Brain imaging in the assessment for epilepsy surgery

doi:10.1016/S1474-4422(15)00383-X

The Lancet Neurology

Volume 15, Issue 4, April 2016, Pages 420-433

https://doi.org/10.1016/S1474-4422(15)00383-X Get rights and content

Summary

Brain imaging has a crucial role in the presurgical assessment of patients with epilepsy. Structural imaging reveals most cerebral lesions underlying focal epilepsy. Advances in MRI acquisitions including diffusion-weighted imaging, post-acquisition image processing techniques, and quantification of imaging data are increasing the accuracy of lesion detection. Functional MRI can be used to identify areas of the cortex that are essential for language, motor function, and memory, and tractography can reveal white matter tracts that are vital for these functions, thus reducing the risk of epilepsy surgery causing new morbidities. PET, SPECT, simultaneous EEG and functional MRI, and electrical and magnetic source imaging can be used to infer the localisation of epileptic foci and assist in the design of intracranial EEG recording strategies. Progress in semi-automated methods to register imaging data into a common space is enabling the creation of multimodal three-dimensional patient-specific datasets. These techniques show promise for the demonstration of the complex relations between normal and abnormal structural and functional data and could be used to direct precise intracranial navigation and surgery for individual patients.

Introduction

Epilepsy develops in 50 in every 100 000 people per year; in a third of these people, antiepileptic drugs do not control seizures.¹ About half of these latter individuals have focal epilepsy that is potentially amenable to neurosurgical treatment if there is evidence to suggest a single focal network underlying the epilepsy, if the individual would be able to withstand neurosurgery,² and if they do not have severe comorbidities, such as active cancer, advanced vascular disease, or dementia.

Brain imaging is of fundamental importance to diagnosis and treatment of epilepsy, particularly when neurosurgical treatment is being considered. Dramatic advances have been made in brain imaging applied to epilepsy in the past 20 years, principally because of advances in MRI scanner technology, acquisition protocols, and image processing methods, and in nuclear medicine.³ In this Review, we focus principally on advances made since 2005 that are of potential clinical importance to the practising neurologist. We first review developments in structural brain imaging with MRI and post-acquisition processing methods to identify cerebral abnormalities that might cause epilepsy, the identification of which might lead to consideration of surgery. We then describe the mapping of areas of cortex that are essential for language, motor, and memory functions (eloquent cortex) and the crucial white matter pathways in the brain. Next, we review PET and other imaging methods to infer the localisation of cerebral networks that could generate epileptic seizures in the context of MRI findings that are inconclusive or discordant with clinical and EEG data. Finally, we review the integration of multimodal three-dimensional imaging data and how these methods have an evolving role in the design of treatment strategies for individual patients, and consider forthcoming advances. Panel 1 comprises a glossary of MRI terms used in this Review.

In the interpretation of imaging studies, an important factor is recognition of the difference between group studies, as used in neuroscience investigations to infer the functional anatomy of the brain and its abnormalities in a disorder, and clinical studies, in which the results affect the diagnostic and treatment pathways of individual patients. The latter are focused on individuals with medically refractory focal epilepsies, and their surgical treatment, in whom the finding of focal abnormalities might lead to a surgical solution and identification of critical structures might constrain the surgical approach.

Section snippets

The sequence of presurgical imaging investigations

The prerequisite for imaging investigations in the presurgical assessment of patients with epilepsy is high-quality structural MRI, interpreted in the context of clinical and EEG data, with quantification of hippocampal volumes and T2 signal, to identify an epileptogenic lesion. If there is a relevant structural lesion that is concordant with the results of scalp video EEG telemetry and not close to eloquent cortex, the patient can be recommended for surgery, with functional MRI (fMRI) at this

Identification of structural cerebral abnormalities

Structural MRI is the main neuroimaging technique for identification of an epileptogenic lesion. Localising and delineating the extent of the underlying lesion and its relation to eloquent cortex forms a crucial part of the assessment for surgery. Identification of a lesion leads to a greater chance of seizure freedom after surgery.5, 6 However, 15–30% of patients with refractory focal epilepsy do not have distinct lesions on MRI (ie, they are MRI negative).7, 8 The underlying pathological

Mapping eloquent brain functions

Identifying the cerebral lateralisation of speech and the localisation of eloquent functions is crucial when planning surgical resections close to areas of the brain involved in these functions, so that the risk of creating new deficits can be taken into account when making a decision about surgery and the surgical approach can be planned to minimise the risk.

Mapping cerebral white matter connections

fMRI can be used to identify eloquent cortex, but surgical damage to white matter connections must also be avoided to prevent postoperative neurological deficits. Tractography data derived from diffusion-weighted MRI, usually diffusion tensor imaging, enables the non-invasive in-vivo delineation of white matter tracts.

Most clinical research into white matter tracts in patients with epilepsy has focused on the optic radiation because damage to Meyer's loop during anterior temporal lobe resection

Localisation of epileptic activity

If MRI does not show a structural lesion that is concordant with clinical and EEG data, further investigations are necessary to infer the localisation of the epileptic network (figure 1).⁴

Integration of multimodal three-dimensional imaging in the epilepsy surgery pathway

In 20–30% of candidates for epilepsy surgery, intracranial EEG is needed to define the epileptogenic zone.¹⁰¹ Increasingly, this is accomplished with stereotactic placement of several (ie, 12–20) depth electrodes (stereoelectroencephalography; SEEG). SEEG electrodes can be used to record from a 1 cm core around the cerebral entry point to the distal end (ie, target), which can be placed in the hippocampus, amygdala, or midline or inferior neocortex. Electrode implantation carries a risk of

Future perspectives

Over the next decade, we anticipate increased availability of 7 T clinical MRI scanners with enhanced sensitivity and improved imaging technology, and development of new magnetic resonance contrasts and analyses that will improve detection of subtle lesions that underlie refractory focal epilepsies and that might be amenable to surgical treatment. With the implementation of uniform protocols for acquisition and processing, we expect that computerised analysis of the much larger datasets than

Search strategy and selection criteria

We searched PubMed for English language articles published between Jan 1, 2005, and Nov 1, 2015, with the search terms “epilep*” and one or more of “MRI”, “fMRI”, “functional MRI”, “PET”, “SPECT”, “MEG”, “electric* source imaging”, “EEG”, “DTI”, “diffusion MRI”, and “surgery”. We also included key earlier references from the authors' files. We selected reports for inclusion in this paper that we judged to be most relevant to clinical practice.

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Development and prospective clinical validation of a convolutional neural network for automated detection and segmentation of focal cortical dysplasias
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Focal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early detection and resection of FCDs have favorable prognostic implications for postoperative seizure freedom. Despite advancements in imaging methods, FCD detection remains challenging. House et al. (2021) introduced a convolutional neural network (CNN) for automated FCD detection and segmentation, achieving a sensitivity of 77.8%. However, its clinical applicability was limited due to a low specificity of 5.5%. The objective of this study was to improve the CNN’s performance through data-driven training and algorithm optimization, followed by a prospective validation on daily-routine MRIs.
A dataset of 300 3 T MRIs from daily clinical practice, including 3D T1 and FLAIR sequences, was prospectively compiled. The MRIs were visually evaluated by two neuroradiologists and underwent morphometric assessment by two epileptologists. The dataset included 30 FCD cases (11 female, mean age: 28.1 ± 10.1 years) and a control group of 150 normal cases (97 female, mean age: 32.8 ± 14.9 years), along with 120 non-FCD pathological cases (64 female, mean age: 38.4 ± 18.4 years). The dataset was divided into three subsets, each analyzed by the CNN. Subsequently, the CNN underwent a two-phase-training process, incorporating subset MRIs and expert-labeled FCD maps. This training employed both classical and continual learning techniques. The CNN’s performance was validated by comparing the baseline model with the trained models at two training levels.
In prospective validation, the best model trained using continual learning achieved a sensitivity of 90.0%, specificity of 70.0%, and accuracy of 72.0%, with an average of 0.41 false positive clusters detected per MRI. For FCD segmentation, an average Dice coefficient of 0.56 was attained. The model’s performance improved in each training phase while maintaining a high level of sensitivity. Continual learning outperformed classical learning in this regard.
Our study presents a promising CNN for FCD detection and segmentation, exhibiting both high sensitivity and specificity. Furthermore, the model demonstrates continuous improvement with the inclusion of more clinical MRI data. We consider our CNN a valuable tool for automated, examiner-independent FCD detection in daily clinical practice, potentially addressing the underutilization of epilepsy surgery in drug-resistant focal epilepsy and thereby improving patient outcomes.
Parvalbumin neurons in the nucleus accumbens shell modulate seizure in temporal lobe epilepsy
2024, Neurobiology of Disease
A growing number of clinical and animal studies suggest that the nucleus accumbens (NAc), especially the shell, is involved in the pathogenesis of temporal lobe epilepsy (TLE). However, the role of parvalbumin (PV) GABAergic neurons in the NAc shell involved in TLE is still unclear. In this study, we induced a spontaneous TLE model by intrahippocampal administration of kainic acid (KA), which generally induce acute seizures in first 2 h (acute phase) and then lead to spontaneous recurrent seizures after two months (chronic phase). We found that chemogenetic activation of NAc shell PV neurons could alleviate TLE seizures by reducing the number and period of focal seizures (FSs) and secondary generalized seizures (sGSs), while selective inhibition of PV exacerbated seizure activity. Ruby-virus mapping results identified that the hippocampus (ventral and dorsal) is one of the projection targets of NAc shell PV neurons. Chemogenetic activation of the NAc-Hip PV projection fibers can mitigate seizures while inhibition has no effect on seizure ictogenesis. In summary, our findings reveal that PV neurons in the NAc shell could modulate the seizures in TLE via a long-range NAc-Hip circuit. All of these results enriched the investigation between NAc and epilepsy, offering new targets for future epileptogenesis research and precision therapy.
Targeted nanotheranostics for the treatment of epilepsy through in vivo hijacking of locally activated macrophages
2024, Acta Biomaterialia
Epilepsy refers to a disabling neurological disorder featured by the long-term and unpredictable occurrence of seizures owing to abnormal excessive neuronal electrical activity and is closely linked to unresolved inflammation, oxidative stress, and hypoxia. The difficulty of accurate localization and targeted drug delivery to the lesion hinders the effective treatment of this disease. The locally activated inflammatory cells in the epileptogenic region offer a new opportunity for drug delivery to the lesion. In this work, CD163-positive macrophages in the epileptogenic region were first harnessed as Trojan horses after being hijacked by targeted albumin manganese dioxide nanoparticles, which effectively penetrated the brain endothelial barrier and delivered multifunctional nanomedicines to the epileptic foci. Hence, accumulative nanoparticles empowered the visualization of the epileptogenic lesion through microenvironment-responsive MR T1-weight imaging of manganese dioxide. Besides, these manganese-based nanomaterials played a pivotal role in shielding neurons from cell apoptosis mediated by oxidative stress and hypoxia. Taken together, the present study provides an up-to-date approach for integrated diagnosis and treatment of epilepsy and other hypoxia-associated inflammatory diseases.
The therapeutic effects of antiepileptic drugs (AEDs) are hindered by insufficient drug accumulation in the epileptic site. Herein, we report an efficient strategy to use locally activated macrophages as carriers to deliver multifunctional nanoparticles to the brain lesion. As MR-responsive T1 contrast agents, multifunctional BMC nanoparticles can be harnessed to accurately localize the epileptogenic region with high sensitivity and specificity. Meanwhile, catalytic nanoparticles BMC can synergistically scavenge ROS, generate O₂ and regulate neuroinflammation for the protection of neurons in the brain.
Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery
2024, Neurosurgery Clinics of North America
Complementary structural and functional abnormalities to localise epileptogenic tissue
2023, eBioMedicine
When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy.
We retrospectively investigated data from 43 patients (42% female) with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study.
Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p = 0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients.
Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations.
This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.
Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value
2023, European Journal of Radiology
Diffusion-weighted imaging (DWI) of the liver suffers from low resolution, noise, and artifacts. This study aimed to investigate the effect of deep learning reconstruction (DLR) on image quality and apparent diffusion coefficient (ADC) quantification of liver DWI at 3 Tesla.
In this prospective study, images of the liver obtained at DWI with b-values of 0 (DWI₀), 50 (DWI₅₀) and 800 s/mm² (DWI₈₀₀) from consecutive patients with liver lesions from February 2022 to February 2023 were reconstructed with and without DLR (non-DLR). Image quality was assessed qualitatively using Likert scoring system and quantitatively using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and liver/parenchyma boundary sharpness from region-of-interest (ROI) analysis. ADC value of lesion were measured. Phantom experiment was also performed to investigate the factors that determine the effect of DLR on ADC value. Qualitative score, SNR, CNR, boundary sharpness, and apparent diffusion coefficients (ADCs) for DWI were compared using paired t-test and Wilcoxon signed rank test. P < 0.05 was considered statistically significant.
A total of 85 patients with 170 lesions were included. DLR group showed a higher qualitative score than the non-DLR group. for example, with DWI₈₀₀ the score was 4.77 ± 0.52 versus 4.30 ± 0.63 (P < 0.001). DLR group also showed higher SNRs, CNRs and boundary sharpness than the non-DLR group. DLR reduced the ADC of malignant tumors (1.105[0.904, 1.340] versus 1.114[0.904, 1.320]) (P < 0.001), but there was no significant difference in the diagnostic value of malignancy for DLR and non-DLR groups (P = 57.3). The phantom study confirmed a reduction of ADC in images with low resolution, and a stronger reduction of ADC in heterogeneous structures than in homogeneous ones (P < 0.001).
DLR improved image quality of liver DWI. DLR reduced the ADC value of lesions, but did not affect the diagnostic performance of ADC in distinguishing malignant tumors on a 3.0-T MRI system.

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ReviewBrain imaging in the assessment for epilepsy surgery

Summary

Introduction

Section snippets

The sequence of presurgical imaging investigations

Identification of structural cerebral abnormalities

Mapping eloquent brain functions

Mapping cerebral white matter connections

Localisation of epileptic activity

Integration of multimodal three-dimensional imaging in the epilepsy surgery pathway

Future perspectives

Search strategy and selection criteria

Epilepsy Behav

Epilepsy Res

Lancet

Epilepsy Res

Epilepsy Res

Neurobiol Aging

Neuroimage

Epilepsy Res

Epilepsy Res

Neuroimage Clin

Neuroimage

Epilepsy Res

Epilepsy Res

Neuroimage

Epilepsy Behav

Neuroimage

Neuroimage

Neuropsychologia

Neuroimage

Neuroimage Clin

Epilepsy Res

Clin Neurol Neurosurg

Epilepsy Res

Neuroimage

Neuroimage

Neuroimage Clin

Neuroimage Clin

Clin Neurophysiol

Epilepsy Res

Epilepsies: diagnosis and management. NICE guideline [CG137]

Resective epilepsy surgery for drug-resistant focal epilepsy: a review

JAMA

Imaging and epilepsy

Brain

Imaging in the surgical treatment of epilepsy

Nat Rev Neurol

Characteristics and surgical outcomes of patients with refractory magnetic resonance imaging-negative epilepsies

Arch Neurol

Recommendations for neuroimaging of patients with epilepsy

Epilepsia

Susceptibility weighted imaging in the diagnostic evaluation of patients with intractable epilepsy

Epilepsia

Proposal for a magnetic resonance imaging protocol for the detection of epileptogenic lesions at early outpatient stages

Epilepsia

3T phased array MRI improves the presurgical evaluation in focal epilepsies: a prospective study

Neurology

7T MRI features in control human hippocampus and hippocampal sclerosis: an ex vivo study with histologic correlations

Epilepsia

Standard magnetic resonance imaging is inadequate for patients with refractory focal epilepsy

J Neurol Neurosurg Psychiatry

Post-processing of structural MRI for individualized diagnostics

Quant Imaging Med Surg

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy

Radiology

Automated hippocampal segmentation in patients with epilepsy: available free online

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Beyond the CA1 subfield: local hippocampal shape changes in MRI-negative temporal lobe epilepsy

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Is the type and extent of hippocampal sclerosis measurable on high-resolution MRI?

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Assessment and surgical outcomes for mild type I and severe type II cortical dysplasia: a critical review and the UCLA experience

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J Neuroimaging

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

Brain

Voxel-based morphometry of temporal lobe epilepsy: an introduction and review of the literature

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Review
Brain imaging in the assessment for epilepsy surgery