Temporal lobe epilepsy with or without hippocampal sclerosis: Structural and functional connectivity using advanced MRI techniques

A specific model of resting-state functional brain network in MRI-negative temporal lobe epilepsy

Purpose

Without any visible indicator on structure magnetic resonance imaging (MRI), the diagnosis of MRI-negative temporal lobe epilepsy (NTLE) gets harder. By considering healthy control (HC), a specific functional connectivity (FC) model was constructed in a network topology to improve FC computation to a high-level.

Methods

MRI data of 20 NTLE patients and 60 HC were pre-processed. Relative to HC, a network-level specific FC model of each network index was built to score the network functions for each NTLE patient. The specific brain areas (regarded as ROIs) were extracted for NTLE by sensitivity analysis of scores. By considering scores of specific ROIs as feature vectors to input into a SVM respectively, a specific NTLE classifier was constructed. Both 10-fold cross validation and hold-out method were utilized to validate the classification and to evaluate the effectiveness of our specific FC models. Simultaneously, the specific FC model was compared to the conventional FC model of Pearson correlation.

Results

By the constructed model for specific FC at a network-level, 11 specific ROIs, such as, frontal lobe, temporal lobe, parietal lobe, hippocampus, and occipital lobe, were extracted for NTLE. Accuracy of our specific NTLE classifier could reach up nearly 93 %, over 6 % greater than conventional FC model of Pearson correlation.

Conclusions

The network-level specific FC model might provide a new methodology for machine-aiding detection of functional abnormal lesions of NTLE by resting-state functional MRI.

Long-term memory plasticity in a decade-long connectivity study post anterior temporal lobe resection

Approximately 40% of individuals undergoing anterior temporal lobe resection for temporal lobe epilepsy experience episodic memory decline. There has been a focus on early memory network changes; longer-term plasticity and its impact on memory function are unclear. Our study investigates neural mechanisms of memory recovery and network plasticity over nearly a decade post-surgery. We assess memory network changes, from 3-12 months to 10 years postoperatively, in 25 patients (12 left-sided resections) relative to 10 healthy matched controls, using longitudinal task-based functional MRI and standard neuropsychology assessments. We observe key adaptive changes in memory networks of a predominantly seizure-free cohort. Ongoing neuroplasticity in posterior medial temporal regions and contralesional cingulum or pallidum contribute to long-term verbal and visual memory recovery. Here, we show the potential for sustained cognitive improvement and importance of strategic approaches in epilepsy treatment, advocating for conservative surgeries and long-term use of cognitive rehabilitation for ongoing recovery.

Advances in Neuroimaging and Multiple Post-Processing Techniques for Epileptogenic Zone Detection of Drug-Resistant Epilepsy

Among the approximately 20 million patients with drug-resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure-inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post-processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning-based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis-based study designs. Therefore, we believe that the application of neuroimaging and post-processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Functional connectivity of EEG motor rhythms after spinal cord injury

Spinal cord injury (SCI), which is the injury of the spinal cord site resulting in motor dysfunction, has prompted the use of motor imagery (MI)-based brain computer interface (BCI) systems for motor function reconstruction. However, analyzing electroencephalogram signals and brain function mechanisms for SCI patients is challenging. This is due to their low signal-to-noise ratio and high variability. We propose using the phase locking value (PLV) to construct the brain network in α and β rhythms for both SCI patients and healthy individuals. This approach aims to analyze the changes in brain network connectivity and brain function mechanisms following SCI. The results show that the connection strength of the α rhythm in the healthy control (HC) group is stronger than that in the SCI group, and the connection strength in the β rhythm of the SCI group is stronger than that in the HC group. Moreover, we extract the PLV with common spatial pattern (PLV-CSP) feature from the MI data of the SCI group. The experimental results for 12 SCI patients include that the peak classification accuracy is 100%, and the average accuracy of the ten-fold cross-verification is 95.6%. Our proposed approach can be used as a potential valuable method for SCI pathological studies and MI-based BCI rehabilitation systems.

The Neurostimulationist will see you now: prescribing direct electrical stimulation therapies for the human brain in epilepsy and beyond

As the pace of research in implantable neurotechnology increases, it is important to take a step back and see if the promise lives up to our intentions. While direct electrical stimulation applied intracranially has been used for the treatment of various neurological disorders, such as Parkinson's, epilepsy, clinical depression, and Obsessive-compulsive disorder, the effectiveness can be highly variable. One perspective is that the inability to consistently treat these neurological disorders in a standardized way is due to multiple, interlaced factors, including stimulation parameters, location, and differences in underlying network connectivity, leading to a trial-and-error stimulation approach in the clinic. An alternate view, based on a growing knowledge from neural data, is that variability in this input (stimulation) and output (brain response) relationship may be more predictable and amenable to standardization, personalization, and, ultimately, therapeutic implementation. In this review, we assert that the future of human brain neurostimulation, via direct electrical stimulation, rests on deploying standardized, constrained models for easier clinical implementation and informed by intracranial data sets, such that diverse, individualized therapeutic parameters can efficiently produce similar, robust, positive outcomes for many patients closer to a prescriptive model. We address the pathway needed to arrive at this future by addressing three questions, namely: (1) why aren't we already at this prescriptive future?; (2) how do we get there?; (3) how far are we from this Neurostimulationist prescriptive future? We first posit that there are limited and predictable ways, constrained by underlying networks, for direct electrical stimulation to induce changes in the brain based on past literature. We then address how identifying underlying individual structural and functional brain connectivity which shape these standard responses enable targeted and personalized neuromodulation, bolstered through large-scale efforts, including machine learning techniques, to map and reverse engineer these input-output relationships to produce a good outcome and better identify underlying mechanisms. This understanding will not only be a major advance in enabling intelligent and informed design of neuromodulatory therapeutic tools for a wide variety of neurological diseases, but a shift in how we can predictably, and therapeutically, prescribe stimulation treatments the human brain.

Bilateral glymphatic dysfunction and its association with disease duration in unilateral temporal lobe epilepsy patients with hippocampal sclerosis

OBJECTIVE

In this study, the diffusion tensor imaging along perivascular space analysis (DTI-ALPS) technique was utilized to evaluate the functional changes in the glymphatic system of the bilateral hemispheres in patients with unilateral temporal lobe epilepsy (TLE) accompanied by hippocampal sclerosis (HS). The aim was to gain insights into the alterations in the glymphatic system function in TLE patients.

METHODS

A total of 61 unilateral TLE patients with HS and 53 healthy controls (HCs) from the Department of Neurosurgery at Xiangya Hospital were included in the study. All subjects underwent DTI using the same 3 T MR Scanner, and the DTI-ALPS index was calculated. Differences in the DTI-ALPS index between TLE patients and HCs were evaluated, along with the correlation between the DTI-ALPS index of TLE and clinical features of epilepsy. These features included age, age of onset, seizure duration, and neuropsychological scores.

RESULTS

Compared to the bilateral means of the HCs, both the ipsilateral and contralateral DTI-ALPS index of the TLE patients were significantly decreased (TLE ipsilateral 1.41 ± 0.172 vs. HC bilateral mean: 1.49 ± 0.116, p = 0.006; TLE contralateral: 1.42 ± 0.158 vs. HC bilateral mean: 1.49 ± 0.116, p = 0.015). The ipsilateral DTI-ALPS index in TLE patients showed a significant negative correlation with disease duration (r = -0.352, p = 0.005).

CONCLUSIONS

The present study suggests the presence of bilateral dysfunctions in the glymphatic system and also highlight a laterality feature in these dysfunctions. Additionally, the study found a significant negative correlation between the ipsilateral DTI-ALPS index and disease duration, underscoring the significance of early effective interventions and indicating potential for the development of innovative treatments targeting the glymphatic system.

Brain connectivity in status epilepticus as a predictor of outcome: A diffusion tensor imaging study

BACKGROUND AND PURPOSE

We aimed to explore structural connectivity in status epilepticus.

METHODS

We enrolled participants who underwent diffusion tensor imaging. We applied graph theory to investigate structural connectivity. We compared the structural connectivity measures between patients and healthy controls and between patients with poor (modified Rankin Scale [mRS] >3) and good (mRS ≤3) admission outcomes.

RESULTS

We enrolled 28 patients and 31 healthy controls (age 65.5 vs.62.0 years, p = .438). Of these patients, 16 and 12 showed poor and good admission outcome (age 65.5 vs.62.0 years, p = .438). The assortative coefficient (-0.113 vs. -0.121, p = .021), mean clustering coefficient (0.007 vs.0.006, p = .009), global efficiency (0.023 vs.0.020, p = .009), transitivity (0.007 vs.0.006, p = .009), and small-worldness index (0.006 vs.0.005, p = .021) were higher in patients with status epilepticus than in healthy controls. The assortative coefficient (-0.108 vs. -0.119, p = .042), mean clustering coefficient (0.007 vs.0.006, p = .042), and transitivity (0.008 vs.0.007, p = .042) were higher in patients with poor admission outcome than in those with good admission outcome. MRS score was positively correlated with structural connectivity measures, including the assortative coefficient (r = 0.615, p = .003), mean clustering coefficient (r = 0.544, p = .005), global efficiency (r = 0.515, p = .007), transitivity (r = 0.547, p = .007), and small-worldness index (r = 0.435, p = .024).

CONCLUSION

We revealed alterations in structural connectivity, showing increased integration and segregation in status epilepticus, which might be related with neuronal synchronization. This effect was more pronounced in patients with a poor admission outcome, potentially reshaping our understanding for comprehension of status epilepticus mechanisms and the development of more targeted treatments.

Exploring ASL perfusion MRI as a substitutive modality for 18F-FDG PET in determining the laterality of mesial temporal lobe epilepsy

OBJECTIVE

The aim of this investigation was to determine whether a correlation could be discerned between perfusion acquired through ASL MRI and metabolic data acquired via 18F-fluorodeoxyglucose (18F-FDG) PET in mesial temporal lobe epilepsy (mTLE).

METHODS

ASL MRI and 18F-FDG PET data were gathered from 22 mTLE patients. Relative cerebral blood flow (rCBF) asymmetry index (AIs) were measured using ASL MRI, and standardized uptake value ratio (SUVr) maps were obtained from 18F-FDG PET, focusing on bilateral vascular territories and key bitemporal lobe structures (amygdala, hippocampus, and parahippocampus). Intra-group comparisons were carried out to detect hypoperfusion and hypometabolism between the left and right brain hemispheres for both rCBF and SUVr in right and left mTLE. Correlations between the two AIs computed for each modality were examined.

RESULTS

Significant correlations were observed between rCBF and SUVr AIs in the middle temporal gyrus, superior temporal gyrus, and hippocampus. Significant correlations were also found in vascular territories of the distal posterior, intermediate anterior, intermediate middle, proximal anterior, and proximal middle cerebral arteries. Intra-group comparisons unveiled significant differences in rCBF and SUVr between the left and right brain hemispheres for right mTLE, while hypoperfusion and hypometabolism were infrequently observed in any intracranial region for left mTLE.

CONCLUSION

The study's findings suggest promising concordance between hypometabolism estimated by 18F-FDG PET and hypoperfusion determined by ASL perfusion MRI. This raises the possibility that, with prospective technical enhancements, ASL perfusion MRI could be considered an alternative modality to 18F-FDG PET in the future.

Abnormal white matter structural network topological property in patients with temporal lobe epilepsy

BACKGROUND

Diffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in patients with temporal lobe epilepsy (TLE). However, alterations in the topological properties of the WM structural network in patients with TLE remain unclear. Graph theoretical analysis provides a new perspective for evaluating the connectivity of WM structural networks.

METHODS

DTI was used to map the structural networks of 18 patients with TLE (10 males and 8 females) and 29 (17 males and 12 females) age- and gender-matched normal controls (NC). Graph theory was used to analyze the whole-brain networks and their topological properties between the two groups. Finally, partial correlation analyses were performed on the weighted network properties and clinical characteristics, namely, duration of epilepsy, verbal intelligence quotient (IQ), and performance IQ.

RESULTS

Patients with TLE exhibited reduced global efficiency and increased characteristic path length. A total of 31 regions with nodal efficiency alterations were detected in the fractional anisotropy_ weighted network of the patients. Communication hubs, such as the middle temporal gyrus, right inferior temporal gyrus, left calcarine, and right superior parietal gyrus, were also differently distributed in the patients compared with the NC. Several node regions showed close relationships with duration of epilepsy, verbal IQ, and performance IQ.

CONCLUSIONS

Our results demonstrate the disruption of the WM structural network in TLE patients. This study may contribute to the further understanding of the pathological mechanism of TLE.

Structural brain network analysis in occipital lobe epilepsy

BACKGROUND

This study aimed to analyze the structural brain network in patients with occipital lobe epilepsy (OLE) and investigate the differences in structural brain networks between patients with OLE and healthy controls.

METHODS

Patients with OLE and healthy controls with normal brain MRI findings were enrolled. They underwent diffusion tensor imaging using a 3.0T MRI scanner, and we computed the network measures of global and local structural networks in patients with OLE and healthy controls using the DSI studio program. We compared network measures between the groups.

RESULTS

We enrolled 23 patients with OLE and 42 healthy controls. There were significant differences in the global structural network between patients with OLE and healthy controls. The assortativity coefficient (-0.0864 vs. -0.0814, p = 0.0214), mean clustering coefficient (0.0061 vs. 0.0064, p = 0.0203), global efficiency (0.0315 vs. 0.0353, p = 0.0086), and small-worldness index (0.0001 vs. 0.0001, p = 0.0175) were lower, whereas the characteristic path length (59.2724 vs. 53.4684, p = 0.0120) was higher in patients with OLE than those in the healthy controls. There were several nodes beyond the occipital lobe that showed significant differences in the local structural network between the groups. In addition, the assortativity coefficient was negatively correlated with the duration of epilepsy (r=-0.676, p = 0.001).

Mass Spectrometry as a Quantitative Proteomic Analysis Tool for the Search for Temporal Lobe Epilepsy Biomarkers: A Systematic Review

Temporal lobe epilepsy (TLE) is the most common form of epilepsy in adults. Tissue reorganization at the site of the epileptogenic focus is accompanied by changes in the expression patterns of protein molecules. The study of mRNA and its corresponding proteins is crucial for understanding the pathogenesis of the disease. Protein expression profiles do not always directly correlate with the levels of their transcripts; therefore, it is protein profiling that is no less important for understanding the molecular mechanisms and biological processes of TLE. The study and annotation of proteins that are statistically significantly different in patients with TLE is an approach to search for biomarkers of this disease, various stages of its development, as well as a method for searching for specific targets for the development of a further therapeutic strategy. When writing a systematic review, the following aggregators of scientific journals were used: MDPI, PubMed, ScienceDirect, Springer, and Web of Science. Scientific articles were searched using the following keywords: "proteomic", "mass-spectrometry", "protein expression", "temporal lobe epilepsy", and "biomarkers". Publications from 2003 to the present have been analyzed. Studies of brain tissues, experimental models of epilepsy, as well as biological fluids, were analyzed. For each of the groups, aberrantly expressed proteins found in various studies were isolated. Most of the studies omitted important characteristics of the studied patients, such as: duration of illness, type and response to therapy, gender, etc. Proteins that overlap across different tissue types and different studies have been highlighted: DPYSL, SYT1, STMN1, APOE, NME1, and others. The most common biological processes for them were the positive regulation of neurofibrillary tangle assembly, the regulation of amyloid fibril formation, lipoprotein catabolic process, the positive regulation of vesicle fusion, the positive regulation of oxidative stress-induced intrinsic apoptotic signaling pathway, removal of superoxide radicals, axon extension, and the regulation of actin filament depolymerization. MS-based proteomic profiling for a relevant study must accept a number of limitations, the most important of which is the need to compare different types of neurological and, in particular, epileptic disorders. Such a criterion could increase the specificity of the search work and, in the future, lead to the discovery of biomarkers for a particular disease.

Episodic memory network connectivity in temporal lobe epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) affects brain networks and is associated with impairment of episodic memory. Temporal and extratemporal reorganization of memory functions is described in functional magnetic resonance imaging (fMRI) studies. Functional reorganizations have been shown at the local activation level, but network-level alterations have been underinvestigated. We aim to investigate the functional anatomy of memory networks using memory fMRI and determine how this relates to memory function in TLE.

METHODS

Ninety patients with unilateral TLE (43 left) and 29 controls performed a memory-encoding fMRI paradigm of faces and words with subsequent out-of-scanner recognition test. Subsequent memory event-related contrasts of words and faces remembered were generated. Psychophysiological interaction analysis investigated task-associated changes in functional connectivity seeding from the mesial temporal lobes (MTLs). Correlations between changes in functional connectivity and clinical memory scores, epilepsy duration, age at epilepsy onset, and seizure frequency were investigated, and between connectivity supportive of better memory and disease burden. Connectivity differences between controls and TLE, and between TLE with and without hippocampal sclerosis, were explored using these confounds as regressors of no interest.

RESULTS

Compared to controls, TLE patients showed widespread decreased connectivity between bilateral MTLs and frontal lobes, and increased local connectivity between the anterior MTLs bilaterally. Increased intrinsic connectivity within the bilateral MTLs correlated with better out-of-scanner memory performance in both left and right TLE. Longer epilepsy duration and higher seizure frequency were associated with decreased connectivity between bilateral MTLs and left/right orbitofrontal cortex (OFC) and insula, connections supportive of memory functions. TLE due to hippocampal sclerosis was associated with greater connectivity disruption within the MTL and extratemporally.

SIGNIFICANCE

Connectivity analyses showed that TLE is associated with temporal and extratemporal memory network reorganization. Increased bilateral functional connectivity within the MTL and connectivity to OFC and insula are efficient, and are disrupted by greater disease burden.

Advanced neuroimaging techniques in epilepsy

PURPOSE OF REVIEW

We review significant advances in epilepsy imaging in recent years.

RECENT FINDINGS

Structural MRI at 7T with optimization of acquisition and postacquisition image processing increases the diagnostic yield but artefactual findings remain a challenge. MRI analysis from multiple sites indicates different atrophy patterns and white matter diffusion abnormalities in temporal lobe and generalized epilepsies, with greater abnormalities close to the presumed seizure source. Structural and functional connectivity relate to seizure spread and generalization; longitudinal studies are needed to clarify the causal relationship of these associations. Diffusion MRI may help predict surgical outcome and network abnormalities extending beyond the epileptogenic zone. Three-dimensional multimodal imaging can increase the precision of epilepsy surgery, improve seizure outcome and reduce complications. Language and memory fMRI are useful predictors of postoperative deficits, and lead to risk minimization. FDG PET is useful for clinical studies and specific ligands probe the pathophysiology of neurochemical fluxes and receptor abnormalities.

SUMMARY

Improved structural MRI increases detection of abnormalities that may underlie epilepsy. Diffusion, structural and functional MRI indicate the widespread associations of epilepsy syndromes. These can assist stratification of surgical outcome and minimize risk. PET has continued utility clinically and for research into the pathophysiology of epilepsies.

Glymphatic system function in patients with newly diagnosed focal epilepsy

INTRODUCTION

The aim of this study was to analyze the glymphatic system function and its relationship with clinical characteristics, global diffusion tensor imaging (DTI) parameters, and global structural connectivity in treatment-naïve patients with newly diagnosed focal epilepsy.

METHODS

This retrospective single-center study investigated patients with focal epilepsy and healthy controls. All participants underwent routine brain magnetic resonance imaging and DTI. DTI analysis along the perivascular space (DTI-ALPS) was used to evaluate glymphatic system function. We also calculated the measures of global DTI parameters, including whole-brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), and performed a graph theoretical network analysis to measure global structural connectivity.

RESULTS

A total of 109 patients with focal epilepsy and 88 healthy controls were analyzed. There were no significant differences in the DTI-ALPS index (1.67 vs. 1.68, p = 0.861) between the groups. However, statistically significant associations were found between the DTI-ALPS index and age (r = -0.242, p = 0.01), FA (r = 0.257, p = 0.007), MD (r = -0.469, p < 0.001), AD (r = -0.303, p = 0.001), RD (r = -0.434, p < 0.001), and the assortative coefficient (r = 0.230, p = 0.016) in patients with focal epilepsy.

CONCLUSION

The main finding of this study is that DTI-ALPS index is significantly correlated with global DTI parameters and structural connectivity measures of the brain in patients with focal epilepsy. In addition, DTI-ALPS index decreases with age in these patients. We conclude that the DTI-ALPS index can be used to investigate glymphatic system function in patients with focal epilepsy.

The role of astrocytes in epileptic disorders

Epilepsy affects about 1% of the population and approximately 30% of epileptic patients are resistant to current antiepileptic drugs. As a hallmark in epileptic tissue, many of the epileptic patients show changes in glia morphology and function. There are characteristic changes in different types of glia in different epilepsy models. Some of these changes such as astrogliosis are enough to provoke epileptic seizures. Astrogliosis is well known in mesial temporal lobe epilepsy (MTLE), the most common form of refractory epilepsy. A better understanding of astrocytes alterations could lead to novel and efficient pharmacological approaches for epilepsy. In this review, we present the alterations of astrocyte morphology and function and present some instances of targeting astrocytes in seizure and epilepsy.

Topological Abnormalities of Pallido-Thalamo-Cortical Circuit in Functional Brain Network of Patients With Nonchemotherapy With Non-small Cell Lung Cancer

INTRODUCTION

Some previous studies in patients with lung cancer have mainly focused on exploring the cognitive dysfunction and deficits of brain function associated with chemotherapy. However, little is known about functional brain alterations that might occur prior to chemotherapy. Therefore, this study aimed to evaluate brain functional changes in patients with nonchemotherapy before chemotherapy with non-small cell lung cancer (NSCLC).

METHODS

Resting-state functional MRI data of 35 patients with NSCLC and 46 matched healthy controls (HCs) were acquired to construct functional brain networks. Graph theoretical analysis was then applied to investigate the differences of the network and nodal measures between groups. Finally, the receiver operating characteristic (ROC) curve analysis was performed to distinguish between NSCLC and HC.

RESULTS

Decreased nodal strength was found in the left inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part), inferior occipital gyrus, and right inferior frontal gyrus (triangular part) of patients with NSCLC while increased nodal strength was found in the right pallidum and thalamus. NSCLC also showed decreased nodal betweenness in the right superior occipital gyrus. Different hub regions distribution was found between groups, however, no hub regions showed group differences in the nodal measures. Furthermore, the ROC curve analysis showed good performance in distinguishing NSCLC from HC.

CONCLUSION

These results suggested that topological abnormalities of pallido-thalamo-cortical circuit in functional brain network might be related to NSCLC prior to chemotherapy, which provided new insights concerning the pathophysiological mechanisms of NSCLC and could serve as promising biological markers for the identification of patients with NSCLC.

Application value of molecular imaging technology in epilepsy

Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.