Voxel-based morphometry in the detection of dysplasia and neoplasia in childhood epilepsy: Combined grey/white matter analysis augments detection

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

OBJECTIVE

Accurate detection of focal cortical dysplasia (FCD) through magnetic resonance imaging (MRI) plays a pivotal role in the preoperative assessment of epilepsy. The integration of multimodal imaging has demonstrated substantial value in both diagnosing FCD and devising effective surgical strategies. This study aimed to enhance MRI post-processing by incorporating positron emission tomography (PET) analysis. We sought to compare the diagnostic efficacy of diverse image post-processing methodologies in patients presenting MRI-negative FCD.

METHODS

In this retrospective investigation, we assembled a cohort of patients with negative preoperative MRI results. T1-weighted volumetric sequences were subjected to morphometric analysis program (MAP) and composite parametric map (CPM) post-processing techniques. We independently co-registered images derived from various methods with PET scans. The alignment was subsequently evaluated, and its correlation was correlated with postoperative seizure outcomes.

RESULTS

A total of 41 patients were enrolled in the study. In the PET-MAP(p = 0.0189) and PET-CPM(p = 0.00041) groups, compared with the non-overlap group, the overlap group significantly associated with better postoperative outcomes. In PET(p = 0.234), CPM(p = 0.686) and MAP(p = 0.672), there is no statistical significance between overlap and seizure-free outcomes. The sensitivity of using the CPM alone outperformed the MAP (0.65 vs 0.46). The use of PET-CPM demonstrated superior sensitivity (0.96), positive predictive value (0.83), and negative predictive value (0.91), whereas the MAP displayed superior specificity (0.71).

CONCLUSIONS

Our findings suggested a superiority in sensitivity of CPM in detecting potential FCD lesions compared to MAP, especially when it is used in combination with PET for diagnosis of MRI-negative epilepsy patients. Moreover, we confirmed the superiority of synergizing metabolic imaging (PET) with quantitative maps derived from structural imaging (MAP or CPM) to enhance the identification of subtle epileptogenic zones (EZs). This study serves to illuminate the potential of integrated multimodal techniques in advancing our capability to pinpoint elusive pathological features in epilepsy cases.

Preoperative Detection of Subtle Focal Cortical Dysplasia in Children by Combined Arterial Spin Labeling, Voxel-Based Morphometry, Electroencephalography-Synchronized Functional MRI, Resting-State Regional Homogeneity, and 18F-fluorodeoxyglucose Positron Emission Tomography

BACKGROUND

Focal cortical dysplasia (FCD) causes drug-resistant epilepsy in children that can be cured surgically, but the lesions are often unseen by imaging.

OBJECTIVE

To assess the efficiency of arterial spin labeling (ASL), voxel-based-morphometry (VBM), fMRI electroencephalography (EEG), resting-state regional homogeneity (ReHo), 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET), and their combination in detecting pediatric FCD.

METHODS

We prospectively included 10 children for whom FCD was localized by surgical resection. They underwent 3T MR acquisition with concurrent EEG, including ASL perfusion, resting-state BOLD fMRI (allowing the processing of EEG-fMRI and ReHo), 3D T1-weighted images processed using VBM, and FDG PET-CT coregistered with MRI. Detection was assessed visually and by comparison with healthy controls (for ASL and VBM).

RESULTS

Eight children had normal MRI, and 2 had asymmetric sulci. Using MR techniques, FCD was accurately detected by ASL for 6/10, VBM for 5/10, EEG-fMRI for 5/8 (excluding 2 with uninterpretable results), and ReHo for 4/10 patients. The combination of ASL, VBM, and ReHo allowed correct FCD detection for 9/10 patients. FDG PET alone showed higher accuracy than the other techniques (7/9), and its combination with VBM allowed correct FCD detection for 8/9 patients. The detection efficiency was better for patients with asymmetric sulci (2/2 for all techniques), but advanced MR techniques and PET were useful for MR-negative patients (7/8).

CONCLUSION

A combination of multiple imaging techniques, including PET, ASL, and VBM analysis of T1-weighted images, is effective in detecting subtle FCD in children.

The Noninvasive Evaluation for Minimally Invasive Pediatric Epilepsy Surgery (MIPES): A Multimodal Exploration of the Localization-Based Hypothesis

Minimally invasive pediatric epilepsy surgery (MIPES) is a rising technique in the management of focal-onset drug-refractory epilepsy. Minimally invasive surgical techniques are based on small, focal interventions (such as parenchymal ablation or localized neuromodulation) leading to elimination of the seizure onset zone or interruption of the larger epileptic network. Precise localization of the seizure onset zone, demarcation of eloquent cortex, and mapping of the network leading to seizure propagation are required to achieve optimal outcomes. The toolbox for presurgical, noninvasive evaluation of focal epilepsy continues to expand rapidly, with a variety of options based on advanced imaging and electrophysiology. In this article, we will examine several of these diagnostic modalities from the standpoint of MIPES and discuss how each can contribute to the development of a localization-based hypothesis for potential surgical targets.

Advanced neuroimaging techniques for evaluating pediatric epilepsy

Accurate localization of the seizure onset zone is important for better seizure outcomes and preventing deficits following epilepsy surgery. Recent advances in neuroimaging techniques have increased our understanding of the underlying etiology and improved our ability to noninvasively identify the seizure onset zone. Using epilepsy-specific magnetic resonance imaging (MRI) protocols, structural MRI allows better detection of the seizure onset zone, particularly when it is interpreted by experienced neuroradiologists. Ultra-high-field imaging and postprocessing analysis with automated machine learning algorithms can detect subtle structural abnormalities in MRI-negative patients. Tractography derived from diffusion tensor imaging can delineate white matter connections associated with epilepsy or eloquent function, thus, preventing deficits after epilepsy surgery. Arterial spin-labeling perfusion MRI, simultaneous electroencephalography (EEG)-functional MRI (fMRI), and magnetoencephalography (MEG) are noinvasive imaging modalities that can be used to localize the epileptogenic foci and assist in planning epilepsy surgery with positron emission tomography, ictal single-photon emission computed tomography, and intracranial EEG monitoring. MEG and fMRI can localize and lateralize the area of the cortex that is essential for language, motor, and memory function and identify its relationship with planned surgical resection sites to reduce the risk of neurological impairments. These advanced structural and functional imaging modalities can be combined with postprocessing methods to better understand the epileptic network and obtain valuable clinical information for predicting long-term outcomes in pediatric epilepsy.

Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening

In this study, we propose a novel anomaly detection model targeting subtle brain lesions in multiparametric MRI. To compensate for the lack of annotated data adequately sampling the heterogeneity of such pathologies, we cast this problem as an outlier detection problem and introduce a novel configuration of unsupervised deep siamese networks to learn normal brain representations using a series of non-pathological brain scans. The proposed siamese network, composed of stacked convolutional autoencoders as subnetworks is designed to map patches extracted from healthy control scans only and centered at the same spatial localization to 'close' representations with respect to the chosen metric in a latent space. It is based on a novel loss function combining a similarity term and a regularization term compensating for the lack of dissimilar pairs. These latent representations are then fed into oc-SVM models at voxel-level to produce anomaly score maps. We evaluate the performance of our brain anomaly detection model to detect subtle epilepsy lesions in multiparametric (T1-weighted, FLAIR) MRI exams considered as normal (MRI-negative). Our detection model trained on 75 healthy subjects and validated on 21 epilepsy patients (with 18 MRI-negatives) achieves a maximum sensitivity of 61% on the MRI-negative lesions, identified among the 5 most suspicious detections on average. It is shown to outperform detection models based on the same architecture but with stacked convolutional or Wasserstein autoencoders as unsupervised feature extraction mechanisms.

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.

Magnetoencephalography and New Imaging Modalities in Epilepsy

The success of epilepsy surgery is highly dependent on correctly identifying the entire epileptogenic region. Current state-of-the-art for localizing the extent of surgically amenable areas involves combining high resolution three-dimensional magnetic resonance imaging (MRI) with electroencephalography (EEG) and magnetoencephalography (MEG) source modeling of interictal epileptiform activity. Coupling these techniques with newer quantitative structural MRI techniques, such as cortical thickness measurements, however, may improve the extent to which the abnormal epileptogenic region can be visualized. In this review we assess the utility of EEG, MEG and quantitative structural MRI methods for the evaluation of patients with epilepsy and introduce a novel method for the co-localization of a structural MRI measurement to MEG and EEG source modeling. When combined, these techniques may better identify the extent of abnormal structural and functional areas in patients with medically intractable epilepsy.

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.

Detection of Lesions Underlying Intractable Epilepsy on T1-Weighted MRI as an Outlier Detection Problem

Pattern recognition methods, such as computer aided diagnosis (CAD) systems, can help clinicians in their diagnosis by marking abnormal regions in an image. We propose a machine learning system based on a one-class support vector machine (OC-SVM) classifier for the detection of abnormalities in magnetic resonance images (MRI) applied to patients with intractable epilepsy. The system learns the features associated with healthy control subjects, allowing a voxelwise assessment of the deviation of a test subject pattern from the learned patterns. While any number of various features can be chosen and learned, here we focus on two texture parameters capturing image patterns associated with epileptogenic lesions on T1-weighted brain MRI e.g. heterotopia and blurred junction between the grey and white matter. The CAD output consists of patient specific 3D maps locating clusters of suspicious voxels ranked by size and degree of deviation from control patterns. System performance was evaluated using realistic simulations of challenging detection tasks as well as clinical data of 77 healthy control subjects and of eleven patients (13 lesions). It was compared to that of a mass univariate statistical parametric mapping (SPM) single subject analysis based on the same set of features. For all simulations, OC-SVM yielded significantly higher values of the area under the ROC curve (AUC) and higher sensitivity at low false positive rate. For the clinical data, both OC-SVM and SPM successfully detected 100% of the lesions in the MRI positive cases (3/13). For the MRI negative cases (10/13), OC-SVM detected 7/10 lesions and SPM analysis detected 5/10 lesions. In all experiments, OC-SVM produced fewer false positive detections than SPM. OC-SVM may be a versatile system for unbiased lesion detection.

Computational analysis in epilepsy neuroimaging: A survey of features and methods

Epilepsy affects 65 million people worldwide, a third of whom have seizures that are resistant to anti-epileptic medications. Some of these patients may be amenable to surgical therapy or treatment with implantable devices, but this usually requires delineation of discrete structural or functional lesion(s), which is challenging in a large percentage of these patients.

Advances in neuroimaging and machine learning allow semi-automated detection of malformations of cortical development (MCDs), a common cause of drug resistant epilepsy. A frequently asked question in the field is what techniques currently exist to assist radiologists in identifying these lesions, especially subtle forms of MCDs such as focal cortical dysplasia (FCD) Type I and low grade glial tumors. Below we introduce some of the common lesions encountered in patients with epilepsy and the common imaging findings that radiologists look for in these patients. We then review and discuss the computational techniques introduced over the past 10 years for quantifying and automatically detecting these imaging findings. Due to large variations in the accuracy and implementation of these studies, specific techniques are traditionally used at individual centers, often guided by local expertise, as well as selection bias introduced by the varying prevalence of specific patient populations in different epilepsy centers. We discuss the need for a multi-institutional study that combines features from different imaging modalities as well as computational techniques to definitively assess the utility of specific automated approaches to epilepsy imaging. We conclude that sharing and comparing these different computational techniques through a common data platform provides an opportunity to rigorously test and compare the accuracy of these tools across different patient populations and geographical locations. We propose that these kinds of tools, quantitative imaging analysis methods and open data platforms for aggregating and sharing data and algorithms, can play a vital role in reducing the cost of care, the risks of invasive treatments, and improve overall outcomes for patients with epilepsy.

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We introduce common epileptogenic lesions encountered in patients with drug resistant epilepsy.

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We discuss state of the art computational techniques used to detect lesions.

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There is a need for multi-institutional studies that combine these techniques.

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Clinically validated pipelines alongside the advances in imaging and electrophysiology will improve outcomes.

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

OBJECTIVE

In the presurgical workup of magnetic resonance imaging (MRI)-negative (MRI(-) or "nonlesional") pharmacoresistant focal epilepsy (PFE) patients, discovering a previously undetected lesion can drastically change the evaluation and likely improve surgical outcome. Our study utilizes a voxel-based MRI postprocessing technique, implemented in a morphometric analysis program (MAP), to facilitate detection of subtle abnormalities in a consecutive cohort of MRI(-) surgical candidates.

METHODS

Included in this retrospective study was a consecutive cohort of 150 MRI(-) surgical patients. MAP was performed on T1-weighted MRI, with comparison to a scanner-specific normal database. Review and analysis of MAP were performed blinded to patients' clinical information. The pertinence of MAP(+) areas was confirmed by surgical outcome and pathology.

RESULTS

MAP showed a 43% positive rate, sensitivity of 0.9, and specificity of 0.67. Overall, patients with the MAP(+) region completely resected had the best seizure outcomes, followed by the MAP(-) patients, and patients who had no/partial resection of the MAP(+) region had the worst outcome (p < 0.001). Subgroup analysis revealed that visually identified subtle findings are more likely correct if also MAP(+) . False-positive rate in 52 normal controls was 2%. Surgical pathology of the resected MAP(+) areas contained mainly non-balloon-cell focal cortical dysplasia (FCD). Multiple MAP(+) regions were present in 7% of patients.

INTERPRETATION

MAP can be a practical and valuable tool to: (1) guide the search for subtle MRI abnormalities and (2) confirm visually identified questionable abnormalities in patients with PFE due to suspected FCD. A MAP(+) region, when concordant with the patient's electroclinical presentation, should provide a legitimate target for surgical exploration.

Multidimensional morphometric 3D MRI analyses for detecting brain abnormalities in children: impact of control population

Automated morphometric approaches are used to detect epileptogenic structural abnormalities in 3D MR images in adults, using the variance of a control population to obtain z-score maps in an individual patient. Due to the substantial changes the developing human brain undergoes, performing such analyses in children is challenging. This study investigated six features derived from high-resolution T1 datasets in four groups: normal children (1.5T or 3T data), normal clinical scans (3T data), and patients with structural brain lesions (3T data), with each n = 10. Normative control data were obtained from the NIH study on normal brain development (n = 401). We show that control group size substantially influences the captured variance, directly impacting the patient's z-scores. Interestingly, matching on gender does not seem to be beneficial, which was unexpected. Using data obtained at higher field scanners produces slightly different base rates of suprathreshold voxels, as does using clinically derived normal studies, suggesting a subtle but systematic effect of both factors. Two approaches for controlling suprathreshold voxels in a multidimensional approach (combining features and requiring a minimum cluster size) were shown to be substantial and effective in reducing this number. Finally, specific strengths and limitations of such an approach could be demonstrated in individual cases.

Linking MRI postprocessing with magnetic source imaging in MRI-negative epilepsy

OBJECTIVE

MRI-negative (MRI-) pharmacoresistant focal epilepsy (PFE) patients are most challenging for epilepsy surgical management. This study utilizes a voxel-based MRI postprocessing technique, implemented using a morphometric analysis program (MAP), aiming to facilitate detection of subtle focal cortical dysplasia (FCD) in MRI- patients. Furthermore, the study examines the concordance between MAP-identified regions and localization from magnetic source imaging (MSI).

METHODS

Included in this retrospective study were 25 MRI- surgical patients. MAP was performed on T1-weighted MRI, with comparison to a normal database. The pertinence of MAP+ areas was confirmed by MSI, surgical outcome and pathology. Analyses of MAP and MSI were performed blindly from patients' clinical information and independently from each other.

RESULTS

The detection rate of subtle changes by MAP was 48% (12/25). Once MAP+ areas were resected, patients were more likely to be seizure-free (p=0.02). There were no false positives in the 25 age-matched normal controls. Seven patients had a concordant MSI correlate. Patients in whom a concordant area was identified by both MAP and MSI had a significantly higher chance of achieving a seizure-free outcome following complete resection of this area (p=0.008). In the 9 resected MAP+ areas, pathology revealed FCD type IA in 7 and type IIB in 2.

INTERPRETATION

MAP shows promise in identifying subtle FCD abnormalities and increasing the diagnostic yield of conventional MRI visual analysis in presurgical evaluation of PFE. Concordant MRI postprocessing and MSI analyses may lead to the noninvasive identification of a structurally and electrically abnormal subtle lesion that can be surgically targeted.

Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy

Intracranial EEG (icEEG) monitoring is critical in epilepsy surgical planning, but it has limitations. The advances of neuroimaging have made it possible to reveal epileptic abnormalities that could not be identified previously and improve the localization of the seizure focus and the vital cortex. A frequently asked question in the field is whether non-invasive neuroimaging could replace invasive icEEG or reduce the need for icEEG in presurgical evaluation. This review considers promising neuroimaging techniques in epilepsy presurgical assessment in order to address this question. In addition, due to large variations in the accuracies of neuroimaging across epilepsy centers, multicenter neuroimaging studies are reviewed, and there is much need for randomized controlled trials (RCTs) to better reveal the utility of presurgical neuroimaging. The results of multiple studies indicate that non-invasive neuroimaging could not replace invasive icEEG in surgical planning especially in non-lesional or extratemporal lobe epilepsies, but it could reduce the need for icEEG in certain cases. With technical advances, multimodal neuroimaging may play a greater role in presurgical evaluation to reduce the costs and risks of epilepsy surgery, and provide surgical options for more patients with drug-resistant epilepsy.

MRI findings in low grade tumours associated with focal cortical dysplasia

Magnetic resonance imaging (MRI) is mandatory to identify the epileptogenic zone in refractory temporal lobe epilepsy (TLE). The correct identification of lesions is essential to obtain good post-surgery seizure control. Low grade tumours (LGT) and focal cortical dysplasia (FCD) are common findings in symptomatic TLE, and frequently coexist. The aim of this study was to identify the MRI characteristics in the diagnosis of FCD associated with LGT. We analyzed 24 subjects with TLE who underwent tailored surgery. They all had LGTs. Two expert neuroradiologists analyzed the imaging data and compared them with histological results, hypothesizing the causes of diagnostic errors in the identification of FCD. We selected three exemplary cases to report the most important causes of errors. In the diagnosis of FCD we reported false positives and false negatives due to different causes. An incomplete MRI protocol, the large dimensions of the tumour, infiltration and related oedema were the most important factors limiting MRI accuracy. MRI can be limited by an incomplete protocol. In addition, the presence of an LGT may limit the neuroradiological diagnosis of FCD in the temporal lobe. Advanced MRI techniques could help reveal subtle lesions that eluded a previous imaging inspection.

Management of cortical dysplasia in epilepsy

Focal cortical dysplasias (FCD) are increasingly diagnosed as a cause of symptomatic focal epilepsy in paediatric and adult patients. Nowadays, focal cortical dysplasias are identified as the underlying pathology in up to 25% of patients with focal epilepsies. The histological appearance can vary from mild architectural disturbances to severe malformation containing atypical cellular elements like dysmorphic neurons and Balloon cells. Clinical presentation depends on the age at onset of epilepsy, the location and size of the lesion. In most patients seizures begin in early childhood and the course of epilepsy is often severe and pharmaco-resistant. For the majority of patients, epilepsy surgery is the only treatment option in order to become seizure free.In this review an overview on the literature of the last ten years is provided, focussing on histological appearance and classification, pathogenetic mechanisms and clinical presentation of cortical dysplasias. Recent developments in the presurgical diagnostic and outcome after operative treatment as well as prognostic factors are summarized. Finally, an outlook is given on the development of future novel treatment options that might be minimally invasive and help especially the patient group who is inoperable or has failed epilepsy surgery.

Multimodality approach in cryptogenic epilepsy with focus on morphometric 3T MRI

PURPOSE

This study aimed to investigate the potential contribution of morphometric MRI analysis in comparison to other modalities, such as MEG, SPECT and PET, in identifying the epileptogenic focus in patients with cryptogenic epilepsy.

PATIENTS AND METHODS

Study inclusion was limited to epilepsy patients with a monolobar focus hypothesis, as concluded from EEG/seizure semiology and the best individual concordance rate. Feature maps, generated by the MATLAB(®) "morphometric analysis program" (MAP), were evaluated by a neuroradiologist blinded to conventional MRI and the focus hypothesis (MAP(1)). In addition, the feature maps were also interpreted by simultaneous matching conventional MRI but, again, with the reader having no knowledge of the focus hypothesis (MAP(2)).

RESULTS

In 12 out of 51 patients, true-positive findings were achieved (MAP(1): sensitivity 24%; specificity 96%). The sensitivity of the MAP(1) results was superior extratemporally. After matching conventional MRI, FCD was traced in six of the 12 patients (MAP(2): sensitivity 12%; specificity 100%). MEG sensitivity was 62%. Sensitivity of interictal and ictal SPECT was 20% and 50%, respectively. PET was not as sensitive extratemporally (19%) as temporally (82%). The greatest correspondence with the best individual concordance rate was noted with PET (14/16; 88%) and MEG (8/10; 80%), followed by interictal (5/8; 63%) and ictal (9/15; 60%) SPECT. Results for MAP(1) were 53% (10/19), and 100% for MAP(2) (6/6).

CONCLUSION

Although MAP sensitivity and specificity results are lower in comparison to other modalities, implementation of the technique should be considered first, before arranging any further investigations. The present study results offer guidelines for the implementation, interpretation and concordance of diagnostic procedures.

Manual, semi-automated, and automated delineation of chronic brain lesions: a comparison of methods

The exact delineation of chronic brain lesions is a crucial step when investigating the relationship between brain structure and (dys-)function. For this, manual tracing, although very time-consuming, is still the gold standard. In order to assess the possible contributions from other methods, we compared manual tracing of lesion boundaries with a newly developed semi-automated and a fully automated approach for lesion definition in a sample of chronic stroke patients (n=11, 5m, median age 12, range 10-30years). Manual tracing requires substantially more human input (4.8-9.6h/subject) than semi-automated (24.9min/subject) and automated processing (1min/subject). When compared with manual tracing as the gold standard, both the semi-automated (tested with 4 different smoothing filters) and the automated approach towards lesion definition performed on an acceptable level, with an average Dice's similarity index of .53-.60 (semi-automated) and .49 (automated processing). In all semi-automated and automated approaches, larger lesions were identified with a significantly higher performance than smaller lesions, as were central versus peripheral voxels, indicating that the surface-to-volume ratio explains this trend. The automated approach failed to identify two lesions. In several cases, indirect lesion effects (such as enlarged ventricles) were detected using the semi-automated or the automated approach. We conclude that manual tracing remains the gold standard for exact lesion delineation, but that semi-automated and automated approaches may be alternatives for larger lesions and/or larger studies. The detection of indirect lesion effects may be another application of such approaches in the future.

Voxel-based morphometry and epilepsy

Voxel-based morphometry is an automated technique for MRI analyses, developed to study differences in brain morphology and frequently used to study patients with diverse disorders. In epilepsy, it has been used to investigate areas with reduction or increase of gray and white matter, in different syndromes (i.e., temporal lobe epilepsy, focal cortical dysplasia and generalized epilepsies). In temporal lobe epilepsy, voxel-based morphometry showed gray/white matter atrophy extending beyond the atrophic hippocampus. These widespread abnormalities have been associated with seizure frequency, epilepsy duration, incidence of precipitating factors, cognitive dysfunction and surgical outcome. In generalized epilepsies, gray matter abnormalities were identified mainly in the thalamus and frontal cortex, reinforcing the role of the thalamocortical network in the mechanisms of generalized seizures.

Current themes in neuroimaging of epilepsy: brain networks, dynamic phenomena, and clinical relevance

Brain scanning methods were first applied in patients with epilepsy more than 30years ago. A very substantial literature now exists in this field, which is exponentially increasing. Contemporary neuroimaging studies in epilepsy reflect new concepts in the epilepsies, as well as current methodological developments. In particular, this area is emphasising the role of networks in epileptogenicity, the existence of dynamic phenomena which can be captured by imaging, and is beginning to validate the implementation of neuroimaging in the clinic. Here, recent studies of the last 5years are reviewed, covering the full range of neuroimaging methods with SPECT, PET and MRI in epilepsy.

Voxel-Based Morphometry in Patients with Cryptogenic Occipital Epilepsies

We evaluated the differences in grey matter concentration (GMC) by voxel-based morphometry (VBM) in patients with cryptogenic occipital epilepsies. VBM analysis was performed in 11 patients with cryptogenic occipital epilepsies compared to 11 healthy controls. VBM analysis in patients revealed focal areas of reduced GMC in the occipital cortex and, more interestingly, increased GMC in the midbrain tegmentum and basal ganglia (globus pallidus and thalamus). VBM may disclose slight structural abnormalities in the brain of cryptogenic epilepsy patients, not evident with standard MRI. To the best of our knowledge, this is the first literature report describing areas of altered GMC in patients with occipital epilepsy. We hypothesize that these findings might be related to epileptic discharges and/or their diffusion and suggest that midbrain, globus pallidus and thalamus may be part of a functional network originating from the occipital areas.

New directions in clinical imaging of cortical dysplasias

Neuroimaging is essential in the work-up of patients with intractable epilepsy. In pediatric patients with medically refractory epilepsy, cortical dysplasias account for a large percentage of the epileptogenic substrate. Unfortunately, these are also the most subtle lesions to identify. For this reason, there has been ongoing interest in utilizing new advanced magnetic resonance imaging (MRI) techniques to improve the ability to identify, diagnose, characterize, and delineate cortical dysplasias. Technologic gains such as multichannel coils (32 phased array and beyond) and higher field strengths (3T, 7T, and greater) coupled with newer imaging sequences such as arterial spin labeling (ASL), susceptibility weighted imaging (SWI) and diffusion tensor/spectrum imaging (DTI/DSI) are likely to increase yield. Improved MRI techniques coupled with a multimodality approach including magnetoencephalography (MEG), positron emission tomography (PET), and other techniques will increase sensitivity and specificity for identifying cortical dysplasias.

Voxel-based morphometry in individual patients: a pilot study in early Huntington disease

BACKGROUND AND PURPOSE

Voxel-based morphometry (VBM) has proved a powerful method to detect subtle changes of gray matter (GM) at the group level but the role of VBM for the detection of GM changes in single subjects, especially in those with suspected neurodegenerative disorder, remains uncertain. Here, we performed single subject analyses in 22 patients in early stages of Huntington disease (HD), a neurodegenerative disorder with a well-known and characteristic pattern of GM loss.

MATERIALS AND METHODS

We applied an ANCOVA with age and gender as covariates and corrected for multiple statistical tests by false discovery rate (P < 0.05). Each patient was compared to 133 healthy controls. The same procedure was applied to 22 of the controls matched for age and gender in a pair-wise manner.

RESULTS

Our analyses yielded biologically plausible results in HD patients in which GM decrease within the caudate nucleus could be identified in 15 of the 16 most affected patients while GM decrease was found in only 1 control subject. Lowering the size of the control group yielded comparable results with 99 and 66 control subjects whereas sensitivity decreased with 33 control subjects.

CONCLUSIONS

Our pilot study demonstrates a potential role of VBM for the detection of cerebral GM changes in single subjects with suspected neurodegenerative disorder.

Voxel-based morphometry in the R6/2 transgenic mouse reveals differences between genotypes not seen with manual 2D morphometry

The R6/2 mouse is the most common mouse model used for Huntington's disease (HD), a fatal, inherited neurodegenerative CAG disorder characterized by marked brain atrophy. We scanned 47 R6/2 transgenic and 42 wildtype (WT) ex vivo mouse brains at 18 weeks of age using high resolution, three-dimensional magnetic resonance imaging (MRI) for automated voxel-based morphometry (VBM) analysis. We found differences between genotypes in specific brain structures. Many of these changes were bilateral and were found in regions known to be involved in the behavioral deficits present in both R6/2 mice and HD patients. In particular, changes were evident in the basal ganglia, hippocampus, cortex and hypothalamus. In the striatum, changes were heterogenous and reminiscent of striosomal distribution. Changes were also seen in the cerebellum, as might be expected in a mouse carrying a repeat length typical of juvenile onset HD. Many of these changes were not detected by manual 2D morphometry from the same MR images. These data indicate that VBM will be a valuable technique for in vivo measurement of developing pathology in HD transgenic mice, and may be particularly useful for correlating histologically undetectable changes with behavioral deficits.