The pathology of magnetic-resonance-imaging-negative epilepsy

The utility of Multicentre Epilepsy Lesion Detection (MELD) algorithm in identifying epileptic activity and predicting seizure freedom in MRI lesion-negative paediatric patients

AIM

Paediatric patients with drug-resistant focal epilepsy (DRFE) who have no clear focal lesion identified on conventional structural magnetic resonance imaging (MRI) are a particularly challenging cohort to treat and form an increasing part of epilepsy surgery programs. A recently developed deep-learning-based MRI lesion detection algorithm, the Multicentre Lesion Detection (MELD) algorithm, has been shown to aid detection of focal cortical dysplasia (FCD). We applied this algorithm retrospectively to a cohort of MRI-negative children with refractory focal epilepsy who underwent stereoelectroencephalography (SEEG) to determine its accuracy in identifying unseen epileptic lesions, seizure onset zones and clinical outcomes.

METHODS

We retrospectively applied the MELD algorithm to a consecutive series of MRI-negative patients who underwent SEEG at our tertiary Paediatric Epilepsy Surgery centre. We assessed the extent to which the identified MELD cluster or lesion area corresponded with the clinical seizure hypothesis, the epileptic network, and the positron emission tomography (PET) focal hypometabolic area. In those who underwent resective surgery, we analysed whether the region of MELD abnormality corresponded with the surgical target and to what extent this was associated with seizure freedom.

RESULTS

We identified 37 SEEG studies in 28 MRI-negative children in whom we could run the MELD algorithm. Of these, 14 (50 %) children had clusters identified on MELD. Nine (32 %) children had clusters concordant with seizure hypothesis, 6 (21 %) had clusters concordant with PET imaging, and 5 (18 %) children had at least one cluster concordant with SEEG electrode placement. Overall, 4 MELD clusters in 4 separate children correctly predicted either seizure onset zone or irritative zone based on SEEG stimulation data. Sixteen children (57 %) went on to have resective or lesional surgery. Of these, only one patient (4 %) had a MELD cluster which co-localised with the resection cavity and this child had an Engel 1 A outcome.

CONCLUSIONS

In our paediatric cohort of MRI-negative patients with drug-resistant focal epilepsy, the MELD algorithm identified abnormal clusters or lesions in half of cases, and identified one radiologically occult focal cortical dysplasia. Machine-learning-based lesion detection is a promising area of research with the potential to improve seizure outcomes in this challenging cohort of radiologically occult FCD cases. However, its application should be approached with caution, especially with regards to its specificity in detecting FCD lesions, and there is still work to be done before it adds to diagnostic utility.

WONOEP 2022: Neurotechnology for the diagnosis of epilepsy

Epilepsy's myriad causes and clinical presentations ensure that accurate diagnoses and targeted treatments remain a challenge. Advanced neurotechnologies are needed to better characterize individual patients across multiple modalities and analytical techniques. At the XVIth Workshop on Neurobiology of Epilepsy: Early Onset Epilepsies: Neurobiology and Novel Therapeutic Strategies (WONOEP 2022), the session on "advanced tools" highlighted a range of approaches, from molecular phenotyping of genetic epilepsy models and resected tissue samples to imaging-guided localization of epileptogenic tissue for surgical resection of focal malformations. These tools integrate cutting edge research, clinical data acquisition, and advanced computational methods to leverage the rich information contained within increasingly large datasets. A number of common challenges and opportunities emerged, including the need for multidisciplinary collaboration, multimodal integration, potential ethical challenges, and the multistage path to clinical translation. Despite these challenges, advanced epilepsy neurotechnologies offer the potential to improve our understanding of the underlying causes of epilepsy and our capacity to provide patient-specific treatment.

Combining magnetic resonance fingerprinting with voxel-based morphometric analysis to reduce false positives for focal cortical dysplasia detection

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.

Evaluation of MRI post-processing methods combined with PET in detecting focal cortical dysplasia lesions for patients with MRI-negative epilepsy

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.

Morphometric magnetic resonance imaging (MRI) postprocessing in MRI-negative patients with first unprovoked seizure

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.

Low prevalence of neural autoantibodies in perioperative cerebrospinal fluid samples of epilepsy surgery patients: A multicenter prospective study

OBJECTIVE

Refractory epilepsy may have an underlying autoimmune etiology. Our aim was to assess the prevalence of neural autoantibodies in a multicenter national prospective cohort of patients with drug-resistant epilepsy undergoing epilepsy surgery utilizing comprehensive clinical, serologic, and histopathological analyses.

METHODS

We prospectively recruited patients undergoing epilepsy surgery for refractory focal epilepsy not caused by a brain tumor from epilepsy surgery centers in the Czech Republic. Perioperatively, we collected cerebrospinal fluid (CSF) and/or serum samples and performed comprehensive commercial and in-house assays for neural autoantibodies. Clinical data were obtained from the patients' medical records, and histopathological analysis of resected brain tissue was performed.

RESULTS

Seventy-six patients were included, mostly magnetic resonance imaging (MRI)-lesional cases (74%). Mean time from diagnosis to surgery was 21 ± 13 years. Only one patient (1.3%) had antibodies in the CSF and serum (antibodies against glutamic acid decarboxylase 65) in relevant titers; histology revealed focal cortical dysplasia (FCD) III (FCD associated with hippocampal sclerosis [HS]). Five patients' samples displayed CSF-restricted oligoclonal bands (OCBs; 6.6%): three cases with FCD (one with FCD II and two with FCD I), one with HS, and one with negative histology. Importantly, eight patients (one of them with CSF-restricted OCBs) had findings on antibody testing in individual serum and/or CSF tests that could not be confirmed by complementary tests and were thus classified as nonspecific, yet could have been considered specific without confirmatory testing. Of these, two had FCD, two gliosis, and four HS. No inflammatory changes or lymphocyte cuffing was observed histopathologically in any of the 76 patients.

SIGNIFICANCE

Neural autoantibodies are a rare finding in perioperatively collected serum and CSF of our cohort of mostly MRI-lesional epilepsy surgery patients. Confirmatory testing is essential to avoid overinterpretation of autoantibody-positive findings.

MP2RAGE vs. MPRAGE surface-based morphometry in focal epilepsy

In drug-resistant focal epilepsy, detecting epileptogenic lesions using MRI poses a critical diagnostic challenge. Here, we assessed the utility of MP2RAGE-a T1-weighted sequence with self-bias correcting properties commonly utilized in ultra-high field MRI-for the detection of epileptogenic lesions using a surface-based morphometry pipeline based on FreeSurfer, and compared it to the common approach using T1w MPRAGE, both at 3T. We included data from 32 patients with focal epilepsy (5 MRI-positive, 27 MRI-negative with lobar seizure onset hypotheses) and 94 healthy controls from two epilepsy centres. Surface-based morphological measures and intensities were extracted and evaluated in univariate GLM analyses as well as multivariate unsupervised 'novelty detection' machine learning procedures. The resulting prediction maps were analyzed over a range of possible thresholds using alternative free-response receiver operating characteristic (AFROC) methodology with respect to the concordance with predefined lesion labels or hypotheses on epileptogenic zone location. We found that MP2RAGE performs at least comparable to MPRAGE and that especially analysis of MP2RAGE image intensities may provide additional diagnostic information. Secondly, we demonstrate that unsupervised novelty-detection machine learning approaches may be useful for the detection of epileptogenic lesions (maximum AFROC AUC 0.58) when there is only a limited lesional training set available. Third, we propose a statistical method of assessing lesion localization performance in MRI-negative patients with lobar hypotheses of the epileptogenic zone based on simulation of a random guessing process as null hypothesis. Based on our findings, it appears worthwhile to study similar surface-based morphometry approaches in ultra-high field MRI (≥ 7 T).

Focal cortical dysplasia is a frequent coexistent pathology in patients with Rasmussen's encephalitis

INTRODUCTION

Rasmussen's encephalitis (RE) is a rare, predominantly pediatric epilepsy disorder of unknown etiology. It classically affects one of the cerebral hemispheres and histologically shows cortical chronic inflammation, gliosis, and neuronal loss. The etiopathogenesis of RE remains unknown, with genetic, infectious, and autoimmune factors all speculated to play a role. Although the histologic findings in RE are well described, few studies have investigated a large cohort of cases looking for the coexistence of RE with focal cortical dysplasia (FCD).

DESIGN

The study is a retrospective review of RE patients who underwent surgical resection of brain tissue between 1979 and 2021. Relevant patient history was retrieved, and available histologic slides were reviewed. The histologic severity of RE was described according to the Pardo criteria. In cases where FCD was present, the observed patterns of FCD (namely Ia, Ib, IIa, IIb, etc.) were described using the International League Against Epilepsy (ILAE) classification.

RESULTS

Thirty-eight resection specimens from 31 patients formed the study cohort. Seventeen patients (54.8 %) were male; average age at surgery was 8 years (range: 2-28 years). Twenty-seven resection specimens (71.1 %) from 23 patients (74 %) showed evidence of coexistent FCD. Most cases with FCD resembled the ILAE type Ib (n = 23) pattern. Cases of RE that did not show FCD were either Pardo stage 1 (n = 5) or 4 (n = 6), with all Pardo stage 2 and 3 cases demonstrating FCD.

CONCLUSIONS

FCD was found in most patients with RE (74 %). The most observed pattern of FCD was ILAE Ib.

[Focal cortical dysplasia: visual assessment of MRI and MR morphometry data]

OBJECTIVE

Assessing the diagnostic significance of MR morphometry in determining the localization of focal cortical dysplasias (FCD).

MATERIAL AND METHODS

The study included 13 children after surgery for drug-resistant epilepsy caused by FCD type II and stable postoperative remission of seizures (Engel class IA, median follow-up 56 months). We analyzed the results of independent expert assessment of native MR data by three radiologists (HARNESS protocol) and MR morphometry data regarding accuracy of FCD localization. We considered 2 indicators, i.e. local cortical thickening and gray-white matter blurring.

RESULTS

FCD detection rate was higher after MR morphometry compared to visual analysis of native MR data using the HARNESS protocol. MR morphometry also makes it possible to more often identify gray-white matter blurring as a sign often missed by radiologists (p<0.05).

CONCLUSION

MR morphometry is an additional non-invasive method for assessing the localization of FCD.

A scoping review of the functional magnetic resonance imaging-based functional connectivity of focal cortical dysplasia-related epilepsy

Focal cortical dysplasia (FCD) is the most frequent etiology of operable pharmacoresistant epilepsy in children. There is burgeoning evidence that FCD-related epilepsy is a disorder that involves distributed brain networks. Functional magnetic resonance imaging (fMRI) is a tool that allows one to infer neuronal activity and to noninvasively map whole-brain functional networks. Despite its relatively widespread availability at most epilepsy centers, the clinical application of fMRI remains mostly task-based in epilepsy. Another approach is to map and characterize cortical functional networks of individuals using resting state fMRI (rsfMRI). The focus of this scoping review is to summarize the evidence to date of investigations of the network basis of FCD-related epilepsy, and to highlight numerous potential future applications of rsfMRI in the exploration of diagnostic and therapeutic strategies for FCD-related epilepsy. There are numerous studies demonstrating a global disruption of cortical functional networks in FCD-related epilepsy. The underlying pathological subtypes of FCD influence overall functional network patterns. There is evidence that cortical functional network mapping may help to predict postsurgical seizure outcomes, highlighting the translational potential of these findings. Additionally, several studies emphasize the important effect of FCD interaction with cortical networks and the expression of epilepsy and its comorbidities.

Application value of multimodal MRI combined with PET metabolic parameters in temporal lobe epilepsy with dual pathology

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.

Multimodal imaging-based diagnostic approach for MRI-negative posterior cortex epilepsy

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.

Interictal high-frequency oscillations, spikes, and connectivity profiles: A fingerprint of epileptogenic brain pathologies

OBJECTIVE

Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug-resistant epilepsy patients. Epileptic spikes, high-frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies.

METHODS

Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug-resistant epilepsy with seizure-free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross-correlation, and phase consistency) were computed for neighboring electrode pairs.

RESULTS

Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy.

SIGNIFICANCE

The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery.

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epileptic foci. Here, we present a neuro-robotic navigation system that is specifically designed for resection of MRI negative epileptic foci. We recruited 52 epileptic patients, and randomly assigned them to treatment group with either neuro-robotic navigation or conventional neuronavigation system. For each patient, in the neuro-robotic navigation group, we integrated multimodality imaging including MRI and PET-CT into the robotic workstation and marked the boundary of foci from the fused image. During surgery, this boundary was delineated by the robotic laser device with high accuracy, guiding resection for the surgeon. For deeply seated foci, we exploited the neuro-robotic navigation system to localize the deepest point with biopsy needle insertion and methylene dye application to locate the boundary of the foci. Our results show that, compared with the conventional neuronavigation, the neuro-robotic navigation system performs equally well in MRI positive epilepsy patients (ENGEL I ratio: 71.4% vs 100%, p = 0.255) systems and show better performance in patients with MRI-negative focal cortical dysplasia (ENGEL I ratio: 88.2% vs 50%, p = 0.0439). At present, there are no documented neurosurgery robots with similar function and application in the field of epilepsy. Our research highlights the added value of using neuro-robotic navigation systems in resection surgery for epilepsy, particularly in cases that involve MRI-negative or deep-seated epileptic foci.

Performance of hippocampal radiomics models based on T2-FLAIR images in mesial temporal lobe epilepsy with hippocampal sclerosis

PURPOSE

Preoperative identification of hippocampal sclerosis (HS) is crucial to successful surgery for mesial temporal lobe epilepsy (MTLE). We aimed to investigate the diagnostic performance of hippocampal radiomics models based on T2 fluid-attenuated inversion recovery (FLAIR) images in MTLE with HS.

METHODS

We analysed 210 cases, including 172 HS pathology-confirmed cases (100 magnetic resonance imaging [MRI]-positive cases [MRI + HS], 72 MRI-negative HS cases [MRI - HS]), and 38 healthy controls (HC). The hippocampus was delineated slice by slice on an oblique coronal plane by a T2-FLAIR sequence, perpendicular to the hippocampus's long axis, to obtain a three-dimensional region of interest. Radiomics were processed using Artificial Intelligence Kit software; logistic regression radiomics models were constructed. The model evaluation indexes included the area under the curve (AUC), accuracy, sensitivity, and specificity.

RESULTS

The respective AUC, accuracy, sensitivity, and specificity were 0.863, 81.4%, 78.0%, and 84.6% between the MRI - HS and HC groups in the training set and 0.855, 75.0%, 68.2%, and 81.8% in the test set; 0.975, 95.0%, 92.9%, and 98.0% between the MRI + HS and HC groups in the training set and 0.954, 88.7%, 90.0%, and 87.0% in the test set; and 0.912, 84.3%, 83.3%, and 86.5% between the MTLE and HC groups in the training set and 0.854, 79.7%, 80.8%, and 77.3% in the test set. The AUC values of the comparative radiomics models were > 0.85, indicating good diagnostic efficiency.

CONCLUSION

The hippocampal radiomics models based on T2-FLAIR images can help diagnose MTLE with HS. They can be used as biological markers for MTLE diagnosis.

Diagnostic Accuracy of Epilepsy-dedicated MRI with Post-processing

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.

Detecting Cortical Thickness Changes in Epileptogenic Lesions Using Machine Learning

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.

White matter alterations in MR-negative temporal and frontal lobe epilepsy using fixel-based analysis

This study focuses on white matter alterations in pharmacoresistant epilepsy patients with no visible lesions in the temporal and frontal lobes on clinical MRI (i.e. MR-negative) with lesions confirmed by resective surgery. The aim of the study was to extend the knowledge about group-specific neuropathology in MR-negative epilepsy. We used the fixel-based analysis (FBA) that overcomes the limitations of traditional diffusion tensor image analysis, mainly within-voxel averaging of multiple crossing fibres. Group-wise comparisons of fixel parameters between healthy controls (N = 100) and: (1) frontal lobe epilepsy (FLE) patients (N = 9); (2) temporal lobe epilepsy (TLE) patients (N = 13) were performed. A significant decrease of the cross-section area of the fixels in the superior longitudinal fasciculus was observed in the FLE. Results in TLE reflected widespread atrophy of limbic, thalamic, and cortico-striatal connections and tracts directly connected to the temporal lobe (such as the anterior commissure, inferior fronto-occipital fasciculus, uncinate fasciculus, splenium of corpus callosum, and cingulum bundle). Alterations were also observed in extratemporal connections (brainstem connection, commissural fibres, and parts of the superior longitudinal fasciculus). To our knowledge, this is the first study to use an advanced FBA method not only on the datasets of MR-negative TLE patients, but also MR-negative FLE patients, uncovering new common tract-specific alterations on the group level.

[Neuroradiological and pathohistological markers of the main epileptogenic substrates in children.Cortical malformations]

High-resolution MRI is an important tool in the diagnosis of structural epilepsy in determining the seizure initiation zones, identification of the mechanisms of epileptogenesis in predicting outcomes and preventing postoperative complications in patients. In this article we demonstrate the neuroradiological and pathohistological characteristics of the main epileptogenic substrates in children using modern classification. The first part of the article is devoted to cortical malformations as the most common epileptogenic cerebral disorders.

Lesion Detection Through MRI Postprocessing in Pathology-Proven Focal Cortical Dysplasia: Experience at a Single Institution in the Republic of Korea

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.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study

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.

Wearable OPM-MEG: A changing landscape for epilepsy

Magnetoencephalography with optically pumped magnometers (OPM-MEG) is an emerging and novel, cost-effective wearable system that can simultaneously record neuronal activity with high temporal resolution ("when" neuronal activity occurs) and spatial resolution ("where" neuronal activity occurs). This paper will first outline recent methodological advances in OPM-MEG compared to conventional superconducting quantum interference device (SQUID)-MEG before discussing how OPM-MEG can become a valuable and noninvasive clinical support tool in epilepsy surgery evaluation. Although OPM-MEG and SQUID-MEG share similar data features, OPM-MEG is a wearable design that fits children and adults, and it is also robust to head motion within a magnetically shielded room. This means that OPM-MEG can potentially extend the application of MEG into the neurobiology of severe childhood epilepsies with intellectual disabilities (e.g., epileptic encephalopathies) without sedation. It is worth noting that most OPM-MEG sensors are heated, which may become an issue with large OPM sensor arrays (OPM-MEG currently has fewer sensors than SQUID-MEG). Future implementation of triaxial sensors may alleviate the need for large OPM sensor arrays. OPM-MEG designs allowing both awake and sleep recording are essential for potential long-term epilepsy monitoring.

Automated Detection and Surgical Planning for Focal Cortical Dysplasia with Multicenter Validation

BACKGROUND

In patients with surgically amenable focal cortical dysplasia (FCD), subtle neuroimaging representation and the risk of open surgery lead to gaps in surgical treatment and delays in surgery.

OBJECTIVE

To construct an integrated platform that can accurately detect FCD and automatically establish trajectory planning for magnetic resonance-guided laser interstitial thermal therapy.

METHODS

This multicenter study included retrospective patients to train the automated detection model, prospective patients for model evaluation, and an additional cohort for construction of the automated trajectory planning algorithm. For automated detection, we evaluated the performance and generalization of the conventional neural network in different multicenter cohorts. For automated trajectory planning, feasibility/noninferiority and safety score were calculated to evaluate the clinical value.

RESULTS

Of the 260 patients screened for eligibility, 202 were finally included. Eighty-eight patients were selected for conventional neural network training, 88 for generalizability testing, and 26 for the establishment of an automated trajectory planning algorithm. The model trained using preprocessed and multimodal neuroimaging displayed the best performance in diagnosing FCD (figure of merit = 0.827 and accuracy range = 75.0%-91.7% across centers). None of the clinical variables had a significant effect on prediction performance. Moreover, the automated trajectory was feasible and noninferior to the manual trajectory (χ2 = 3.540, P = .060) and significantly safer (overall: test statistic = 30.423, P < .001).

CONCLUSION

The integrated platform validated based on multicenter, prospective cohorts exhibited advantages of easy implementation, high performance, and generalizability, thereby indicating its potential in the diagnosis and minimally invasive treatment of FCD.

Imaging in medically refractory epilepsy at 3 Tesla: a 13-year tertiary adult epilepsy center experience

Objectives

MRI negative epilepsy has evolved through increased usage of 3 T and insights from surgically correlated studies. The goal of this study is to describe dedicated 3 T epilepsy MRI findings in medically refractory epilepsy (MRE) patients at a tertiary epilepsy center to familiarize radiologists with an updated spectrum and frequency of potential imaging findings in the adult MRE population.

Methods

Included were all patients with MRE admitted to the epilepsy monitoring unit who were discussed at weekly interdisciplinary imaging conferences at Toronto Western Hospital with MRI studies (3 T with dedicated epilepsy protocol) performed between January 2008 and January 2021. Lesion characterization was performed by two readers based on most likely imaging diagnosis in consensus. Lobes involved per case were recorded.

Results

A total of 738 patients (386 female; mean age 35 years, range 15–77) were included. A total of 262 patients (35.5%) were MRI negative. The most common imaging finding was mesial temporal sclerosis, seen in 132 patients (17.9%), followed by encephalomalacia and gliosis, either posttraumatic, postoperative, postischemic, or postinfectious in nature, in 79 patients (10.7%). The most common lobar involvement (either partially or uniquely) was temporal (341 cases, 58.6%). MRE patients not candidates for surgical resection were included in the study, as were newly described pathologies from surgically correlated studies revealing findings seen retrospectively on reported MRI negative exams (isolated enlargement of the amygdala, temporal pole white matter abnormality, temporal encephalocele).

Conclusion

This study provides an updated description of the spectrum of 3 T MRI findings in adult MRE patients from a tertiary epilepsy center.

MRI of focal cortical dysplasia

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.

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

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.

Detection of Hippocampal Subfield Asymmetry at 7T With Automated Segmentation in Epilepsy Patients With Normal Clinical Strength MRIs

While the etiology of hippocampal sclerosis (HS) in epilepsy patients remains unknown, distinct phenotypes of hippocampal subfield atrophy have been associated with different clinical presentations and surgical outcomes. The advent of novel techniques including ultra-high field 7T magnetic resonance imaging (MRI) and automated subfield volumetry have further enabled detection of hippocampal pathology in patients with epilepsy, however, studies combining both 7T MRI and automated segmentation in epilepsy patients with normal-appearing clinical MRI are limited. In this study, we present a novel application of the automated segmentation of hippocampal subfields (ASHS) software to determine subfield volumes of the CA1, CA2/3, CA4/DG, and the subiculum using ultra high-field 7T MRI scans, including T1-weighted MP2RAGE and T2-TSE sequences, in 27 patients with either mesial temporal lobe epilepsy (mTLE) or neocortical epilepsy (NE) compared to age and gender matched healthy controls. We found that 7T improved visualization of structural abnormalities not otherwise seen on clinical strength MRIs in patients with unilateral mTLE. Additionally, our automated segmentation algorithm was able to detect structural differences in volume and asymmetry across hippocampal subfields in unilateral mTLE patients compared to controls. Specifically, amongst unilateral mTLE patients with longer disease durations, volume loss was observed in the ipsilateral CA1 and CA2/3 subfields and contralateral CA1. There were no differences in subfield volumes in patients with NE compared to controls. We report the first application of 7T with automated segmentation to characterize the relationship between disease duration burden and asymmetry across specific hippocampal subfields in this population. Disease duration was found to have a statistically significant positive relationship with subfield asymmetry within the unilateral mTLE cohort. These findings highlight the ability of 7T MRI and automated segmentation to provide novel qualitative and quantitative information in epilepsy patients who are otherwise MRI-negative at clinical field strengths.

Epilepsy Surgery: Special Circumstances

Epilepsy surgery has proven to be very effective in treating refractory focal epilepsies in children, producing seizure freedom or partial seizure control well beyond any other medical or dietary therapies. While surgery is mostly utilized in certain clinical phenotypes, either based on the location such as temporal lobe epilepsy, or based on the presence of known epileptogenic lesions such as focal cortical dysplasia, tumors or hemimegalencephaly, there is a growing body of evidence to support the role of surgery in other patients' cohorts that were classically not thought of as surgical candidates. These include patients with rare genetic disorders, electrical status epilepticus in sleep, status epilepticus and the very young patients. Furthermore, epilepsy surgery is not considered as a "last resort" as seizure and cognitive outcomes of surgery are considerably better when done earlier rather than later in relation to the time of onset of epilepsy and age of surgery especially in the context of known focal cortical dysplasia. This article examines the accumulating evidence of the utility of epilepsy surgery in these special circumstances.

Improving surgical outcome with electric source imaging and high field magnetic resonance imaging

While most patients with focal epilepsy present with clear structural abnormalities on standard, 1.5 or 3 T MRI, some patients are MRI-negative. For those, quantitative MRI techniques, such as volumetry, voxel-based morphometry, and relaxation time measurements can aid in finding the epileptogenic focus. High-field MRI, just recently approved for clinical use by the FDA, increases the resolution and, in several publications, was shown to improve the detection of focal cortical dysplasias and mild cortical malformations. For those cases without any tissue abnormality in neuroimaging, even at 7 T, scalp EEG alone is insufficient to delimitate the epileptogenic zone. They may benefit from the use of high-density EEG, in which the increased number of electrodes helps improve spatial sampling. The spatial resolution of even low-density EEG can benefit from electric source imaging techniques, which map the source of the recorded abnormal activity, such as interictal epileptiform discharges, focal slowing, and ictal rhythm. These EEG techniques help localize the irritative, functional deficit, and seizure-onset zone, to better estimate the epileptogenic zone. Combining those technologies allows several drug-resistant cases to be submitted to surgery, increasing the odds of seizure freedom and providing a must needed hope for patients with epilepsy.

Toward a refined genotype-phenotype classification scheme for the international consensus classification of Focal Cortical Dysplasia

Focal Cortical Dysplasia (FCD) is the most common cause of drug-resistant focal epilepsy in children and young adults. The diagnosis of currently defined FCD subtypes relies on a histopathological assessment of surgical brain tissue. The many ongoing challenges in the diagnosis of FCD and their various subtypes mandate, however, continuous research and consensus agreement to develop a reliable classification scheme. Advanced neuroimaging and genetic studies have proven to augment the diagnosis of FCD subtypes and should be considered for an integrated clinico-pathological and molecular classification. In this review, we will discuss the histopathological foundation of the current FCD classification and potential advancements when using genetic analysis of somatic brain mutations in neurosurgically resected brain specimens and postprocessing of presurgical neuroimaging data. Combining clinical, imaging, histopathology, and molecular studies will help to define the disease spectrum better and finally unveil FCD-specific treatment options.

7T MRI with post-processing for the presurgical evaluation of pharmacoresistant focal epilepsy

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.

Quantitative assessment of structural and functional changes in temporal lobe epilepsy with hippocampal sclerosis

Background

Magnetic resonance imaging (MRI) changes in hippocampal sclerosis (HS) could be subtle in a significant proportion of mesial temporal lobe epilepsy (mTLE) patients. In this study, we aimed to document the structural and functional changes in the hippocampus and amygdala seen in HS patients.

Methods

Quantitative features of the hippocampus and amygdala were extracted from structural MRI data in 66 mTLE patients and 28 controls. Structural covariance analysis was undertaken using volumetric data from the amygdala and hippocampus. Functional connectivity (FC) measured using resting intracranial electroencephalography (EEG) was analyzed in 22 HS patients and 16 non-HS disease controls.

Results

Hippocampal atrophy was present in both MRI-positive and MRI-negative HS groups (Mann-Whitney U: 7.61, P<0.01; Mann-Whitney U: 6.51, P<0.01). Amygdala volumes were decreased in the patient group (Mann-Whitney U: 2.92, P<0.05), especially in MRI-negative HS patients (Mann-Whitney U: 2.75, P<0.05). The structural covariance analysis showed the normalized volumes of the amygdala and hippocampus were tightly coupled in both controls and HS patients (ρ_Spearman =0.72, P<0.01). FC analysis indicated that HS patients had significantly increased connectivity (Student's t: 2.58, P=0.03) within the hippocampus but decreased connectivity between the hippocampus and amygdala (Student's t: 3.33, P=0.01), particularly for MRI-negative HS patients.

Conclusions

Quantitative structural changes, including hippocampal atrophy and temporal pole blurring, are present in both MRI-positive and MRI-negative HS patients, suggesting the potential usefulness of incorporating quantitative analyses into clinical practice. HS is characterized by increased intra-hippocampal EEG synchronization and decreased coupling between the hippocampus and amygdala.

Gray Matter Sampling Differences Between Subdural Electrodes and Stereoelectroencephalography Electrodes

Objective: Stereoelectroencephalography (SEEG) has seen a recent increase in popularity in North America; however, concerns regarding the spatial sampling capabilities of SEEG remain. We aimed to quantify and compare the spatial sampling of subdural electrode (SDE) and SEEG implants.

Methods: Patients with drug-resistant epilepsy who underwent invasive monitoring were included in this retrospective case-control study. Ten SEEG cases were compared with ten matched SDE cases based on clinical presentation and pre-implantation hypothesis. To quantify gray matter sampling, MR and CT images were coregistered and a 2.5mm radius sphere was superimposed over the center of each electrode contact. The estimated recording volume of gray matter was defined as the cortical voxels within these spherical models. Paired t-tests were performed to compare volumes and locations of SDE and SEEG recording. A Ripley's K-function analysis was performed to quantify differences in spatial distributions.

Results: The average recording volume of gray matter by each individual contact was similar between the two modalities. SEEG implants sampled an average of 20% more total gray matter, consisted of an average of 17% more electrode contacts, and had 77% more of their contacts covering gray matter within sulci. Insular coverage was only achieved with SEEG. SEEG implants generally consist of discrete areas of dense local coverage scattered across the brain; while SDE implants cover relatively contiguous areas with lower density recording.

Significance: Average recording volumes per electrode contact are similar for SEEG and SDE, but SEEG may allow for greater overall volumes of recording as more electrodes can be routinely implanted. The primary difference lies in the location and distribution of gray matter than can be sampled. The selection between SEEG and SDE implantation depends on sampling needs of the invasive implant.

Seizure outcome after epilepsy surgery for patients with normal MRI: A Single center experience

OBJECTIVE

To analyze the surgical outcome in non-lesional intractable focal epilepsies in our center and to find possible predictors for better outcome.

METHODS

This is a retrospective study for 40 adult patients with intractable focal epilepsy following at KFSHRC-Riyadh, who underwent presurgical evaluation followed by resective surgery and continued follow up for a minimum of 2 years. The surgery outcome was evaluated based on the type of surgical procedure and histopathology results.

RESULTS

Out of all 40 patients studied, seizure freedom was achieved in 19 (47.5 %) and 17 (42.5 %) patients at the first and second year respectively in all non-lesional cases. Seizure freedom in non-lesional temporal lobe surgery was achieved in 10 (45 %) of patients at 2 years, 5 (38 %) in non-lesional frontal lobe patients at 2 years and 8 (44 %), 7 (38 %) for all extratemporal at 1 and 2 years respectively. Good prognosis was seen in patients with localized positron emission tomography (PET), had no aura and had a clear ictal onset either on scalp electroencephalogram (EEG) or subdural invasive electroencephalogram.

SIGNIFICANCE

The best surgical outcome is achievable in patients with non-lesional focal epilepsy. This study highlights the prognostic value of the PET scan and ictal scalp/subdural invasive EEG.

Automated detection and segmentation of focal cortical dysplasias (FCDs) with artificial intelligence: Presentation of a novel convolutional neural network and its prospective clinical validation

PURPOSE

Focal cortical dysplasias (FCDs) represent one of the most frequent causes of pharmaco-resistant focal epilepsies. Despite improved clinical imaging methods over the past years, FCD detection remains challenging, as FCDs vary in location, size, and shape and commonly blend into surrounding tissues without clear definable boundaries. We developed a novel convolutional neural network for FCD detection and segmentation and validated it prospectively on daily-routine MRIs.

MATERIAL AND METHODS

The neural network was trained on 201 T1 and FLAIR 3 T MRI volume sequences of 158 patients with mainly FCDs, regardless of type, and 7 focal PMG. Non-FCD/PMG MRIs, drawn from 100 normal MRIs and 50 MRIs with non-FCD/PMG pathologies, were added to the training. We applied the algorithm prospectively on 100 consecutive MRIs of patients with focal epilepsy from daily clinical practice. The results were compared with corresponding neuroradiological reports and morphometric MRI analyses evaluated by an experienced epileptologist.

RESULTS

Best training results reached a sensitivity (recall) of 70.1 % and a precision of 54.3 % for detecting FCDs. Applied on the daily-routine MRIs, 7 out of 9 FCDs were detected and segmented correctly with a sensitivity of 77.8 % and a specificity of 5.5 %. The results of conventional visual analyses were 33.3 % and 94.5 %, respectively (3/9 FCDs detected); the results of morphometric analyses with overall epileptologic evaluation were both 100 % (9/9 FCDs detected) and thus served as reference.

CONCLUSION

We developed a 3D convolutional neural network with autoencoder regularization for FCD detection and segmentation. Our algorithm employs the largest FCD training dataset to date with various types of FCDs and some focal PMG. It provided a higher sensitivity in detecting FCDs than conventional visual analyses. Despite its low specificity, the number of false positively predicted lesions per MRI was lower than with morphometric analysis. We consider our algorithm already useful for FCD pre-screening in everyday clinical practice.

Automatic Detection of Focal Cortical Dysplasia Type II in MRI: Is the Application of Surface-Based Morphometry and Machine Learning Promising?

Background and Objectives

Focal cortical dysplasia (FCD) is a type of malformations of cortical development and one of the leading causes of drug-resistant epilepsy. Postoperative results improve the diagnosis of lesions on structural MRIs. Advances in quantitative algorithms have increased the identification of FCD lesions. However, due to significant differences in size, shape, and location of the lesion in different patients and a big deal of time for the objective diagnosis of lesion as well as the dependence of individual interpretation, sensitive approaches are required to address the challenge of lesion diagnosis. In this research, a FCD computer-aided diagnostic system to improve existing methods is presented.

Methods

Magnetic resonance imaging (MRI) data were collected from 58 participants (30 with histologically confirmed FCD type II and 28 without a record of any neurological prognosis). Morphological and intensity-based features were calculated for each cortical surface and inserted into an artificial neural network. Statistical examinations evaluated classifier efficiency.

Results

Neural network evaluation metrics—sensitivity, specificity, and accuracy—were 96.7, 100, and 98.6%, respectively. Furthermore, the accuracy of the classifier for the detection of the lobe and hemisphere of the brain, where the FCD lesion is located, was 84.2 and 77.3%, respectively.

Conclusion

Analyzing surface-based features by automated machine learning can give a quantitative and objective diagnosis of FCD lesions in presurgical assessment and improve postsurgical outcomes.

Voxel-based morphometric MRI post-processing and PET/MRI co-registration reveal subtle abnormalities in cingulate epilepsy

OBJECTIVE

Diagnostic challenges exist in the presurgical evaluation of patients with magnetic resonance imaging (MRI) negative cingulate epilepsy (CE) because of the heterogeneity in clinical semiology and lack of localizing findings on scalp electroencephalographic (EEG) recordings. We aimed to examine the neuroimaging characteristics in a consecutive cohort of patients with MRI-negative CE with a focus on two image post-processing methods, including the MRI post-processing morphometric analysis program (MAP) and ¹⁸F-fluorodeoxyglucose-positron emission tomography-MRI (PET/MRI) co-registration.

METHODS

Included in this retrospective study were patients with MRI-negative CE who met the following criteria: negative on preoperative MRI, invasive EEG (iEEG) confirmed cingulate gyrus-onset seizures, surgical resection of the cingulate gyrus with/without adjacent cortex, and seizure-free for more than 12 months. MAP and PET/MRI co-registration were performed and investigated by comparison to ictal intracranial EEG findings. Other characteristics obtained from scalp EEG, magnetoencephalography (MEG), iEEG, and pathological study were also reported.

RESULTS

Ten patients were included, of which eight were diagnosed with anterior CE, one with middle CE, and one with posterior CE. The semiology included fear, embarrassment, vocalization, ictal pouting, asymmetric tonic posture, hypermotor, and automatism. Scalp EEG revealed unilateral or bilateral frontal-temporal onset. MEG localized the dipoles correctly in one patient (1/10). MAP detected subtle abnormalities in regions concordant with iEEG onset in seven patients (7/10) while PET/MRI co-registration revealed focal concordant hypometabolism in five patients (5/10). Combining MAP with PET/MRI co-registration improved the detection rate to 90 % in this cohort. The pathology was focal cortical dysplasia (FCD), including FCD type IIA in three, type IIB in three, and type I in four.

CONCLUSION

MAP and PET/MRI co-registration show promising results in identifying subtle FCD abnormalities in CE with negative results on conventional MRI, which can be otherwise challenging. More importantly, a combination of MRI post-processing and PET/MRI co-registration can greatly improve the identification of epileptic abnormalities, which can be used as surgical target. MAP and PET/MRI co-registration should be incorporated into the routine presurgical evaluation.

Novel tonometer device distinguishes brain stiffness in epilepsy surgery

Complete surgical resection of abnormal brain tissue is the most important predictor of seizure freedom following surgery for cortical dysplasia. While lesional tissue is often visually indiscernible from normal brain, anecdotally, it is subjectively stiffer. We report the first experience of the use of a digital tonometer to understand the biomechanical properties of epilepsy tissue and to guide the conduct of epilepsy surgery. Consecutive epilepsy surgery patients (n = 24) from UCLA Mattel Children’s Hospital were recruited to undergo intraoperative brain tonometry at the time of open craniotomy for epilepsy surgery. Brain stiffness measurements were corrected with abnormalities on neuroimaging and histopathology using mixed-effects multivariable linear regression. We collected 249 measurements across 30 operations involving 24 patients through the pediatric epilepsy surgery program at UCLA Mattel Children’s Hospital. On multivariable mixed-effects regression, brain stiffness was significantly associated with the presence of MRI lesion (β = 32.3, 95%CI 16.3–48.2; p < 0.001), severity of cortical disorganization (β = 19.8, 95%CI 9.4–30.2; p = 0.001), and recent subdural grid implantation (β = 42.8, 95%CI 11.8–73.8; p = 0.009). Brain tonometry offers the potential of real-time intraoperative feedback to identify abnormal brain tissue with millimeter spatial resolution. We present the first experience with this novel intraoperative tool for the conduct of epilepsy surgery. A carefully designed prospective study is required to elucidate whether the clinical application of brain tonometry during resective procedures could guide the area of resection and improve seizure outcomes.

Surgery for Radiologically Normal-Appearing Temporal Lobe Epilepsy in a Centre with Limited Resources

Approximately 26-30% of temporal lobe epilepsy (TLE) cases display a normal-appearing magnetic resonance image (MRI) leading to difficulty in determining the epileptogenic focus. This causes challenges in surgical management, especially in countries with limited resources. The medical records of 154 patients with normal-appearing MRI TLE who underwent epilepsy surgery between July 1999 and July 2019 in our epilepsy centre in Indonesia were examined. The primary outcome was the Engel classification of seizures. Anterior temporal lobectomy was performed in 85.1% of the 154 patients, followed by selective amygdalo-hippocampectomy and resection surgery. Of 82 patients (53.2%), Engel Class I result was reported in 69.5% and Class II in 25.6%. The median seizure-free period was 13 (95% CI,12.550-13.450) years, while the seizure-free rate at 5 and 12 years follow-up was 96.3% and 69.0%, respectively. Patients with a sensory aura had better seizure-free outcome 15 (11.575-18.425) years. Anterior temporal lobectomy and selective amygdala-hippocampectomy gave the same favourable outcome. Despite the challenges of surgical procedures for normal MRI TLE, our outcome has been favourable. This study suggests that epilepsy surgery in normal MRI TLE can be performed in centres with limited resources.

Surgical Technique and Outcome of Extensive Frontal Lobectomy for Treatment of Intracable Non-lesional Frontal Lobe Epilepsy

Although extensive frontal lobectomy (eFL) is a common surgical procedure for intractable frontal lobe epilepsy (FLE), there have been very few reports regarding surgical techniques for eFL. This article provides step-by-step descriptions of our surgical technique for non-lesional FLE. Sixteen patients undergoing eFL were included in this study. The goals were to maximize gray matter removal, including the orbital gyrus and subcallosal area, and to spare the primary motor and premotor cortexes and anterior perforated substance. The eFL consists of three steps: (1) positioning, craniotomy, and exposure; (2) lateral frontal lobe resection; and (3), resection of the rectus gyrus and orbital gyrus. Resection ahead of bregma allows preservation of motor and premotor area function. To remove the orbital gyrus preserving anterior perforated substance, it is essential to visualize the olfactory trigone beneath the pia. It is important to observe the surface of the contralateral medial frontal lobe for complete removal of the subcallosal area of the frontal lobe. Thirteen patients (81.25%) became seizure-free and three patients (18.75%) continued to have seizures. None of the patients showed any complications. The eFL is a good surgical technique for the treatment of intractable non-lesional FLE. For treatment of epilepsy by eFL, it is important to resect the non-eloquent area of the frontal lobe as much as possible with preservation of the eloquent cortex.

Long term sequelae of amygdala enlargement in temporal lobe epilepsy

PURPOSE

Amygdala enlargement (AE) has been reported in drug resistant lesional and non-lesional temporal lobe epilepsy (TLE). Its contribution to development of intractability of epilepsy is at best uncertain. Our aim was to study the natural course of AE in a heterogenous group of TLE patients with follow-up imaging and clinical outcomes.

METHODS

A prospective observational study in patients with TLE with imaging features of AE recruited from epilepsy clinics between 1994 and 2018. Demographic data, details of epilepsy syndrome, outcomes and follow up neuroimaging were extracted.

RESULTS

Forty-two patients were recruited including 19 males (45 %). Mean age at onset of epilepsy was 30.6 years and mean duration of epilepsy was 19.9 years. On MRI, 33 patients had isolated unilateral AE and eleven had AE with hippocampal enlargement (HE). Twenty (48 %) underwent temporal resections with most common histopathology being amygdalar gliosis (40 %). Engel Class IA outcome at last follow up (mean, 10 years) was 60 %. Thirty-four patients had neuroimaging follow up of at least 1 year (mean, 5 years). AE resolved in 6, persisted in 25, evolved into bilateral HS in 1, bilateral mesial temporal atrophy in 1 and ipsilateral mesial temporal atrophy in 1. Resolution of AE was associated with better seizure free outcomes (p = 0.013).

CONCLUSIONS

TLE with AE is associated with favourable prognosis yet not benign. Over 50 % were drug resistant and surgical outcomes were similar to mTLE. Resolution of AE on follow up neuroimaging was associated with better seizure free outcomes.

Automated detection of hippocampal sclerosis using clinically empirical and radiomics features

OBJECTIVE

Temporal lobe epilepsy is a common form of epilepsy that might be amenable to surgery. However, magnetic resonance imaging (MRI)-negative hippocampal sclerosis (HS) can hamper early diagnosis and surgical intervention for patients in clinical practice, resulting in disease progression. Our aim was to automatically detect and evaluate the structural alterations of HS.

METHODS

Eighty patients with pharmacoresistant epilepsy and histologically proven HS and 80 healthy controls were included in the study. Two automated classifiers relying on clinically empirical and radiomics features were developed to detect HS. Cross-validation was implemented on all participants, and specificity was assessed in the 80 controls. The performance, robustness, and clinical utility of the model were also evaluated. Structural analysis was performed to investigate the morphological abnormalities of HS.

RESULTS

The computational model based on clinical empirical features showed excellent performance, with an area under the curve (AUC) of 0.981 in the primary cohort and 0.993 in the validation cohort. One of the features, gray-white matter boundary blurring in the temporal pole, exhibited the highest weight in model performance. Another model based on radiomics features also showed satisfactory performance, with AUC of 0.997 in the primary cohort and 0.978 in the validation cohort. In particular, the model improved the detection rate of MRI-negative HS to 96.0%. The novel feature of cortical folding complexity of the temporal pole not only played a crucial role in the classifier but also had significant correlation with disease duration.

SIGNIFICANCE

Machine learning with quantitative clinical and radiomics features is shown to improve HS detection. HS-related structural alterations were similar in the MRI-positive and MRI-negative HS patient groups, indicating that misdiagnosis originates mainly from empirical interpretation. The cortical folding complexity of the temporal pole is a potentially valuable feature for exploring the nature of HS.

MP2RAGE multispectral voxel-based morphometry in focal epilepsy

We assessed the applicability of MP2RAGE for voxel‐based morphometry. To this end, we analyzed its brain tissue segmentation characteristics in healthy subjects and the potential for detecting focal epileptogenic lesions (previously visible and nonvisible). Automated results and expert visual interpretations were compared with conventional VBM variants (i.e., T1 and T1 + FLAIR). Thirty‐one healthy controls and 21 patients with focal epilepsy were recruited. 3D T1‐, T2‐FLAIR, and MP2RAGE images (consisting of INV1, INV2, and MP2 maps) were acquired on a 3T MRI. The effects of brain tissue segmentation and lesion detection rates were analyzed among single‐ and multispectral VBM variants. MP2‐single‐contrast gave better delineation of deep, subcortical nuclei but was prone to misclassification of dura/vessels as gray matter, even more than conventional‐T1. The addition of multispectral combinations (INV1, INV2, or FLAIR) could markedly reduce such misclassifications. MP2 + INV1 yielded generally clearer gray matter segmentation allowing better differentiation of white matter and neighboring gyri. Different models detected known lesions with a sensitivity between 60 and 100%. In non lesional cases, MP2 + INV1 was found to be best with a concordant rate of 37.5%, specificity of 51.6% and concordant to discordant ratio of 0.60. In summary, we show that multispectral MP2RAGE VBM (e.g., MP2 + INV1, MP2 + INV2) can improve brain tissue segmentation and lesion detection in epilepsy.

Prognostic factors of postoperative seizure outcome in patients with temporal lobe epilepsy and normal magnetic resonance imaging

PURPOSE

To retrospectively analyse a single-centre consecutive surgical series of patients with temporal lobe epilepsy (TLE) and negative MRI. To identify factors associated with postoperative seizure outcome among several presurgical, surgical and postsurgical variables.

METHODS

Clinical records of 866 patients who received temporal lobe resections and with a minimum follow-up of 12 months were retrospectively searched for MRI-negative cases. Anamnestic, clinical, neurophysiological, surgical, histopathological and postsurgical data were collected. Seizure outcome was categorised as favourable (Engel's class I) and unfavourable (Engel's classes II-IV). Uni- and multivariate statistical analysis was performed to identify variables having a significant association with seizure outcome.

RESULTS

Forty-eight patients matched the inclusion criteria. 26 (54.1%) patients required invasive EEG evaluation with Stereo-electro-encephalography (SEEG) before surgery. Histological evaluation was unremarkable in 34 cases (70.8%), revealed focal cortical dysplasias in 13 cases and hippocampal sclerosis in 2. 28 (58.3%) patients were in Engel's class I after a mean follow-up of 82 months (SD ± 74; range 12-252). Multivariate analysis indicated auditory aura, contralateral diffusion of the discharge at Video-EEG monitoring and use of ¹⁸F-FDG PET as variables independently associated with seizure outcome.

CONCLUSION

Carefully selected patients with MRI-negative TLE can be good candidates for surgery. Surgery should be considered with caution in patients with clinical features of neocortical seizure onset and contralateral propagation of the discharge. Use of ¹⁸F-FDG PET may be helpful to improve SEEG and surgical strategies. The presented data help in optimising the selection of patients with MRI-negative TLE with good chances to benefit from surgery.

Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: From focal lesions to macroscale networks

Epilepsy is among the most common chronic neurologic disorders, with 30%-40% of patients having seizures despite antiepileptic drug treatment. The advent of brain imaging and network analyses has greatly improved the understanding of this condition. In particular, developments in magnetic resonance imaging (MRI) have provided measures for the noninvasive characterization and detection of lesions causing epilepsy. MRI techniques can probe structural and functional connectivity, and network analyses have shaped our understanding of whole-brain anomalies associated with focal epilepsies. This review considers the progress made by neuroimaging and connectomics in the study of drug-resistant epilepsies due to focal substrates, particularly temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal lobe epilepsies associated with malformations of cortical development. In these disorders, there is evidence of widespread disturbances of structural and functional connectivity that may contribute to the clinical and cognitive prognosis of individual patients. It is hoped that studying the interplay between macroscale network anomalies and lesional profiles will improve our understanding of focal epilepsies and assist treatment choices.

7T MRI in epilepsy patients with previously normal clinical MRI exams compared against healthy controls

Objective

To compare by 7 Tesla (7T) magnetic resonance imaging (MRI) in patients with focal epilepsy who have non-lesional clinical MRI scans with healthy controls.

Methods

37 patients with focal epilepsy, based on clinical and electroencephalogram (EEG) data, with non-lesional MRIs at clinical field strengths and 21 healthy controls were recruited for the 7T imaging study. The MRI protocol consisted of high resolution T₁-weighted, T₂-weighted and susceptibility weighted imaging sequences of the entire cortex. The images were read by two neuroradiologists, who were initially blind to clinical data, and then reviewed a second time with knowledge of the seizure onset zone.

Results

A total of 25 patients had findings with epileptogenic potential. In five patients these were definitely related to their epilepsy, confirmed through surgical intervention, in three they co-localized to the suspected seizure onset zone and likely caused the seizures. In seven patients the imaging findings co-localized to the suspected seizure onset zone but were not the definitive cause, and ten had cortical lesions with epileptogenic potential that did not localize to the suspected seizure onset zone. There were multiple other findings of uncertain significance found in both epilepsy patients and healthy controls. The susceptibility weighted imaging sequence was instrumental in guiding more targeted inspection of the other structural images and aiding in the identification of cortical lesions.

Significance

Information revealed by the improved resolution and enhanced contrast provided by 7T imaging is valuable in noninvasive identification of lesions in epilepsy patients who are non-lesional at clinical field strengths.

Voxel-based morphometric magnetic resonance imaging postprocessing in non-lesional pediatric epilepsy patients using pediatric normal databases

BACKGROUND AND PURPOSE

Pre-surgical evaluation of pediatric patients with drug-resistant focal epilepsy and negative (non-lesional) magnetic resonance imaging (MRI) is particularly challenging. Focal cortical dysplasia (FCD), a frequent pathological substrate in such setting, may be subtle on MRI and evade detection. The aim of this study was to use voxel-based MRI postprocessing to improve the detection of subtle FCD in pediatric surgical candidates.

METHODS

A consecutive cohort of pediatric patients undergoing pre-surgical evaluation with a negative MRI by visual analysis was included. MRI postprocessing was performed using a voxel-based morphometric analysis program (MAP) on T1-weighted volumetric MRI, with comparison to an age-specific normal pediatric database. The pertinence of MAP-positive areas was confirmed by surgical outcome and pathology.

RESULTS

A total of 78 patients were included. Forty-four patients (56%) had positive MAP regions. Complete resection of the MAP-positive regions was positively associated with seizure-free outcome compared with the no/partial resection group (P < 0.001). Patients with no/partial resection of the MAP-positive regions had worse seizure outcomes than the MAP-negative group (P = 0.002). The MAP-positive rate was 100%, 77%, 63% and 40% in the 3-5, 5-10, 10-15 and 15-21 year age groups, respectively. MAP-positive rates were 45% in patients with temporal resection and 63% in patients with extratemporal resection. Complete resection of the MAP-positive regions was positively associated with seizure-free outcome in the extratemporal group (P = 0.001) but not in the temporal group (P = 0.070).

CONCLUSION

Our data suggest the importance of using MRI postprocessing in the pre-surgical evaluation process of pediatric epilepsy patients with apparently normal MRI.