Voxel-based morphometric magnetic resonance imaging (MRI) postprocessing in MRI-negative epilepsies

External validation of automated focal cortical dysplasia detection using morphometric analysis

OBJECTIVE

Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric analysis of T1-weighted images, for example, using the Morphometric Analysis Program (v2018; MAP18), which was introduced in 2005, independently validated for its clinical benefits, and successfully integrated in standard presurgical workflows of numerous epilepsy centers worldwide. Here we aimed to develop an artificial neural network (ANN) classifier for robust automated detection of FCDs based on these morphometric maps and probe its generalization performance in a large, independent data set.

METHODS

In this retrospective study, we created a feed-forward ANN for FCD detection based on the morphometric output maps of MAP18. The ANN was trained and cross-validated on 113 patients (62 female, mean age ± SD =29.5 ± 13.6 years) with manually segmented FCDs and 362 healthy controls (161 female, mean age ± SD =30.2 ± 9.6 years) acquired on 13 different scanners. In addition, we validated the performance of the trained ANN on an independent, unseen data set of 60 FCD patients (28 female, mean age ± SD =30 ± 15.26 years) and 70 healthy controls (42 females, mean age ± SD = 40.0 ± 12.54 years).

RESULTS

In the cross-validation, the ANN achieved a sensitivity of 87.4% at a specificity of 85.4% on the training data set. On the independent validation data set, our method still reached a sensitivity of 81.0% at a comparably high specificity of 84.3%.

SIGNIFICANCE

Our method shows a robust automated detection of FCDs and performance generalizability, largely independent of scanning site or MR-sequence parameters. Taken together with the minimal input requirements of a standard T1 image, our approach constitutes a clinically viable and useful tool in the presurgical diagnostic routine for drug-resistant focal epilepsy.

Ultra-high field magnetic resonance imaging in human epilepsy: A systematic review

RATIONALE

Resective epilepsy surgery is an evidence-based curative treatment option for patients with drug-resistant focal epilepsy. The major preoperative predictor of a good surgical outcome is detection of an epileptogenic lesion by magnetic resonance imaging (MRI). Application of ultra-high field (UHF) MRI, i.e. field strengths ≥ 7 Tesla (T), may increase the sensitivity to detect such a lesion.

METHODS

A keyword search strategy was submitted to Pubmed, EMBASE, Cochrane Database and clinicaltrials.gov to select studies on UHF MRI in patients with epilepsy. Follow-up study selection and data extraction were performed following PRISMA guidelines. We focused on I) diagnostic gain of UHF- over conventional MRI, II) concordance of MRI-detected lesion, seizure onset zone and surgical decision-making, and III) postoperative histopathological diagnosis and seizure outcome.

RESULTS

Sixteen observational cohort studies, all using 7T MRI were included. Diagnostic gain of 7T over conventional MRI ranged from 8% to 67%, with a pooled gain of 31%. Novel techniques to visualize pathological processes in epilepsy and lesion detection are discussed. Seizure freedom was achieved in 73% of operated patients; no seizure outcome comparison was made between 7T MRI positive, 7T negative and 3T positive patients. 7T could influence surgical decision-making, with high concordance of lesion and seizure onset zone. Focal cortical dysplasia (54%), hippocampal sclerosis (12%) and gliosis (8.1%) were the most frequently diagnosed histopathological entities.

SIGNIFICANCE

UHF MRI increases, yet variably, the sensitivity to detect an epileptogenic lesion, showing potential for use in clinical practice. It remains to be established whether this results in improved seizure outcome after surgical treatment. Prospective studies with larger cohorts of epilepsy patients, uniform scan and sequence protocols, and innovative post-processing technology are equally important as further increasing field strengths. Besides technical ameliorations, improved correlation of imaging features with clinical semiology, histopathology and clinical outcome has to be established.

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.

Distinguishing type II focal cortical dysplasias from normal cortex: A novel normative modeling approach

OBJECTIVE

Focal cortical dysplasias (FCDs) are a common cause of apparently non-lesional drug-resistant focal epilepsy. Visual detection of subtle FCDs on MRI is clinically important and often challenging. In this study, we implement a set of 3D local image filters adapted from computer vision applications to characterize the appearance of normal cortex surrounding the gray-white junction. We create a normative model to serve as the basis for a novel multivariate constrained outlier approach to automated FCD detection.

METHODS

Standardized MPRAGE, T₂ and FLAIR MR images were obtained in 15 patients with radiologically or histologically diagnosed FCDs and 30 healthy volunteers. Multiscale 3D local image filters were computed for each MR contrast then sampled onto the gray-white junction surface. Using an iterative Gaussianization procedure, we created a normative model of cortical variability in healthy volunteers, allowing for identification of outlier regions and estimates of similarity in normal cortex and FCD lesions. We used a constrained outlier approach following local normalization to automatically detect FCD lesions based on projection onto the mean FCD feature vector.

RESULTS

FCDs as well as some normal cortical regions such as primary sensorimotor and paralimbic regions appear as outliers. Regions such as the paralimbic regions and the anterior insula have similar features to FCDs. Our constrained outlier approach allows for automated FCD detection with 80% sensitivity and 70% specificity.

SIGNIFICANCE

A normative model using multiscale local image filters can be used to describe the normal cortical variability. Although FCDs appear similar to some cortical regions such as the anterior insula and paralimbic cortices, they can be identified using a constrained outlier detection approach. Our method for detecting outliers and estimating similarity is generic and could be extended to identification of other types of lesions or atypical cortical areas.

Improved detection of focal cortical dysplasia in normal-appearing FLAIR images using a Bayesian classifier

PURPOSE

Focal cortical dysplasia (FCD) is a malformation of cortical development that often causes pharmacologically intractable epilepsy. However, FCD lesions are frequently characterized by minor structural abnormalities that can easily go unrecognized, making diagnosis difficult. Therefore, many epileptic patients have had pathologically confirmed FCD lesions that appeared normal in pre-surgical fluid-attenuated inversion recovery (FLAIR) magnetic resonance (MR) studies. Such lesions are called "FLAIR-negative." This study aimed to improve the detection of histopathologically verified FCD in a sample of patients without visually appreciable lesions.

METHODS

The technique first extracts a series of features from a FLAIR image. Then, three naive Bayesian classifiers with probability (NBCP) are trained based on different numbers of feature maps to classify voxels as lesional or healthy voxels and assign the lesions a probability of correct classification. This method classifies the three-dimensional (3D) images of all patients using leave-one-out cross-validation (LOOCV). Finally, the 3D lesion probability map, including epileptogenic lesions, is obtained by removing false-positive voxel outliers using the morphological method. The performance of the NBCP was assessed for quantitative analysis by specificity, accuracy, recall, precision, and Dice coefficient in subject-wise, lesion-wise, and voxel-wise manners.

RESULTS

The best detection results were obtained by using four features: cortical thickness, symmetry, K-means, and modified texture energy. There were eight lesions in seven patients. The subject-wise sensitivity of the proposed method was 85.71% (6/7). Seven out of eight lesions were detected, so the lesion-wise sensitivity was 87.50% (7/8). No significant differences in effectiveness were found between automated lesion detection using four features and lesion detection using manual segmentation, as voxels were quantitatively analyzed in terms of specificity (mean ± SD = 99.64 ± 0.13), accuracy (mean ± SD = 99.62 ± 0.14), recall (mean ± SD = 73.27 ± 26.11), precision (mean ± SD = 11.93 ± 8.16), and Dice coefficient (mean ± SD = 22.82 ± 15.57).

CONCLUSION

We developed a novel automatic voxel-based method to improve the detection of FCD FLAIR-negative lesions. To the best of our knowledge, this study is the first to detect FCD lesions that appear normal in pre-surgical 3D high-resolution FLAIR images alone with a limited number of radiomics features. We optimized the algorithm and selected the best prior probability to improve the detection. For non-temporal lobe epilepsy (non-TLE) patients, lesions could be accurately located, although there were still false-positive areas.

Brain MRI post-processing with MAP07 in the preoperative evaluation of patients with pharmacoresistant epilepsy - Croatian single centre experience

OBJECTIVE

This study aimed to determine the role of brain MRI post-processing method MAP07 (Morphometric Analysis Program) in detecting epileptogenic brain lesions in patients with pharmacoresistant epilepsy (PE). MAP07 is a sophisticated diagnostic program that offers several morphometric maps and facilitates the detection and localization of hippocampal sclerosis (HS), focal cortical dysplasias (FCD), and other types of cortical malformations, which could be undetected by conventional visual MRI analysis (CVA).

METHODS

120 patients aged > 16 years with PE have been recruited. 3 T MRI was performed according to epilepsy imaging protocol followed by image postprocessing with a fully automated MATLAB script, MAP07, by applying SPM5 algorithms. Statistical analysis was performed in IBM SPSS Statistics, version 25.0.

RESULTS

Analysis in our patients showed a high sensitivity of MAP07 with low specificity and with a high proportion of false-positive patients. After MRI analysis, out of 120 patients, 32 were found to have no structural abnormalities by conventional visual analysis in whom after MAP07 in 5 patients structural lesions were found (in one HS, in one FCD, in two perinatal vascular lesions, and in one hippocampal hyperintensity). There was a quite high overall coincidence of the findings of MAP07 and MRI for the detection of FCD, HS, perinatal ischemia/chronic vascular lesions, heterotopias, and polymicrogyria (kappa coefficient above 0.700).

CONCLUSIONS

MAP07 analysis is a useful, additional, and automated method that may guide re-evaluation of MRI by highlighting suspicious cortical regions, as a complementary method to CVA, by enhancing the visualization of cortical malformations and lesions.

Connectome biomarkers of drug-resistant epilepsy

Drug-resistant epilepsy (DRE) considerably affects patient health, cognition, and well-being, and disproportionally contributes to the overall burden of epilepsy. The most common DRE syndromes are temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal epilepsy related to cortical malformations. Both syndromes have been traditionally considered as "focal," and most patients benefit from brain surgery for long-term seizure control. However, increasing evidence indicates that many DRE patients also present with widespread structural and functional network disruptions. These anomalies have been suggested to relate to cognitive impairment and prognosis, highlighting their importance for patient management. The advent of multimodal neuroimaging and formal methods to quantify complex systems has offered unprecedented ability to profile structural and functional brain networks in DRE patients. Here, we performed a systematic review on existing DRE network biomarker candidates and their contribution to three key application areas: (1) modeling of cognitive impairments, (2) localization of the surgical target, and (3) prediction of clinical and cognitive outcomes after surgery. Although network biomarkers hold promise for a range of clinical applications, translation of neuroimaging biomarkers to the patient's bedside has been challenged by a lack of clinical and prospective studies. We therefore close by highlighting conceptual and methodological strategies to improve the evaluation and accessibility of network biomarkers, and ultimately guide clinically actionable decisions.

Value of 7T MRI and post-processing in patients with nonlesional 3T MRI undergoing epilepsy presurgical evaluation

OBJECTIVE

Ultra-high-field 7-Tesla (7T) magnetic resonance imaging (MRI) offers increased signal-to-noise and contrast-to-noise ratios, which may improve visualization of cortical malformations. We aim to assess the clinical value of in vivo structural 7T MRI and its post-processing for the noninvasive identification of epileptic brain lesions in patients with pharmacoresistant epilepsy and nonlesional 3T MRI who are undergoing presurgical evaluation.

METHODS

Sixty-seven patients were included who had nonlesional 3T MRI by official radiology report. Epilepsy protocols were used for the 3T and 7T acquisitions. Post-processing of the 7T T1-weighted magnetization-prepared two rapid acquisition gradient echoes sequence was performed using the morphometric analysis program (MAP) with comparison to a normal database consisting of 50 healthy controls. Review of 7T was performed by an experienced board-certified neuroradiologist and at the multimodal patient management conference. The clinical significance of 7T findings was assessed based on intracranial electroencephalography (ICEEG) ictal onset, surgery, postoperative seizure outcomes, and histopathology.

RESULTS

Unaided visual review of 7T detected previously unappreciated subtle lesions in 22% (15/67). When aided by 7T MAP, the total yield increased to 43% (29/67). The location of the 7T-identified lesion was identical to or contained within the ICEEG ictal onset in 13 of 16 (81%). Complete resection of the 7T-identified lesion was associated with seizure freedom (P = .03). Histopathology of the 7T-identified lesions encountered mainly focal cortical dysplasia (FCD). 7T MAP yielded 25% more lesions (6/24) than 3T MAP, and showed improved conspicuity in 46% (11/24).

SIGNIFICANCE

Our data suggest a major benefit of 7T with post-processing for detecting subtle FCD lesions for patients with pharmacoresistant epilepsy and nonlesional 3T MRI.

[Surgical treatment of epilepsy in children with focal cortical dysplasia]

OBJECTIVE

Surgery is the first-line treatment option in children with FCD and refractory epilepsy, but the rate of success and patient numbers who became free of seizures vary widely from series to series.

STUDY AIMS

To elicit variables affecting the outcome and predicting achievement of the long-term seizure-free status.

MATERIAL AND METHODS

One hundred sixty-nine children with cortical dysplasia and DR-epilepsy underwent surgery Preoperative evaluation included prolonged video-EEG and MRI (in all patients) and neuropsychological testing when possible. Fourteen patients underwent invasive EEG, fMRI and MEG were used also in some cases. Including 27 repeat procedures the list of overall 196 surgeries performed consists of: cortectomy (lesionectomy with or without adjacent epileptogenic cortices) – in 116 cases; lobectomy – in 46; and various disconnective procedures – in 34 patients. Almost routinely employed intraoperative ECOG (134 surgeries) was combined with stimulation and/or SSEP in 47 cases to map eloquent cortex (with CST-tracking in some). A new permanent and not anticipated neurological deficit developed post-surgery in 5 cases (2,5%). Patients were follow-upped using video-EEG and MRI and FU which lasts more than 2 years (median – 3 years) is known in 56 cases. Thirty-two children were free of seizures at the last check (57,2% rate of Engel IA). A list of variables regarding patients’ demography, seizure type, lesion pathology and localization, and those related to surgery and its extent were evaluated to figure out anyone associated with favorable outcome.

RESULTS

Both Type II FCDs and their anatomically complete excision are positive predictors for favorable outcome and achievement of SF-status (p<0,05). Residual epileptic activity on immediate post-resection ECOG do not affect the outcome.

CONCLUSION

Patients with Type II FCD, particularly with Type IIb malformations are the best candidates for curative surgery, including cases with lesions in brain eloquent areas. Kids with Type I FCD have much less chances to become free of seizures when attempting focal cortectomy. However, some of them with early onset catastrophic epilepsies may benefit from larger surgeries using lobectomy or various disconnections.

Improved detection of focal cortical dysplasia using a novel 3D imaging sequence: Edge-Enhancing Gradient Echo (3D-EDGE) MRI

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Detection of focal cortical dysplasia remains a substantial challenge in radiology.

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3D-EDGE is a novel MR method to directly image abnormalities of gray-white boundary.

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3D-EDGE had a significantly higher contrast for FCD than FLAIR and MP2RAGE.

Epilepsy is a common neurological disorder with focal cortical dysplasia (FCD) being one of the most common lesional causes. Detection of FCD by MRI is a major determinant of surgical outcome. Evolution of MRI sequences and hardware has greatly increased the detection rate of FCD, but these gains have largely been related to the more visible Type IIb FCD, with Type I and IIa remaining elusive. While most sequence improvements have relied on increasing contrast between gray and white matter, we propose a novel imaging approach, 3D Edge-Enhancing Gradient Echo (3D-EDGE), to directly image the gray-white boundary. By acquiring images at an inversion time where gray and white matter have equal signal but opposite phases, voxels with a mixture of gray and white matter (e.g., at the gray-white boundary) will have cancellation of longitudinal magnetization producing a thin area of signal void at the normal boundary. By creating greater sensitivity for minor changes in T1 relaxation, microarchitectural abnormalities present in FCD produce greater contrast than on other common MRI sequences. 3D-EDGE had a significantly greater contrast ratio between lesion and white matter for FCD compared to MP2RAGE (98% vs 17%; p = 0.0006) and FLAIR (98% vs 19%; p = 0.0006), which highlights its potential to improve outcomes in epilepsy. We present a discussion of the framework for 3D-EDGE, optimization strategies, and analysis of a series of FCDs to highlight the benefit of 3D-EDGE in FCD detection compared to commonly used sequences in epilepsy.

EEG Source Imaging (ESI) utility in clinical practice

Epilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73-91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.

Planning stereoelectroencephalography using automated lesion detection: Retrospective feasibility study

Objective

This retrospective, cross‐sectional study evaluated the feasibility and potential benefits of incorporating deep‐learning on structural magnetic resonance imaging (MRI) into planning stereoelectroencephalography (sEEG) implantation in pediatric patients with diagnostically complex drug‐resistant epilepsy. This study aimed to assess the degree of colocalization between automated lesion detection and the seizure onset zone (SOZ) as assessed by sEEG.

Methods

A neural network classifier was applied to cortical features from MRI data from three cohorts. (1) The network was trained and cross‐validated using 34 patients with visible focal cortical dysplasias (FCDs). (2) Specificity was assessed in 20 pediatric healthy controls. (3) Feasibility of incorporation into sEEG implantation plans was evaluated in 34 sEEG patients. Coordinates of sEEG contacts were coregistered with classifier‐predicted lesions. sEEG contacts in seizure onset and irritative tissue were identified by clinical neurophysiologists. A distance of <10 mm between SOZ contacts and classifier‐predicted lesions was considered colocalization.

Results

In patients with radiologically defined lesions, classifier sensitivity was 74% (25/34 lesions detected). No clusters were detected in the controls (specificity = 100%). Of the total 34 sEEG patients, 21 patients had a focal cortical SOZ, of whom eight were histopathologically confirmed as having an FCD. The algorithm correctly detected seven of eight of these FCDs (86%). In patients with histopathologically heterogeneous focal cortical lesions, there was colocalization between classifier output and SOZ contacts in 62%. In three patients, the electroclinical profile was indicative of focal epilepsy, but no SOZ was localized on sEEG. In these patients, the classifier identified additional abnormalities that had not been implanted.

Significance

There was a high degree of colocalization between automated lesion detection and sEEG. We have created a framework for incorporation of deep‐learning–based MRI lesion detection into sEEG implantation planning. Our findings support the prospective evaluation of automated MRI analysis to plan optimal electrode trajectories.

Morphometric MRI Analysis: Improved Detection of Focal Cortical Dysplasia Using the MP2RAGE Sequence

BACKGROUND AND PURPOSE

Focal cortical dysplasias are the most common resected epileptogenic lesions in children and the third most common lesion in adults, but they are often subtle and frequently overlooked on MR imaging. The purpose of this study was to evaluate whether MP2RAGE-based morphometric MR imaging analysis is superior to MPRAGE-based analysis in the detection of focal cortical dysplasia.

MATERIALS AND METHODS

MPRAGE and MP2RAGE datasets were acquired in a consecutive series of 640 patients with epilepsy. Datasets were postprocessed using the Morphometric Analysis Program to generate morphometric z score maps such as junction, extension, and thickness images based on both MPRAGE and MP2RAGE images. Focal cortical dysplasia lesions were manually segmented in the junction images, and volumes and mean z scores of the lesions were measured.

RESULTS

Of 21 focal cortical dysplasias discovered, all were clearly visible on MP2RAGE junction images, whereas 2 were not visible on MPRAGE junction images. In all except 4 patients, the volume of the focal cortical dysplasia was larger and mean lesion z scores were higher on MP2RAGE junction images compared with the MPRAGE-based images (P = .005, P = .013).

CONCLUSIONS

In this study, MP2RAGE-based morphometric analysis created clearer output maps with larger lesion volumes and higher z scores than the MPRAGE-based analysis. This new approach may improve the detection of subtle, otherwise overlooked focal cortical dysplasia.

Merging Magnetoencephalography into Epilepsy Presurgical Work-up Under the Framework of Multimodal Integration

Multimodal image integration is the procedure that puts together imaging data from multiple sources into the same space by a computerized registration process. This procedure is relevant to patients with difficult-to-localize epilepsy undergoing presurgical evaluation, who typically have many tests performed, including MR imaging, PET, ictal single-photon emission computed tomography, magnetoencephalography (MEG), and intracranial electroencephalogram (EEG). This article describes the methodology of such integration, focusing on integration of MEG. Also discussed is the clinical value of integration of MEG, in terms of planning of intracranial EEG implantation, interpretation of intracranial EEG data, planning of final resection, and addressing surgical failures.

Pilot Study of Voxel-Based Morphometric MRI Post-processing in Patients With Non-lesional Operculoinsular Epilepsy

Objective: The aim of this study was to use voxel-based MRI post-processing in detection of subtle FCD in drug-resistant operculoinsular epilepsy patients with negative presurgical MRI, and by combining magnetoencephalography (MEG) to improve the localization of epileptogenic zone.

Methods: Operculoinsular epilepsy patients with a negative presurgical MRI were included in this study. MRI post-processing was performed using a Morphometric Analysis Program (MAP) on T1-weighted volumetric MRI. Clinical information including semiology, MEG, scalp electroencephalogram (EEG), intracranial EEG and surgical strategy was retrospectively reviewed. The pertinence of MAP-positive areas was confirmed by surgical outcome and pathology.

Results: A total of 20 patients were diagnosed with operculoinsular epilepsy had non-lesional MRI during 2010–2018, of which 11 patients with resective surgeries were included. MEG showed clusters of single equivalent current dipole (SECD) in inferior frontal regions in five patients and temporal-insular/ frontal-temporal-insular/parietal-insular regions in five patients. Four out of 11 patients had positive MAP results. The MAP positive rate was 36.4%. The positive regions were in insular in one patient and operculoinsular regions in three patients. Three of the four patients who were MAP-positive got seizure-free after successfully resect the MAP-positive and MEG-positive regions (the pathology results were FCD IIb in two patients and FCD IIa in one patient).

Conclusions: MAP is a useful tool in detection the epileptogenic lesions in patients with MRI-negative operculoinsular epilepsy. Notably, in order to make a right surgical regime decision, MAP results should always be interpreted in the context of the patient's anatomo-electroclinical presentation.

In Vivo Imaging of Neuroinflammatory Targets in Treatment-Resistant Epilepsy

PURPOSE OF REVIEW

Recent evidence indicates that chronic, low-level neuroinflammation underlies epileptogenesis. Targeted imaging of key neuroinflammatory cells, receptors, and tissues may enable localizing epileptogenic onset zone, especially in those patients who are treatment-resistant and considered MRI-negative. Finding a specific, sensitive neuroimaging-based biomarker could aid surgical planning and improve overall prognosis in eligible patients. This article reviews recent research on in vivo imaging of neuroinflammatory targets in patients with treatment-resistant, non-lesional epilepsy.

RECENT FINDINGS

A number of advanced approaches based on imaging neuroinflammation are being implemented in order to assist localization of epileptogenic onset zone. The most exciting tools are based on radioligand-based nuclear imaging or revisiting of existing technology in novel ways. The greatest limitations stem from gaps in knowledge about the exact function of neuroinflammatory targets (e.g., neurotoxic or neuroprotective). Further, lingering questions about each approach's specificity, reliability, and sensitivity must be addressed, and clinical utility must be validated before any novel method is incorporated into mainstream clinical practice. Current applications of imaging neuroinflammation in humans are limited and underutilized, but offer hope for finding sensitive and specific neuroimaging-based biomarker(s). Future work necessitates appreciation of investigations to date, significant findings, and neuroinflammatory targets worth exploring further.

Changing concepts in presurgical assessment for epilepsy surgery

Candidates for epilepsy surgery must undergo presurgical evaluation to establish whether and how surgical treatment can stop seizures without causing neurological deficits. Various techniques, including MRI, PET, single-photon emission CT, video-EEG, magnetoencephalography and invasive EEG, aim to identify the diseased brain tissue and the involved network. Recent technical and methodological developments, encompassing both advances in existing techniques and new combinations of technologies, are enhancing the ability to define the optimal resection strategy. Multimodal interpretation and predictive computer models are expected to aid surgical planning and patient counselling, and multimodal intraoperative guidance is likely to increase surgical precision. In this Review, we discuss how the knowledge derived from these new approaches is challenging our way of thinking about surgery to stop focal seizures. In particular, we highlight the importance of looking beyond the EEG seizure onset zone and considering focal epilepsy as a brain network disease in which long-range connections need to be taken into account. We also explore how new diagnostic techniques are revealing essential information in the brain that was previously hidden from view.

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.

Long-term seizure outcomes after pediatric temporal lobectomy: does brain MRI lesion matter?

OBJECTIVE

There is emerging data that adults with temporal lobe epilepsy (TLE) without a discrete lesion on brain MRI have surgical outcomes comparable to those with hippocampal sclerosis (HS). However, pediatric TLE is different from its adult counterpart. In this study, the authors investigated if the presence of a potentially epileptogenic lesion on presurgical brain MRI influences the long-term seizure outcomes after pediatric temporal lobectomy.

METHODS

Children who underwent temporal lobectomy between 2007 and 2015 and had at least 1 year of seizure outcomes data were identified. These were classified into lesional and MRI-negative groups based on whether an epilepsy-protocol brain MRI showed a lesion sufficiently specific to guide surgical decisions. These patients were also categorized into pure TLE and temporal plus epilepsies based on the neurophysiological localization of the seizure-onset zone. Seizure outcomes at each follow-up visit were incorporated into a repeated-measures generalized linear mixed model (GLMM) with MRI status as a grouping variable. Clinical variables were incorporated into GLMM as covariates.

RESULTS

One hundred nine patients (44 females) were included, aged 5 to 21 years, and were classified as lesional (73%), MRI negative (27%), pure TLE (56%), and temporal plus (44%). After a mean follow-up of 3.2 years (range 1.2-8.8 years), 66% of the patients were seizure free for ≥ 1 year at last follow-up. GLMM analysis revealed that lesional patients were more likely to be seizure free over the long term compared to MRI-negative patients for the overall cohort (OR 2.58, p < 0.0001) and for temporal plus epilepsies (OR 1.85, p = 0.0052). The effect of MRI lesion was not significant for pure TLE (OR 2.64, p = 0.0635). Concordance of ictal electroencephalography (OR 3.46, p < 0.0001), magnetoencephalography (OR 4.26, p < 0.0001), and later age of seizure onset (OR 1.05, p = 0.0091) were associated with a higher likelihood of seizure freedom. The most common histological findings included cortical dysplasia types 1B and 2A, HS (40% with dual pathology), and tuberous sclerosis.

CONCLUSIONS

A lesion on presurgical brain MRI is an important determinant of long-term seizure freedom after pediatric temporal lobectomy. Pediatric TLE is heterogeneous regarding etiologies and organization of seizure-onset zones with many patients qualifying for temporal plus nosology. The presence of an MRI lesion determined seizure outcomes in patients with temporal plus epilepsies. However, pure TLE had comparable surgical seizure outcomes for lesional and MRI-negative groups.

Multimodal noninvasive evaluation in MRI-negative operculoinsular epilepsy

OBJECTIVE

Presurgical evaluation of patients with operculoinsular epilepsy and negative MRI presents major challenges. Here the authors examined the yield of noninvasive modalities such as voxel-based morphometric MRI postprocessing, FDG-PET, subtraction ictal SPECT coregistered to MRI (SISCOM), and magnetoencephalography (MEG) in a cohort of patients with operculoinsular epilepsy and negative MRI.

METHODS

Twenty-two MRI-negative patients were included who had focal ictal onset from the operculoinsular cortex on intracranial EEG, and underwent focal resection limited to the operculoinsular cortex. MRI postprocessing was applied to presurgical T1-weighted volumetric MRI using a morphometric analysis program (MAP). Individual and combined localization yields of MAP, FDG-PET, MEG, and SISCOM were compared with the ictal onset location on intracranial EEG. Seizure outcomes were reported at 1 year and 2 years (when available) using the Engel classification.

RESULTS

Ten patients (45.5%, 10/22) had operculoinsular abnormalities on MAP; 5 (23.8%, 5/21) had operculoinsular hypometabolism on FDG-PET; 4 (26.7%, 4/15) had operculoinsular hyperperfusion on SISCOM; and 6 (30.0%, 6/20) had an MEG cluster (3 tight, 3 loose) within the operculoinsular cortex. The highest yield of a 2-test combination was 59.1%, seen with MAP and SISCOM, followed by 54.5% with MAP and FDG-PET, and also 54.5% with MAP and MEG. The highest yield of a 3-test combination was 68.2%, seen with MAP, MEG, and SISCOM. The yield of the 4-test combination remained at 68.2%. When all other tests were negative or nonlocalizing, unique information was provided by MAP in 5, MEG in 1, SISCOM in 2, and FDG-PET in none of the patients. One-year follow-up was available in all patients, and showed 11 Engel class IA, 4 class IB, 4 class II, and 3 class III/IV. Two-year follow-up was available in 19 patients, and showed 9 class IA, 3 class IB, 1 class ID, 3 class II, and 3 class III/IV.

CONCLUSIONS

This study highlights the individual and combined values of multiple noninvasive modalities for the evaluation of nonlesional operculoinsular epilepsy. The 3-test combination of MAP, MEG, and SISCOM represented structural, interictal, and ictal localization information, and constituted the highest yield. MAP showed the highest yield of unique information when other tests were negative or nonlocalizing.

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.

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.

MRI in epilepsy: clinical standard and evolution

PURPOSE OF REVIEW

MRI has a crucial position in the diagnostic routine of epilepsy patients. It relevantly contributes to etiological diagnostics and is indispensable in presurgical evaluation. As modern MRI research has been a boon to clinical neuroscience in general, it also holds the promise of enhancing diagnostics of epilepsy patients; i.e. increasing the diagnostic yield while decreasing the number of MRI-negative patients. Its rapid progress, however, has caused uncertainty about which of its latest developments already are of clinical interest and which still are of academic interest. It is the purpose of this review to clarify what, to the authors' mind, good practice of MRI in epilepsy patient care is today and what it might be tomorrow.

RECENT FINDINGS

Progress of diagnostic MRI in epilepsy patients is driven by development of scanner hardware, scanner sequence and data postprocessing. Ultra high-field MRI and elaborate sequences provide datasets of novel quality which can be fed into postprocessing programs extracting pathognomonic features of structural or functional anatomy. The integration of these features by means of computerized classifiers yield previously unsurpassed diagnostic validity. Enthusiasm about Diffusion Tensor Imaging and functional MRI in the evaluation before epilepsy surgery is quelled.

SUMMARY

The application of an epilepsy tailored MRI protocol at 3 Tesla followed by meticulous expert evaluation early after the onset of epilepsy is most crucial. It is hoped that future research will result in MRI workups more standardized than today and widely used postprocessing routines analyzing co-registered three-dimensional volumes from different modalities.

Multimodal quantitative magnetic resonance imaging analysis with individualized postprocessing in patients with drug-resistant focal epilepsy and conventional visual inspection negative for epileptogenic lesions

OBJECTIVES

Approximately one-third of candidates for epilepsy surgery have no visible abnormalities on conventional magnetic resonance imaging. This is extremely discouraging, as these patients have a less favorable prognosis. We aimed to evaluate the utility of quantitative magnetic resonance imaging in patients with drug-resistant neocortical focal epilepsy and negative imaging.

METHODS

A prospective study including 46 patients evaluated through individualized postprocessing of five quantitative measures: cortical thickness, white and gray matter junction signal, relaxation rate, magnetization transfer ratio, and mean diffusivity. Scalp video-electroencephalography was used to suggest the epileptogenic zone. A volumetric fluid-attenuated inversion recovery sequence was performed to aid visual inspection. A critical assessment of follow-up was also conducted throughout the study.

RESULTS

In the subgroup classified as having an epileptogenic zone, individualized postprocessing detected abnormalities within the region of electroclinical origin in 9.7% to 31.0% of patients. Abnormalities outside the epileptogenic zone were more frequent, up to 51.7%. In five patients initially included with negative imaging, an epileptogenic structural abnormality was identified when a new visual magnetic resonance imaging inspection was guided by information gleaned from postprocessing. In three patients, epileptogenic lesions were detected after visual evaluation with volumetric fluid-attenuated sequence guided by video electroencephalography.

CONCLUSION

Although quantitative magnetic resonance imaging analyses may suggest hidden structural lesions, caution is warranted because of the apparent low specificity of these findings for the epileptogenic zone. Conversely, these methods can be used to prevent visible lesions from being ignored, even in referral centers. In parallel, we need to highlight the positive contribution of the volumetric fluid-attenuated sequence.

MRI Abnormalities Predominate in the Bottom Part of the Sulcus with Type II Focal Cortical Dysplasia: A Quantitative Study

BACKGROUND AND PURPOSE

Type II focal cortical dysplasia is a common histopathological substrate in focal epilepsy. This study explored the spatial distribution of abnormal findings on MR imaging across the sulcus with type II focal cortical dysplasia using quantitative MR imaging postprocessing techniques.

MATERIALS AND METHODS

The morphometric analysis program and normalized FLAIR signal intensity analysis were applied to retrospectively analyze the MR imaging data of 58 patients with histopathologically confirmed type II focal cortical dysplasia. We divided the dysplastic sulcus into the bottom and nonbottom parts. Then spatial distribution types 1, 2, and 3 were arbitrarily defined as the abnormal findings on MR imaging (z-value > threshold) located in the bottom part, both the bottom and nonbottom parts, and the nonbottom part, respectively. For type 2, the mean z-values and standardized volumes of abnormal findings on MR imaging were compared between the bottom and nonbottom parts.

RESULTS

Abnormal findings on MR imaging were detected by quantitative techniques in 42 of 58 enrolled patients. Among these 42 patients, 38 and 26 patients showed gray-white matter junction blurring and cortical FLAIR hyperintensity, respectively, which were the 2 most common abnormal MR imaging features. Gray-white matter junction blurring manifested as types 1, 2, and 3 in 24, 13, and 1 patient, respectively, and the corresponding counts for cortical FLAIR hyperintensity were 12, 13, and 1 patient. For the 2 most common abnormal findings on MR imaging spatially manifested as type 2, higher mean z-values and larger corresponding standardized volumes of abnormalities were found in the bottom part.

CONCLUSIONS

Abnormal findings on MR imaging predominate in the bottom part of the sulcus with type II focal cortical dysplasia, which indicates that this malformation is bottom-of-sulcus-rooted.

Application of MRI Post-processing in Presurgical Evaluation of Non-lesional Cingulate Epilepsy

Background and Purpose: Surgical management of patients with cingulate epilepsy (CE) is highly challenging, especially when the MRI is non-lesional. We aimed to use a voxel-based MRI post-processing technique, implemented in a morphometric analysis program (MAP), to facilitate detection of subtle epileptogenic lesions in CE, thereby improving surgical evaluation of patients with CE with non-lesional MRI by visual inspection.

Methods: Included in this retrospective study were 9 patients with CE (6 with negative 3T MRI and 3 with subtly lesional 3T MRI) who underwent surgery and became seizure-free or had marked seizure improvement with at least 1-year follow-up. MRI post-processing was applied to pre-surgical T1-weighted volumetric sequence using MAP. The MAP finding was then coregistered and compared with other non-invasive imaging tests (FDG-PET, SPECT and MEG), intracranial EEG ictal onset, surgery location and histopathology.

Results: Single MAP+ abnormalities were found in 6 patients, including 3 patients with negative MRI, and 3 patients with subtly lesional MRI. Out of these 6 MAP+ patients, 4 patients became seizure-free after complete resection of the MAP+ abnormalities; 2 patients didn't become seizure-free following laser ablation that only partially overlapped with the MAP+ abnormalities. All MAP+ foci were concordant with intracranial EEG ictal onset (when performed). The localization value of FDG-PET, SPECT and MEG was limited in this cohort. FCD was identified in all patients' surgical pathology except for two cases of laser ablation with no tissue available.

Conclusion: MAP provided helpful information for identifying subtle epileptogenic abnormalities in patients with non-lesional cingulate epilepsy. MRI postprocessing should be considered to add to the presurgical evaluation test battery of non-lesional cingulate epilepsy.

The neuronal migration hypothesis of dyslexia: A critical evaluation 30 years on

The capacity for language is one of the key features underlying the complexity of human cognition and its evolution. However, little is known about the neurobiological mechanisms that mediate normal or impaired linguistic ability. For developmental dyslexia, early postmortem studies conducted in the 1980s linked the disorder to subtle defects in the migration of neurons in the developing neocortex. These early studies were reinforced by human genetic analyses that identified dyslexia susceptibility genes and subsequent evidence of their involvement in neuronal migration. In this review, we examine recent experimental evidence that does not support the link between dyslexia and neuronal migration. We critically evaluate gene function studies conducted in rodent models and draw attention to the lack of robust evidence from histopathological and imaging studies in humans. Our review suggests that the neuronal migration hypothesis of dyslexia should be reconsidered, and the neurobiological basis of dyslexia should be approached with a fresh start.

Systematic Assessment of Multispectral Voxel-Based Morphometry in Previously MRI-Negative Focal Epilepsy

BACKGROUND AND PURPOSE

Voxel-based morphometry is widely used for detecting gray matter abnormalities in epilepsy. However, its performance with changing parameters, smoothing and statistical threshold, is debatable. More important, the potential yield of combining multiple MR imaging contrasts (multispectral voxel-based morphometry) is still unclear. Our aim was to objectify smoothing and statistical cutoffs and systematically compare the performance of multispectral voxel-based morphometry with existing T1 voxel-based morphometry in patients with focal epilepsy and previously negative MRI.

MATERIALS AND METHODS

3D T1-, T2-, and T2-weighted FLAIR scans were acquired for 62 healthy volunteers and 13 patients with MR imaging negative for focal epilepsy on a Magnetom Skyra 3T scanner with an isotropic resolution of 0.9 mm³. We systematically optimized the main voxel-based morphometry parameters, smoothing level and statistical cutoff, with T1 voxel-based morphometry as a reference. As a next step, the performance of multispectral voxel-based morphometry models, T1+T2, T1+FLAIR, and T1+T2+FLAIR, was compared with that of T1 voxel-based morphometry using gray matter concentration and gray matter volume analysis.

RESULTS

We found the best performance of T1 at 12 mm and a T-threshold (statistical cutoff) of 3.7 for gray matter concentration analysis. When we incorporated these parameters, after expert visual interpretation of concordant and discordant findings, we identified T1+FLAIR as the best model with a concordant rate of 46.2% and a concordant rate/discordant rate of 1.20 compared with T1 with 30.8% and 0.67, respectively. Visual interpretation of voxel-based morphometry findings decreased concordant rates from 38.5%-46.2% to 15.4%-46.2% and discordant rates from 53.8%-84.6% to 30.8%-46.2% and increased specificity across models from 33.9%-40.3% to 46.8%-54.8%.

CONCLUSIONS

Multispectral voxel-based morphometry, especially T1+FLAIR, can yield superior results over single-channel T1 in focal epilepsy patients with a negative conventional MR imaging.

Levetiracetam-Induced Seizure Aggravation in Patients With Focal Cortical Dysplasia

OBJECTIVES

The choice of antiepileptic drug is typically based on seizure type, and there is no evidence for superior effectiveness or potential deterioration of particular antiepileptic drug in specific etiologic subgroups. The aim of the study was to identify etiological factor(s) associated with increased risk of seizure aggravation with levetiracetam (LEV).

METHODS

A retrospective analysis of 139 patients treated with LEV was performed. Seizure aggravation was defined as a 100% or greater increase in seizures frequency, which occurred within 1 month of drug introduction.

RESULTS

Five patients who fulfilled the selection criteria were identified. Seizure aggravation occurred with low doses (500-1000 mg) of LEV. In addition to increased frequency and duration, 2 patients developed new seizure types. Withdrawal of LEV resulted in seizure return to background frequency in all patients. Four of 5 patients have distinctive magnetic resonance imaging finding of focal cortical dysplasia. No patients with paradoxical effect of LEV were detected in the idiopathic epilepsy group or other types of symptomatic epilepsies.

CONCLUSIONS

Our results suggest that LEV may possibly induce seizure exacerbation in a subset of patients with focal cortical dysplasia-related epilepsy, although large studies are needed to establish the relation. Underlying causes of epilepsy could impact the treatment choice because electroclinical semiology might be the "final common pathway" of different epileptogenic mechanisms in diverse etiologies.

Quantitative positron emission tomography-guided magnetic resonance imaging postprocessing in magnetic resonance imaging-negative epilepsies

OBJECTIVE

Detection of focal cortical dysplasia (FCD) is of paramount importance in epilepsy presurgical evaluation. Our study aims at utilizing quantitative positron emission tomography (QPET) analysis to complement magnetic resonance imaging (MRI) postprocessing by a morphometric analysis program (MAP) to facilitate automated identification of subtle FCD.

METHODS

We retrospectively included a consecutive cohort of surgical patients who had a negative preoperative MRI by radiology report. MAP was performed on T1-weighted volumetric sequence and QPET was performed on PET/computed tomographic data, both with comparison to scanner-specific normal databases. Concordance between MAP and QPET was assessed at a lobar level, and the significance of concordant QPET-MAP⁺ abnormalities was confirmed by postresective seizure outcome and histopathology. QPET thresholds of standard deviations (SDs) of -1, -2, -3, and -4 were evaluated to identify the optimal threshold for QPET-MAP analysis.

RESULTS

A total of 104 patients were included. When QPET thresholds of SD = -1, -2, and -3 were used, complete resection of the QPET-MAP⁺ region was significantly associated with seizure-free outcome when compared with the partial resection group (P = 0.023, P < 0.001, P = 0.006) or the no resection group (P = 0.002, P < 0.001, P = 0.001). The SD threshold of -2 showed the best combination of positive rate (55%), sensitivity (0.68), specificity (0.88), positive predictive value (0.88), and negative predictive value (0.69). Surgical pathology of the resected QPET-MAP⁺ areas revealed mainly FCD type I. Multiple QPET-MAP⁺ regions were present in 12% of the patients at SD = -2.

SIGNIFICANCE

Our study demonstrates a practical and effective approach to combine quantitative analyses of functional (QPET) and structural (MAP) imaging data to improve identification of subtle epileptic abnormalities. This approach can be readily adopted by epilepsy centers to improve postresective seizure outcomes for patients without apparent lesions on MRI.

Multimodality Image Post-processing in Detection of Extratemporal MRI-Negative Cortical Dysplasia

Purpose: To determine the diagnostic value of individual image post-processing techniques in a series of patients who underwent extratemporal operations for histologically proven, MRI-negative focal cortical dysplasia (FCD). Methods: The morphometric analysis program (MAP), PET/MRI co-registration and statistical parametric mapping (SPM) analysis of PET (SPM-PET) techniques were analyzed in 33 consecutive patients. The epileptogenic zone (EZ) assumed by MAP, PET/MRI, and SPM-PET was compared with the location of the FCD lesions determined by stereoelectroencephalography (SEEG) and histopathological study. The detection rate of each modality was statistically compared. Results: Three lesions were simultaneously detected by the three post-processing methods, while two lesions were only MAP positive, and 8 were only PET/MRI positive. The detection rate of MAP, PET/MRI, SPM-PET and the combination of the three modalities was 24.2, 90.9, 57.6, and 97.0%, respectively. Taking the pathological subtype into account, no type I lesions were detected by MAP, and PET/MRI was the most sensitive method for detecting FCD types II and IIA. During a mean follow-up period of 22.94 months, seizure freedom was attained in 26/33 patients (78.8%) after focal corticectomy. Conclusions: MAP, PET/MRI, and SPM-PET provide complementary information for FCD detection, intracranial electrode design, and lesion resection. PET/MRI was particularly useful, with the highest detection rate of extratemporal MRI-negative FCD.

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning

OBJECTIVE

Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In this study, we utilized surface-based MRI morphometry and machine learning for automated lesion detection in a mixed cohort of patients with FCD type II from 3 different epilepsy centers.

METHODS

Sixty-one patients with pharmacoresistant epilepsy and histologically proven FCD type II were included in the study. The patients had been evaluated at 3 different epilepsy centers using 3 different MRI scanners. T1-volumetric sequence was used for postprocessing. A normal database was constructed with 120 healthy controls. We also included 35 healthy test controls and 15 disease test controls with histologically confirmed hippocampal sclerosis to assess specificity. Features were calculated and incorporated into a nonlinear neural network classifier, which was trained to identify lesional cluster. We optimized the threshold of the output probability map from the classifier by performing receiver operating characteristic (ROC) analyses. Success of detection was defined by overlap between the final cluster and the manual labeling. Performance was evaluated using k-fold cross-validation.

RESULTS

The threshold of 0.9 showed optimal sensitivity of 73.7% and specificity of 90.0%. The area under the curve for the ROC analysis was 0.75, which suggests a discriminative classifier. Sensitivity and specificity were not significantly different for patients from different centers, suggesting robustness of performance. Correct detection rate was significantly lower in patients with initially normal MRI than patients with unequivocally positive MRI. Subgroup analysis showed the size of the training group and normal control database impacted classifier performance.

SIGNIFICANCE

Automated surface-based MRI morphometry equipped with machine learning showed robust performance across cohorts from different centers and scanners. The proposed method may be a valuable tool to improve FCD detection in presurgical evaluation for patients with pharmacoresistant epilepsy.

A multimodal concept for invasive diagnostics and surgery based on neuronavigated voxel-based morphometric MRI postprocessing data in previously nonlesional epilepsy

OBJECTIVE

Diagnosis and surgical treatment of refractory and apparent nonlesional focal epilepsy is challenging. Morphometric MRI voxel-based and other postprocessing methods can help to localize the epileptogenic zone and thereby support the planning of further invasive electroencephalography (EEG) diagnostics, and maybe resective epilepsy surgery.

METHODS

The authors developed an algorithm to implement regions of interest (ROI), based on postprocessed MRI data, into a neuronavigation tool. This was followed by stereotactic ROI-guided implantation of depth electrodes and ROI-navigated resective surgery. Data on diagnostic yield, histology, and seizure outcome were collected and evaluated.

RESULTS

Fourteen consecutive patients with apparently nonlesional epilepsy were included in this study. Reevaluation of the MR images with the help of MRI postprocessing analysis led to the identification of probable subtle lesions in 11 patients. Additional information obtained by SPECT imaging and MRI reevaluation suggested possible lesions in the remaining 3 patients. The ROI-guided invasive implantation of EEG yielded interictal and ictal activity in 13 patients who were consequently referred to resective surgery. Despite the apparently negative MRI findings, focal cortical dysplasia was found in 64% of the patients (n = 9). At the last available outcome, 8 patients (57%) were completely seizure free (International League Against Epilepsy Class 1).

CONCLUSIONS

The results demonstrate the feasibility and usefulness of a robust and straightforward algorithm for implementation of MRI postprocessing-based targets into the neuronavigation system. This approach allowed the stereotactic implantation of a low number of depth electrodes only, which confirmed the seizure-onset hypothesis in 90% of the cases without causing any complications. Furthermore, the neuronavigated ROI-guided lesionectomy helped to perform resective surgery in this rather challenging subgroup of patients with apparent nonlesional epilepsy.

Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias

OBJECTIVE

Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identification/localization; nevertheless, many FCDs are small or subtle, and difficult to find on routine radiological inspection. We aimed to automatically detect subtle or visually-unidentifiable FCDs by building a classifier based on an optimized cortical surface sampling of combined MRI and PET features.

METHODS

Cortical surfaces of 28 patients with histopathologically-proven FCDs were extracted. Morphology and intensity-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface, and fed to a 2-step (Support Vector Machine and patch-based) classifier. Classifier performance was assessed compared to manual lesion labels.

RESULTS

Our classifier using combined feature selections from MRI and PET outperformed both quantitative MRI and multimodal visual analysis in FCD detection (93% vs 82% vs 68%). No false positives were identified in the controls, whereas 3.4% of the vertices outside FCD lesions were also classified to be lesional ("extralesional clusters"). Patients with type I or IIa FCDs displayed a higher prevalence of extralesional clusters at an intermediate distance to the FCD lesions compared to type IIb FCDs (p < 0.05). The former had a correspondingly lower chance of positive surgical outcome (71% vs 91%).

CONCLUSIONS

Machine learning with multimodal feature sampling can improve FCD detection. The spread of extralesional clusters characterize different FCD subtypes, and may represent structurally or functionally abnormal tissue on a microscopic scale, with implications for surgical outcomes.

Personalized structural image analysis in patients with temporal lobe epilepsy

Volumetric and morphometric studies have demonstrated structural abnormalities related to chronic epilepsies on a cohort- and population-based level. On a single-patient level, specific patterns of atrophy or cortical reorganization may be widespread and heterogeneous but represent potential targets for further personalized image analysis and surgical therapy. The goal of this study was to compare morphometric data analysis in 37 patients with temporal lobe epilepsies with expert-based image analysis, pre-informed by seizure semiology and ictal scalp EEG. Automated image analysis identified abnormalities exceeding expert-determined structural epileptogenic lesions in 86% of datasets. If EEG lateralization and expert MRI readings were congruent, automated analysis detected abnormalities consistent on a lobar and hemispheric level in 82% of datasets. However, in 25% of patients EEG lateralization and expert readings were inconsistent. Automated analysis localized to the site of resection in 60% of datasets in patients who underwent successful epilepsy surgery. Morphometric abnormalities beyond the mesiotemporal structures contributed to subtype characterisation. We conclude that subject-specific morphometric information is in agreement with expert image analysis and scalp EEG in the majority of cases. However, automated image analysis may provide non-invasive additional information in cases with equivocal radiological and neurophysiological findings.

Neuroimaging in Epilepsy

In recent years, the field of neuroimaging has undergone dramatic development. Specifically, of importance for clinicians and researchers managing patients with epilepsies, new methods of brain imaging in search of the seizure-producing abnormalities have been implemented, and older methods have undergone additional refinement. Methodology to predict seizure freedom and cognitive outcome has also rapidly progressed. In general, the image data processing methods are very different and more complicated than even a decade ago. In this review, we identify the recent developments in neuroimaging that are aimed at improved management of epilepsy patients. Advances in structural imaging, diffusion imaging, fMRI, structural and functional connectivity, hybrid imaging methods, quantitative neuroimaging, and machine-learning are discussed. We also briefly summarize the potential new developments that may shape the field of neuroimaging in the near future and may advance not only our understanding of epileptic networks as the source of treatment-resistant seizures but also better define the areas that need to be treated in order to provide the patients with better long-term outcomes.

Voxel-based magnetic resonance image postprocessing in epilepsy

Objective

Although the general utility of voxel‐based processing of structural magnetic resonance imaging (MRI) data for detecting occult lesions in focal epilepsy is established, many differences exist among studies, and it is unclear which processing method is preferable. The aim of this study was to compare the ability of commonly used methods to detect epileptogenic lesions in magnetic resonance MRI‐positive and MRI‐negative patients, and to estimate their diagnostic yield.

Methods

We identified 144 presurgical focal epilepsy patients, 15 of whom had a histopathologically proven and MRI‐visible focal cortical dysplasia; 129 patients were MRI negative with a clinical hypothesis of seizure origin, 27 of whom had resections. We applied four types of voxel‐based morphometry (VBM), three based on T1 images (gray matter volume, gray matter concentration, junction map [JM]) and one based on normalized fluid‐attenuated inversion recovery (nFSI). Specificity was derived from analysis of 50 healthy controls.

Results

The four maps had different sensitivity and specificity profiles. All maps showed detection rates for focal cortical dysplasia patients (MRI positive and negative) of >30% at a strict threshold of p < 0.05 (family‐wise error) and >60% with a liberal threshold of p < 0.0001 (uncorrected), except for gray matter volume (14% and 27% detection rate). All maps except nFSI showed poor specificity, with high rates of false‐positive findings in controls. In the MRI‐negative patients, absolute detection rates were lower. A concordant nFSI finding had a significant positive odds ratio of 7.33 for a favorable postsurgical outcome in the MRI‐negative group. Spatial colocalization of JM and nFSI was rare, yet showed good specificity throughout the thresholds.

Significance

All VBM variants had specific diagnostic properties that need to be considered for an adequate interpretation of the results. Overall, structural postprocessing can be a useful tool in presurgical diagnostics, but the low specificity of some maps has to be taken into consideration.

Epilepsy Treatment: A Futurist View

Advances in epilepsy treatment are occurring at a rapid pace, and it is challenging for us to keep up with the latest in our field. As we struggle to keep up with the literature and concentrate on our own research and clinical work, we often fail to exercise our imagination and envision what our field will be like in future decades. This was the assignment to the speakers for the Presidential Symposium at the 2016 American Epilepsy Society Annual Meeting. I challenged the experts to step outside the frame of their usual daily work to imagine what epilepsy treatment would and should look like for the next generation of epilepsy specialists and their patients. As you will read in the following sections, the speakers truly stepped up to the challenge to look into the crystal ball. The following are summaries of each lecture that describe the current state, existing cutting edge ideas, and some surprising predictions for the future. I am grateful for the tremendous effort these experts put into this challenge and hope they stimulate your imagination so you will work to bring these advances to our patients.

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.

MRI postprocessing in presurgical evaluation

PURPOSE OF REVIEW

Advanced MRI postprocessing techniques are increasingly used to complement visual analysis and elucidate structural epileptogenic lesions. This review summarizes recent developments in MRI postprocessing in the context of epilepsy presurgical evaluation, with the focus on patients with unremarkable MRI by visual analysis (i.e. 'nonlesional' MRI).

RECENT FINDINGS

Various methods of MRI postprocessing have been reported to show additional clinical values in the following areas: lesion detection on an individual level; lesion confirmation for reducing the risk of over reading the MRI; detection of sulcal/gyral morphologic changes that are particularly difficult for visual analysis; and delineation of cortical abnormalities extending beyond the visible lesion. Future directions to improve the performance of MRI postprocessing include using higher magnetic field strength for better signal-to-noise ratio and contrast-to-noise ratio adopting a multicontrast frame work and integration with other noninvasive modalities.

SUMMARY

MRI postprocessing can provide essential value to increase the yield of structural MRI and should be included as part of the presurgical evaluation of nonlesional epilepsies. MRI postprocessing allows for more accurate identification/delineation of cortical abnormalities, which should then be more confidently targeted and mapped.

Presurgical diagnosis of epilepsies – concepts and diagnostic tools

Introduction.Numerous reviews of the currently established concepts, strategies and diagnostic tools used in epilepsy surgery have been published. The focus concept which was initially developed by Forster, Penfield and Jasper and popularised and enriched by Lüders, is still fundamental for epilepsy surgery.

Aim.To present different conceptual views of the focus concept and to discuss more recent network hypothesis, emphasizing so-called “critical modes of an epileptogenic circuit”.

Method.A literature search was conducted using keywords: presurgical evaluation, epileptic focus concepts, cortical zones, diagnostic tools.

Review and remarks.The theoretical concepts of the epileptic focus are opposed to the network hypothesis. The definitions of the various cortical zones have been conceptualized in the presurgical evaluation of candidates for epilepsy surgery: the seizure onset zone versus the epileptogenic zone, the symptomatogenic zone, the irritative and functional deficit zones are characterized. The epileptogenic lesion, the “eloquent cortex” and secondary epileptogenesis (mirror focus) are dealt with. The current diagnostic techniques used in the definition of these cortical zones, such as video-EEG monitoring, non-invasive and invasive EEG recording techniques, magnetic resonance imaging, ictal single photon emission computed tomography, and positron emission tomography, are discussed and illustrated. Potential modern surrogate markers of epileptogenicity, such asHigh frequency oscillations, Ictal slow waves/DC shifts, Magnetic resonance spectroscopy, Functional MRI,the use ofMagnetized nanoparticlesin MRI,Transcranial magnetic stimulation,Optical intrinsic signalimaging, andSeizure predictionare discussed. Particular emphasis is put on the EEG: Scalp EEG, semi-invasive and invasive EEG (Stereoelectroencephalography) and intraoperative electrocorticography are illustrated. Ictal SPECT and18F-FDG PET are very helpful and several other procedures, such as dipole source localization and spike-triggered functional MRI are already widely used. The most important lateralizing and localizing ictal signs and symptoms are summarized. It is anticipated that the other clinically valid surrogate markers of epileptogenesis and epileptogenicity will be further developed in the near future. Until then the concordance of the results of seizure semiology, localization of epileptogenicity by EEG and MRI remains the most important prerequisite for successful epilepsy surgery.

Conclusions and future perspectives.Resective epilepsy surgery is a widely accepted and successful therapeutic approach, rendering up to 80% of selected patients seizure free. Although other therapies, such as radiosurgery, and responsive neurostimulation will increasingly play a role in patients with an unresectable lesion, it is unlikely that they will replace selective resective surgery. The hope is that new diagnostic techniques will be developed that permit more direct definition and measurement of the epileptogenic zone.

Re-review of MRI with post-processing in nonlesional patients in whom epilepsy surgery has failed

Management of MRI-negative patients with intractable focal epilepsy after failed surgery is particularly challenging. In this study, we aim to investigate whether MRI post-processing could identify relevant targets for the re-evaluation of MRI-negative patients who failed the initial resective surgery. We examined a consecutive series of 56 MRI-negative patients who underwent resective surgery and had recurring seizures at 1-year follow-up. T1-weighted volumetric sequence from the pre-surgical MRI was used for voxel-based MRI post-processing which was implemented in a morphometric analysis program (MAP). MAP was positive in 15 of the 56 patients included in this study. In 5 patients, the MAP+ regions were fully resected. In 10 patients, the MAP+ regions were not or partially resected: two out of the 10 patients had a second surgery including the unresected MAP+ region, and both became seizure-free; the remaining 8 patients did not undergo further surgery, but the unresected MAP+ regions were concordant with more than one noninvasive modality in 7. In the 8 patients who had unresected MAP+ regions and intracranial-EEG before the previous surgery, the unresected MAP+ regions were concordant with ictal onset in 6. Our data suggest that scrutiny of the presurgical MRI guided by MRI post-processing may reveal relevant targets for reoperation in nonlesional epilepsies. MAP findings, when concordant with the patient's other noninvasive data, should be considered when planning invasive evaluation/reoperation for this most challenging group of patients.