Small focal cortical dysplasia lesions are located at the bottom of a deep sulcus

The clinical, imaging, pathological and genetic landscape of bottom-of-sulcus dysplasia

Bottom-of-sulcus dysplasia (BOSD) is increasingly recognized as a cause of drug-resistant, surgically-remediable, focal epilepsy, often in seemingly MRI-negative patients. We describe the clinical manifestations, morphological features, localization patterns and genetics of BOSD, with the aims of improving management and understanding pathogenesis. We studied 85 patients with BOSD diagnosed between 2005-2022. Presenting seizure and EEG characteristics, clinical course, genetic findings and treatment response were obtained from medical records. MRI (3 T) and 18F-FDG-PET scans were reviewed systematically for BOSD morphology and metabolism. Histopathological analysis and tissue genetic testing were performed in 64 operated patients. BOSD locations were transposed to common imaging space to study anatomical location, functional network localization and relationship to normal MTOR gene expression. All patients presented with stereotyped focal seizures with rapidly escalating frequency, prompting hospitalization in 48%. Despite 42% patients having seizure remissions, usually with sodium channel blocking medications, most eventually became drug-resistant and underwent surgery (86% seizure-free). Prior developmental delay was uncommon but intellectual, language and executive dysfunction were present in 24%, 48% and 29% when assessed preoperatively, low intellect being associated with greater epilepsy duration. BOSDs were missed on initial MRI in 68%, being ultimately recognized following repeat MRI, 18F-FDG-PET or image postprocessing. MRI features were grey-white junction blurring (100%), cortical thickening (91%), transmantle band (62%), increased cortical T1 signal (46%) and increased subcortical FLAIR signal (26%). BOSD hypometabolism was present on 18F-FDG-PET in 99%. Additional areas of cortical malformation or grey matter heterotopia were present in eight patients. BOSDs predominated in frontal and pericentral cortex and related functional networks, mostly sparing temporal and occipital cortex, and limbic and visual networks. Genetic testing yielded pathogenic mTOR pathway variants in 63% patients, including somatic MTOR variants in 47% operated patients and germline DEPDC5 or NPRL3 variants in 73% patients with familial focal epilepsy. BOSDs tended to occur in regions where the healthy brain normally shows lower MTOR expression, suggesting these regions may be more vulnerable to upregulation of MTOR activity. Consistent with the existing literature, these results highlight (i) clinical features raising suspicion of BOSD; (ii) the role of somatic and germline mTOR pathway variants in patients with sporadic and familial focal epilepsy associated with BOSD; and (iii) the role of 18F-FDG-PET alongside high-field MRI in detecting subtle BOSD. The anatomical and functional distribution of BOSDs likely explain their seizure, EEG and cognitive manifestations and may relate to relative MTOR expression.

Automated detection of focal cortical dysplasia based on magnetic resonance imaging and positron emission tomography

PURPOSE

Focal cortical dysplasia (FCD) is a common etiology of drug-resistant focal epilepsy. Visual identification of FCD is usually time-consuming and depends on personal experience. Herein, we propose an automated type II FCD detection approach utilizing multi-modal data and 3D convolutional neural network (CNN).

METHODS

MRI and positron emission tomography (PET) data of 82 patients with FCD were collected, including 55 (67.1%) histopathologically, and 27 (32.9%) radiologically diagnosed patients. Three types of morphometric feature maps and three types of tissue maps were extracted from the T1-weighted images. These maps, T1, and PET images formed the inputs for CNN. Five-fold cross-validations were carried out on the training set containing 62 patients, and the model behaving best was chosen to detect FCD on the test set of 20 patients. Furthermore, ablation experiments were performed to estimate the value of PET data and CNN.

RESULTS

On the validation set, FCD was detected in 90.3% of the cases, with an average of 1.7 possible lesions per patient. The sensitivity on the test set was 90.0%, with 1.85 possible lesions per patient. Without the PET data, the sensitivity decreased to 80.0%, and the average lesion number increased to 2.05 on the test set. If an artificial neural network replaced the CNN, the sensitivity decreased to 85.0%, and the average lesion number increased to 4.65.

SIGNIFICANCE

Automated detection of FCD with high sensitivity and few false-positive findings is feasible based on multi-modal data. PET data and CNN could improve the performance of automated detection.

18F-FDG-PET/CT for Localizing the Epileptogenic Focus in Patients with Different Types of Focal Cortical Dysplasia

Purpose

To determine the diagnostic and localization value of 18F-fluorodeoxyglucose-positron emission tomography (PET)/computed tomography (CT) in patients with focal cortical dysplasia (FCD) who underwent epilepsy surgery.

Methods

One hundred and eight patients with pathologically proven FCD who underwent surgery for refractory epilepsy were retrospectively analyzed. All patients underwent magnetic resonance imaging (MRI), 18F-FDG-PET/CT, and video electroencephalography. An MRI diagnosis of FCD was defined as MRI+. A PET/CT diagnosis of FCD was defined as PET/CT+.

Results

MRI and PET/CT detected FCD in 20.37% and 93.52% of patients, respectively. The difference was significant. Twenty-one patients were MRI+/PET+, 80 were MRI-/PET+, six were MRI-/PET-, and one was MRI+/PET-. The MRI positivity rate was lowest in patients with FCD type IIIa (5.6%, P < 0.05). Prevalence of MRI-/PET+ was highest in patients with FCD type IIIa (88.89%, P < 0.05).

Conclusion

PET/CT is superior to MRI in detecting FCD. FCD type IIIa was more likely than other types to show MRI-/PET+. This suggests that PET/CT has particular diagnostic value for FCD type IIIa patients with negative MRI findings.

Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review

Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)-one of the most commonly used non-invasive neuroimaging methods for evaluating the structure of the brain-is often implemented along with automatic methods to diagnose FCD. In this review, we define three categories for FCD identification based on MRI: visual, semi-automatic, and fully automatic methods. By conducting a systematic review following the PRISMA statement, we identified 65 relevant papers that have contributed to our understanding of automatic FCD identification techniques. The results of this review present a comprehensive overview of the current state-of-the-art in the field of automatic FCD identification and highlight the progress made and challenges ahead in developing reliable, efficient methods for automatic FCD diagnosis using MRI images. Future developments in this area will most likely lead to the integration of these automatic identification tools into medical image-viewing software, providing neurologists and radiologists with enhanced diagnostic capabilities. Moreover, new MRI sequences and higher-field-strength scanners will offer improved resolution and anatomical detail for precise FCD characterization. This review summarizes the current state of automatic FCD identification, thereby contributing to a deeper understanding and the advancement of FCD diagnosis and management.

Successful stereoelectroencephalography re-evaluation in epilepsy patients after failed initial subdural grid evaluation

OBJECTIVE

Epilepsy surgery success is dependent on accurate localization of the epileptogenic zone. Despite the use of invasive EEG using subdural grids and strips, surgical failures can occur. In this series, we explore the utility of a second evaluation with stereoelectroencephalography in patients whose initial invasive evaluation with subdural grid electrodes was unsuccessful in localizing seizure origin.

METHODS

We conducted a retrospective review of patients who underwent subdural grid evaluation (SDE) at our center and identified patients who underwent a re-evaluation with stereoelectroencephalography (SEEG).

RESULTS

We identified three patients who had both subdural and SEEG electrodes in the region of the identified epileptogenic zone in whom the initial SDE evaluation failed to make the patients seizure-free. Two of these patients underwent a second resection and became seizure-free.

SIGNIFICANCE

Stereoelectroencephalography can be useful in the re-evaluation and re-operation of patients who previously had surgical failure using SDE.

Intrinsic and secondary epileptogenicity in focal cortical dysplasia type II

OBJECTIVE

Favorable seizure outcome is reported following resection of bottom-of-sulcus dysplasia (BOSD). We assessed the distribution of epileptogenicity and dysplasia in and around BOSD to better understand this clinical outcome and the optimal surgical approach.

METHODS

We studied 27 children and adolescents with magnetic resonance imaging (MRI)-positive BOSD who underwent epilepsy surgery; 85% became seizure-free postresection (median = 5.0 years follow-up). All patients had resection of the dysplastic sulcus, and 11 had additional resection of the gyral crown (GC) or adjacent gyri (AG). Markers of epileptogenicity were relative cortical hypometabolism on preoperative 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET), and spiking, ripples, fast ripples, spike-high-frequency oscillation cross-rate, and phase amplitude coupling (PAC) on preresection and postresection electrocorticography (ECoG), all analyzed at the bottom-of-sulcus (BOS), top-of-sulcus (TOS), GC, and AG. Markers of dysplasia were increased cortical thickness on preoperative MRI, and dysmorphic neuron density and variant allele frequency of somatic MTOR mutations in resected tissue, analyzed at similar locations.

RESULTS

Relative cortical metabolism was significantly reduced and ECoG markers were significantly increased at the BOS compared to other regions. Apart from spiking and PAC, which were greater at the TOS compared to the GC, there were no significant differences in PET and other ECoG markers between the TOS, GC, and AG, suggesting a cutoff of epileptogenicity at the TOS rather than a tapering gradient on the cortical surface. MRI and tissue markers of dysplasia were all maximal in the BOS, reduced in the TOS, and mostly absent in the GC. Spiking and PAC reduced significantly over the GC after resection of the dysplastic sulcus.

SIGNIFICANCE

These findings support the concept that dysplasia and intrinsic epileptogenicity are mostly limited to the dysplastic sulcus in BOSD and support resection or ablation confined to the MRI-visible lesion as a first-line surgical approach. 18 F-FDG PET and ECoG abnormalities in surrounding cortex seem to be secondary phenomena.

Long-term seizure outcome with the surgically remediable syndrome of frontal lobe epilepsy associated with superior frontal sulcus-related dysplasia

Objective

To assess the long-term outcome of the surgically remediable syndrome of frontal lobe epilepsy (FLE) associated with superior frontal sulcus (SFS)-related dysplasia.

Methods

We retrospectively reviewed the medical charts and surgical features of 31 patients with drug-resistant frontal lobe epilepsy in our centers between 2016 and 2018. All patients underwent surgical resection. According to the epileptogenic zone (EZ), localization and resection extent were classified as (1) pure SFS group (PS group), (2) associated SFS group (AS group), and (3) no SFS group (NS group). The general characteristics, neuroradiological findings, morbidity, pathology, and long-term seizure outcome after surgery were analyzed to extract the potential value of the surgery for SFS-related dysplasia.

Results

Of 31 patients with FLE who underwent epilepsy surgery, 15 patients (nine men) were included PS group, five patients (five men) in the AS group, and 11 patients (eight men) in the NS group. Eleven patients detected abnormal focal signals in the presurgical MRI. Six patients in the PS group demonstrated the suspected focal cortical dysplasia (FCD) in the SFS detected with MRI. All patients demonstrated focal abnormal hypometabolism foci in the PET-MR co-registration. Twenty-five patients (80.6%) were seizure-free since surgery, including all 15 patients (100%) of the PS group, three in five patients (60%) of the AS group, and seven in 11 patients (63.6%) of the NS group. The difference in outcome between different groups was significant (p = 0.004, PS vs. AS group; p = 0.005, PS vs. NS group). As of the last follow-up (mean 66.2 ± 9.7months), 25 patients (80.6%) were seizure-free since surgery (Engel's class I). In addition, antiseizure medication was withdrawn in 19 patients (61.3%). Histologic examination of resected specimens revealed FCD in all 31 patients. The percentage of FCD II type was 100, 60, and 63.6% in the three different groups, respectively.

Conclusion

SFS-related dysplasia is a neuropathologic entity with a favorable postoperative outcome. FCD II is the most common type of SFS-related dysplasia. FDG-PET co-registered with MRI should be performed in patients with suspected SFS-related dysplasia, since it may depict areas of hypometabolism suggestive of dysplasia in the absence of MRI abnormalities.

MRI Abnormalities of the Brain After Complex Febrile Seizures in Children

Background Though simple febrile seizures do not cause significant and lasting neurological deficits, complex febrile seizures (CFS) can result in neurologic sequelae. Because CFS causes cortical focal injuries and other brain lesions, it needs to be evaluated. Objective The objective of this study was to evaluate the MRI brain changes in CFS, the incidence of seizures in children aged six months to five years, and their severity in relation to MRI findings of the brain. Methods In this observational study, 36 children aged six months to five years, having fever with seizure, and fulfilling the criteria of CFS were enrolled within 48 hours of the episode. Detailed clinical and neurological examinations were performed with MRI scans to find out the probable CNS lesions of CFS. Two radiologists separately evaluated all MRI brains. Results MRI lesions of the brain were found in 11 (30.56%) CFS patients. Generalized tonic-clonic seizures (GTCS) (n=31, 86.11%) were the most common type of seizure among CFS cases. Cortical focal hyperintensity (CFH) (42.1%) was the most common MRI presentation. Positive MRI findings were significantly associated with focal convulsions (n=5, 100%) as compared to GTCS cases (n=6, 19%) (p=0.001). Conclusions CFH is the most common abnormality in the MRI brain among CFS cases. CFS patients with focal seizures or prolonged seizures in 24 hours have higher abnormal neuroimaging findings. MRI should be considered a preferred investigatory tool for detecting CNS pathology in CFS cases. Follow-up studies are needed to determine the long-term outcomes of CNS lesions in children with CFS.

PET image enhancement using artificial intelligence for better characterization of epilepsy lesions

INTRODUCTION

[18F]fluorodeoxyglucose ([18F]FDG) brain PET is used clinically to detect small areas of decreased uptake associated with epileptogenic lesions, e.g., Focal Cortical Dysplasias (FCD) but its performance is limited due to spatial resolution and low contrast. We aimed to develop a deep learning-based PET image enhancement method using simulated PET to improve lesion visualization.

METHODS

We created 210 numerical brain phantoms (MRI segmented into 9 regions) and assigned 10 different plausible activity values (e.g., GM/WM ratios) resulting in 2100 ground truth high quality (GT-HQ) PET phantoms. With a validated Monte-Carlo PET simulator, we then created 2100 simulated standard quality (S-SQ) [18F]FDG scans. We trained a ResNet on 80% of this dataset (10% used for validation) to learn the mapping between S-SQ and GT-HQ PET, outputting a predicted HQ (P-HQ) PET. For the remaining 10%, we assessed Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Root Mean Squared Error (RMSE) against GT-HQ PET. For GM and WM, we computed recovery coefficients (RC) and coefficient of variation (COV). We also created lesioned GT-HQ phantoms, S-SQ PET and P-HQ PET with simulated small hypometabolic lesions characteristic of FCDs. We evaluated lesion detectability on S-SQ and P-HQ PET both visually and measuring the Relative Lesion Activity (RLA, measured activity in the reduced-activity ROI over the standard-activity ROI). Lastly, we applied our previously trained ResNet on 10 clinical epilepsy PETs to predict the corresponding HQ-PET and assessed image quality and confidence metrics.

RESULTS

Compared to S-SQ PET, P-HQ PET improved PNSR, SSIM and RMSE; significatively improved GM RCs (from 0.29 ± 0.03 to 0.79 ± 0.04) and WM RCs (from 0.49 ± 0.03 to 1 ± 0.05); mean COVs were not statistically different. Visual lesion detection improved from 38 to 75%, with average RLA decreasing from 0.83 ± 0.08 to 0.67 ± 0.14. Visual quality of P-HQ clinical PET improved as well as reader confidence.

CONCLUSION

P-HQ PET showed improved image quality compared to S-SQ PET across several objective quantitative metrics and increased detectability of simulated lesions. In addition, the model generalized to clinical data. Further evaluation is required to study generalization of our method and to assess clinical performance in larger cohorts.

Genetic map of regional sulcal morphology in the human brain from UK biobank data

Genetic associations with macroscopic brain structure can provide insights into brain function and disease. However, specific associations with measures of local brain folding are largely under-explored. Here, we conducted large-scale genome- and exome-wide associations of regional cortical sulcal measures derived from magnetic resonance imaging scans of 40,169 individuals in UK Biobank. We discovered 388 regional brain folding associations across 77 genetic loci, with genes in associated loci enriched for expression in the cerebral cortex, neuronal development processes, and differential regulation during early brain development. We integrated brain eQTLs to refine genes for various loci, implicated several genes involved in neurodevelopmental disorders, and highlighted global genetic correlations with neuropsychiatric phenotypes. We provide an interactive 3D visualisation of our summary associations, emphasising added resolution of regional analyses. Our results offer new insights into the genetic architecture of brain folding and provide a resource for future studies of sulcal morphology in health and disease.

Multimodal combination of neuroimaging methods for localizing the epileptogenic zone in MR-negative epilepsy

The objective was to determine the optimal combination of multimodal imaging methods (IMs) for localizing the epileptogenic zone (EZ) in patients with MR-negative drug-resistant epilepsy. Data from 25 patients with MR-negative focal epilepsy (age 30 ± 10 years, 16M/9F) who underwent surgical resection of the EZ and from 110 healthy controls (age 31 ± 9 years; 56M/54F) were used to evaluate IMs based on 3T MRI, FDG-PET, HD-EEG, and SPECT. Patients with successful outcomes and/or positive histological findings were evaluated. From 38 IMs calculated per patient, 13 methods were selected by evaluating the mutual similarity of the methods and the accuracy of the EZ localization. The best results in postsurgical patients for EZ localization were found for ictal/ interictal SPECT (SISCOM), FDG-PET, arterial spin labeling (ASL), functional regional homogeneity (ReHo), gray matter volume (GMV), cortical thickness, HD electrical source imaging (ESI-HD), amplitude of low-frequency fluctuation (ALFF), diffusion tensor imaging, and kurtosis imaging. Combining IMs provides the method with the most accurate EZ identification in MR-negative epilepsy. The PET, SISCOM, and selected MRI-post-processing techniques are useful for EZ localization for surgical tailoring.

Black Line Sign in Focal Cortical Dysplasia IIB: A 7T MRI and Electroclinicopathologic Study

BACKGROUND AND OBJECTIVES

We aim to provide detailed imaging-electroclinicopathologic characterization of the black line sign, a novel MRI marker for focal cortical dysplasia (FCD) IIB.

METHODS

7T T2*-weighted gradient-echo (T2*w-GRE) images were retrospectively reviewed in a consecutive cohort of patients with medically intractable epilepsy with pathology-proven FCD II, for the occurrence of the black line sign. We examined the overlap between the black line region and the seizure-onset zone (SOZ) defined by intracranial EEG (ICEEG) and additionally assessed whether complete inclusion of the black line region in the surgical resection was associated with postoperative seizure freedom. The histopathologic specimen was aligned with the MRI to investigate the pathologic underpinning of the black line sign. Region-of-interest-based quantitative MRI (qMRI) analysis on the 7T T1 map was performed in the black line region, entire lesional gray matter (GM), and contralateral/ipsilateral normal gray and white matter (WM).

RESULTS

We included 20 patients with FCD II (14 IIB and 6 IIA). The black line sign was identified in 12/14 (85.7%) of FCD IIB and 0/6 of FCD IIA on 7T T2*w-GRE. The black line region was highly concordant with the ICEEG-defined SOZ (5/7 complete and 2/7 partial overlap). Seizure freedom was seen in 8/8 patients whose black line region was completely included in the surgical resection; in the 2 patients whose resection did not completely include the black line region, both had recurring seizures. Inclusion of the black line region in the surgical resection was significantly associated with seizure freedom (p = 0.02). QMRI analyses showed that the T1 mean value of the black line region was significantly different from the WM (p < 0.001), but similar to the GM. Well-matched histopathologic slices in one case revealed accumulated dysmorphic neurons and balloon cells in the black line region.

DISCUSSION

The black line sign may serve as a noninvasive marker for FCD IIB. Both MRI-pathology and qMRI analyses suggest that the black line region was an abnormal GM component within the FCD. Being highly concordant with ICEEG-defined SOZ and significantly associated with seizure freedom when included in resection, the black line sign may contribute to the planning of ICEEG/surgery of patients with medically intractable epilepsy with FCD IIB.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that in individuals with intractable focal epilepsy undergoing resection who have a 7T MRI with adequate image quality, the presence of the black line sign may suggest FCD IIB, be concordant with SOZ from ICEEG, and be associated with more seizure freedom if fully included in resection.

Bilateral Structural Network Abnormalities in Epilepsy Associated With Bottom-of-Sulcus Dysplasia

BACKGROUND AND OBJECTIVES

To identify white matter fiber tracts that exhibit structural abnormality in patients with bottom-of-sulcus dysplasia (BOSD) and investigate their association with seizure activity.

METHODS

Whole-brain fixel-based analysis of diffusion MRI data was performed to identify white matter fiber tracts with significant reductions in fiber density and cross-section in patients with BOSD (n = 20) when compared to healthy control participants (n = 40). Results from whole-brain analysis were used to investigate the association of fiber tract abnormality with seizure frequency and epilepsy duration.

RESULTS

Despite the focal nature of the dysplasia, patients with BOSD showed widespread abnormality in white matter fiber tracts, including the bilateral corticospinal, corticothalamic, and cerebellothalamic tracts, superior longitudinal fasciculi, corpus callosum (body), and the forceps major. This pattern of bilateral connectivity reduction was not related to the laterality of the lesion. Exploratory post hoc analyses showed that high seizure frequency was associated with greater reduction in fiber density at the forceps major, bilateral corticospinal, and cerebellothalamic tracts.

DISCUSSION

We demonstrate evidence of a bilaterally distributed, specific white matter network that is vulnerable to disruption in BOSD. The degree of tract abnormality is partly related to seizure activity, but additional contributors such as the genetic background and effects of treatment or environment have not been excluded.

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.

Multicenter Validation of a Deep Learning Detection Algorithm for Focal Cortical Dysplasia

BACKGROUND AND OBJECTIVE

To test the hypothesis that a multicenter-validated computer deep learning algorithm detects MRI-negative focal cortical dysplasia (FCD).

METHODS

We used clinically acquired 3-dimensional (3D) T1-weighted and 3D fluid-attenuated inversion recovery MRI of 148 patients (median age 23 years [range 2-55 years]; 47% female) with histologically verified FCD at 9 centers to train a deep convolutional neural network (CNN) classifier. Images were initially deemed MRI-negative in 51% of patients, in whom intracranial EEG determined the focus. For risk stratification, the CNN incorporated bayesian uncertainty estimation as a measure of confidence. To evaluate performance, detection maps were compared to expert FCD manual labels. Sensitivity was tested in an independent cohort of 23 cases with FCD (13 ± 10 years). Applying the algorithm to 42 healthy controls and 89 controls with temporal lobe epilepsy disease tested specificity.

RESULTS

Overall sensitivity was 93% (137 of 148 FCD detected) using a leave-one-site-out cross-validation, with an average of 6 false positives per patient. Sensitivity in MRI-negative FCD was 85%. In 73% of patients, the FCD was among the clusters with the highest confidence; in half, it ranked the highest. Sensitivity in the independent cohort was 83% (19 of 23; average of 5 false positives per patient). Specificity was 89% in healthy and disease controls.

DISCUSSION

This first multicenter-validated deep learning detection algorithm yields the highest sensitivity to date in MRI-negative FCD. By pairing predictions with risk stratification, this classifier may assist clinicians in adjusting hypotheses relative to other tests, increasing diagnostic confidence. Moreover, generalizability across age and MRI hardware makes this approach ideal for presurgical evaluation of MRI-negative epilepsy.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that deep learning on multimodal MRI accurately identifies FCD in patients with epilepsy initially diagnosed as MRI negative.

Practical Fundamentals of Clinical MEG Interpretation in Epilepsy

Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to explain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.

Surgical outcomes in children with bottom-of-sulcus dysplasia and drug-resistant epilepsy: a retrospective cohort study

OBJECTIVE

Bottom-of-sulcus dysplasia (BOSD) is challenging to identify radiologically. The aim of this study was to explore seizure outcomes after resective surgery or MR-guided laser interstitial thermal therapy (MRgLITT) in children with BOSD.

METHODS

Children with radiologically defined BOSD who underwent resective surgery or MRgLITT, with at least 1 year of follow-up were included. Clinical, radiological, neurophysiological, and histological data were extracted from medical records. Invasive video EEG (IVEEG) was used to evaluate the ictal onset zone or motor/language mapping, wherever appropriate. Histology of MRI-visible BOSD, including the overlying and adjacent cortex, was also evaluated.

RESULTS

Forty-one children with BOSD underwent surgical treatment. The lesion was initially overlooked on MRI in 20 patients (48.8%). Of 34 patients who underwent IVEEG and who had available ictal data, the ictal onset zone extended beyond the MRI-visible BOSD in 23 patients (67.6%). Surgical treatment included lesionectomy (24 patients), extended lesionectomy (12 patients), lobectomy (1 patient), and ablation of BOSD (4 patients). The pathology in 37 patients who underwent resection showed focal cortical dysplasia type IIB and type IIA in 21 (53.8%) and 16 patients (41%), respectively. Seizure freedom was achieved in 32 patients (78.1%) after a mean follow-up of 4.3 years.

CONCLUSIONS

Seizure outcomes after resective surgery or MRgLITT in children with BOSD were generally favorable. The authors found that the neurophysiological abnormality and pathology often extended beyond the MRI-visible BOSD.

Localization of the Epileptogenic Zone by Multimodal Neuroimaging and High-Frequency Oscillation

Accurate localization of the epileptogenic zone (EZ) is a key factor to obtain good surgical outcome for refractory epilepsy patients. However, no technique, so far, can precisely locate the EZ, and there are barely any reports on the combined application of multiple technologies to improve the localization accuracy of the EZ. In this study, we aimed to explore the use of a multimodal method combining PET-MRI, fluid and white matter suppression (FLAWS)—a novel MRI sequence, and high-frequency oscillation (HFO) automated analysis to delineate EZ. We retrospectively collected 15 patients with refractory epilepsy who underwent surgery and used the above three methods to detect abnormal brain areas of all patients. We compared the PET-MRI, FLAWS, and HFO results with traditional methods to evaluate their diagnostic value. The sensitivities, specificities of locating the EZ, and marking extent removed versus not removed [RatioChann(ev)] of each method were compared with surgical outcome. We also tested the possibility of using different combinations to locate the EZ. The marked areas in every patient established using each method were also compared to determine the correlations among the three methods. The results showed that PET-MRI, FLAWS, and HFOs can provide more information about potential epileptic areas than traditional methods. When detecting the EZs, the sensitivities of PET-MRI, FLAWS, and HFOs were 68.75, 53.85, and 87.50%, and the specificities were 80.00, 33.33, and 100.00%. The RatioChann(ev) of HFO-marked contacts was significantly higher in patients with good outcome than those with poor outcome (p< 0.05). When intracranial electrodes covered all the abnormal areas indicated by neuroimaging with the overlapping EZs being completely removed referred to HFO analysis, patients could reach seizure-free (p < 0.01). The periphery of the lesion marked by neuroimaging may be epileptic, but not every lesion contributes to seizures. Therefore, approaches in multimodality can detect EZ more accurately, and HFO analysis may help in defining real epileptic areas that may be missed in the neuroimaging results. The implantation of intracranial electrodes guided by non-invasive PET-MRI and FLAWS findings as well as HFO analysis would be an optimized multimodal approach for locating EZ.

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.

Automatic recognition of specific local cortical folding patterns

The study of local cortical folding patterns showed links with psychiatric illnesses as well as cognitive functions. Despite the tools now available to visualize cortical folds in 3D, manually classifying local sulcal patterns is a time-consuming and tedious task. In fact, 3D visualization of folds helps experts to identify different sulcal patterns but fold variability is so high that the distinction between these patterns sometimes requires the definition of complex criteria, making manual classification difficult and not reliable. However, the assessment of the impact of these patterns on the functional organization of the cortex could benefit from the study of large databases, especially when studying rare patterns. In this paper, several algorithms for the automatic classification of fold patterns are proposed to allow morphological studies to be extended and confirmed on such large databases. Three methods are proposed, the first based on a Support Vector Machine (SVM) classifier, the second on the Scoring by Non-local Image Patch Estimator (SNIPE) approach and the third based on a 3D Convolution Neural Network (CNN). These methods are generic enough to be applicable to a wide range of folding patterns. They are tested on two types of patterns for which there is currently no method to automatically identify them: the Anterior Cingulate Cortex (ACC) patterns and the Power Button Sign (PBS). The two ACC patterns are almost equally present whereas PBS is a particularly rare pattern in the general population. The three models proposed achieve balanced accuracies of approximately 80% for ACC patterns classification and 60% for PBS classification. The CNN-based model is more interesting for the classification of ACC patterns thanks to its rapid execution. However, SVM and SNIPE-based models are more effective in managing unbalanced problems such as PBS recognition.

Geometric deep learning on brain shape predicts sex and age

The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.

One-Stage, Limited-Resection Epilepsy Surgery for Bottom-of-Sulcus Dysplasia

OBJECTIVE

To determine whether 1-stage, limited corticectomy controls seizures in patients with MRI-positive, bottom-of-sulcus dysplasia (BOSD).

METHODS

We reviewed clinical, neuroimaging, electrocorticography (ECoG), operative, and histopathology findings in consecutively operated patients with drug-resistant focal epilepsy and MRI-positive BOSD, all of whom underwent corticectomy guided by MRI and ECoG.

RESULTS

Thirty-eight patients with a median age at surgery of 10.2 (interquartile range [IQR] 6.0-14.1) years were included. BOSDs involved eloquent cortex in 15 patients. Eighty-seven percent of patients had rhythmic spiking on preresection ECoG. Rhythmic spiking was present in 22 of 24 patients studied with combined depth and surface electrodes, being limited to the dysplastic sulcus in 7 and involving the dysplastic sulcus and gyral crown in 15. Sixty-eight percent of resections were limited to the dysplastic sulcus, leaving the gyral crown. Histopathology was focal cortical dysplasia (FCD) type IIb in 29 patients and FCDIIa in 9. Dysmorphic neurons were present in the bottom of the sulcus but not the top or the gyral crown in 17 of 22 patients. Six (16%) patients required reoperation for postoperative seizures and residual dysplasia; reoperation was not correlated with ECoG, neuroimaging, or histologic abnormalities in the gyral crown. At a median 6.3 (IQR 4.8-9.9) years of follow-up, 33 (87%) patients are seizure-free, 31 off antiseizure medication.

CONCLUSION

BOSD can be safely and effectively resected with MRI and ECoG guidance, corticectomy potentially being limited to the dysplastic sulcus, without need for intracranial EEG monitoring and functional mapping.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that 1-stage, limited corticectomy for BOSD is safe and effective for control of seizures.

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.

Magnetic resonance imaging findings and clinical characteristics in mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy in a predominantly adult cohort

OBJECTIVE

We aimed to better characterize the magnetic resonance imaging (MRI) findings of mild malformation of cortical development with oligodendroglial hyperplasia (MOGHE), a rare clinicopathological entity associated with pharmacoresistance recently described in patients with frontal lobe epilepsy.

METHODS

We studied 12 patients who underwent epilepsy surgery and whose surgical specimens showed histopathological findings of MOGHE, characterized by preserved cortical lamination, blurred gray-white matter interface due to increased number of oligodendrocytes, and heterotopic neurons in the white matter. The age at MRI evaluation ranged from 11 to 58 years, except for one 4.5-year-old patient.

RESULTS

Following a detailed MRI analysis using an in-house protocol, we found abnormalities in all cases. The lesion was circumscribed in the frontal lobe in six (50%) and in the temporal lobe in three (25%) patients. In the remaining three patients (25%), the lesion was multilobar (frontotemporal and temporoparieto-occipital). Cortical thickening was mild in all patients, except in the 4.5-year-old patient, who had pronounced cortical thickening and white matter blurring. We also identified cortical/subcortical hyperintense T2/fluid-attenuated inversion recovery signal associated with gray/white matter blurring in all but one patient. When present, cleft cortical dimple, and deep sulci aided in localizing the lesion. Overall, the MRI findings were like those in focal cortical dysplasia (FCD) Type IIa. Surgical outcome was excellent in five patients (Engel Class I in 25% and II in 17%). The remaining seven patients (58%) had worthwhile seizure reduction (Engle Class III). Incomplete lesion resection was significantly associated with worse outcomes.

SIGNIFICANCE

MRI findings associated with MOGHE are similar to those described in FCD Type IIa. Although more frequent in the frontal lobe, MOGHE also occurred in the temporal lobe or involved multiple lobes. Multilobar or extensive MOGHE MRI lesions are associated with less favorable surgical outcomes. Because this is a rare condition, multicenter studies are necessary to characterize MOGHE further.

Neuroimaging and genetic characteristics of malformation of cortical development due to mTOR pathway dysregulation: clues for the epileptogenic lesions and indications for epilepsy surgery

Introduction: Malformation of cortical development (MCD) is strongly associated with drug-resistant epilepsies for which surgery to remove epileptogenic lesions is common. Two notable technological advances in this field are identification of the underlying genetic cause and techniques in neuroimaging. These now question how presurgical evaluation ought to be approached for 'mTORpathies.'Area covered: From review of published primary and secondary articles, the authors summarize evidence to consider focal cortical dysplasia (FCD), tuber sclerosis complex (TSC), and hemimegalencephaly (HME) collectively as MCD mTORpathies. The authors also consider the unique features of these related conditions with particular focus on the practicalities of using neuroimaging techniques currently available to define surgical targets and predict post-surgical outcome. Ultimately, the authors consider the surgical dilemmas faced for each condition.Expert opinion: Considering FCD, TSC, and HME collectively as mTORpathies has some merit; however, a unified approach to presurgical evaluation would seem unachievable. Nevertheless, the authors believe combining genetic-centered classification and morphologic findings using advanced imaging techniques will eventually form the basis of a paradigm when considering candidacy for early surgery.

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.

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.

Bottom-of-sulcus dysplasia: the role of 18F-FDG PET in identifying a focal surgically remedial epileptic lesion

PURPOSE

Bottom-of-sulcus dysplasia (BOSD) is a type of focal cortical dysplasia and an important cause of intractable epilepsy. While the MRI features of BOSD have been well documented, the contribution of PET to the identification of these small lesions has not been widely explored. The aim of this study was to investigate the role of F-18 fluorodeoxyglucose (¹⁸F-FDG) PET in the identification of BOSD.

METHODS

Twenty patients with BOSD underwent both ¹⁸F-FDG PET and structural MRI scans as part of preoperative planning for surgery. Visual PET analysis was performed, and patients were classified as positive if they exhibited a focal or regional hypometabolic abnormality, or negative in the absence of a hypometabolic abnormality. MRI data were reviewed to determine if any structural abnormality characteristic of BOSD were observed before and after co-registration with PET findings.

RESULTS

PET detected hypometabolic abnormalities consistent with the seizure focus location in 95% (19/20) of cases. Focal abnormalities were detected on ¹⁸F-FDG PET in 12/20 (60%) patients, while regional hypometabolism was evident in 7/20 (35%). BOSD lesions were missed in 20% (4/20) of cases upon initial review of MRI scans. Co-registration of ¹⁸F-FDG PET with MRI enabled detection of the BOSD in all four cases where the lesion was initially missed.

CONCLUSION

Our findings show that ¹⁸F-FDG PET provides additional clinical value in the localisation and detection of BOSD lesions, when used in conjunction with MRI.

Anatomical Variations, Mimics, and Pitfalls in Imaging of Patients with Epilepsy

Epilepsy is among one of the most common neurologic disorders. The role of magnetic resonance imaging (MRI) in the diagnosis and management of patients with epilepsy is well established, and most patients with epilepsy are likely to undergo at least one or more MRI examinations in the course of their disease. Recent advances in high-field MRI have enabled high resolution in vivo visualization of small and intricate anatomic structures that are of great importance in the assessment of seizure disorders. Familiarity with normal anatomic variations is essential in the accurate diagnosis and image interpretation, as these variations may be mistaken for epileptogenic foci, leading to unnecessary follow-up imaging, or worse, unnecessary treatment. After a brief overview of normal imaging anatomy of the mesial temporal lobe, this article will review a few important common and uncommon anatomic variations, mimics, and pitfalls that may be encountered in the imaging evaluation of patients with epilepsy.

Focal cortical dysplasia imaging discrepancies between MRI and FDG-PET: Unique association with temporal lobe location

PURPOSE

Although magnetic resonance imaging (MRI) and ¹⁸F-2-fluorodeoxyglucose-positron emission tomography (FDG-PET) are used for pre-surgical assessment of focal cortical dysplasia (FCD), they often disagree. This study aimed to identify factors that contribute to discrepancies in FCD imaging between MRI and FDG-PET.

METHODS

Sixty-two patients (mean age, 18.9 years) with a FCD type I or II were retrospectively selected. These patients were visually categorized into two groups: 1) extent of PET abnormality larger than MRI abnormality and 2) vice versa or equivalent. Predictive factors of these two groups were analyzed by multivariate logistic regression. The extent of hypometabolic transient zone surrounding FCDs and their mean standardized uptake values were measured and compared by the Mann-Whitney U-test.

RESULTS

FCDs were detected on MRI and PET in 46 and 55 patients, respectively, whereas no abnormality was detected in 4 patients. The PET hypometabolic areas were larger than the MRI abnormal areas in 26 patients (88 % in the temporal lobe), whereas the PET hypometabolic areas were equivalent or smaller than the MRI abnormal areas in 32 patients (69 % in the frontal lobe). The temporal lobe location was an independent predictor for differentiating the two groups (OR = 35.2, 95 % CI = 6.81-168.0, P < .001). The temporal lobe lesions had significantly wider transient zones and lower standardized uptake values than those in the other lobes (P < .001, both).

CONCLUSION

The discrepancies between MRI and FDG-PET findings of FCD were associated with temporal lobe location.

Sulcus-centered resection for focal cortical dysplasia type II: surgical techniques and outcomes

Focal cortical dysplasia type II (FCD II) is a common histopathological substrate of epilepsy surgery. Here, the authors propose a sulcus-centered resection strategy for this malformation, provide technical details, and assess the efficacy and safety of this technique. The main purpose of the sulcus-centered resection is to remove the folded gray matter surrounding a dysplastic sulcus, particularly that at the bottom of the sulcus. The authors also retrospectively reviewed the records of 88 consecutive patients with FCD II treated with resective surgery between January 2015 and December 2018. The demographics, clinical characteristics, electrophysiological recordings, neuroimaging studies, histopathological findings, surgical outcomes, and complications were collected. After the exclusion of diffusely distributed and gyrus-based lesions, 71 patients (30 females, 41 males) who had undergone sulcus-centered resection were included in this study. The mean (± standard deviation) age of the cohort was 17.78 ± 10.54 years (38 pediatric patients, 33 adults). Thirty-five lesions (49%) were demonstrated on MRI; 42 patients (59%) underwent stereo-EEG monitoring before resective surgery; and 37 (52%) and 34 (48%) lesions were histopathologically proven to be FCD IIa and IIb, respectively. At a mean follow-up of 3.34 ± 1.17 years, 64 patients (90%) remained seizure free, and 7 (10%) had permanent neurological deficits including motor weakness, sensory deficits, and visual field deficits. The study findings showed that in carefully selected FCD II cases, sulcus-centered resection is an effective and safe surgical strategy.

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.

Recent Advances in Flexible and Stretchable Sensing Systems: From the Perspective of System Integration

Biological signals generated during various biological processes are critically important for providing insight into the human physiological status. Recently, there have been many great efforts in developing flexible and stretchable sensing systems to provide biological signal monitoring platforms with intimate integration with biological surfaces. Here, this review summarizes the recent advances in flexible and stretchable sensing systems from the perspective of electronic system integration. A comprehensive general sensing system architecture is described, which consists of sensors, sensor interface circuits, memories, and digital processing units. The subsequent content focuses on the integration requirements and highlights some advanced progress for each component. Next, representative examples of flexible and stretchable sensing systems for electrophysiological, physical, and chemical information monitoring are introduced. This review concludes with an outlook on the remaining challenges and opportunities for future fully flexible or stretchable sensing systems.

Interpretation of the Intracranial Stereoelectroencephalography Signal

The intracranial electroencephalogram (iEEG) is essential in decision making for epilepsy surgery. Although localization of epileptogenic brain regions by means of iEEG has been the gold standard for surgical decision-making for more than 70 years, established guidelines for what constitutes genuine iEEG epileptic activity and what is normal brain activity are not available. This review provides a summary of the current state of knowledge and understanding on normal iEEG entities and variants, the effects of sleep on regional and lobar iEEG, iEEG patterns of interictal and ictal epileptic activity and their relation to well-described epileptogenic pathologies and surgical outcome.

Realistic modeling of mesoscopic ephaptic coupling in the human brain

Several decades of research suggest that weak electric fields may influence neural processing, including those induced by neuronal activity and proposed as a substrate for a potential new cellular communication system, i.e., ephaptic transmission. Here we aim to model mesoscopic ephaptic activity in the human brain and explore its trajectory during aging by characterizing the electric field generated by cortical dipoles using realistic finite element modeling. Extrapolating from electrophysiological measurements, we first observe that modeled endogenous field magnitudes are comparable to those in measurements of weak but functionally relevant self-generated fields and to those produced by noninvasive transcranial brain stimulation, and therefore possibly able to modulate neuronal activity. Then, to evaluate the role of these fields in the human cortex in large MRI databases, we adapt an interaction approximation that considers the relative orientation of neuron and field to estimate the membrane potential perturbation in pyramidal cells. We use this approximation to define a simplified metric (EMOD1) that weights dipole coupling as a function of distance and relative orientation between emitter and receiver and evaluate it in a sample of 401 realistic human brain models from healthy subjects aged 16-83. Results reveal that ephaptic coupling, in the simplified mesoscopic modeling approach used here, significantly decreases with age, with higher involvement of sensorimotor regions and medial brain structures. This study suggests that by providing the means for fast and direct interaction between neurons, ephaptic modulation may contribute to the complexity of human function for cognition and behavior, and its modification across the lifespan and in response to pathology.

Functional and resting-state characterizations of a periventricular heterotopic nodule associated with epileptogenic activity

The object of this study was to extensively characterize a region of periventricular nodular heterotopia (PVNH) in an epilepsy patient to reveal its possible neurocognitive functional role(s). The authors used 3-T MRI approaches to exhaustively characterize a single, right hemisphere heterotopion in a high-functioning adult male with medically responsive epilepsy, which had manifested during late adolescence. The heterotopion proved to be spectroscopically consistent with a cortical-like composition and was interconnected with nearby ipsilateral cortical fundi, as revealed by fiber tractography (diffusion-weighted imaging) and resting-state functional connectivity MRI (rsfMRI). Moreover, the region of PVNH demonstrated two novel characterizations for a heterotopion. First, functional MRI (fMRI), as distinct from rsfMRI, showed that the heterotopion was significantly modulated while the patient watched animated video scenes of biological motion (i.e., cartoons). Second, rsfMRI, which demonstrated correlated brain activity during a task-negative state, uniquely showed directionality within an interconnected network, receiving positive path effects from patent cortical and cerebellar foci while outputting only negative path effects to specific brain foci.These findings are addressed in the context of the impact on noninvasive presurgical brain mapping strategies for adult and pediatric patient workups, as well as the impact of this study on an understanding of the functional cortical architecture underlying cognition from a neurodiversity and evolutionary perspective.

Superior Frontal Sulcus Focal Cortical Dysplasia Type II: An MRI, PET, and Quantified SEEG Study

Purpose: The superior frontal sulcus (SFS), located in the prefrontal and premotor cortex, is considered as one of the common locations of focal cortical dysplasia (FCD). However, the characteristics of seizures arising from this area are incompletely known. The primary purpose of this study was to investigate the clinical features and the epileptic networks of seizures originating from the SFS.

Methods: We included seventeen patients with type II FCD within the SFS. SFS was identified both visually and automatically. Semiological features were evaluated and grouped. Interictal 18FDG-PET imaging in all patients was compared to controls using statistical parametric mapping (SPM-PET). In those subjects with stereoelectroencephalography (SEEG), two different quantitative intracranial electroencephalography analyses were applied. Finally, the locations of the SFS-related hypometabolic regions and epileptogenic zones (EZs) were transformed into standard space for group analysis.

Results: We identified two semiological groups. Group 1 (9/17) showed elementary motor signs (head version and tonic posturing), while group 2 (8/17) exhibited complex motor behavior (fear, hypermotor, and ictal pouting). Based on SPM-PET, an SFS-supplementary motor area (SMA) epileptic propagation network was found in group 1, and an SFS-middle cingulate cortex (MCC)-pregenual anterior cingulate cortex (pACC) propagation network was discovered in group 2. Intracranial EEG analysis suggested similar affected structures with high epileptogenicity. The SFS-related hypometabolic regions and EZs in these groups showed a posterior-anterior spatial relationship.

Conclusions: Even though originating from the spatially restricted cortex, SFS seizures can be divided into two groups based on semiological features. The SFS-SMA and SFS-MCC-pACC epileptic propagation networks may play pivotal roles in the generation of different semiologies. The posterior-anterior spatial relationship of both hypometabolic regions and EZs provides potentially useful information for distinguishing different types of SFS seizures and surgical evaluation.

Detection of epileptogenic focus using advanced dynamic statistical parametric mapping with magnetoencephalography in a patient with MRI-negative focal cortical dysplasia type IIB

Advanced dynamic statistical parametric mapping (AdSPM) with magnetoencephalography (MEG) was used to identify MRI-negative epileptogenic lesions in this report. A 15-year-old girl had MRI-negative and pharmacology-resistant focal-onset epilepsy. She experienced two types of seizures. Type I consisted of her arousal from sleep, staring, and a forced head-turning movement to the left, followed by secondary generalization. Type II began with an aura of dizziness followed by staring and postictal headache with fatigue. Scalp video-electroencephalography (EEG) captured two type I seizures originating from the right frontocentral region. MEG showed scattered dipoles over the right frontal region. AdSPM identified the spike source at the bottom of the right inferior frontal sulcus. Intracranial video-EEG captured one type I seizure, which originated from the depth electrode at the bottom of the sulcus and correlated with the AdSPM spike source. Accordingly, the patient underwent resection of the middle and inferior frontal gyri, including the AdSPM-identified spike source. Histopathological examination revealed that the patient had focal cortical dysplasia type IIB. To date, the patient has been seizure free for 2 years while receiving topiramate treatment. This is the first preliminary report to identify MRI-negative epilepsy using AdSPM. Further investigation of AdSPM would be valuable for cases of MRI-negative focal epilepsy.

Recommendations of the Russian League Against Epilepsy (RLAE) on the use of magnetic resonance imaging in the diagnosis of epilepsy

Introduction. The MRI method has revolutionized the diagnosis of epilepsy. However, the widespread adoption of MRI in clinical practice is slowed by an insufficient number of high-field MRI scanners, a shortage of trained specialists, and the lack of standard examination protocols. The aim of this article is to present the Recommendations of the Russian League Against Epilepsy (RLAE) on the use of magnetic resonance imaging in the diagnosis of epilepsy.

Materials and methods. As a structural element of the International League Against Epilepsy (ILAE), the RLAE considers it important to adapt the Protocol developed by ILAE for specialists in Russia and EAEU countries. The working group analyzed and generalized the clinical practice existing in the Russian Federation, the Republic of Kazakhstan, the Republic of Belarus and the Republic of Uzbekistan. These recommendations are intended for doctors in specialized centers of epilepsy surgery, and for doctors in general medical centers. The recommendations are applicable primarily to adult patients, but the general principles are relevant to children as well.

Results. In all patients with convulsive seizures shortly after the first seizure, or patients diagnosed with epilepsy who have an unexplained increase in the frequency of seizures, rapid decrease in cognitive functions or the appearance / worsening of neuropsychiatric symptoms, the RLAE recommends using a unified MR protocol for the neuroimaging of structural sequences in epilepsy with three-dimensional pulse sequences T1 and T2 FLAIR with isotropic voxel 1 × 1 × 1 mm3 and two-dimensional T2- weighted pulse sequences with a pixel size of 1 × 1 mm2 or less. The MRI examination should be combined with EEG or EEG-video monitoring. Using this protocol allows one to set a unified standard for examining patients with epilepsy in order to detect (with high sensitivity) brain lesions playing a key role in the occurrence of seizures. Here, all 13 recommendations are presented.

Conclusion. Implementation of these recommendations in clinical practice will improve the access to high-tech medical care and optimize health care costs. 

A Surgical Case of Complete Resection of the Focal Cortical and Subcortical Dysplasia in the Motor Cortex

BACKGROUND

Focal cortical dysplasias (FCDs) are highly epileptogenic and frequently associated with medically refractory focal epilepsy. FCDs are frequently located in the frontal lobe, making its complete resection highly challenging when in proximity to the motor cortex.

CASE DESCRIPTION

We report a case of a 25-year-old woman with medically refractory epilepsy secondary to a focal cortical dysplasia in the motor cortex and extending deeply into the subcortical white matter. A detailed presurgical evaluation and invasive electroencephalographic monitoring performed at our epilepsy monitoring unit, along with the use of motor mapping, functional magnetic resonance imaging, diffusion tensor imaging, and the Stealth navigation system resulted in the complete resection of the lesion without a permanent postoperative motor deficit. The patient remained seizure-free at a 63-month follow-up while being maintained on a single antiepileptic drug.

CONCLUSION

A detailed presurgical evaluation, accurate mapping of the functional and dysplastic cortex, and a well-planned tailored and complete surgical resection of the cortical dysplasia can result in a favorable outcome with relatively little risk of postoperative neurologic deficit.

Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers

Purpose:

To test whether our proposed denoising approach with deep learning-based reconstruction (dDLR) can effectively denoise brain MR images.

Methods:

In an initial experimental study, we obtained brain images from five volunteers and added different artificial noise levels. Denoising was applied to the modified images using a denoising convolutional neural network (DnCNN), a shrinkage convolutional neural network (SCNN), and dDLR. Using these brain MR images, we compared the structural similarity (SSIM) index and peak signal-to-noise ratio (PSNR) between the three denoising methods. Two neuroradiologists assessed the image quality of the three types of images. In the clinical study, we evaluated the denoising effect of dDLR in brain images with different levels of actual noise such as thermal noise. Specifically, we obtained 2D-T₂-weighted image, 2D-fluid-attenuated inversion recovery (FLAIR) and 3D-magnetization-prepared rapid acquisition with gradient echo (MPRAGE) from 15 healthy volunteers at two different settings for the number of image acquisitions (NAQ): NAQ2 and NAQ5. We reconstructed dDLR-processed NAQ2 from NAQ2, then compared with SSIM and PSNR. Two neuroradiologists separately assessed the image quality of NAQ5, NAQ2 and dDLR-NAQ2. Statistical analysis was performed in the experimental and clinical study. In the clinical study, the inter-observer agreement was also assessed.

Results:

In the experimental study, PSNR and SSIM for dDLR were statistically higher than those of DnCNN and SCNN (P < 0.001). The image quality of dDLR was also superior to DnCNN and SCNN. In the clinical study, dDLR-NAQ2 was significantly better than NAQ2 images for SSIM and PSNR in all three sequences (P < 0.05), except for PSNR in FLAIR. For all qualitative items, dDLR-NAQ2 had equivalent or better image quality than NAQ5, and superior quality to that of NAQ2 (P < 0.05), for all criteria except artifact. The inter-observer agreement ranged from substantial to near perfect.

Conclusion:

dDLR reduces image noise while preserving image quality on brain MR images.

Recommendations for the use of structural magnetic resonance imaging in the care of patients with epilepsy: A consensus report from the International League Against Epilepsy Neuroimaging Task Force

Structural magnetic resonance imaging (MRI) is of fundamental importance to the diagnosis and treatment of epilepsy, particularly when surgery is being considered. Despite previous recommendations and guidelines, practices for the use of MRI are variable worldwide and may not harness the full potential of recent technological advances for the benefit of people with epilepsy. The International League Against Epilepsy Diagnostic Methods Commission has thus charged the 2013-2017 Neuroimaging Task Force to develop a set of recommendations addressing the following questions: (1) Who should have an MRI? (2) What are the minimum requirements for an MRI epilepsy protocol? (3) How should magnetic resonance (MR) images be evaluated? (4) How to optimize lesion detection? These recommendations target clinicians in established epilepsy centers and neurologists in general/district hospitals. They endorse routine structural imaging in new onset generalized and focal epilepsy alike and describe the range of situations when detailed assessment is indicated. The Neuroimaging Task Force identified a set of sequences, with three-dimensional acquisitions at its core, the harmonized neuroimaging of epilepsy structural sequences-HARNESS-MRI protocol. As these sequences are available on most MR scanners, the HARNESS-MRI protocol is generalizable, regardless of the clinical setting and country. The Neuroimaging Task Force also endorses the use of computer-aided image postprocessing methods to provide an objective account of an individual's brain anatomy and pathology. By discussing the breadth and depth of scope of MRI, this report emphasizes the unique role of this noninvasive investigation in the care of people with epilepsy.