negative epilepsy. The PET, SISCOM, and selected MRI-post-processing techniques are useful for EZ localization for surgical tailoring.
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Affiliation(s)
- Pavel Říha
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Irena Doležalová
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Radek Mareček
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Lamoš
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Michaela Bartoňová
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Kojan
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Michal Mikl
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Gajdoš
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Lubomír Vojtíšek
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Marek Bartoň
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ondřej Strýček
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Martin Pail
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Milan Brázdil
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic. .,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
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Tang Y, Blümcke I, Su TY, Choi JY, Krishnan B, Murakami H, Alexopoulos AV, Najm IM, Jones SE, Wang ZI. Black Line Sign in Focal Cortical Dysplasia IIB: A 7T MRI and Electroclinicopathologic Study. Neurology 2022; 99:e616-e626. [PMID: 35940890 PMCID: PMC9442623 DOI: 10.1212/wnl.0000000000200702] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 03/23/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES We aim to provide detailed imaging-electroclinicopathologic characterization of the black line sign, a novel MRI marker for focal cortical dysplasia (FCD) IIB. METHODS 7T T2*-weighted gradient-echo (T2*w-GRE) images were retrospectively reviewed in a consecutive cohort of patients with medically intractable epilepsy with pathology-proven FCD II, for the occurrence of the black line sign. We examined the overlap between the black line region and the seizure-onset zone (SOZ) defined by intracranial EEG (ICEEG) and additionally assessed whether complete inclusion of the black line region in the surgical resection was associated with postoperative seizure freedom. The histopathologic specimen was aligned with the MRI to investigate the pathologic underpinning of the black line sign. Region-of-interest-based quantitative MRI (qMRI) analysis on the 7T T1 map was performed in the black line region, entire lesional gray matter (GM), and contralateral/ipsilateral normal gray and white matter (WM). RESULTS We included 20 patients with FCD II (14 IIB and 6 IIA). The black line sign was identified in 12/14 (85.7%) of FCD IIB and 0/6 of FCD IIA on 7T T2*w-GRE. The black line region was highly concordant with the ICEEG-defined SOZ (5/7 complete and 2/7 partial overlap). Seizure freedom was seen in 8/8 patients whose black line region was completely included in the surgical resection; in the 2 patients whose resection did not completely include the black line region, both had recurring seizures. Inclusion of the black line region in the surgical resection was significantly associated with seizure freedom (p = 0.02). QMRI analyses showed that the T1 mean value of the black line region was significantly different from the WM (p < 0.001), but similar to the GM. Well-matched histopathologic slices in one case revealed accumulated dysmorphic neurons and balloon cells in the black line region. DISCUSSION The black line sign may serve as a noninvasive marker for FCD IIB. Both MRI-pathology and qMRI analyses suggest that the black line region was an abnormal GM component within the FCD. Being highly concordant with ICEEG-defined SOZ and significantly associated with seizure freedom when included in resection, the black line sign may contribute to the planning of ICEEG/surgery of patients with medically intractable epilepsy with FCD IIB. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in individuals with intractable focal epilepsy undergoing resection who have a 7T MRI with adequate image quality, the presence of the black line sign may suggest FCD IIB, be concordant with SOZ from ICEEG, and be associated with more seizure freedom if fully included in resection.
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Affiliation(s)
- Yingying Tang
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Ingmar Blümcke
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Ting-Yu Su
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Joon Yul Choi
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Balu Krishnan
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Hiroatsu Murakami
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Andreas V Alexopoulos
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Imad M Najm
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Stephen E Jones
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Zhong Irene Wang
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH.
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Urbach H, Kellner E, Kremers N, Blümcke I, Demerath T. MRI of focal cortical dysplasia. Neuroradiology 2022; 64:443-452. [PMID: 34839379 PMCID: PMC8850246 DOI: 10.1007/s00234-021-02865-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 11/17/2021] [Indexed: 11/09/2022]
Abstract
Focal cortical dysplasia (FCD) are histopathologically categorized in ILAE type I to III. Mild malformations of cortical development (mMCD) including those with oligodendroglial hyperplasia (MOGHE) are to be integrated into this classification yet. Only FCD type II have distinctive MRI and molecular genetics alterations so far. Subtle FCD including FCD type II located in the depth of a sulcus are often overlooked requiring the use of dedicated sequences (MP2RAGE, FLAWS, EDGE) and/or voxel (VBM)- or surface-based (SBM) postprocessing. The added value of 7 Tesla MRI has to be proven yet.
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Affiliation(s)
- Horst Urbach
- Dept. of Neuroradiology, Medical Center - University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
| | - Elias Kellner
- Dept. of Medical Physics, Medical Center - University of Freiburg, Freiburg, Germany
| | - Nico Kremers
- Dept. of Neuroradiology, Medical Center - University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany
| | - Ingmar Blümcke
- Dept. of Neuropathology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Theo Demerath
- Dept. of Neuroradiology, Medical Center - University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany
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Rodriguez-Cruces R, Royer J, Larivière S, Bassett DS, Caciagli L, Bernhardt BC. Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies. Netw Neurosci 2022; 6:320-338. [PMID: 35733426 PMCID: PMC9208009 DOI: 10.1162/netn_a_00237] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/02/2022] [Indexed: 11/05/2022] Open
Abstract
Epilepsy is one of the most common chronic neurological conditions, traditionally defined as a disorder of recurrent seizures. Cognitive and affective dysfunction are increasingly recognized as core disease dimensions and can affect patient well-being, sometimes more than the seizures themselves. Connectome-based approaches hold immense promise for revealing mechanisms that contribute to dysfunction and to identify biomarkers. Our review discusses emerging multimodal neuroimaging and connectomics studies that highlight network substrates of cognitive/affective dysfunction in the common epilepsies. We first discuss work in drug-resistant epilepsy syndromes, that is, temporal lobe epilepsy, related to mesiotemporal sclerosis (TLE), and extratemporal epilepsy (ETE), related to malformations of cortical development. While these are traditionally conceptualized as ‘focal’ epilepsies, many patients present with broad structural and functional anomalies. Moreover, the extent of distributed changes contributes to difficulties in multiple cognitive domains as well as affective-behavioral challenges. We also review work in idiopathic generalized epilepsy (IGE), a subset of generalized epilepsy syndromes that involve subcortico-cortical circuits. Overall, neuroimaging and network neuroscience studies point to both shared and syndrome-specific connectome signatures of dysfunction across TLE, ETE, and IGE. Lastly, we point to current gaps in the literature and formulate recommendations for future research. Epilepsy is increasingly recognized as a network disorder characterized by recurrent seizures as well as broad-ranging cognitive difficulties and affective dysfunction. Our manuscript reviews recent literature highlighting brain network substrates of cognitive and affective dysfunction in common epilepsy syndromes, namely temporal lobe epilepsy secondary to mesiotemporal sclerosis, extratemporal epilepsy secondary to malformations of cortical development, and idiopathic generalized epilepsy syndromes arising from subcortico-cortical pathophysiology. We discuss prior work that has indicated both shared and distinct brain network signatures of cognitive and affective dysfunction across the epilepsy spectrum, improves our knowledge of structure-function links and interindividual heterogeneity, and ultimately aids screening and monitoring of therapeutic strategies.
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Affiliation(s)
- Raul Rodriguez-Cruces
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Sara Larivière
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Dani S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania 19104 USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104 USA
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania 19104 USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, United Kingdom
| | - Boris C. Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Kong Y, Cheng N, Dang N, Hu XB, Zhang GQ, Dong YW, Wang X, Gao JY. Application of combined multimodal neuroimaging and video-electroencephalography in intractable epilepsy patients for improved post-surgical outcome prediction. Clin Radiol 2022; 77:e250-e259. [PMID: 35000762 DOI: 10.1016/j.crad.2021.12.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/02/2021] [Indexed: 11/25/2022]
Abstract
AIM To investigate the ability of a multidisciplinary approach that combines multimodal neuroimaging with video-electroencephalography (v-EEG) to predict post-surgical outcomes in patients with intractable epilepsy, and explore prognostic predictors for these patients. MATERIALS AND METHODS Fifty-eight patients with intractable epilepsy who underwent surgery between March 2016 and October 2019 were reviewed retrospectively. Demographic, clinical, v-EEG, neuroimaging, surgical, and regular follow-up seizure outcome data were collected. Forty-six patients with a follow-up of at least 12 months were graded by Engel scores. Univariate and multivariate analyses were applied to explore prognostic factors that could predict post-surgical seizure outcomes. RESULTS Of the 58 patients, 28 were males. The median age was 27 years, the median age at first seizure was 11 years, and the median duration of seizures was 10 years. The Kaplan-Meier log-rank test showed that regardless of whether the follow-up duration was considered, epilepsy type, v-EEG, PET/CT, image post-processing methods, and a multidisciplinary approach that combined multimodal imaging with v-EEG were all correlated with seizure outcomes. Multivariate analysis found that the multidisciplinary approach was an independent predictor of post-surgical outcomes in patients with intractable epilepsy (hazard ratio = 11.400, 95% confidence interval = 2.249-57.787, p=0.003). CONCLUSIONS The present study showed that the multidisciplinary approach could provide independent prognostic information for patients with intractable epilepsy undergoing surgery. This approach has strong potential for the easier selection of patients to undergo surgical treatment and accurate prognostication.
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Affiliation(s)
- Y Kong
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.
| | - N Cheng
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - N Dang
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - X-B Hu
- MRI Unit of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - G-Q Zhang
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - Y-W Dong
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - X Wang
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - J-Y Gao
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
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van Lanen RHGJ, Wiggins CJ, Colon AJ, Backes WH, Jansen JFA, Uher D, Drenthen GS, Roebroeck A, Ivanov D, Poser BA, Hoeberigs MC, van Kuijk SMJ, Hoogland G, Rijkers K, Wagner GL, Beckervordersandforth J, Delev D, Clusmann H, Wolking S, Klinkenberg S, Rouhl RPW, Hofman PAM, Schijns OEMG. Value of ultra-high field MRI in patients with suspected focal epilepsy and negative 3 T MRI (EpiUltraStudy): protocol for a prospective, longitudinal therapeutic study. Neuroradiology 2022; 64:753-764. [PMID: 34984522 PMCID: PMC8907090 DOI: 10.1007/s00234-021-02884-8] [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: 09/28/2021] [Accepted: 12/09/2021] [Indexed: 10/30/2022]
Abstract
PURPOSE Resective epilepsy surgery is a well-established, evidence-based treatment option in patients with drug-resistant focal epilepsy. A major predictive factor of good surgical outcome is visualization and delineation of a potential epileptogenic lesion by MRI. However, frequently, these lesions are subtle and may escape detection by conventional MRI (≤ 3 T). METHODS We present the EpiUltraStudy protocol to address the hypothesis that application of ultra-high field (UHF) MRI increases the rate of detection of structural lesions and functional brain aberrances in patients with drug-resistant focal epilepsy who are candidates for resective epilepsy surgery. Additionally, therapeutic gain will be addressed, testing whether increased lesion detection and tailored resections result in higher rates of seizure freedom 1 year after epilepsy surgery. Sixty patients enroll the study according to the following inclusion criteria: aged ≥ 12 years, diagnosed with drug-resistant focal epilepsy with a suspected epileptogenic focus, negative conventional 3 T MRI during pre-surgical work-up. RESULTS All patients will be evaluated by 7 T MRI; ten patients will undergo an additional 9.4 T MRI exam. Images will be evaluated independently by two neuroradiologists and a neurologist or neurosurgeon. Clinical and UHF MRI will be discussed in the multidisciplinary epilepsy surgery conference. Demographic and epilepsy characteristics, along with postoperative seizure outcome and histopathological evaluation, will be recorded. CONCLUSION This protocol was reviewed and approved by the local Institutional Review Board and complies with the Declaration of Helsinki and principles of Good Clinical Practice. Results will be submitted to international peer-reviewed journals and presented at international conferences. TRIAL REGISTRATION NUMBER www.trialregister.nl : NTR7536.
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Affiliation(s)
- R H G J van Lanen
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, the Netherlands. .,School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.
| | - C J Wiggins
- Scannexus, Ultra-High Field MRI Research Center, Maastricht, the Netherlands
| | - A J Colon
- Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands
| | - W H Backes
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - J F A Jansen
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - D Uher
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - G S Drenthen
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - A Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - D Ivanov
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - B A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - M C Hoeberigs
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - S M J van Kuijk
- Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, the Netherlands
| | - G Hoogland
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands
| | - K Rijkers
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands
| | - G L Wagner
- Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands
| | | | - D Delev
- Department of Neurosurgery, RWTH Aachen University Hospital, Aachen, Germany
| | - H Clusmann
- Department of Neurosurgery, RWTH Aachen University Hospital, Aachen, Germany
| | - S Wolking
- Department of Epileptology and Neurology, RWTH Aachen University Hospital, Aachen, Germany
| | - S Klinkenberg
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - R P W Rouhl
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - P A M Hofman
- Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - O E M G Schijns
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, the Netherlands.,School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.,Academic Centre for Epileptology, Kempenhaeghe/Maastricht University Medical Center, Heeze/Maastricht, the Netherlands
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Evidence of graphomotor dysfunction in children with dyslexia A combined behavioural and fMRI experiment. Cortex 2022; 148:68-88. [DOI: 10.1016/j.cortex.2021.11.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 08/19/2021] [Accepted: 11/26/2021] [Indexed: 01/02/2023]
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Guo K, Wang J, Wang Z, Wang Y, Cui B, Zhao G, Lu J. Morphometric analysis program and quantitative positron emission tomography in presurgical localization in MRI-negative epilepsies: a simultaneous PET/MRI study. Eur J Nucl Med Mol Imaging 2021; 49:1930-1938. [PMID: 34939175 DOI: 10.1007/s00259-021-05657-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 12/12/2021] [Indexed: 01/21/2023]
Abstract
PURPOSE To evaluate morphometric analysis program (MAP) and quantitative positron emission tomography (QPET) in epileptogenic zone (EZ) identification using a simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) system in MRI-negative epilepsies. METHODS Seventy-one localization-related MRI-negative epilepsies who underwent preoperative simultaneous PET/MRI examination and surgical resection were enrolled retrospectively. MAP was performed on a T1-weighted volumetric sequence, and QPET was analyzed using statistical parametric mapping (SPM) with comparison to age- and gender-matched normal controls. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MAP, QPET, MAP + QPET, and MAP/QPET in EZ localization were assessed. The correlations between surgical outcome and modalities concordant with cortical resection were analyzed. RESULTS Forty-five (63.4%) patients had Engel I seizure outcomes. The sensitivity, specificity, PPV, and NPV of MAP were 64.4%, 69.2%, 78.3%, and 52.9%, respectively. The sensitivity, specificity, PPV, NPV of QPET were 73.3%, 65.4%, 78.6%, and 58.6%, respectively. MAP + QPET, defined as two tests concordant with cortical resection, had reduced sensitivity (53.3%) but increased specificity (88.5%) relative to individual tests. MAP/QPET, defined as one or both tests concordant with cortical resection, had increased sensitivity (86.7%) but reduced specificity (46.2%) relative to individual tests. The regions determined by MAP, QPET, MAP + QPET, or MAP/QPET concordant with cortical resection were significantly associated with the seizure-free outcome. CONCLUSION QPET has a superior sensitivity than MAP, while the combined MAP + QPET obtained from a simultaneous PET/MRI scanner may improve the specificity of the diagnostic tests in EZ localization coupled with the preferable surgical outcome in MRI-negative epilepsies.
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Affiliation(s)
- Kun Guo
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Jingjuan Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Zhenming Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Yihe Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing, 100053, China. .,Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.
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Demerath T, Kaller CP, Heers M, Staack A, Schwarzwald R, Kober T, Reisert M, Schulze-Bonhage A, Huppertz HJ, Urbach H. Fully automated detection of focal cortical dysplasia: Comparison of MPRAGE and MP2RAGE sequences. Epilepsia 2021; 63:75-85. [PMID: 34800337 DOI: 10.1111/epi.17127] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 11/05/2021] [Accepted: 11/05/2021] [Indexed: 12/01/2022]
Abstract
OBJECTIVE The detection of focal cortical dysplasia (FCD) in magnetic resonance imaging is challenging. Voxel-based morphometric analysis and automated FCD detection using an artificial neural network (ANN) integrated into the Morphometric Analysis Program (MAP18) have been shown to facilitate FCD detection. This study aimed to evaluate whether the detection of FCD can be further improved by feeding this approach with magnetization prepared two rapid acquisition gradient echoes (MP2RAGE) instead of magnetization-prepared rapid acquisition gradient echo (MPRAGE) datasets. METHODS MPRAGE and MP2RAGE datasets were acquired in a consecutive sample of 32 patients with FCD and postprocessed using MAP18. Visual analysis and, if available, histopathology served as the gold standard for assessing the sensitivity and specificity of FCD detection. Out-of-sample specificity was evaluated in a cohort of 32 healthy controls. RESULTS The sensitivity and specificity of FCD detection were 82.4% and 62.5% for the MPRAGE and 97.1% and 34.4% for the MP2RAGE sequences, respectively. Median volumes of true-positive voxel clusters were .16 ml for the MPRAGE and .52 ml for the MP2RAGE sequences compared to .08- and .04-ml volumes of false-positive clusters. With regard to cluster volumes, FCD detection was substantially improved for the MP2RAGE data when the estimated optimal threshold of .23 ml was applied (sensitivity = 72.9%, specificity = 83.0%). In contrast, the estimated optimal threshold of .37 ml for the MPRAGE data did not improve FCD lesion detection (sensitivity = 42.9%, specificity = 79.5%). SIGNIFICANCE In this study, the sensitivity of FCD detection by morphometric analysis and an ANN integrated into MAP18 was higher for MP2RAGE than for MPRAGE sequences. Additional usage of cluster volume information helped to discriminate between true- and false-positive MP2RAGE results.
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Affiliation(s)
- Theo Demerath
- Department of Neuroradiology, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Christoph P Kaller
- Department of Neuroradiology, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Marcel Heers
- Epilepsy Center, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | | | - Ralf Schwarzwald
- Department of Neuroradiology, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
| | - Marco Reisert
- Department of Medical Physics, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
| | | | - Horst Urbach
- Department of Neuroradiology, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany
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Holthausen H, Coras R, Tang Y, Bai L, Wang I, Pieper T, Kudernatsch M, Hartlieb T, Staudt M, Winkler P, Hofer W, Jabari S, Kobow K, Blumcke I. Multilobar unilateral hypoplasia with emphasis on the posterior quadrant and severe epilepsy in children with FCD ILAE Type 1A. Epilepsia 2021; 63:42-60. [PMID: 34741301 DOI: 10.1111/epi.17114] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 10/08/2021] [Accepted: 10/18/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVE Focal cortical dysplasia (FCD) Type 1 and its three subtypes have yet not been fully characterized at the clinical, anatomopathological, and molecular level (International League Against Epilepsy [ILAE] FCD classification from 2011). We aimed to describe the clinical phenotype of patients with histopathologically confirmed FCD1A obtained from a single epilepsy center between 2002 and 2016. METHODS Medical records were retrieved from the hospital's archive. Results from electroencephalography (EEG) video recordings, neuroimaging, and histopathology were reevaluated. Magnetic resonance imaging (MRI) post-processing was retrospectively performed in nine patients. DNA methylation studies were carried out from archival surgical brain tissue in 11 patients. RESULTS Nineteen children with a histopathological diagnosis of FCD1A were included. The average onset of epilepsy was 0.9 years (range 0.2-10 years). All children had severe cognitive impairment and one third had mild motor deficits, yet fine finger movements were preserved in all patients. All patients had daily seizures, being drug resistant from disease onset. Interictal electroencephalography revealed bilateral multi-regional epileptiform discharges. Interictal status epilepticus was observed in 8 and countless subclinical seizures in 11 patients. Regional continuous irregular slow waves were of higher lateralizing and localizing yield than spikes. Posterior background rhythms were normal in 16 of 19 children. Neuroimaging showed unilateral multilobar hypoplasia and increased T2-FLAIR signals of the white matter in 18 of 19 patients. All children underwent tailored multilobar resections, with seizure freedom achieved in 47% (Engel class I). There was no case with frontal involvement without involvement of the posterior quadrant by MRI and histopathology. DNA methylation profiling distinguished FCD1A samples from all other epilepsy specimens and controls. SIGNIFICANCE We identified a cohort of young children with drug resistance from seizure onset, bad EEG with posterior emphasis, lack of any focal neurological deficits but severe cognitive impairment, subtle hypoplasia of the epileptogenic area on MRI, and histopathologically defined and molecularly confirmed by DNA methylation analysis as FCD ILAE Type 1A.
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Affiliation(s)
- Hans Holthausen
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
| | - Roland Coras
- Department of Neuropathology, University Hospitals Erlangen, Erlangen, Germany
| | - Yingying Tang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Lily Bai
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Irene Wang
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Tom Pieper
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
| | - Manfred Kudernatsch
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany.,Paracelsus Private Medical University, Salzburg, Austria
| | - Till Hartlieb
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany.,Paracelsus Private Medical University, Salzburg, Austria
| | - Martin Staudt
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
| | - Peter Winkler
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
| | - Wiebke Hofer
- Center for Pediatric Neurology, Neurorehabilitation, and Epileptology, Schoen-Clinic, Vogtareuth, Germany
| | - Samir Jabari
- Department of Neuropathology, University Hospitals Erlangen, Erlangen, Germany
| | - Katja Kobow
- Department of Neuropathology, University Hospitals Erlangen, Erlangen, Germany
| | - Ingmar Blumcke
- Department of Neuropathology, University Hospitals Erlangen, Erlangen, Germany.,Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
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Abstract
PURPOSE To evaluate a MRI postprocessing tool for the enhanced and rapid detection of focal cortical dysplasia (FCD). METHODS MP2RAGE sequences of 40 consecutive, so far MRI-negative patients and of 32 healthy controls were morphometrically analyzed to highlight typical FCD features. The resulting morphometric maps served as input for an artificial neural network generating a FCD probability map. The FCD probability map was inversely normalized, co-registered to the MPRAGE2 sequence, and re-transferred into the PACS system. Co-registered images were scrolled through "within a minute" to determine whether a FCD was present or not. RESULTS Fifteen FCD, three subcortical band heterotopias (SBH), and one periventricular nodular heterotopia were identified. Of those, four FCD and one SBH were only detected by MRI postprocessing while one FCD and one focal polymicrogryia were missed, respectively. False-positive results occurred in 21 patients and 22 healthy controls. However, true positive cluster volumes were significantly larger than volumes of false-positive clusters (p < 0.001). The area under the curve of the receiver operating curve was 0.851 with a cut-off volume of 0.05 ml best indicating a FCD. CONCLUSION Automated MRI postprocessing and presentation of co-registered output maps in the PACS allowed for rapid (i.e., "within a minute") identification of FCDs in our clinical setting. The presence of false-positive findings currently requires a careful comparison of postprocessing results with conventional MR images but may be reduced in the future using a neural network better adapted to MP2RAGE images.
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Isen J, Perera-Ortega A, Vos SB, Rodionov R, Kanber B, Chowdhury FA, Duncan JS, Mousavi P, Winston GP. Non-parametric combination of multimodal MRI for lesion detection in focal epilepsy. NEUROIMAGE-CLINICAL 2021; 32:102837. [PMID: 34619650 PMCID: PMC8503566 DOI: 10.1016/j.nicl.2021.102837] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/10/2021] [Accepted: 09/20/2021] [Indexed: 12/21/2022]
Abstract
Multivariate voxel-based analysis useful for lesion detection in focal epilepsy. Non-parametric combination algorithm used to combine data from various MR sequences. Successful lesion detection demonstrated in MRI-positive and MRI-negative patients. Multimodal analysis detected abnormalities from diverse epileptogenic pathologies. Sensitivity of multivariate analysis notably higher than univariate analyses.
One third of patients with medically refractory focal epilepsy have normal-appearing MRI scans. This poses a problem as identification of the epileptogenic region is required for surgical treatment. This study performs a multimodal voxel-based analysis (VBA) to identify brain abnormalities in MRI-negative focal epilepsy. Data was collected from 69 focal epilepsy patients (42 with discrete lesions on MRI scans, 27 with no visible findings on scans), and 62 healthy controls. MR images comprised T1-weighted, fluid-attenuated inversion recovery (FLAIR), fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging, and neurite density index (NDI) from neurite orientation dispersion and density imaging. These multimodal images were coregistered to T1-weighted scans, normalized to a standard space, and smoothed with 8 mm FWHM. Initial analysis performed voxel-wise one-tailed t-tests separately on grey matter concentration (GMC), FLAIR, FA, MD, and NDI, comparing patients with epilepsy to controls. A multimodal non-parametric combination (NPC) analysis was also performed simultaneously on FLAIR, FA, MD, and NDI. Resulting p-maps were family-wise error rate corrected, threshold-free cluster enhanced, and thresholded at p < 0.05. Sensitivity was established through visual comparison of results to manually drawn lesion masks or seizure onset zone (SOZ) from stereoelectroencephalography. A leave-one-out cross-validation with the same analysis protocols was performed on controls to determine specificity. NDI was the best performing individual modality, detecting focal abnormalities in 38% of patients with normal MRI and conclusive SOZ. GMC demonstrated the lowest sensitivity at 19%. NPC provided superior performance to univariate analyses with 50% sensitivity. Specificity in controls ranged between 96 and 100% for all analyses. This study demonstrated the utility of a multimodal VBA utilizing NPC for detecting epileptogenic lesions in MRI-negative focal epilepsy. Future work will apply this approach to datasets from other centres and will experiment with different combinations of MR sequences.
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Affiliation(s)
- Jonah Isen
- School of Computing, Queen's University, Kingston, Canada
| | | | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London, London, UK; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK
| | - Baris Kanber
- Centre for Medical Image Computing, University College London, London, UK; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - Parvin Mousavi
- School of Computing, Queen's University, Kingston, Canada
| | - Gavin P Winston
- School of Computing, Queen's University, Kingston, Canada; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK; Department of Medicine, Division of Neurology & Centre for Neuroscience Studies, Queen's University, Kingston, Canada.
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Individual localization value of resting-state fMRI in epilepsy presurgical evaluation: A combined study with stereo-EEG. Clin Neurophysiol 2021; 132:3197-3206. [PMID: 34538574 DOI: 10.1016/j.clinph.2021.07.028] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/30/2021] [Accepted: 07/21/2021] [Indexed: 02/08/2023]
Abstract
OBJECTIVE To examine the individual-patient-level localization value of resting-state functional MRI (rsfMRI) metrics for the seizure onset zone (SOZ) defined by stereo-electroencephalography (SEEG) in patients with medically intractable focal epilepsies. METHODS We retrospectively included 19 patients who underwent SEEG implantation for epilepsy presurgical evaluation. Voxel-wise whole-brain analysis was performed on 3.0 T rsfMRI to generate clusters for amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo) and degree centrality (DC), which were co-registered with the SEEG-defined SOZ to evaluate their spatial overlap. Subgroup and correlation analyses were conducted for various clinical characteristics. RESULTS ALFF demonstrated concordant clusters with SEEG-defined SOZ in 73.7% of patients, with 93.3% sensitivity and 77.8% PPV. The concordance rate showed no significant difference when subgrouped by lesional/non-lesional MRI, SOZ location, interictal epileptiform discharges on scalp EEG, pathology or seizure outcomes. No significant correlation was seen between ALFF concordance rate and epilepsy duration, seizure-onset age, seizure frequency or number of antiseizure medications. ReHo and DC did not achieve favorable concordance results (10.5% and 15.8%, respectively). All concordant clusters showed regional activation, representing increased neural activities. CONCLUSION ALFF had high concordance rate with SEEG-defined SOZ at individual-patient level. SIGNIFICANCE ALFF activation on rsfMRI can add localizing information for the noninvasive presurgical workup of intractable focal epilepsies.
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Jin L, Choi JY, Bulacio J, Alexopoulos AV, Burgess RC, Murakami H, Bingaman W, Najm I, Wang ZI. Multimodal Image Integration for Epilepsy Presurgical Evaluation: A Clinical Workflow. Front Neurol 2021; 12:709400. [PMID: 34421808 PMCID: PMC8372749 DOI: 10.3389/fneur.2021.709400] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 06/25/2021] [Indexed: 12/02/2022] Open
Abstract
Multimodal image integration (MMII) is a promising tool to help delineate the epileptogenic zone (EZ) in patients with medically intractable focal epilepsies undergoing presurgical evaluation. We report here the detailed methodology of MMII and an overview of the utility of MMII at the Cleveland Clinic Epilepsy Center from 2014 to 2018, exemplified by illustrative cases. The image integration was performed using the Curry platform (Compumedics Neuroscan™, Charlotte, NC, USA), including all available diagnostic modalities such as Magnetic resonance imaging (MRI), Positron Emission Tomography (PET), single-photon emission computed tomography (SPECT) and Magnetoencephalography (MEG), with additional capability of trajectory planning for intracranial EEG (ICEEG), particularly stereo-EEG (SEEG), as well as surgical resection planning. In the 5-year time span, 467 patients underwent MMII; of them, 98 patients (21%) had a history of prior neurosurgery and recurring seizures. Of the 467 patients, 425 patients underwent ICEEG implantation with further CT co-registration to identify the electrode locations. A total of 351 patients eventually underwent surgery after MMII, including 197 patients (56%) with non-lesional MRI and 223 patients (64%) with extra-temporal lobe epilepsy. Among 269 patients with 1-year post-operative follow up, 134 patients (50%) had remained completely seizure-free. The most common histopathological finding is focal cortical dysplasia. Our study illustrates the usefulness of MMII to enhance SEEG electrode trajectory planning, assist non-invasive/invasive data interpretation, plan resection strategy, and re-evaluate surgical failures. Information presented by MMII is essential to the understanding of the anatomo-functional-electro-clinical correlations in individual cases, which leads to the ultimate success of presurgical evaluation of patients with medically intractable focal epilepsies.
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Affiliation(s)
- Liri Jin
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China.,Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
| | - Joon Yul Choi
- Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
| | - Juan Bulacio
- Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
| | | | | | | | - William Bingaman
- Department of Neurosurgery, Cleveland Clinic, Cleveland, OH, United States
| | - Imad Najm
- Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
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Sone D. Making the Invisible Visible: Advanced Neuroimaging Techniques in Focal Epilepsy. Front Neurosci 2021; 15:699176. [PMID: 34385902 PMCID: PMC8353251 DOI: 10.3389/fnins.2021.699176] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/28/2021] [Indexed: 12/30/2022] Open
Abstract
It has been a clinically important, long-standing challenge to accurately localize epileptogenic focus in drug-resistant focal epilepsy because more intensive intervention to the detected focus, including resection neurosurgery, can provide significant seizure reduction. In addition to neurophysiological examinations, neuroimaging plays a crucial role in the detection of focus by providing morphological and neuroanatomical information. On the other hand, epileptogenic lesions in the brain may sometimes show only subtle or even invisible abnormalities on conventional MRI sequences, and thus, efforts have been made for better visualization and improved detection of the focus lesions. Recent advance in neuroimaging has been attracting attention because of the potentials to better visualize the epileptogenic lesions as well as provide novel information about the pathophysiology of epilepsy. While the progress of newer neuroimaging techniques, including the non-Gaussian diffusion model and arterial spin labeling, could non-invasively detect decreased neurite parameters or hypoperfusion within the focus lesions, advances in analytic technology may also provide usefulness for both focus detection and understanding of epilepsy. There has been an increasing number of clinical and experimental applications of machine learning and network analysis in the field of epilepsy. This review article will shed light on recent advances in neuroimaging for focal epilepsy, including both technical progress of images and newer analytical methodologies and discuss about the potential usefulness in clinical practice.
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Affiliation(s)
- Daichi Sone
- Department of Psychiatry, The Jikei University School of Medicine, Tokyo, Japan.,Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom
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Chen C, Xie JJ, Ding F, Jiang YS, Jin B, Wang S, Ding Y, Li H, Jiang B, Zhu JM, Ding MP, Chen Z, Wu ZY, Zhang BR, Hsu YC, Lai HY, Wang S. 7T MRI with post-processing for the presurgical evaluation of pharmacoresistant focal epilepsy. Ther Adv Neurol Disord 2021; 14:17562864211021181. [PMID: 34163537 PMCID: PMC8191069 DOI: 10.1177/17562864211021181] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 05/07/2021] [Indexed: 11/17/2022] Open
Abstract
Background: We aimed to evaluate the diagnostic yield of seven-tesla (7T) magnetic resonance imaging (MRI) with post-processing of three-dimensional (3D) T1-weighted (T1W) images by the morphometric analysis program (MAP) in epilepsy surgical candidates whose 3T MRI results were inconclusive or negative. Methods: We recruited 35 patients with pharmacoresistant focal epilepsy. A multidisciplinary team including an experienced neuroradiologist evaluated their seizure semiology, video-electroencephalography data, 3T MRI and post-processing results, and co-registered FDG-PET. Eleven patients had suspicious lesions on 3T MRI and the other 24 patients were strictly MRI-negative. 7T MRI evaluation was then performed to aid clinical decision. Among patients with pathologically proven focal cortical dysplasia (FCD) type II, signs of FCD were retrospectively evaluated in each MRI sequence (T1W, T2W, and FLAIR), and positive rates were analyzed in each MAP feature map (junction, extension, and thickness). Results: 7T MRI evaluation confirmed the lesion in nine of the 11 (81.8%) patients with suspicious lesions on 3T MRI. It also revealed new lesions in four of the 24 (16.7%) strictly MRI-negative patients. Histopathology showed FCD type II in 11 of the 13 (84.6%) 7T MRI-positive cases. Unexpectedly, three of the four newly identified FCD lesions were located in the posterior quadrant. Blurred gray–white boundary was the most frequently observed sign of FCD, appearing on 7T T1W image in all cases and on T2W and FLAIR images in only about half cases. The 7T junction map successfully detected FCD (10/11) in more cases than the extension (1/11) and thickness (0/11) maps. The 3D T1W images at 7T exhibited superior cerebral gray–white matter contrast, more obviously blurred gray–white boundary of FCD, and larger and brighter positive zones in post-processing than 3T T1W images. Conclusion: 7T MRI with post-processing can enhance the detection of subtle epileptogenic lesions for MRI-negative epilepsy and may optimize surgical strategies for patients with focal epilepsy.
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Affiliation(s)
- Cong Chen
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Juan-Juan Xie
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | - Fang Ding
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ya-Si Jiang
- Department of Neurology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bo Jin
- Department of Neurology, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, China
| | - Shan Wang
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Ding
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Li
- Department of Radiology, and Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Biao Jiang
- Department of Radiology, and Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jun-Ming Zhu
- Epilepsy Center and Department of Neurosurgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mei-Ping Ding
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhong Chen
- Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhi-Ying Wu
- Department of Neurology, and Research Center of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | - Bao-Rong Zhang
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yi-Cheng Hsu
- MR collaboration NE Asia, Siemens Healthcare, Shanghai, China
| | - Hsin-Yi Lai
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuang Wang
- Department of Neurology and Epilepsy Center, Research Center of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
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Sun K, Yu T, Yang D, Ren Z, Qiao L, Ni D, Wang X, Zhao Y, Chen X, Xiang J, Chen N, Gao R, Yang K, Lin Y, Kober T, Zhang G. Fluid and White Matter Suppression Imaging and Voxel-Based Morphometric Analysis in Conventional Magnetic Resonance Imaging-Negative Epilepsy. Front Neurol 2021; 12:651592. [PMID: 33995250 PMCID: PMC8116947 DOI: 10.3389/fneur.2021.651592] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 03/18/2021] [Indexed: 01/23/2023] Open
Abstract
Purpose: Delineation of subtle lesions in magnetic resonance imaging (MRI)-negative patients is of great importance in preoperative epilepsy evaluation. The aim of our study was to explore the diagnostic value of the novel fluid and white matter suppression (FLAWS) sequence in comparison with a voxel-based MRI postprocessing morphometric analysis program (MAP) in a consecutive cohort of non-lesional patients. Methods: Surgical candidates with a negative finding on an official neuroradiology report were enrolled. High-resolution FLAWS image and MAP maps generated based on high-resolution three-dimensional (3D) T1 image were visually inspected for each patient. The findings of FLAWS or MAP-positive (FLAWS/MAP+) regions were compared with the surgical resection cavity in correlation with surgical outcome and pathology. Results: Forty-five patients were enrolled; the pathological examination revealed focal cortical dysplasia (FCD) in 32 patients and other findings in 13 patients. The positive rate, sensitivity, and specificity were 48.9%, 0.43, and 0.87, respectively, for FLAWS and 64.4%, 0.57, and 0.8, respectively, for MAP. Concordance between surgical resection and FLAWS+ or MAP+ regions was significantly associated with a seizure-free outcome (FLAWS: p = 0.002; MAP: p = 0.0003). A positive finding in FLAWS and MAP together with abnormalities in the same gyrus (FLAWS–MAP gyral+) was detected in 31.1% of patients. FLAWS+ only and MAP+ only were found in 7 (15.5%) and 14 (31.1%) patients, respectively. Conclusions: FLAWS showed a promising value for identifying subtle epileptogenic lesions and can be used as a complement to current MAP in patients with MRI-negative epilepsy.
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Affiliation(s)
- Ke Sun
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Dongju Yang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhiwei Ren
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Liang Qiao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Duanyu Ni
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xueyuan Wang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yongxiang Zhao
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xin Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Xiang
- Department of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Nan Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Runshi Gao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kun Yang
- Department of Evidence-Based Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yicong Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Guojun Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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Abstract
INTRODUCTION Focal cortical dysplasias (FCDs) represent the most common etiology in pediatric drug-resistant focal epilepsies undergoing surgical treatment. The localization, extent and histopathological features of FCDs are considerably variable. Somatic mosaic mutations of genes that encode proteins in the PI3K-AKTmTOR pathway, which also includes the tuberous sclerosis associated genes TSC1 and TSC2, have been implicated in FCD type II in a substantial subset of patients. Surgery is the principal therapeutic option for FCD-related epilepsy. Advanced neurophysiological and neuroimaging techniques have improved surgical outcome and reduced the risk of postsurgical deficits. Pharmacological MTOR inhibitors are being tested in clinical trials and might represent an example of personalized treatment of epilepsy based on the known mechanisms of disease, used alone or in combination with surgery. AREAS COVERED This review will critically analyze the advances in the diagnosis and treatment of FCDs, with a special focus on the novel therapeutic options prompted by a better understanding of their pathophysiology. EXPERT OPINION Focal cortical dysplasia is a main cause of drug-resistant epilepsy, especially in children. Novel, personalized approaches are needed to more effectively treat FCD-related epilepsy and its cognitive consequences.
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Affiliation(s)
- Renzo Guerrini
- Neuroscience Department, Children's Hospital Meyer-University of Florence, Florence, Italy
| | - Carmen Barba
- Neuroscience Department, Children's Hospital Meyer-University of Florence, Florence, Italy
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González-Ortiz S, Medrano S, Capellades J, Vilas M, Mestre A, Serrano L, Conesa G, Pérez-Enríquez C, Arumi M, Bargalló N, Delgado-Martinez I, Rocamora R. Voxel-based morphometry for the evaluation of patients with pharmacoresistant epilepsy with apparently normal MRI. J Neuroimaging 2021; 31:560-568. [PMID: 33817887 DOI: 10.1111/jon.12849] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 02/15/2021] [Accepted: 02/18/2021] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND AND PURPOSE Magnetic resonance imaging (MRI) is essential in the diagnosis of pharmacoresistant epilepsy (PRE), because patients with lesions detected by MRI have a better prognosis after surgery. Focal cortical dysplasia (FCD) is one of the most frequent etiologies of PRE but can be difficult to identify by MRI. Voxel-based morphometric analysis programs, like the Morphometric Analysis Program (MAP), have been developed to help improve MRI detection. Our objective was to evaluate the clinical usefulness of MAP in patients with PRE and an apparently normal MRI. METHODS We studied 70 patients with focal PRE and a nonlesional MRI. The 3DT1 sequence was processed with MAP, obtaining three z-score maps. Patients were classified as MAP+ if one or more z-score maps showed a suspicious area of brightness, and MAP- if the z-score maps did not show any suspicious areas. For MAP+ cases, a second-look MRI was performed with a dedicated inspection based on the MAP findings. The MAP results were correlated with the epileptogenic zone. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS Thirty-one percent of patients were classified as MAP+ and 69% were MAP-. Results showed a sensitivity of 0.57, specificity of 0.8, PPV of 0.91, and NPV of 0.35. In 19% of patients, an FCD was found in the second-look MRI after MAP. CONCLUSIONS MAP was helpful in the detection of lesions in PRE patients with a nonlesional MRI, which could have important repercussions for the clinical management and postoperative prognosis of these patients.
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Affiliation(s)
- Sofía González-Ortiz
- Radiology Department, Hospital del Mar, Barcelona, Spain.,Epilpsy Reserach Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain
| | | | | | - Marta Vilas
- Radiology Department, Hospital del Mar, Barcelona, Spain
| | - Antoni Mestre
- Nuclear Medicine Department, Hospital Trueta, Girona, Spain
| | - Laura Serrano
- Neurosurgery Department, Hospital del Mar, Barcelona, Spain
| | - Gerardo Conesa
- Neurosurgery Department, Hospital del Mar, Barcelona, Spain.,Epilpsy Reserach Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain
| | - Carmen Pérez-Enríquez
- Neurology Department, Hospital del Mar, Barcelona, Spain.,Epilpsy Reserach Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain
| | - Montserrat Arumi
- Anatomic Pathology Department, Hospital del Mar, Barcelona, Spain
| | - Nuria Bargalló
- Centre de Diagnosi per la Imatge, Hospital Clínic, Barcelona, Spain
| | - Ignacio Delgado-Martinez
- Neurosurgery Department, Hospital del Mar, Barcelona, Spain.,Epilpsy Reserach Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain
| | - Rodrigo Rocamora
- Neurology Department, Hospital del Mar, Barcelona, Spain.,Epilpsy Reserach Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain
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49
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Abstract
Human neuroimaging has had a major impact on the biological understanding of epilepsy and the relationship between pathophysiology, seizure management, and outcomes. This review highlights notable recent advancements in hardware, sequences, methods, analyses, and applications of human neuroimaging techniques utilized to assess epilepsy. These structural, functional, and metabolic assessments include magnetic resonance imaging (MRI), positron emission tomography (PET), and magnetoencephalography (MEG). Advancements that highlight non-invasive neuroimaging techniques used to study the whole brain are emphasized due to the advantages these provide in clinical and research applications. Thus, topics range across presurgical evaluations, understanding of epilepsy as a network disorder, and the interactions between epilepsy and comorbidities. New techniques and approaches are discussed which are expected to emerge into the mainstream within the next decade and impact our understanding of epilepsies. Further, an increasing breadth of investigations includes the interplay between epilepsy, mental health comorbidities, and aberrant brain networks. In the final section of this review, we focus on neuroimaging studies that assess bidirectional relationships between mental health comorbidities and epilepsy as a model for better understanding of the commonalities between both conditions.
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Affiliation(s)
- Adam M. Goodman
- Department of Neurology, UAB Epilepsy Center, University of Alabama At Birmingham, 312 Civitan International Research Center, Birmingham, AL 35294 USA
| | - Jerzy P. Szaflarski
- Department of Neurology, UAB Epilepsy Center, University of Alabama At Birmingham, 312 Civitan International Research Center, Birmingham, AL 35294 USA
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50
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Specchio N, Pepi C, De Palma L, Trivisano M, Vigevano F, Curatolo P. Neuroimaging and genetic characteristics of malformation of cortical development due to mTOR pathway dysregulation: clues for the epileptogenic lesions and indications for epilepsy surgery. Expert Rev Neurother 2021; 21:1333-1345. [PMID: 33754929 DOI: 10.1080/14737175.2021.1906651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Introduction: Malformation of cortical development (MCD) is strongly associated with drug-resistant epilepsies for which surgery to remove epileptogenic lesions is common. Two notable technological advances in this field are identification of the underlying genetic cause and techniques in neuroimaging. These now question how presurgical evaluation ought to be approached for 'mTORpathies.'Area covered: From review of published primary and secondary articles, the authors summarize evidence to consider focal cortical dysplasia (FCD), tuber sclerosis complex (TSC), and hemimegalencephaly (HME) collectively as MCD mTORpathies. The authors also consider the unique features of these related conditions with particular focus on the practicalities of using neuroimaging techniques currently available to define surgical targets and predict post-surgical outcome. Ultimately, the authors consider the surgical dilemmas faced for each condition.Expert opinion: Considering FCD, TSC, and HME collectively as mTORpathies has some merit; however, a unified approach to presurgical evaluation would seem unachievable. Nevertheless, the authors believe combining genetic-centered classification and morphologic findings using advanced imaging techniques will eventually form the basis of a paradigm when considering candidacy for early surgery.
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Affiliation(s)
- Nicola Specchio
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Chiara Pepi
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Luca De Palma
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Marina Trivisano
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Federico Vigevano
- Department of Neuroscience, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Paolo Curatolo
- Child Neurology and Psychiatry Unit, Systems Medicine Department, Tor Vergata University, Rome, Italy
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