FDG-PET Profiles of Extratemporal Metabolism as a Predictor of Surgical Failure in Temporal Lobe Epilepsy

Metabolic connectivity as a predictor of surgical outcome in mesial temporal lobe epilepsy

OBJECTIVE

The study investigated metabolic connectivity (MC) differences between patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS) and healthy controls (HCs), based on [18 F]-fluorodeoxyglucose (FDG)-PET data. We focused on the MC changes dependent on the lateralization of the epileptogenic lobe and on correlations with postoperative outcomes.

METHODS

FDG-PET scans of 47 patients with unilateral MTLE with histopathologically proven HS and 25 HC were included in the study. All the patients underwent a standard anterior temporal lobectomy and were more than 2 years after the surgery. MC changes were compared between the two HS groups (left HS, right HS) and HC. Differences between the metabolic network of seizure-free and non-seizure-free patients after surgery were depicted afterward. Network changes were correlated with clinical characteristics.

RESULTS

The study showed widespread metabolic network changes in the HS patients as compared to HC. The changes were more extensive in the right HS than in the left HS. Unfavorable surgical outcomes were found in patients with decreased MC within the network including both the lesional and contralesional hippocampus, ipsilesional frontal operculum, and contralesional insula. Favorable outcomes correlated with decreased MC within the network involving both orbitofrontal cortices and the ipsilesional temporal lobe.

SIGNIFICANCE

There are major differences in the metabolic networks of left and right HS, with more extensive changes in right HS. The changes within the metabolic network could help predict surgical outcomes in patients with HS. MC may identify patients with potentially unfavorable outcomes and direct them to a more detailed presurgical evaluation.

PLAIN LANGUAGE SUMMARY

Metabolic connectivity is a promising method for metabolic network mapping. Metabolic networks in mesial temporal lobe epilepsy are dependent on lateralization of the epileptogenic lobe and could predict surgical outcomes.

Identifying important factors for successful surgery in patients with lateral temporal lobe epilepsy

OBJECTIVE

Lateral temporal lobe epilepsy (LTLE) has been diagnosed in only a small number of patients; therefore, its surgical outcome is not as well-known as that of mesial temporal lobe epilepsy. We aimed to evaluate the long-term (5 years) and short-term (2 years) surgical outcomes and identify possible prognostic factors in patients with LTLE.

METHODS

This retrospective cohort study was conducted between January 1995 and December 2018 among patients who underwent resective surgery in a university-affiliated hospital. Patients were classified as LTLE if ictal onset zone was in lateral temporal area. Surgical outcomes were evaluated at 2 and 5 years. We subdivided based on outcomes and compared clinical and neuroimaging data including cortical thickness between two groups.

RESULTS

Sixty-four patients were included in the study. The mean follow-up duration after the surgery was 8.4 years. Five years after surgery, 45 of the 63 (71.4%) patients achieved seizure freedom. Clinically and statistically significant prognostic factors for postsurgical outcomes were the duration of epilepsy before surgery and focal cortical dysplasia on postoperative histopathology at the 5-year follow-up. Optimal cut-off point for epilepsy duration was eight years after the seizure onset (odds ratio 4.375, p-value = 0.0214). Furthermore, we propose a model for predicting seizure outcomes 5 years after surgery using the receiver operating characteristic curve and nomogram (area under the curve = 0.733; 95% confidence interval, 0.588-0.879). Cortical thinning was observed in ipsilateral cingulate gyrus and contralateral parietal lobe in poor surgical group compared to good surgical group (p-value < 0.01, uncorrected).

CONCLUSIONS

The identified predictors of unfavorable surgical outcomes may help in selecting optimal candidates and identifying the optimal timing for surgery among patients with LTLE. Additionally, cortical thinning was more extensive in the poor surgical group.

Abnormal metabolic connectivity in default mode network of right temporal lobe epilepsy

Aims

Temporal lobe epilepsy (TLE) is a common neurological disorder associated with the dysfunction of the default mode network (DMN). Metabolic connectivity measured by 18F-fluorodeoxyglucose Positron Emission Computed Tomography (18F-FDG PET) has been widely used to assess cumulative energy consumption and provide valuable insights into the pathophysiology of TLE. However, the metabolic connectivity mechanism of DMN in TLE is far from fully elucidated. The present study investigated the metabolic connectivity mechanism of DMN in TLE using 18F-FDG PET.

Method

Participants included 40 TLE patients and 41 health controls (HC) who were age- and gender-matched. A weighted undirected metabolic network of each group was constructed based on 14 primary volumes of interest (VOIs) in the DMN, in which Pearson's correlation coefficients between each pair-wise of the VOIs were calculated in an inter-subject manner. Graph theoretic analysis was then performed to analyze both global (global efficiency and the characteristic path length) and regional (nodal efficiency and degree centrality) network properties.

Results

Metabolic connectivity in DMN showed that regionally networks changed in the TLE group, including bilateral posterior cingulate gyrus, right inferior parietal gyrus, right angular gyrus, and left precuneus. Besides, significantly decreased (P < 0.05, FDR corrected) metabolic connections of DMN in the TLE group were revealed, containing bilateral hippocampus, bilateral posterior cingulate gyrus, bilateral angular gyrus, right medial of superior frontal gyrus, and left inferior parietal gyrus.

Conclusion

Taken together, the present study demonstrated the abnormal metabolic connectivity in DMN of TLE, which might provide further insights into the understanding the dysfunction mechanism and promote the treatment for TLE patients.

Expression of fructose-1,6-bisphosphatase 1 is associated with [18F]FDG uptake and prognosis in patients with mesial temporal lobe epilepsy

OBJECTIVES

To determine whether fructose-1,6-bisphosphatase 1 (FBP1) expression is associated with [¹⁸F]FDG PET uptake and postsurgical outcomes in patients with mesial temporal lobe epilepsy (mTLE) and to investigate whether the molecular mechanism involving gamma-aminobutyric acid type A receptor (GABA_AR), glucose transporter-3 (GLUT-3), and hexokinase-II (HK-II).

METHODS

Forty-three patients with mTLE underwent [¹⁸F]FDG PET/CT. Patients were divided into Ia (Engel class Ia) and non-Ia (Engel class Ib-IV) groups according to more than 1 year of follow-up after surgery. The maximum standard uptake value (SUV_max) and asymmetry index (AI) of hippocampus were measured. The relationship among the SUV_max, AI, prognosis, and FBP1 expression was analyzed. A lithium-pilocarpine acute mTLE rat model was subjected to [¹⁸F]FDG micro-PET/CT. Hippocampal SUV_max and FBP1, GABA_AR, GLUT-3, and HK-II expression were analyzed.

RESULTS

SUV_max was higher in the Ia group than in the non-Ia group (7.31 ± 0.97 vs. 6.56 ± 0.96, p < 0.05) and FBP1 expression was lower in the Ia group (0.24 ± 0.03 vs. 0.27 ± 0.03, p < 0.01). FBP1 expression was negatively associated with SUV_max and AI (p < 0.01). In mTLE rats, the hippocampal FBP1 increased (0.26 ± 0.00 vs. 0.17 ± 0.00, p < 0.0001), and SUV_max, GLUT-3 and GABA_AR levels decreased significantly (0.73 ± 0.12 vs. 1.46 ± 0.23, 0.20 ± 0.01 vs. 0.32 ± 0.05, 0.26 ± 0.02 vs. 0.35 ± 0.02, p < 0.05); no significant difference in HK-II levels was observed. In mTLE patients and rats, FBP1 negatively correlated with SUV_max and GLUT-3 and GABA_AR levels (p < 0.05).

CONCLUSION

FBP1 expression was inversely associated with SUV_max in mTLE, which might inhibit [¹⁸F]FDG uptake by regulating GLUT-3 expression. High FBP1 expression was indicative of low GABA_AR expression and poor prognosis.

KEY POINTS

• It is of paramount importance to explore the deep pathophysiological mechanisms underlying the pathogenesis of mesial temporal lobe epilepsy and find potential therapeutic targets. • [¹⁸F]FDG PET has demonstrated low metabolism in epileptic regions during the interictal period, and hypometabolism may be associated with prognosis, but the pathomechanism of this association remains uncertain. • Our results support the possibility that FBP1 might be simultaneously involved in the regulation of glucose metabolism levels and the excitability of neurons and suggest that targeting FBP1 may be a viable strategy in the diagnosis and treatment of mesial temporal lobe epilepsy.

White matter alterations in MR-negative temporal and frontal lobe epilepsy using fixel-based analysis

This study focuses on white matter alterations in pharmacoresistant epilepsy patients with no visible lesions in the temporal and frontal lobes on clinical MRI (i.e. MR-negative) with lesions confirmed by resective surgery. The aim of the study was to extend the knowledge about group-specific neuropathology in MR-negative epilepsy. We used the fixel-based analysis (FBA) that overcomes the limitations of traditional diffusion tensor image analysis, mainly within-voxel averaging of multiple crossing fibres. Group-wise comparisons of fixel parameters between healthy controls (N = 100) and: (1) frontal lobe epilepsy (FLE) patients (N = 9); (2) temporal lobe epilepsy (TLE) patients (N = 13) were performed. A significant decrease of the cross-section area of the fixels in the superior longitudinal fasciculus was observed in the FLE. Results in TLE reflected widespread atrophy of limbic, thalamic, and cortico-striatal connections and tracts directly connected to the temporal lobe (such as the anterior commissure, inferior fronto-occipital fasciculus, uncinate fasciculus, splenium of corpus callosum, and cingulum bundle). Alterations were also observed in extratemporal connections (brainstem connection, commissural fibres, and parts of the superior longitudinal fasciculus). To our knowledge, this is the first study to use an advanced FBA method not only on the datasets of MR-negative TLE patients, but also MR-negative FLE patients, uncovering new common tract-specific alterations on the group level.

Nuclear imaging for localization and surgical outcome prediction in epilepsy: A review of latest discoveries and future perspectives

Background

Epilepsy is one of the most common neurological disorders. Approximately, one-third of patients with epilepsy have seizures refractory to antiepileptic drugs and further require surgical removal of the epileptogenic region. In the last decade, there have been many recent developments in radiopharmaceuticals, novel image analysis techniques, and new software for an epileptogenic zone (EZ) localization.

Objectives

Recently, we provided the latest discoveries, current challenges, and future perspectives in the field of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in epilepsy.

Methods

We searched for relevant articles published in MEDLINE and CENTRAL from July 2012 to July 2022. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis was conducted using the keywords "Epilepsy" and "PET or SPECT." We included both prospective and retrospective studies. Studies with preclinical subjects or not focusing on EZ localization or surgical outcome prediction using recently developed PET radiopharmaceuticals, novel image analysis techniques, and new software were excluded from the review. The remaining 162 articles were reviewed.

Results

We first present recent findings and developments in PET radiopharmaceuticals. Second, we present novel image analysis techniques and new software in the last decade for EZ localization. Finally, we summarize the overall findings and discuss future perspectives in the field of PET and SPECT in epilepsy.

Conclusion

Combining new radiopharmaceutical development, new indications, new techniques, and software improves EZ localization and provides a better understanding of epilepsy. These have proven not to only predict prognosis but also to improve the outcome of epilepsy surgery.

Metabolic connectivity is associated with seizure outcome in surgically treated temporal lobe epilepsies: A 18F-FDG PET seed correlation analysis

¹⁸F-FDG PET provides high sensitivity for the pre-surgical assessment of drug-resistant temporal lobe epilepsy (TLE). However, little is known about the metabolic connectivity of epileptogenic networks involved. This study therefore aimed to evaluate the association between metabolic connectivity and seizure outcome in surgically treated TLE.

METHODS

The study included 107 right-handed patients that had undergone a presurgical interictal ¹⁸F-FDG PET assessment followed by an anterior temporal lobectomy and were classified according to seizure outcome 2 years after surgery. Metabolic connectivity was evaluated by seed correlation analysis in left and right epilepsy patients with a Class Engel IA or > IA outcome and compared to age-, sex- and handedness-matched healthy controls.

RESULTS

Increased metabolic connectivity was observed in the >IA compared to the IA group within the operated temporal lobe (respective clusters of 7.5 vs 3.3 cm³ and 2.6 cm³ vs 2.2 cm³ in left and right TLE), and to a lower extent with the contralateral temporal lobe (1.2 vs 0.7 cm³ and 1.7 cm³ vs 0.7 cm³ in left and right TLE). Seed correlations provided added value for the estimated individual performance of seizure outcome over the group comparisons in left TLE (AUC of 0.74 vs 0.67).

CONCLUSION

Metabolic connectivity is associated with outcome in surgically treated TLE with a strengthened epileptogenic connectome in patients with non-free-seizure outcomes. The added value of seed correlation analysis in left TLE underlines the importance of evaluating metabolic connectivity in network related diseases.

Cortical abnormalities of synaptic vesicle protein 2A in focal cortical dysplasia type II identified in vivo with 18F-SynVesT-1 positron emission tomography imaging

PURPOSE

The loss of synaptic vesicle glycoprotein 2A (SV2A) is well established as the major correlate of epileptogenesis in focal cortical dysplasia type II (FCD II), but this has not been directly tested in vivo. In this positron emission tomography (PET) study with the new tracer ¹⁸F-SynVesT-1, we evaluated SV2A abnormalities in patients with FCD II and compared the pattern to ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG).

METHODS

Sixteen patients with proven FCD II and 16 healthy controls were recruited. All FCD II patients underwent magnetic resonance imaging (MRI) and static PET imaging with both ¹⁸F-SynVesT-1 and ¹⁸F-FDG, while the controls underwent MRI and PET with only ¹⁸F-SynVesT-1. Visual assessment of PET images was undertaken. The standardized uptake values (SUVs) of ¹⁸F-SynVesT-1 were computed for regions of interest (ROIs), along with SUV ratio (SUVr) between ROI and centrum semiovale (white matter). Asymmetry indices (AIs) were analyzed between the lesion and the contralateral hemisphere for intersubject comparisons.

RESULTS

Lesions in the brains of FCD II patients had significantly reduced ¹⁸F-SynVesT-1 uptake compared with contralateral regions, and brains of the controls. ¹⁸F-SynVesT-1 PET indicated low lesion uptake in 14 patients (87.5%), corresponding to hypometabolism detected by ¹⁸F-FDG PET, with higher accuracy for lesion localization than MRI (43.8%) (P < 0.05). AI analyses demonstrated that in the lesions, SUVr for each of the radiotracers were not significantly different (P > 0.05), and ¹⁸F-SynVesT-1 SUVr correlated with that of ¹⁸F-FDG across subjects (R² = 0.41, P = 0.008). Subsequent visual ratings indicated that ¹⁸F-SynVesT-1 uptake had a more restricted pattern of reduction than ¹⁸F-FDG uptake in FCD II lesions (P < 0.05).

CONCLUSION

SV2A PET with ¹⁸F-SynVesT-1 shows a higher accuracy for the localization of FCD II lesions than MRI and a more restricted pattern of abnormality than ¹⁸F-FDG PET.

Detection of changes in synaptic density in amyotrophic lateral sclerosis patients using 18 F-SynVesT-1 positron-emission tomography

BACKGROUND

Synaptic loss is well established as the major correlate of characteristic and consistent pathology in amyotrophic lateral sclerosis (ALS). We aimed to assess the possible discriminant diagnostic value of ¹⁸ F-SynVesT-1 positron-emission tomography (PET) as a marker of ALS pathology and investigate whether specific synaptic density signatures are present in ALS with different subtypes.

METHODS

Twenty-one patients with ALS and 25 healthy controls (HCs) were recruited. All participants underwent ¹⁸ F-SynVesT-1-PET. Synaptic density between ALS and HCs and between different ALS subgroups were compared. Correlation between synaptic density and clinical features in ALS was also performed.

RESULTS

Low uptake distribution was found in the group comprising 21 ALS patients as compared with HCs in the right temporal lobe and the bilateral inferior frontal gyrus, anterior cingulate, and hippocampus-insula region. We also found a low uptake in the bilateral superior temporal gyrus, hippocampus-insula, anterior cingulate and left inferior frontal gyrus in ALS patients with cognitive impairment compared to HCs. Furthermore, compared to spinal-onset ALS, bulbar-onset ALS showed low uptake in the bilateral cingulate gyrus and high uptake in the bilateral superior temporal gyrus and left occipital lobe. No significant result was found in correlation analysis.

CONCLUSION

This approach may provide a direct measure of synaptic density, and it therefore might represent a potentially useful biomarker for ALS diagnosis, as well as for estimating the cognitive decline and site of onset in ALS. ¹⁸ F-SynVesT-1-PET is presently not justified as a routine investigation to detect evidence of brain dysfunction justifying progression in ALS.

Machine Learning-Derived Multimodal Neuroimaging of Presurgical Target Area to Predict Individual's Seizure Outcomes After Epilepsy Surgery

Objectives: Half of the patients who have tailored resection of the suspected epileptogenic zone for drug-resistant epilepsy have recurrent postoperative seizures. Although neuroimaging has become an indispensable part of delineating the epileptogenic zone, no validated method uses neuroimaging of presurgical target area to predict an individual's post-surgery seizure outcome. We aimed to develop and validate a machine learning-powered approach incorporating multimodal neuroimaging of a presurgical target area to predict an individual's post-surgery seizure outcome in patients with drug-resistant focal epilepsy. Materials and Methods: One hundred and forty-one patients with drug-resistant focal epilepsy were classified either as having seizure-free (Engel class I) or seizure-recurrence (Engel class II through IV) at least 1 year after surgery. The presurgical magnetic resonance imaging, positron emission tomography, computed tomography, and postsurgical magnetic resonance imaging were co-registered for surgical target volume of interest (VOI) segmentation; all VOIs were decomposed into nine fixed views, then were inputted into the deep residual network (DRN) that was pretrained on Tiny-ImageNet dataset to extract and transfer deep features. A multi-kernel support vector machine (MKSVM) was used to integrate multiple views of feature sets and to predict seizure outcomes of the targeted VOIs. Leave-one-out validation was applied to develop a model for verifying the prediction. In the end, performance using this approach was assessed by calculating accuracy, sensitivity, and specificity. Receiver operating characteristic curves were generated, and the optimal area under the receiver operating characteristic curve (AUC) was calculated as a metric for classifying outcomes. Results: Application of DRN-MKSVM model based on presurgical target area neuroimaging demonstrated good performance in predicting seizure outcomes. The AUC ranged from 0.799 to 0.952. Importantly, the classification performance DRN-MKSVM model using data from multiple neuroimaging showed an accuracy of 91.5%, a sensitivity of 96.2%, a specificity of 85.5%, and AUCs of 0.95, which were significantly better than any other single-modal neuroimaging (all p ˂ 0.05). Conclusion: DRN-MKSVM, using multimodal compared with unimodal neuroimaging from the surgical target area, accurately predicted postsurgical outcomes. The preoperative individualized prediction of seizure outcomes in patients who have been judged eligible for epilepsy surgery could be conveniently facilitated. This may aid epileptologists in presurgical evaluation by providing a tool to explore various surgical options, offering complementary information to existing clinical techniques.

Individual Brain Metabolic Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation Predicts Seizure Outcomes of Temporal Lobe Epilepsy

Objective: We aimed to use an individual metabolic connectome method, the Jensen-Shannon Divergence Similarity Estimation (JSSE), to characterize the aberrant connectivity patterns and topological alterations of the individual-level brain metabolic connectome and predict the long-term surgical outcomes in temporal lobe epilepsy (TLE). Methods: A total of 128 patients with TLE (63 females, 65 males; 25.07 ± 12.01 years) who underwent Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) imaging were enrolled. Patients were classified either as experiencing seizure recurrence (SZR) or seizure free (SZF) at least 1 year after surgery. Each individual's metabolic brain network was ascertained using the proposed JSSE method. We compared the similarity and difference in the JSSE network and its topological measurements between the two groups. The two groups were then classified by combining the information from connection and topological metrics, which was conducted by the multiple kernel support vector machine. The validation was performed using the nested leave-one-out cross-validation strategy to confirm the performance of the methods. Results: With a median follow-up of 33 months, 50% of patients achieved SZF. No relevant differences in clinical features were found between the two groups except age at onset. The proposed JSSE method showed marked degree reductions in IFGoperc.R, ROL. R, IPL. R, and SMG. R; and betweenness reductions in ORBsup.R and IOG. R; meanwhile, it found increases in the degree analysis of CAL. L and PCL. L, and in the betweenness analysis of PreCG.R, IOG. R, PoCG.R, PCL. L and PCL.R. Exploring consensus significant metabolic connections, we observed that the most involved metabolic motor networks were the INS-TPOmid.L, MTG. R-SMG. R, and MTG. R-IPL.R pathways between the two groups, and yielded another detailed individual pathological connectivity in the PHG. R-CAU.L, PHG. R-HIP.L, TPOmid.L-LING.R, TPOmid.L-DCG.R, MOG. R-MTG.R, MOG. R-ANG.R, and IPL. R-IFGoperc.L pathways. These aberrant functional network measures exhibited ideal classification performance in predicting SZF individuals from SZR ones at a sensitivity of 75.00%, a specificity of 92.79%, and an accuracy of 83.59%. Conclusion: The JSSE method indicator can identify abnormal brain networks in predicting an individual's long-term surgical outcome of TLE, thus potentially constituting a clinically applicable imaging biomarker. The results highlight the biological meaning of the estimated individual brain metabolic connectome.