Metabolic patterns and seizure outcomes following anterior temporal lobectomy

Automated segmentation of epilepsy surgical resection cavities: Comparison of four methods to manual segmentation

Accurate resection cavity segmentation on MRI is important for neuroimaging research involving epilepsy surgical outcomes. Manual segmentation, the gold standard, is highly labour intensive. Automated pipelines are an efficient potential solution; however, most have been developed for use following temporal epilepsy surgery. Our aim was to compare the accuracy of four automated segmentation pipelines following surgical resection in a mixed cohort of subjects following temporal or extra temporal epilepsy surgery. We identified 4 open-source automated segmentation pipelines. Epic-CHOP and ResectVol utilise SPM-12 within MATLAB, while Resseg and Deep Resection utilise 3D U-net convolutional neural networks. We manually segmented the resection cavity of 50 consecutive subjects who underwent epilepsy surgery (30 temporal, 20 extratemporal). We calculated Dice similarity coefficient (DSC) for each algorithm compared to the manual segmentation. No algorithm identified all resection cavities. ResectVol (n = 44, 88 %) and Epic-CHOP (n = 42, 84 %) were able to detect more resection cavities than Resseg (n = 22, 44 %, P < 0.001) and Deep Resection (n = 23, 46 %, P < 0.001). The SPM-based pipelines (Epic-CHOP and ResectVol) performed better than the deep learning-based pipelines in the overall and extratemporal surgery cohorts. In the temporal cohort, the SPM-based pipelines had higher detection rates, however there was no difference in the accuracy between methods. These pipelines could be applied to machine learning studies of outcome prediction to improve efficiency in pre-processing data, however human quality control is still required.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

Evidence based noninvasive presurgical evaluation for patients with drug resistant epilepsies

PURPOSE OF REVIEW

To review the current practices and evidence for the diagnostic accuracy and the benefits of presurgical evaluation.

RECENT FINDINGS

Preoperative evaluation of patients with drug-resistant focal epilepsies and subsequent epilepsy surgery leads to a significant proportion of seizure-free patients. Even those who are not completely seizure free postoperatively often experience improved quality of life with better social integration. Systematic reviews and meta-analysis on the diagnostic accuracy are available for Video-electroencephalographic (EEG) monitoring, magnetic resonance imaging (MRI), electric and magnetic source imaging, and functional MRI for lateralization of language and memory. There are currently no evidence-based international guidelines for presurgical evaluation and epilepsy surgery.

SUMMARY

Presurgical evaluation is a complex multidisciplinary and multiprofessional clinical pathway. We rely on limited consensus-based recommendations regarding the required staffing or methodological expertise in epilepsy centers.

Interictal HFO and FDG-PET correlation predicts surgical outcome following SEEG

OBJECTIVE

This study aimed to investigate the quantitative relationship between interictal ¹⁸ F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and interictal high-frequency oscillations (HFOs) from stereo-electroencephalography (SEEG) recordings in patients with refractory epilepsy.

METHODS

We retrospectively included 32 patients. FDG-PET data were quantified through statistical parametric mapping (SPM) t test modeling with normal controls. Interictal SEEG segments with four, 10-min segments were selected randomly. HFO detection and classification procedures were automatically performed. Channel-based HFOs separating ripple (80-250 Hz) and fast ripple (FR; 250-500 Hz) counts were correlated with the surrounding metabolism T score at the individual and group level, respectively. The association was further validated across anatomic seizure origins and sleep vs wake states. We built a joint feature FR × T reflecting the FR and hypometabolism concordance to predict surgical outcomes in 28 patients who underwent surgery.

RESULTS

We found a negative correlation between interictal FDG-PET and HFOs through the linear mixed-effects model (R²  = .346 and .457 for ripples and FRs, respectively, p < .001); these correlations were generalizable to different epileptogenic-zone lobar localizations and vigilance states. The FR × T inside the resection volume could be used as a predictor for surgical outcomes with an area under the curve of 0.81.

SIGNIFICANCE

The degree of hypometabolism is associated with HFO generation rate, especially for FRs. This relationship would be meaningful for selection of SEEG candidates and for optimizing SEEG scheme planning. The concordance between FRs and hypometabolism inside the resection volume could provide prognostic information regarding surgical outcome.

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.

Functional Connectivity Alterations Based on Hypometabolic Region May Predict Clinical Prognosis of Temporal Lobe Epilepsy: A Simultaneous 18F-FDG PET/fMRI Study

(1) Background: Accurate localization of the epileptogenic zone and understanding the related functional connectivity (FC) alterations are critical for the prediction of clinical prognosis in patients with temporal lobe epilepsy (TLE). We aim to localize the hypometabolic region in TLE patients, compare the differences in FC alterations based on hypometabolic region and structural lesion, respectively, and explore their relationships with clinical prognosis. (2) Methods: Thirty-two TLE patients and 26 controls were recruited. Patients underwent 18F-FDG PET/MR scan, surgical treatment, and a 2−3-year follow-up. Visual assessment and voxel-wise analyses were performed to identify hypometabolic regions. ROI-based FC analyses were performed. Relationships between clinical prognosis and FC values were performed by using Pearson correlation analyses and receiver operating characteristic (ROC) analysis. (3) Results: Hypometabolic regions in TLE patients were found in the ipsilateral hippocampus, parahippocampal gyrus, and temporal lobe (p < 0.001). Functional alterations based on hypometabolic regions showed a more extensive whole-brain FC reduction. FC values of these regions negatively correlated with epilepsy duration (p < 0.05), and the ROC curve of them showed significant accuracy in predicting postsurgical outcome. (4) Conclusions: In TLE patients, FC related with hypometabolic region obtained by PET/fMRI may provide value in the prediction of disease progression and seizure-free outcome.

Combined [18F]FDG-PET with MRI structural patterns in predicting post-surgical seizure outcomes in temporal lobe epilepsy patients

OBJECTIVES

To integrate the glucose metabolism measured using [¹⁸F]FDG PET/CT and anatomical features measured using MRI to forecast the post-surgical seizure outcomes of intractable temporal lobe epilepsy.

METHODS

This retrospective study enrolled 63 patients with drug-resistant temporal lobe epilepsy. Z-transform of the patients' PET images based on comparison with a database of healthy controls, cortical thickness, and quantitative anisotropy (QA) of the diffusion spectrum imaging concordant/non-concordant with cortical resection was adopted to quantify their predictive values for the post-surgical seizure outcomes.

RESULTS

The PET hypometabolism region was concordant with the surgical field in 47 of the 63 patients. Forty-two patients were seizure-free post-surgery. The sensitivity and specificity of PET in predicting seizure freedom were 89.4% and 68.8%, respectively. Complete resection of foci with overlapped PET, cortical thickness, and QA abnormalities resulted in Engel I in 27 patients, which was a good predictor of seizure freedom with an odds ratio (OR) of 19.57 (95% CI 2.38-161.25, p = 0.006). Hypometabolism involved in multiple lobes (OR = 7.18, 95% CI 1.02-50.75, p = 0.048) and foci of hypometabolism with QA/cortical thickness abnormalities outside surgical field (OR = 14.72, 95% CI 2.13-101.56, p = 0.006) were two major predictors of Engel III/IV outcomes. ORs of QA to predict Engel I and seizure recurrence were 14.64 (95% CI 2.90-73.80, p = 0.001) and 12.01 (95% CI 2.91-49.65, p = 0.001), respectively.

CONCLUSION

Combined PET and structural pattern is helpful to predict the post-surgical seizure outcomes and worse outcomes of Engel III/IV. This might decrease unnecessary surgical injuries to patients who are potentially not amenable to surgery.

KEY POINTS

• A combined metabolic and structural pattern is helpful to predict the post-surgical seizure outcomes. • Favorable post-surgical seizure outcome was most likely reached in patients whose hypometabolism overlapped with the structural changes. • Hypometabolism in multiple lobes and QA or cortical thickness abnormalities outside the surgical field were predictors of worse seizure outcomes of Engel III/IV.

Predictive value of metabolic and perfusion changes outside the seizure onset zone for postoperative outcome in patients with refractory focal epilepsy

The value of functional molecular changes outside the seizure onset zone as independent predictive factors of surgical outcome has been scarcely evaluated. The aim of this retrospective study was to evaluate relative metabolic and perfusion changes outside the seizure onset zone as predictors of postoperative outcome in patients with unifocal refractory focal epilepsy. Eighty-six unifocal epilepsy patients who underwent ¹⁸F-FDG PET prior to surgery were included. Ictal and interictal perfusion SPECT was available in 65 patients. Good postoperative outcome was defined as the International League against Epilepsy class 1. Using univariate statistical analysis, the predictive ability of volume-of-interest based relative metabolism/perfusion for outcome classification was quantified by AUC ROC-curve, using composite, unilateral cortical (frontal, orbitofrontal, temporal, parietal, occipital) and central volumes-of-interest. The results were cross-validated, and a false discovery rate (FDR) correction was applied. As a secondary objective, a subgroup analysis was performed on temporal lobe epilepsy patients (N = 64). Increased relative ictal perfusion in the contralateral central volume-of-interest was significantly associated with the good surgical outcome both in the total population (AUC 0.79, p_FDR = 0.009) and the temporal lobe epilepsy subgroup (AUC 0.80, p_FDR = 0.028). No other significant associations between functional molecular changes and postoperative outcome were found. Increased relative ictal perfusion in the contralateral central region significantly predicted outcome after epilepsy surgery in patients with refractory focal epilepsy. We postulate that these relative perfusion changes could be an expression of better preoperative neuronal network integration and centralization in the contralateral central structures, which is suggested to be associated with better postoperative outcome.

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.

Machine Learning Approaches for Imaging-Based Prognostication of the Outcome of Surgery for Mesial Temporal Lobe Epilepsy

Objectives

Around 30% of patients undergoing surgical resection for drug‐resistant mesial temporal lobe epilepsy (MTLE) do not obtain seizure freedom. Success of anterior temporal lobe resection (ATLR) critically depends on the careful selection of surgical candidates, aiming at optimizing seizure freedom while minimizing postoperative morbidity. Structural MRI and FDG‐PET neuroimaging are routinely used in presurgical assessment and guide the decision to proceed to surgery. In this study, we evaluate the potential of machine learning techniques applied to standard presurgical MRI and PET imaging features to provide enhanced prognostic value relative to current practice.

Methods

Eighty two patients with drug resistant MTLE were scanned with FDG‐PET pre‐surgery and T1‐weighted MRI pre‐ and postsurgery. From these images the following features of interest were derived: volume of temporal lobe (TL) hypometabolism, % of extratemporal hypometabolism, presence of contralateral TL hypometabolism, presence of hippocampal sclerosis, laterality of seizure onset volume of tissue resected and % of temporal lobe hypometabolism resected. These measures were used as predictor variables in logistic regression, support vector machines, random forests and artificial neural networks.

Results

In the study cohort, 24 of 82 (28.3%) who underwent an ATLR for drug‐resistant MTLE did not achieve Engel Class I (i.e., free of disabling seizures) outcome at a minimum of 2 years of postoperative follow‐up. We found that machine learning approaches were able to predict up to 73% of the 24 ATLR surgical patients who did not achieve a Class I outcome, at the expense of incorrect prediction for up to 31% of patients who did achieve a Class I outcome. Overall accuracies ranged from 70% to 80%, with an area under the receiver operating characteristic curve (AUC) of .75–.81. We additionally found that information regarding overall extent of both total and significantly hypometabolic tissue resected was crucial to predictive performance, with AUC dropping to .59–.62 using presurgical information alone. Incorporating the laterality of seizure onset and the choice of machine learning algorithm did not significantly change predictive performance.

Significance

Collectively, these results indicate that "acceptable" to "good" patient‐specific prognostication for drug‐resistant MTLE surgery is feasible with machine learning approaches utilizing commonly collected imaging modalities, but that information on the surgical resection region is critical for optimal prognostication.

Electroclinical and Multimodality Neuroimaging Characteristics and Predictors of Post-Surgical Outcome in Focal Cortical Dysplasia Type IIIa

Focal cortical dysplasia (FCD) type IIIa is an easily ignored cause of intractable temporal lobe epilepsy. This study aimed to analyze the clinical, electrophysiological, and imaging characteristics in FCD type IIIa and to search for predictors associated with postoperative outcome in order to identify potential candidates for epilepsy surgery. We performed a retrospective review including sixty-six patients with FCD type IIIa who underwent resection for drug-resistant epilepsy. We evaluated the clinical, electrophysiological, and neuroimaging features for potential association with seizure outcome. Univariate and multivariate analyses were conducted to explore their predictive role on the seizure outcome. We demonstrated that thirty-nine (59.1%) patients had seizure freedom outcomes (Engel class Ia) with a median postsurgical follow-up lasting 29.5 months. By univariate analysis, duration of epilepsy (less than 12 years) (p = 0.044), absence of contralateral insular lobe hypometabolism on PET/MRI (p_Log-rank = 0.025), and complete resection of epileptogenic area (p_Log-rank = 0.004) were associated with seizure outcome. The incomplete resection of the epileptogenic area (hazard ratio = 2.977, 95% CI 1.218–7.277, p = 0.017) was the only independent predictor for seizure recurrence after surgery by multivariate analysis. The results of past history, semiology, electrophysiological, and MRI were not associated with seizure outcomes. Carefully included patients with FCD type IIIa through a comprehensive evaluation of their clinical, electrophysiological, and neuroimaging characteristics can be good candidates for resection. Several preoperative factors appear to be predictive of the postoperative outcome and may help in optimizing the selection of ideal candidates to benefit from epilepsy surgery.

Individual [18F]FDG PET and functional MRI based on simultaneous PET/MRI may predict seizure recurrence after temporal lobe epilepsy surgery

OBJECTIVES

To investigate the individual measures of brain glucose metabolism, neural activity obtained from simultaneous ¹⁸[F]FDG PET/MRI, and their association with surgical outcomes in medial temporal lobe epilepsy due to hippocampal sclerosis (mTLE-HS).

METHODS

Thirty-nine unilateral mTLE-HS patients who underwent anterior temporal lobectomy were classified as having completely seizure-free (Engel class IA; n = 22) or non-seizure-free (Engel class IB-IV; n = 17) outcomes at 1 year after surgery. Preoperative [¹⁸F]FDG PET and functional MRI (fMRI) were obtained from a simultaneous PET/MRI scanner, and individual glucose metabolism and fractional amplitude of low-frequency fluctuation (fALFF) were evaluated by standardizing these with respect to healthy controls. These abnormality measures and clinical data from each patient were incorporated into a machine learning framework (gradient boosting decision tree and logistic regression analysis) to estimate seizure recurrence. The predictive values of features were evaluated by the receiver operating characteristic (ROC) curve in the training and test cohorts.

RESULTS

The machine learning classification model showed [¹⁸F]FDG PET and fMRI variations in contralateral hippocampal network and age of onset identify unfavorable surgical outcomes effectively. In the validation dataset, the logistic regression model with [¹⁸F]FDG PET and fALFF obtained from simultaneous [¹⁸F]FDG PET/MRI gained the maximum area under the ROC curve of 0.905 for seizure recurrence, higher than 0.762 with ¹⁸[F]-FDG PET, and 0.810 with fALFF alone.

CONCLUSION

Machine learning model suggests individual [¹⁸F]FDG PET and fMRI variations in contralateral hippocampal network based on ¹⁸[F]-FDG PET/MRI could serve as a potential biomarker of unfavorable surgical outcomes.

KEY POINTS

• Individual [¹⁸F]FDG PET and fMRI obtained from preoperative [¹⁸F]FDG PET/MR were investigated. • Individual differences were further assessed based on a seizure propagation network. • Machine learning can classify surgical outcomes with 90.5% accuracy.

[18F]FDG PET/MRI and magnetoencephalography may improve presurgical localization of temporal lobe epilepsy

OBJECTIVES

To evaluate the clinical value of the combination of [¹⁸F]FDG PET/MRI and magnetoencephalography (MEG) ([¹⁸F]FDG PET/MRI/MEG) in localizing the epileptogenic zone (EZ) in temporal lobe epilepsy (TLE) patients.

METHODS

Seventy-three patients with localization-related TLE who underwent [¹⁸F]FDG PET/MRI and MEG were enrolled retrospectively. PET/MRI images were interpreted by two radiologists; the focal hypometabolism on PET was identified using statistical parametric mapping (SPM). MEG spike sources were co-registered onto T1-weighted sequence and analyzed by Neuromag software. The clinical value of [¹⁸F]FDG PET/MRI, MEG, and PET/MRI/MEG in locating the EZ was assessed using cortical resection and surgical outcomes as criteria. The correlations between surgical outcomes and modalities concordant or non-concordant with cortical resection were analyzed.

RESULTS

For 46.6% (34/73) of patients, MRI showed definitely structural abnormality concordant with surgical resection. SPM results of [¹⁸F]FDG PET showed focal temporal lobe hypometabolism concordant with surgical resection in 67.1% (49/73) of patients, while the concordant cases increased to 82.2% (60/73) patients with simultaneous MRI co-registration. MEG was concordant with surgical resection in 71.2% (52/73) of patients. The lobar localization was defined in 94.5% (69/73) of patients by the [¹⁸F]FDG PET/MRI/MEG. The results of PET/MRI/MEG concordance with surgical resection were significantly higher than that of PET/MRI or MEG (χ² = 13.948, p < 0.001; χ² = 5.393, p = 0.020). The results of PET/MRI/MEG cortical resection concordance with surgical outcome were shown to be better than PET/MRI or MEG (χ² = 6.695, p = 0.012; χ² = 16.991, p < 0.0001).

CONCLUSIONS

Presurgical evaluation by [¹⁸F]FDG PET/MRI/MEG could improve the identification of the EZ in TLE and may further guide surgical decision-making.

KEY POINTS

• Lobar localization was defined in 94.5% of patients by the [¹⁸F]FDG PET/MRI/MEG. • The results of PET/MRI/MEG concordance with surgical resection were significantly higher than that of PET/MRI or MEG alone. • The results of PET/MRI/MEG cortical resection concordance with surgical outcome were shown to be better than that of PET/MRI or MEG alone.

Low prevalence of amyloid and tau pathology in drug-resistant temporal lobe epilepsy

OBJECTIVE

Cognitive impairment is common in patients with chronic drug-resistant temporal lobe epilepsy (TLE). Hyperphosphorylated tau (pTau) and amyloid-β (Aβ) plaques, pathological hallmarks of Alzheimer disease, have been hypothesized to play a mechanistic role. We investigated Aβ plaques and pTau prevalence in TLE patients who underwent resective surgery and correlated their presence with preoperative psychometric test scores and clinical factors.

METHODS

Patients were retrospectively selected from the epilepsy surgery register of the Royal Melbourne Hospital, Australia. Sections from the resected temporal lobe were immunostained for pTau and Aβ plaques (antibodies: AT8, 1E8). The presence and severity of pathology were correlated with clinical characteristics, and verbal and visual learning functions as measured by the Verbal Pair Associates (VPA) test and Rey Complex Figure Test.

RESULTS

Fifty-six patients (55% female) aged 20-68 years (median = 34 years) at surgery were included. Aβ plaques were detected in four patients (7%), all at the moderate level. There was no difference in duration, age at onset of epilepsy, or side of resection between patients with and without Aβ plaques. Sparse pTau was found in two patients (3.5%). Both had moderate Aβ plaques and were >50 years of age. Patients with Aβ plaques had a lower median score for the VPA hard assessment compared to those without (0 vs. 4; p = .02). There was otherwise no correlation between pathology and psychometric test scores.

SIGNIFICANCE

Aβ plaques and pTau were uncommon in the resected brain tissue of patients who have undergone temporal lobectomy, and did not correlate with clinical characteristics or preoperative psychometric test scores, except for a lower VPA median score in patients with Aβ plaques. Therefore, considering the low prevalence of Aβ plaques and pTau herein observed, it is unlikely that cognitive impairment in TLE is driven by the same mechanisms as in Alzheimer disease.

Brain metabolic characteristics distinguishing typical and atypical benign epilepsy with centro-temporal spikes

OBJECTIVES

Atypical benign epilepsy with centro-temporal spikes (BECTS) have less favorable outcomes than typical BECTS, and thus should be accurately identified for adequate treatment. We aimed to investigate the glucose metabolic differences between typical and atypical BECTS using ¹⁸F-fluorodeoxyglucose positron emission tomography ([¹⁸F]FDG PET) imaging, and explore whether these differences can help distinguish.

METHODS

Forty-six patients with typical BECTS, 31 patients with atypical BECTS and 23 controls who underwent [¹⁸F]FDG PET examination were retrospectively involved. Absolute asymmetry index (|AI|) was applied to evaluate the severity of metabolic abnormality. Glucose metabolic differences were investigated among typical BECTS, atypical BECTS, and controls by using statistical parametric mapping (SPM). Logistic regression analyses were performed based on clinical, PET, and hybrid features.

RESULTS

The |AI| was found significantly higher in atypical BECTS than in typical BECTS (p = 0.040). Atypical BECTS showed more hypo-metabolism regions than typical BECTS, mainly located in the fronto-temporo-parietal cortex. The PET model had significantly higher area under the curve (AUC) than the clinical model (0.91 vs. 0.70, p = 0.006). The hybrid model had the highest sensitivity (0.90), specificity (0.85), and accuracy (0.87) of all three models.

CONCLUSIONS

Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, depending on which the two groups can be well distinguished. The combination of metabolic characteristics and clinical variables has the potential to be used clinically to distinguish between typical and atypical BECTS.

KEY POINTS

• Distinguishing between typical and atypical BECTS is very important for the formulation of treatment regimens in clinical practice. • Atypical BECTS showed more widespread and severe hypo-metabolism than typical BECTS, mainly located in the fronto-temporo-parietal cortex. • The logistic regression model based on PET outperformed that based on clinical characteristics in classification of typical and atypical BECTS, and the hybrid model achieved the best classification performance.

Quantitative [18]FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy

OBJECTIVE

Fluorodeoxyglucose-positron emission tomography (FDG-PET) is an established, independent, strong predictor of surgical outcome in refractory epilepsy. In this study, we explored the added value of quantitative [¹⁸F]FDG-PET features combined with clinical variables, including electroencephalography (EEG), [¹⁸F]FDG-PET, and magnetic resonance imaging (MRI) qualitative interpretations, to predict long-term seizure recurrence (mean post-op follow-up of 5.85 ± 3.77 years).

METHODS

Machine learning predictive models of surgical outcome were created using a random forest classifier trained on quantitative features in 89 patients with drug-refractory temporal lobe epilepsy evaluated at the Hospital of the University of Pennsylvania epilepsy surgery program (2003-2016). Quantitative features were calculated from asymmetry features derived from image processing using Advanced Normalization Tools (ANTs).

RESULTS

The best-performing model used quantification and had an out-of-bag accuracy of 0.71 in identifying patients with seizure recurrence (Engel IB or worse) which outperformed that using qualitative clinical data by 10%. This model is shared through open-source software for research use. In addition, several asymmetry features in temporal and extratemporal regions that were significantly associated with seizure freedom are identified for future study.

SIGNIFICANCE

Complex quantitative [¹⁸F]FDG-PET imaging features can predict seizure recurrence in patients with refractory temporal lobe epilepsy. These initial retrospective results in a cohort with long-term follow-up suggest that using quantitative imaging features from regions in the epileptogenic network can inform the clinical decision-making process.

An evaluation of the diagnostic equivalence of 18F-FDG-PET between hybrid PET/MRI and PET/CT in drug-resistant epilepsy: A pilot study

OBJECTIVE

Hybrid PET/MRI may improve detection of seizure-onset zone (SOZ) in drug-resistant epilepsy (DRE), however, concerns over PET bias from MRI-based attenuation correction (MRAC) have limited clinical adoption of PET/MRI. This study evaluated the diagnostic equivalency and potential clinical value of PET/MRI against PET/CT in DRE.

MATERIALS AND METHODS

MRI, FDG-PET and CT images (n = 18) were acquired using a hybrid PET/MRI and a CT scanner. To assess diagnostic equivalency, PET was reconstructed using MRAC (RESOLUTE) and CT-based attenuation correction (CTAC) to generate PET/MRI and PET/CT images, respectively. PET/MRI and PET/CT images were compared qualitatively through visual assessment and quantitatively through regional standardized uptake value (SUV) and z-score assessment. Diagnostic accuracy and sensitivity of PET/MRI and PET/CT for SOZ detection were calculated through comparison to reference standards (clinical hypothesis and histopathology, respectively).

RESULTS

Inter-reader agreement in visual assessment of PET/MRI and PET/CT images was 78 % and 81 %, respectively. PET/MRI and PET/CT were strongly correlated in mean SUV (r = 0.99, p < 0.001) and z-scores (r = 0.92, p < 0.001) across all brain regions. MRAC SUV bias was <5% in most brain regions except the inferior temporal gyrus, temporal pole, and cerebellum. Diagnostic accuracy and sensitivity were similar between PET/MRI and PET/CT (87 % vs. 85 % and 83 % vs. 83 %, respectively).

CONCLUSION

We demonstrate here that PET/MRI with optimal MRAC can yield similar diagnostic performance as PET/CT. Nevertheless, further exploration of the potential added value of PET/MRI is necessary before clinical adoption of PET/MRI for epilepsy imaging.

Correlations between interictal extratemporal spikes and clinical features, imaging characteristics, and surgical outcomes in patients with mesial temporal lobe epilepsy

PURPOSE

The significance of interictal epileptiform discharges (IEDs) observed in the extratemporal lobe has not been fully evaluated in patients with mesial temporal lobe epilepsy (MTLE). This study aimed to evaluate the surgical outcomes, clinical features, and functional neuroimaging characteristics of patients in relation to the presence or absence of extratemporal IED in MTLE with hippocampal sclerosis (HS).

METHODS

A total of 165 patients with HS-induced MTLE who had undergone anterior temporal lobectomy were enrolled and stratified into the extratemporal interictal epileptiform discharges (ETD) and the temporal lobe discharges (TD) groups. We analyzed the differentiating features of pre- and postsurgical evaluation data between the two groups. For outcome assessment, only patients with a follow-up of at least 2 years were enrolled, and the outcomes were classified based on Engel classification.

RESULTS

The ETD group showed extensive glucose hypometabolism involving the temporal lobe and extratemporal regions (p < 0.001), and IEDs were observed bilaterally or contralateral to the ictal focus (p = 0.02). However, there was no difference in the surgical outcomes between the two groups. On multivariate analysis, statistically significant variables related to ETD occurrence including seizure onset age were not identified nevertheless.

CONCLUSION

Our results indicate that ETD had a surgical outcome comparable to that of TD. Therefore, a surgical intervention need not be delayed even if extratemporal IED may be found in presurgical long-term scalp EEG monitoring.

18F-FDG PET-guided diffusion tractography reveals white matter abnormalities around the epileptic focus in medically refractory epilepsy: implications for epilepsy surgical evaluation

BACKGROUND

Hybrid PET/MRI can non-invasively improve localization and delineation of the epileptic focus (EF) prior to surgical resection in medically refractory epilepsy (MRE), especially when MRI is negative or equivocal. In this study, we developed a PET-guided diffusion tractography (PET/DTI) approach combining ¹⁸F-fluorodeoxyglucose PET (FDG-PET) and diffusion MRI to investigate white matter (WM) integrity in MRI-negative MRE patients and its potential impact on epilepsy surgical planning.

METHODS

FDG-PET and diffusion MRI of 14 MRI-negative or equivocal MRE patients were used to retrospectively pilot the PET/DTI approach. We used asymmetry index (AI) mapping of FDG-PET to detect the EF as brain areas showing the largest decrease in FDG uptake between hemispheres. Seed-based WM fiber tracking was performed on DTI images with a seed location in WM 3 mm from the EF. Fiber tractography was repeated in the contralateral brain region (opposite to EF), which served as a control for this study. WM fibers were quantified by calculating the fiber count, mean fractional anisotropy (FA), mean fiber length, and mean cross-section of each fiber bundle. WM integrity was assessed through fiber visualization and by normalizing ipsilateral fiber measurements to contralateral fiber measurements. The added value of PET/DTI in clinical decision-making was evaluated by a senior neurologist.

RESULTS

In over 60% of the patient cohort, AI mapping findings were concordant with clinical reports on seizure-onset localization and lateralization. Mean FA, fiber count, and mean fiber length were decreased in 14/14 (100%), 13/14 (93%), and 12/14 (86%) patients, respectively. PET/DTI improved diagnostic confidence in 10/14 (71%) patients and indicated that surgical candidacy be reassessed in 3/6 (50%) patients who had not undergone surgery.

CONCLUSIONS

We demonstrate here the utility of AI mapping in detecting the EF based on brain regions showing decreased FDG-PET activity and, when coupled with DTI, could be a powerful tool for detecting EF and assessing WM integrity in MRI-negative epilepsy. PET/DTI could be used to further enhance clinical decision-making in epilepsy surgery.