Nomograms to predict naming decline after temporal lobe surgery in adults with epilepsy

Predictive models of epilepsy outcomes

PURPOSE OF REVIEW

Multiple complex medical decisions are necessary in the course of a chronic disease like epilepsy. Predictive tools to assist physicians and patients in navigating this complexity have emerged as a necessity and are summarized in this review.

RECENT FINDINGS

Nomograms and online risk calculators are user-friendly and offer individualized predictions for outcomes ranging from safety of antiseizure medication withdrawal (accuracy 65-73%) to seizure-freedom, naming, mood, and language outcomes of resective epilepsy surgery (accuracy 72-81%). Improving their predictive performance is limited by the nomograms' inability to ingest complex data inputs. Conversely, machine learning offers the potential of multimodal and expansive model inputs achieving human-expert level accuracy in automated scalp electroencephalogram (EEG) interpretation but lagging in predictive performance or requiring validation for other applications.

SUMMARY

Good to excellent predictive models are now available to guide medical and surgical epilepsy decision-making with nomograms offering individualized predictions and user-friendly tools, and machine learning approaches offering the potential of improved performance. Future research is necessary to bridge the two approaches for optimal translation to clinical care.

Neurobehavioral and Clinical Comorbidities in Epilepsy: The Role of White Matter Network Disruption

Epilepsy is a common neurological disorder associated with alterations in cortical and subcortical brain networks. Despite a historical focus on gray matter regions involved in seizure generation and propagation, the role of white matter (WM) network disruption in epilepsy and its comorbidities has sparked recent attention. In this review, we describe patterns of WM alterations observed in focal and generalized epilepsy syndromes and highlight studies linking WM disruption to cognitive and psychiatric comorbidities, drug resistance, and poor surgical outcomes. Both tract-based and connectome-based approaches implicate the importance of extratemporal and temporo-limbic WM disconnection across a range of comorbidities, and an evolving literature reveals the utility of WM patterns for predicting outcomes following epilepsy surgery. We encourage new research employing advanced analytic techniques (e.g., machine learning) that will further shape our understanding of epilepsy as a network disorder and guide individualized treatment decisions. We also address the need for research that examines how neuromodulation and other treatments (e.g., laser ablation) affect WM networks, as well as research that leverages larger and more diverse samples, longitudinal designs, and improved magnetic resonance imaging acquisitions. These steps will be critical to ensuring generalizability of current research and determining the extent to which neuroplasticity within WM networks can influence patient outcomes.

Impact of white matter networks on risk for memory decline following resection versus ablation in temporal lobe epilepsy

BACKGROUND

With expanding neurosurgical options in epilepsy, it is important to characterise each options' risk for postoperative cognitive decline. Here, we characterise how patients' preoperative white matter (WM) networks relates to postoperative memory changes following different epilepsy surgeries.

METHODS

Eighty-nine patients with temporal lobe epilepsy with T1-weighted and diffusion-weighted imaging as well as preoperative and postoperative verbal memory scores (prose recall) underwent either anterior temporal lobectomy (ATL: n=38) or stereotactic laser amygdalohippocampotomy (SLAH; n=51). We computed laterality indices (ie, asymmetry) for volume of the hippocampus and fractional anisotropy (FA) of two deep WM tracts (uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF)).

RESULTS

Preoperatively, left-lateralised FA of the ILF was associated with higher prose recall (p<0.01). This pattern was not observed for the UF or hippocampus (ps>0.05). Postoperatively, right-lateralised FA of the UF was associated with less decline following left ATL (p<0.05) but not left SLAH (p>0.05), while right-lateralised hippocampal asymmetry was associated with less decline following both left ATL and SLAH (ps<0.05). After accounting for preoperative memory score, age of onset and hippocampal asymmetry, the association between UF and memory decline in left ATL remained significant (p<0.01).

CONCLUSIONS

Asymmetry of the hippocampus is an important predictor of risk for memory decline following both surgeries. However, asymmetry of UF integrity, which is only severed during ATL, is an important predictor of memory decline after ATL only. As surgical procedures and pre-surgical mapping evolve, understanding the role of frontal-temporal WM in memory networks could help to guide more targeted surgical approaches to mitigate cognitive decline.

Sex differences in the pre and postoperative neuropsychological function of epilepsy surgery candidates

Objective: As programs expand globally, epilepsy surgery is becoming increasingly available as an effective treatment for some people with medically intractable seizures. Prospective candidates require careful neuropsychological evaluation and follow-up. The aim of this study was to examine the sex differences in neuropsychological function in presurgical presentation and postoperative outcomes in people with temporal lobe epilepsy referred for epilepsy surgery. Methods: Three hundred and seventy-two patients (202 Female; 170 Male) with a homogenous underlying pathology (hippocampal sclerosis) underwent a preoperative assessment on tests of intellectual, language, and memory function and were followed up one year after undergoing a unilateral temporal lobe resection; n = 169 Right (RTL), n = 203 Left (LTL). Results: There was no impact of sex or laterality of surgery on seizure outcome; 84% of males and 80% of females were seizure free at follow-up. Before surgery, sex effects were evident on tests of verbal memory with females performing better than males. Declines in verbal memory function following surgery were greater in females than males. Being female had a stronger association with postoperative decline on immediate prose recall (partial eta squared η2 = 0.029), than side of surgery (η2 = 0.018) albeit with a small effect size. Conclusions: There are subtle but significant sex differences in the neuropsychological profiles of people with temporal lobe epilepsy, before and following surgery. Whilst females generally perform better than males on tests of verbal memory function before surgery they demonstrate greater post-operative declines on these measures following surgery.

Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome

Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.

Age of epilepsy onset as modulating factor for naming deficit after epilepsy surgery: a voxel-based lesion-symptom mapping study

Age at onset of epilepsy is an important predictor of deterioration in naming ability following epilepsy surgery. In 141 patients with left hemispheric epilepsy and language dominance who received epilepsy surgery at the Epilepsy Centre Erlangen, naming of objects (Boston naming test, BNT) was assessed preoperatively and 6 months postoperatively. Surgical lesions were plotted on postoperative MRI and normalized for statistical analysis using voxel-based lesion-symptom mapping (VBLSM). The correlation between lesion and presence of postoperative naming deterioration was examined varying the considered age range of epilepsy onsets. The VBLSM analysis showed that volumes of cortex areas in the left temporal lobe, which were associated with postoperative decline of naming, increased with each year of later epilepsy onset. In patients with later onset, an increasing left posterior temporobasal area was significantly associated with a postoperative deficit when included in the resection. For late epilepsy onset, the temporomesial expansion also included the left hippocampus. The results underline that early onset of epilepsy is a good prognostic factor for unchanged postoperative naming ability following epilepsy surgery. For later age of epilepsy onset, the extent of the area at risk of postoperative naming deficit at 6 months after surgery included an increasing left temporobasal area which finally also comprised the hippocampus.

What are we really predicting with fMRI in epilepsy surgery?

While memory and language functional magnetic resonance imaging (fMRI) paradigms are becoming evermore refined, the measures of outcome they predict following epilepsy surgery tend to remain single scores on pencil and paper tests that were developed decades ago and have been repeatedly shown to bear little relation to patients' subjective reports of memory problems in the real world. The growing imbalance between the increasing sophistication of the predictive paradigms on the one hand and the vintage measures of the outcome on the other in the fMRI epilepsy surgery literature threatens the clinical relevance of studies employing these technologies. This paper examines some of the core principles of assessing neuropsychological outcomes following epilepsy surgery and explores how these may be adapted and applied in fMRI study designs to maximize the clinical relevance of these studies.

The impact of temporal lobe epilepsy surgery on picture naming and its relationship to network metric change

BACKGROUND

Anterior temporal lobe resection (ATLR) is a successful treatment for medically-refractory temporal lobe epilepsy (TLE). In the language-dominant hemisphere, 30%- 50% of individuals experience a naming decline which can impact upon daily life. Measures of structural networks are associated with language performance pre-operatively. It is unclear if analysis of network measures may predict post-operative decline.

METHODS

White matter fibre tractography was performed on preoperative diffusion MRI of 44 left lateralised and left resection individuals with TLE to reconstruct the preoperative structural network. Resection masks, drawn on co-registered pre- and post-operative T1-weighted MRI scans, were used as exclusion regions on pre-operative tractography to estimate the post-operative network. Changes in graph theory metrics, cortical strength, betweenness centrality, and clustering coefficient were generated by comparing the estimated pre- and post-operative networks. These were thresholded based on the presence of the connection in each patient, ranging from 75% to 100% in steps of 5%. The average graph theory metric across thresholds was taken. We incorporated leave-one-out cross-validation with smoothly clipped absolute deviation (SCAD) least absolute shrinkage and selection operator (LASSO) feature selection and a support vector classifier to assess graph theory metrics on picture naming decline. Picture naming was assessed via the Graded Naming Test preoperatively and at 3 and 12 months post-operatively and the outcome was classified using the reliable change index (RCI) to identify clinically significant decline. The best feature combination and model was selected using the area under the curve (AUC). The sensitivity, specificity and F1-score were also reported. Permutation testing was performed to assess the machine learning model and selected regions difference significance.

RESULTS

A combination of clinical and graph theory metrics were able to classify outcome of picture naming at 3 months with an AUC of 0.84. At 12 months, change in strength to cortical regions was best able to correctly classify outcome with an AUC of 0.86. Longitudinal analysis revealed that betweenness centrality was the best metric to identify patients who declined at 3 months, who will then continue to experience decline from 3 to 12 months. Both models were significantly higher AUC values than a random classifier.

CONCLUSION

Our results suggest that inferred changes of network integrity were able to correctly classify picture naming decline after ATLR. These measures may be used to prospectively to identify patients who are at risk of picture naming decline after surgery and could potentially be utilised to assist tailoring the resection in order to prevent this decline.

Characterization and Prediction of Short-term Outcomes in Memory After Temporal Lobe Resection in Children With Epilepsy

BACKGROUND AND OBJECTIVES

The aim of this study was to characterize short-term outcomes in episodic memory, as assessed by the Children's Memory Scale (CMS), after temporal lobe resection in children with epilepsy using empirical methods for assessing cognitive change (i.e., reliable change indices [RCI] and standardized regression-based change scores [SRB]) and develop and internally validate clinically applicable models to predict postoperative memory decline.

METHODS

This retrospective cohort study included children aged 6-16 years who underwent resective epilepsy surgery that included the temporal lobe (temporal only: "temporal" and multilobar: "temporal plus") and who completed preoperative and postoperative neuropsychological assessments including the CMS. Change scores on the CMS delayed memory subtests (Faces, Stories, and Word Pairs) were classified as decline, no change, or improvement using epilepsy-specific RCI and SRB. Logistic regression models for predicting postoperative memory decline were developed and internally validated with bootstrapping.

RESULTS

Of the 126 children included, most of them demonstrated either no significant change (54%-69%) or improvement (8%-14%) in memory performance using RCI on individual measures at a median of 7 months after surgery. A subset of children (23%-33%) showed postoperative declines. Change distributions obtained using RCI and SRB were not statistically significantly different from each other. Preoperative memory test score, surgery side, surgery extent, and preoperative full-scale IQ were predictors of memory decline. Prediction models for memory decline included subsets of these variables with bias-corrected concordance statistics ranging from 0.70 to 0.75. The models were well calibrated although slightly overestimated the probability of verbal memory decline in high-risk patients.

DISCUSSION

This study used empiric methodology to characterize memory outcome in children after temporal lobe resection. Provided online calculator and nomograms may be used by clinicians to estimate the risk of postoperative memory decline for individual patients before surgery.

The who, what, when and why of cognitive difficulties in epilepsy

Cognitive complaints are very common in people diagnosed with epilepsy. These difficulties are often another manifestation of the same pathology responsible for seizures. They can be further exacerbated by treatments aimed at seizure control. Other common comorbidities of epilepsy such as low mood and elevated anxiety can also contribute to cognitive complaints. There is surprisingly little overlap between memory complaints and performance on formal memory tests in this population. This article examines the multifactorial and heterogeneous nature of cognitive difficulties in epilepsy and makes the case for the provision of basic psychoeducation as the foundation for all interventions aimed at ameliorating these difficulties in this patient population.

New insights for predicting surgery outcome in patients with temporal lobe epilepsy. A systematic review

Resective surgery is the treatment of choice for one-third of adult patients with focal, drug-resistant epilepsy. This procedure is associated with substantial clinical and cognitive risks. In clinical practice, there is no validated model for epilepsy surgery outcome prediction (ESOP). Meta-analyses on ESOP studies assessing prognostic factors report discrepancies in terms of study design. Our review aims to systematically investigate methodological and analytical aspects of studies predicting clinical and cognitive outcomes after temporal lobe epilepsy surgery. A systematic review of ESOP studies published between 2000 and 2022 from three databases (MEDLINE, Web of Science, and PsycINFO) was completed by following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. It yielded 4867 articles. Among them, 21 corresponded to our inclusion criteria and were therefore retained in the final review. The risk of bias was assessed using A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies (PROBAST). Data extracted from the 21 studies were analyzed using narrative synthesis and descriptive statistics. Our findings show an increase in the use of multimodal datasets and machine learning analyses in recent ESOP studies, although regression remained the most frequently used approach. We also identified a more frequent use of network notions in recent ESOP studies. Nevertheless, several methodological issues were noted, such as small sample sizes, lack of information on the follow-up period, variability in seizure outcome, and the definition of neuropsychological postoperative change. Of 21 studies, only one provided a clinical tool to anticipate the cognitive outcome after epilepsy surgery. We conclude that methodological issues should be overcome before we move towards more complete models to better predict clinical and cognitive outcomes after epilepsy surgery. Recommendations for future studies to harness the possibilities of multimodal datasets and data fusion, are provided. A stronger bridge between fundamental and clinical research may result in developing accessible clinical tools.

A procedure for predicting, illustrating, communicating, and optimizing patient-centered outcomes of epilepsy surgery using nomograms and Bayes' theorem

Clinicians have an ethical obligation to obtain and convey relevant information about possible treatment outcomes in a manner that can be comprehended by patients. This contributes to the processes of informed consent and shared prospective decision-making. In epilepsy neurosurgery, there has historically been an emphasis on studying clinician-centered (e.g., seizure- and cognition-related) outcomes and using these data to inform recommendations and, by extension, to frame pre-surgical counseling with respect to patients' decisions about elective neurosurgery. In contrast, there is a relative dearth of available data related to patient-centered outcomes of epilepsy neurosurgery, such as functional (e.g., employment) status, and there is also a lack of methods to communicate these data to patients. Here, illustrated using a hypothetical case scenario, we present a potential solution to the latter of these problems using principles of evidence-based neuropsychology; published data on patient employment status before and after epilepsy neurosurgery; and Bayes' theorem. First, we reviewed existing literature on employment outcomes following epilepsy neurosurgery to identify and extract data relevant to our hypothetical patient, clinical question, and setting. Then, we used the base rate (prior probability) of post-surgical unemployment, contingency tables (to derive likelihood ratios), and Bayes' theorem to compute the conditional (posterior) probability of post-surgical employment status for our hypothetical patient scenario. Finally, we translated this information to an intuitive visual format (Bayesian nomogram) that can support evidence-based pre-surgical counseling. We propose that the application of our patient-centered decision-support process and visual aid will improve clinician-patient communication about prospective risks and benefits of epilepsy neurosurgery and will empower clinicians and patients to make informed decisions about whether or not to pursue elective neurosurgery with a greater degree of confidence and with more realistic and concrete expectations about possible outcomes. We further propose that clinicians and patients would benefit from incorporating this evidence-based framework into a broader sequence of function-focused epilepsy treatment that includes pre-surgical assessments and interventions ("prehabilitation"), neurosurgery, and post-surgical cognitive/vocational rehabilitation.

The Processing Differences between Chinese Proper Nouns and Common Nouns in the Left and Right Hemispheres of the Brain

In this study, we investigated whether there were differences between the processing of Chinese proper nouns and common nouns in the left and that in the right hemispheres of the brain by using a visual half-field technique. The experimental materials included four types of proper nouns (people’s names, landmark names, country names, and brand names), four types of common nouns (animals, fruits and vegetables, tools, and abstract nouns), and pseudowords. Participants were asked to judge whether target words that had been quickly presented in their left or right visual field were meaningful words. The results showed that there was a distinction between the processing of the two types of words in the left and right hemispheres. There was no significant difference in the processing of the two types of nouns in the right hemisphere, but the left hemisphere processed common nouns more effectively than proper nouns. Furthermore, the processing difference of proper nouns between the two hemispheres was less than that of common nouns, suggesting that proper nouns have a smaller lateralization effect than common nouns.

Machine Learning for Precision Epilepsy Surgery

Brain surgery offers the best chance of seizure-freedom for patients with focal drug-resistant epilepsy, but only 50% achieve sustained seizure-freedom. With the explosion of data collected during routine presurgical evaluations and recent advances in computational science, we now have a tremendous potential to achieve precision epilepsy surgery: a data-driven tailoring of surgical planning. This review highlights the clinical need, the relevant computational science focusing on machine learning, and discusses some specific applications in epilepsy surgery.

Reward-based decision-making in mesial temporal lobe epilepsy patients with unilateral hippocampal sclerosis pre- and post-surgery

BACKGROUND

Correct functioning of the reward processing system is critical for optimizing decision-making as well as preventing the development of addictions and/or neuropsychiatric symptoms such as depression, apathy, and anhedonia. Consequently, patients with mesial temporal lobe epilepsy due to unilateral hippocampal sclerosis (mTLE-UHS) represent an excellent opportunity to study the brain networks involved in this system.

OBJECTIVE

The aim of the current study was to evaluate decision-making and the electrophysiological correlates of feedback processing in a sample of mTLE-UHS patients, compared to healthy controls. In addition, we assessed the impact of mesial temporal lobe surgical resection on these processes, as well as general, neuropsychological functioning.

METHOD

17 mTLE-UHS patients and 17 matched healthy controls completed: [1] a computerized version of the Game of Dice Task, [2] a Standard Iowa Gambling Task, and [3] a modified ERP version of a probabilistic gambling task coupled with multichannel electroencephalography. Neuropsychological scores were also obtained both pre- and post-surgery.

RESULTS

Behavioral analyses showed a pattern of increased risk for the mTLE-UHS group in decision-making under ambiguity compared to the control group. A decrease in the amplitude of the Feedback Related Negativity (FRN), a weaker effect of valence on delta power, and a general reduction of delta and theta power in the mTLE-UHS group, as compared to the control group, were also found. The beta-gamma activity associated with the delivery of positive reward was similar in both groups. Behavioral performance and electrophysiological measures did not worsen post-surgery.

CONCLUSIONS

Patients with mTLE-UHS showed impairments in decision-making under ambiguity, particularly when they had to make decisions based on the outcomes of their choices, but not in decision-making under risk. No group differences were observed in decision-making when feedbacks were random. These results might be explained by the abnormal feedback processing seen in the EEG activity of patients with mTLE-UHS, and by concomitant impairments in working memory, and memory. These impairments may be linked to the disruption of mesial temporal lobe networks. Finally, feedback processing and decision-making under ambiguity were already affected in mTLE-UHS patients pre-surgery and did not show evidence of clear worsening post-surgery.

fMRI to Predict Naming Decline: Can We Improve the Grade From a C to an A?

Prediction of Naming Outcome With fMRI Language Lateralization in Left Temporal Epilepsy Surgery

Gross WL, Helfand AI, Swanson SJ, Conant LL, Humphries CJ, Raghavan M, Mueller WM, Busch RM, Allen L, Anderson CT, Carlson CE, Lowe MJ, Langfitt JT, Tivarus ME, Drane DL, Loring DW, Jacobs M, Morgan VL, Allendorfer JB, Szaflarski JP, Bonilha L, Bookheimer S, Grabowski T, Vannest J, Binder JR; FMRI in Anterior Temporal Epilepsy Surgery (FATES) Study. Neurology. 2022;98(23):e2337-e2346. doi:10.1212/WNL.0000000000200552. PMID: 35410903; PMCID: PMC9202528.

Background and Objectives:

Naming decline after left temporal lobe epilepsy (TLE) surgery is common and difficult to predict. Preoperative language fMRI may predict naming decline, but this application is still lacking evidence. We performed a large multicenter cohort study of the effectiveness of fMRI in predicting naming deficits after left TLE surgery.

Methods:

At 10 US epilepsy centers, 81 patients with left TLE were prospectively recruited and given the Boston Naming Test (BNT) before and ≈7 months after anterior temporal lobectomy. An fMRI language laterality index (LI) was measured with an auditory semantic decision-tone decision task contrast. Correlations and a multiple regression model were built with a priori chosen predictors.

Results:

Naming decline occurred in 56% of patients and correlated with fMRI LI (r = −0.41, p < 0.001), age at epilepsy onset (r = −0.30, p = 0.006), age at surgery (r = −0.23, p = 0.039), and years of education (r = 0.24, p = 0.032). Preoperative BNT score and duration of epilepsy were not correlated with naming decline. The regression model explained 31% of the variance, with fMRI contributing 14%, with a 96% sensitivity, and 44% specificity for predicting meaningful naming decline. Cross-validation resulted in an average prediction error of 6 points.

Discussion:

An fMRI-based regression model predicted naming outcome after left TLE surgery in a large, prospective multicenter sample, with fMRI as the strongest predictor. These results provide evidence supporting the use of preoperative language fMRI to predict language outcome in patients undergoing left TLE surgery.

Genetic and molecular features of seizure-freedom following surgical resections for focal epilepsy: A pilot study

Objective

Seizure outcomes after brain surgery for drug-resistant epilepsy (DRE) are very heterogeneous and difficult to predict with models utilizing the current clinical, imaging, and electrophysiological variables. In this pilot study, we investigated whether genetic and molecular biomarkers (e.g., genomic, transcriptomic) can provide additional insight into differential response to surgery.

Methods

Post-operative seizure-outcomes were collected at last follow-up (>6 months) for 201 adult patients with DRE who underwent surgery between 2004 and 2020. Resected tissue was sent for miRNA sequencing (n = 132) and mRNA sequencing (n = 135). Following the selection of 10 genes (SCN1A, NBEA, PTEN, GABRA1, LGL1, DEPDC5, IL1A, ABCB1, C3, CALHM1), we investigated SNPs in those 10 genes from previously acquired exome sequencing data (n = 106). Logistic regression was performed to test for associations between individual features (mRNAs, miRNAs, and SNPs) and post-operative seizure-outcome with an exploratory FDR P < 0.25 as the threshold for significance. Post-operative time-to-seizure analyses were performed for each SNP using a Cox proportional hazards model.

Results

The majority of patients (83%) had temporal lobe epilepsy. Mean age at surgery was 38.3 years, and 56% were female. Three SNPs (rs10276036, rs11975994, rs1128503) in multi-drug resistance gene, ABCB1, were associated with post-operative seizure outcomes. Patients with alternate alleles in ABCB1 were more likely to be seizure-free at last follow-up (52–56% reduction in seizure recurrence; FDR P = 0.24). All three SNPs were in linkage disequilibrium and highly correlated with each other. Median post-operative time-to-seizure was 63 months for patients with 2 alternate alleles, 24–33 months with 1 alternate allele, and 10–11 months with 0 alternate alleles. These SNPs improved outcome prediction beyond MRI and sex alone. No independent miRNAs or mRNAs were significantly associated with seizure-outcome (P > 0.05). However, pathway analysis identified “cancer drug resistance by drug efflux” (mir-154 and mir-379) as enriched (P = 0.02), supporting the role of drug response genes in post-operative seizure recurrence.

Significance

ABCB1 may have a role in epileptogenesis and surgery outcomes independent of its drug efflux activity necessitating further investigation. SNPs in ABCB1 may serve as independent predictors of post-operative outcome.

The importance of basal-temporal white matter to pre- and post-surgical naming ability in temporal lobe epilepsy

OBJECTIVE

Emerging research highlights the importance of basal-temporal cortex, centered on the fusiform gyrus, to both pre-surgical naming ability and post-surgical naming outcomes in temporal lobe epilepsy (TLE). In this study, we investigate whether integrity of the white matter network that interconnects this basal region to the distributed language network affects naming ability and risk for post-surgical naming decline.

METHODS

Patients with drug-resistant TLE were recruited from two epilepsy centers in a prospective longitudinal study. The pre-surgical dataset included 50 healthy controls, 47 left TLE (L-TLE), and 41 right TLE (R-TLE) patients. All participants completed pre-surgical T1- and diffusion-weighted MRI (dMRI), as well as neuropsychological tests of auditory and visual naming. Nineteen L-TLE and 18 R-TLE patients underwent anterior temporal lobectomy (ATL) and also completed post-surgical neuropsychological testing. Pre-surgical fractional anisotropy (FA) of the white matter directly beneath the fusiform neocortex (i.e., superficial white matter; SWM) and of deep white matter tracts with connections to the basal-temporal cortex [inferior longitudinal fasciculus (ILF) and inferior frontal occipital fasciculus (IFOF)] was calculated. Clinical variables, hippocampal volume, and FA of each white matter tract or region were examined in linear regressions with naming scores, or change in naming scores, as the primary outcomes.

RESULTS

Pre-surgically, higher FA in the bilateral ILF, bilateral IFOF, and left fusiform SWM was associated with better visual and auditory naming scores (all ps < 0.05 with FDR correction). In L-TLE, higher pre-surgical FA was also associated with less naming decline post-surgically, but results varied across tracts. When including only patients with typical language dominance, only integrity of the right fusiform SWM was associated with less visual naming decline (p = .0018).

DISCUSSION

Although a broad network of white matter network matter may contribute to naming ability pre-surgically, the reserve capacity of the contralateral (right) fusiform SWM may be important for mitigating visual naming decline following ATL in L-TLE. This shows that the study of the structural network interconnecting the basal-temporal region to the wider language network has implications for understanding both pre- and post-surgical naming in TLE.

Cognitive outcomes following pediatric epilepsy surgery

OBJECTIVES

To characterize outcomes following pediatric epilepsy surgery across a broad range of cognitive domains using empirical methods (i.e., reliable change indices: RCIs), compare these outcomes with those based on traditional methods (i.e., standard deviation: SD), and identify factors associated with postoperative cognitive declines and/or improvements.

METHODS

This retrospective cohort study included 186 children who underwent surgical resection for treatment of pharmacoresistant epilepsy and who completed pre- and postoperative neuropsychological assessments. Postoperative testing occurred approximately 6.5 months after surgery and included measures of intelligence, attention/working memory, processing speed, language, executive functioning, visuospatial skills, memory, and academic achievement. Change scores for each patient were classified as decline, no change, or improvement using epilepsy-specific RCIs. Chi-square goodness of fit tests were used to compare the distribution of outcomes as classified with RCIs to those obtained using a traditional one SD cutoff. Multinomial regression analyses were conducted to identify factors associated with cognitive decline and/or improvement.

RESULTS

While 18% of children demonstrated no postoperative declines or improvements in any cognitive domain, the majority demonstrated relatively focal changes (declines and/or improvements in 1-2 cognitive domains). Rates of postoperative decline and improvement across individual cognitive domains were variable and ranged from 4-35% and 2-31%, respectively. Compared to RCIs, SD methodology often overestimated postoperative improvements and varied with respect to declines. Factors associated with RCI decline or improvement included preoperative performance, age at surgery, surgery site, and postoperative seizures.

SIGNIFICANCE

Results suggest substantial variability in individual cognitive outcomes approximately 6.5 months following pediatric epilepsy surgery. The differences in change distributions obtained using epilepsy-specific RCIs versus SDs highlight the need for studies using empiric methodology to study postoperative cognitive change. Variables associated with postoperative cognitive change may be used to develop multivariable prediction models in future studies to aid clinical decision-making and patient counseling.

Mapping of Language-and-Memory Networks in Patients With Temporal Lobe Epilepsy by Using the GE2REC Protocol

Preoperative mapping of language and declarative memory functions in temporal lobe epilepsy (TLE) patients is essential since they frequently encounter deterioration of these functions and show variable degrees of cerebral reorganization. Due to growing evidence on language and declarative memory interdependence at a neural and neuropsychological level, we propose the GE2REC protocol for interactive language-and-memory network (LMN) mapping. GE2REC consists of three inter-related tasks, sentence generation with implicit encoding (GE) and two recollection (2REC) memory tasks: recognition and recall. This protocol has previously been validated in healthy participants, and in this study, we showed that it also maps the LMN in the left TLE (N = 18). Compared to healthy controls (N = 19), left TLE (LTLE) showed widespread inter- and intra-hemispheric reorganization of the LMN through reduced activity of regions engaged in the integration and the coordination of this meta-network. We also illustrated how this protocol could be implemented in clinical practice individually by presenting two case studies of LTLE patients who underwent efficient surgery and became seizure-free but showed different cognitive outcomes. This protocol can be advantageous for clinical practice because it (a) is short and easy to perform; (b) allows brain mapping of essential cognitive functions, even at an individual level; (c) engages language-and-memory interaction allowing to evaluate the integrative processes within the LMN; (d) provides a more comprehensive assessment by including both verbal and visual modalities, as well as various language and memory processes. Based on the available postsurgical data, we presented preliminary results obtained with this protocol in LTLE patients that could potentially inform the clinical practice. This implies the necessity to further validate the potential of GE2REC for neurosurgical planning, along with two directions, guiding resection and describing LMN neuroplasticity at an individual level.

Uses and abuses of the neuropsychological assessment in the presurgical evaluation of epilepsy surgery candidates

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Results from the neuropsychological assessment must be integrated into the wider clinical picture for all epilepsy surgery candidates.

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Motivation for surgery must be fully explored to ensure informed consent, even in ‘ideal’ surgical candidates.

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Inappropriate weight should not be given to standalone neuropsychological scores in the surgical decision making process.

Recent guidelines from the International League Against Epilepsy (ILAE) delineating the role of the neuropsychologist in the assessment of epilepsy surgery patients stress the collaborative contribution neuropsychologists should make to seizure characterization, lateralization and localization in the pre-surgical setting. The role they should play in the comprehensive counselling of surgical candidates, including exploration of the patient’s expectations of surgical treatment is also mandated. In this paper we present two contrasting case studies which illustrate the importance of these roles and the impact they can have on patient outcomes. In Case A we describe the patient journey of a 69-year-old women with left hippocampal sclerosis and concordant neurophysiology and seizure semiology. We present the series of discussions and decisions which led her to reject the surgical option following a detailed exploration of her motivations for surgery and the likely cognitive consequences of the procedure. In Case B we describe the series of errors and omissions which led to the failure of a clinical team to correctly interpret and integrate neuropsychological findings into the larger clinical picture of a 19-year-old woman with a seven year history of seizures. These errors ultimately culminated in the patient undergoing a right temporal lobe resection to treat psychogenic nonepileptic seizures (PNES).

The extent of integration of the data from the clinical neuropsychological assessment in the full presurgical evaluation was critical in determining the outcomes in both of these cases. Surgery did not solve Case B’s problems and left her with the lifelong cognitive vulnerabilities that are associated with unilateral temporal lobe resection. In contrast, Case A was a good surgical candidate, but comprehensive integration of the neuropsychological findings into the larger clinical picture established that surgery was not the best solution to the problem she wished to solve.

Prediction of the clinical and naming status after anterior temporal lobe resection in patients with epilepsy

By assessing the cognitive capital, neuropsychological evaluation (NPE) plays a vital role in the perioperative workup of patients with refractory focal epilepsy. In this retrospective study, we used cutting-edge statistical approaches to examine a group of 47 patients with refractory temporal lobe epilepsy (TLE), who underwent standard anterior temporal lobectomy (ATL). Our objective was to determine whether NPE may represent a robust predictor of the postoperative status, two years after surgery. Specifically, based on pre- and postsurgical neuropsychological data, we estimated the sensitivity of cognitive indicators to predict and to disentangle phenotypes associated with more or less favorable outcomes. Engel (ENG) scores were used to assess clinical outcome, and picture naming (NAM) performance to estimate naming status. Two methods were applied: (a) machine learning (ML) to explore cognitive sensitivity to postoperative outcomes; and (b) graph theory (GT) to assess network properties reflecting favorable vs. less favorable phenotypes after surgery. Specific neuropsychological indices assessing language, memory, and executive functions can globally predict outcomes. Interestingly, preoperative cognitive networks associated with poor postsurgical outcome already exhibit an atypical, highly modular and less densely interconnected configuration. We provide statistical and clinical tools to anticipate the condition after surgery and achieve a more personalized clinical management. Our results also shed light on possible mechanisms put in place for cognitive adaptation after acute injury of central nervous system in relation with surgery.

Automated Identification of Surgical Candidates and Estimation of Postoperative Seizure Freedom in Children - A Focused Review

Surgery is an effective but underused treatment for drug-resistant epilepsy in children. Algorithms to identify surgical candidates and estimate the likelihood of postoperative clinical improvement may be valuable to improve access to epilepsy surgery. We provide a focused review of these approaches. For adults with epilepsy, tools to identify surgical candidates and predict seizure and cognitive outcomes (Ie, Cases for Epilepsy (toolsforepilepsy.com) and Epilepsy Surgery Grading Scale) have been validated and are in use. Analogous tools for children need development. A promising approach is to apply statistical learning tools to clinical datasets, such as electroencephalogram tracings, imaging studies, and the text of clinician notes. Demonstration projects suggest these techniques have the potential to be highly accurate, and await further validation and clinical application.

Healthcare professionals' knowledge, attitude, and perception of epilepsy surgery: A systematic review

OBJECTIVE

The epilepsy surgery treatment gap is well defined and secondary to a broad range of issues, including healthcare professionals' (HCPs') knowledge, attitude, and perception (KAP) toward epilepsy surgery. However, no previous systematic reviews investigated this important topic.

METHODS

The systematic review was conducted according to Preferred Reporting Items for the Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We identified a total of 652 articles from multiple databases using database-specific queries and included 65 articles for full-text review after screening the titles and abstracts of the articles. Finally, we selected 11 papers for qualitative analysis. We critically appraised the quality of the studies using the Joanna Briggs critical appraisal tool.

RESULTS

The qualitative analysis of the content identified several key reasons causing healthcare professional-related barriers to epilepsy surgery: inadequate knowledge and awareness about the role of epilepsy surgery in drug-resistant epilepsy (DRE), poor identification and referral of patients with DRE, insufficient selection of candidates for presurgical workup, negative or ambivalent attitudes and perceptions regarding epilepsy surgery, deficient communication practices with patients regarding risk-benefit analysis of epilepsy surgery, and challenging coordination issues with the surgical referral. Neurologists with formal instruction in epilepsy, surgical exposure during training, participation in high volume epilepsy practice, or prior experience in surgical referral may refer more patients for surgical evaluation.

CONCLUSIONS

While significant work has been conducted in a limited number of studies to explore HCPs' knowledge gap and educational need regarding epilepsy surgery, further research is needed in defining the learning goals, assessing and validating specific learning gaps among providers, defining the learning outcomes, optimizing the educational format, content, and outcome measures, and appraising the achieved results following the educational intervention.

GPER1 Modulates Synaptic Plasticity During the Development of Temporal Lobe Epilepsy in Rats

G-protein coupled estrogen receptor 1 (GPER1) is a novel type of estrogen receptor. Several studies have shown that it has an anti-inflammatory action,which plays an important role in remyelination and cognitive ability adjustment. However, whether it is involved in the development of temporal lobe epilepsy (TLE) is still unknown. The present study established a TLE model by intraperitoneal injection of lithium chloride (3 mmol/kg) and pilocarpine (50 mg/kg) in rats to study the effect of GPER1 in the synaptic plasticity during the development of temporal lobe epilepsy. A microinjection cannula was implanted into the lateral ventricle region of rats via a stereotaxic instrument. G-1 is the specific GPER1 agonist and G15 is the specific GPER1 antagonist. The G1 or G15 and Dimethyl sulfoxide were injected into the rat brains in the intervention groups and control group, respectively. After G1 intervention, the learning and memory abilities and hippocampal neuron damage in epileptic rats were significantly improved, while G15 weakened the neuroprotective effect of GPER1. Meanwhile, G1 controlled the abnormal formation of hippocampal mossy fiber sprouting caused by seizures, and participated in the regulation of synaptic plasticity by reducing the expression of Synapsin I and increasing the expression of gephyrin. Inhibitory synapse gephyrin may play a significant role in synaptic plasticity.

Experiences of emotional and psychosocial functioning after frontal lobe resection for epilepsy

PURPOSE

Frontal lobe resection (FLR) is the second most common epilepsy surgery procedure in adults. Few studies address neuropsychological consequences after FLR. The aim of this study was to explore patients' and relatives' experiences of cognitive, emotional and social cognitive functioning after frontal lobe epilepsy surgery.

METHODS

Semi-structured interviews were held with 14 patients having gone through FLR as adults during the years 2000-2016 and 12 of their relatives. Interviews were audio-recorded, transcribed and analyzed with inductive qualitative content analysis.

RESULTS

Positive as well as negative consequences were described both by patients and relatives. Feelings of relief and an increased capacity to experience emotions of well-being were mainly experienced as related to seizure freedom. A newfound autonomy and a more grown-up identity as opposed to a self-image based on epilepsy was also highlighted. However, results also showed that even for seizure free patients, FLR could give rise to negative experiences, the most prominent of which were mental fatigue, lowered mood and social withdrawal. Coping strategies included planning ahead to avoid mental exhaustion. Over all, respondents considered that the epilepsy surgery had been a risk well worth taking and that positive consequences outweighed the negative ones.

CONCLUSIONS

This study shows a range of positive as well as negative outcomes after FLR for epilepsy. The findings indicate that lowered mood and mental fatigue could affect the life situation in a negative way, regardless of seizure outcome. This is important to consider in the preoperative counselling of patients and their families, as well as in the postsurgical follow-up. It is also crucial that the epilepsy surgery team has the possibility to offer rehabilitation and support to families regarding these aspects after surgery.

Nomograms to Predict Verbal Memory Decline After Temporal Lobe Resection in Adults With Epilepsy

OBJECTIVE

To develop and externally validate models to predict the probability of postoperative verbal memory decline in adults after temporal lobe resection (TLR) for epilepsy using easily accessible preoperative clinical predictors.

METHODS

Multivariable models were developed to predict delayed verbal memory outcome on 3 commonly used measures: Rey Auditory Verbal Learning Test (RAVLT) and Logical Memory (LM) and Verbal Paired Associates (VPA) subtests from Wechsler Memory Scale-Third Edition. With the use of the Harrell step-down procedure for variable selection, models were developed in 359 adults who underwent TLR at the Cleveland Clinic and validated in 290 adults at 1 of 5 epilepsy surgery centers in the United States or Canada.

RESULTS

Twenty-nine percent of the development cohort and 26% of the validation cohort demonstrated significant decline on at least 1 verbal memory measure. Initial models had good to excellent predictive accuracy (calibration [c] statistic range 0.77-0.80) in identifying patients with memory decline; however, models slightly underestimated decline in the validation cohort. Model coefficients were updated with data from both cohorts to improve stability. The model for RAVLT included surgery side, baseline memory score, and hippocampal resection. The models for LM and VPA included surgery side, baseline score, and education. Updated model performance was good to excellent (RAVLT c = 0.81, LM c = 0.76, VPA c = 0.78). Model calibration was very good, indicating no systematic overestimation or underestimation of risk.

CONCLUSIONS

Nomograms are provided in 2 easy-to-use formats to assist clinicians in estimating the probability of verbal memory decline in adults considering TLR for treatment of epilepsy.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that multivariable prediction models accurately predict verbal memory decline after TLR for epilepsy in adults.

Does etiology really matter for epilepsy surgery outcome?

Multiple factors influence the outcomes of epilepsy surgery. Prognostic indicators varying from clinical characteristics, imaging findings, ictal, and interictal electrophysiological activity have been linked to surgical outcomes. In this review, we focus on the relatively under‐studied role of the underlying epilepsy histopathology in driving post‐surgical outcomes, specifically focusing on the broad categories of seizure outcomes and cognitive outcomes. For each of these two outcomes of interest, we answer two questions: 1)‐ does etiology matter? and 2)‐ how could it matter? The goal is to review the existing literature on the relationship between etiology and surgical outcomes to provide the best possible judgment as to whether a causal relationship exists between histopathology and the ultimate surgical outcome as an initial step. Then, we delve into the possible mechanisms via which such relationships can be explained. We conclude with a call to action to the epilepsy surgery and histopathology research community to push the mechanistic understanding of the pathology‐outcome interaction and identify actionable knowledge and biomarkers that could inform patient care in a timely fashion.

In this review, we focus on the relatively under‐studied role of the underlying epilepsy histopathology in driving post‐surgical outcomes, specifically focusing on the broad categories of seizure outcomes and cognitive outcomes. For each of these two outcomes of interest, we answer two questions: (1) does etiology matter? and (2) how could it matter? We then delve into the mechanisms of these answers.

Nomogram to Predict Cognitive Dysfunction After a Minor Ischemic Stroke in Hospitalized-Population

An easily scoring system to predict the risk of cognitive impairment after minor ischemic stroke has not been available. We aimed to develop and externally validate a nomogram for predicting the probability of post-stroke cognitive impairment (PSCI) among hospitalized population with minor stroke. Moreover, the association of Trimethylamine N-oxide (TMAO) with PSCI is also investigated. We prospectively conducted a developed cohort on collected data in stroke center from June 2017 to February 2018, as well as an external validation cohort between June 2018 and February 2019. The main outcome is cognitive impairment defined as <22 Montreal Cognition Assessment (MoCA) score points 6 – 12 months following a minor stroke onset. Based on multivariate logistic models, the nomogram model was generated. Plasma TMAO levels were assessed at admission using liquid chromatography tandem mass spectrometry. A total of 228 participants completed the follow-up data for generating the nomogram. After multivariate logistic regression, seven variables remained independent predictors of PSCI to compose the nomogram included age, female, Fazekas score, educational level, number of intracranial atherosclerotic stenosis (ICAS), HbA1c, and cortical infarction. The area under the receiver-operating characteristic (AUC-ROC) curve of model was 0.829, C index was good (0.810), and the AUC-ROC of the model applied in validation cohort was 0.812. Plasma TMAO levels were higher in patients with cognitive impairment than in them without cognitive dysfunction (median 4.56 vs. 3.22 μmol/L; p ≤ 0.001). In conclusion, this scoring system is the first nomogram developed and validated in a stroke center cohort for individualized prediction of cognitive impairment after minor stroke. Higher plasma TMAO level at admission suggests a potential marker of PSCI.

Underutilization of epilepsy surgery: Part II: Strategies to overcome barriers

Interventions focused on utilization of epilepsy surgery can be divided into groups: those that improve patients' access to surgical evaluation and those that facilitate completion of the surgical evaluation and treatment. Educational intervention, technological innovation, and effective coordination and communication can significantly improve patients' access to surgery. Patient and public facing, individualized (analog and/or digital) communication can raise awareness and acceptance of epilepsy surgery. Educational interventions aimed at providers may mitigate knowledge gaps using practical and concise consensus statements and guidelines, while specific training can improve awareness around implicit bias. Innovative technology, such as clinical decision-making toolkits within the electronic medical record (EMR), machine learning techniques, online decision-support tools, nomograms, and scoring algorithms can facilitate timely identification of appropriate candidates for epilepsy surgery with individualized guidance regarding referral appropriateness, postoperative seizure freedom rate, and risks of complication after surgery. There are specific strategies applicable for epilepsy centers' success: building a multidisciplinary setup, maintaining/tracking volume and complexity of cases, collaborating with other centers, improving surgical outcome with reduced complications, utilizing advanced diagnostics tools, and considering minimally invasive surgical techniques. Established centers may use other strategies, such as multi-stage procedures for multifocal epilepsy, advanced functional mapping with tailored surgery for epilepsy involving the eloquent cortex, and generation of fresh hypotheses in cases of surgical failure. Finally, improved access to epilepsy surgery can be accomplished with policy changes (e.g., anti-discrimination policy, exemption in transportation cost, telehealth reimbursement policy, patient-centered epilepsy care models, pay-per-performance models, affordability and access to insurance, and increased funding for research). Every intervention should receive regular evaluation and feedback-driven modification to ensure appropriate utilization of epilepsy surgery.

Stereoelectroencephalographic language mapping of the basal temporal cortex predicts postoperative naming outcome

OBJECTIVE

In drug-resistant temporal lobe epilepsy (TLE) patients, the authors evaluated early and late outcomes for decline in visual object naming after dominant temporal lobe resection (TLR) according to the resection status of the basal temporal language area (BTLA) identified by cortical stimulation during stereoelectroencephalography (SEEG).

METHODS

Twenty patients who underwent SEEG for drug-resistant TLE met the inclusion criteria. During language mapping, a site was considered positive when stimulation of two contiguous contacts elicited at least one naming impairment during two remote sessions. After TLR ipsilateral to their BTLA, patients were classified as BTLA+ when at least one positive language site was resected and as BTLA- when all positive language sites were preserved. Outcomes in naming and verbal fluency tests were assessed using pre- and postoperative (means of 7 and 25 months after surgery) scores at the group level and reliable change indices (RCIs) for clinically meaningful changes at the individual level.

RESULTS

BTLA+ patients (n = 7) had significantly worse naming scores than BTLA- patients (n = 13) within 1 year after surgery but not at the long-term evaluation. No difference in verbal fluency tests was observed. When RCIs were used, 5 of 18 patients (28%) had naming decline within 1 year postoperatively (corresponding to 57% of BTLA+ and 9% of BTLA- patients). A significant correlation was found between BTLA resection and naming decline.

CONCLUSIONS

BTLA resection is associated with a specific and early naming decline. Even if this decline is transient, naming scores in BTLA+ patients tend to remain lower compared to their baseline. SEEG mapping helps to predict postoperative language outcome after dominant TLR.

The cognitive costs, contraindications and complications of epilepsy surgery in adults

PURPOSE OF REVIEW

Access to epilepsy surgery is rapidly growing throughout the world. While it is an established and effective treatment for seizures, epilepsy surgery has the potential to exacerbate cognitive comorbidities of the condition.

RECENT FINDINGS

Not all surgical patients experience a postoperative decline in cognitive function. Postoperative cognitive function depends upon the functional integrity of the tissue to be removed and the functional reserve of the structures that remain in situ. While developments in surgical technique can reduce the cognitive morbidity of epilepsy surgery, the same procedure may result in different cognitive outcomes for different candidates, depending on their preoperative characteristics and postoperative trajectories. Multivariate models can be used to identify those most at risk of cognitive decline. There remains a significant lack of research into clinical interventions aimed at reducing the impact of surgically induced cognitive deficits on the lives of the patients who experience them.

SUMMARY

Accurate identification of the cognitive risks associated with surgery, based on an individual's personal risk profile rather than the generic risks associated with the procedure, is now recognized as a mandatory part of the preoperative evaluation and is one of the pillars of informed consent for the procedure.

Predicting mood decline following temporal lobe epilepsy surgery in adults

OBJECTIVE

To develop a model to predict the probability of mood decline in adults following temporal lobe resection for the treatment of pharmacoresistant epilepsy.

METHODS

Variable selection was performed on 492 patients from the Cleveland Clinic using best subsets regression. After completing variable selection, a subset of variables was requested from four epilepsy surgery centers across North America (n = 100). All data were combined to develop a final model to predict postoperative mood decline (N = 592). Internal validation with bootstrap resampling was performed. A clinically significant increase in depressive symptoms was defined as a 15% increase in Beck Depression Inventory-Second Edition score and a postoperative raw score > 11.

RESULTS

Fourteen percent of patients in the Cleveland Clinic cohort and 22% of patients in the external cohort experienced clinically significant increases in depressive symptoms following surgery. The final prediction model included six predictor variables: psychiatric history, resection side, relationship status, verbal fluency score, age at preoperative testing, and presence/absence of malformation of cortical development on magnetic resonance imaging. The model had an optimism-adjusted c-statistic of .70 and good calibration, with slight probability overestimation in higher risk patients.

SIGNIFICANCE

Clinicians can utilize our nomogram via a paper tool or online calculator to estimate the risk of postoperative mood decline for individual patients prior to temporal lobe epilepsy surgery.

Nomogram to Predict Poor Outcome after Mechanical Thrombectomy at Older Age and Histological Analysis of Thrombus Composition

An easy scoring system to predict the risk of poor outcome after mechanical thrombectomy among the elderly is currently not available. Therefore, we aimed to develop a nomogram for predicting the probability of negative prognosis in aged patients with acute ischemic stroke undergoing thrombectomy. In addition, we sought to investigate the association between histological thrombus composition and stroke characteristics. To this end, we prospectively studied a developed cohort using data collected from a stroke center from November 2015 to December 2019. The main outcome was functional independence, defined as a modified Rankin Scale score ≤ 2 at 90 days following a mechanical thrombectomy. A nomogram model based on multivariate logistic models was generated. The retrieved thrombi were stained with hematoxylin and eosin and assessed according to histological composition. Our results demonstrated that age ≥ 72 years was independently associated with poor outcome. A total of 304 participants completed the follow-up data to generate the nomogram model. After multivariate logistic regression, five variables remained independent predictors of outcome, including older age, hemorrhagic transformation, thrombolysis in cerebral infarction score, National Institute of Health Stroke score, and neutrophil-to-lymphocyte ratio, and were used to generate the nomogram. The area under the receiver-operating characteristic curve of the model was 0.803. The clots from elderly subjects with large-artery atherosclerosis, anterior circulation, and successful recanalization groups had a higher percentage of fibrin compared to those of younger patients. This is the first nomogram to be developed and validated in a stroke center cohort for individualized prediction of poor outcome in elderly patients after mechanical thrombectomy. Clot composition provides valuable information on the underlying pathogenesis of oxidation in older patients.

Connectome biomarkers of drug-resistant epilepsy

Drug-resistant epilepsy (DRE) considerably affects patient health, cognition, and well-being, and disproportionally contributes to the overall burden of epilepsy. The most common DRE syndromes are temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal epilepsy related to cortical malformations. Both syndromes have been traditionally considered as "focal," and most patients benefit from brain surgery for long-term seizure control. However, increasing evidence indicates that many DRE patients also present with widespread structural and functional network disruptions. These anomalies have been suggested to relate to cognitive impairment and prognosis, highlighting their importance for patient management. The advent of multimodal neuroimaging and formal methods to quantify complex systems has offered unprecedented ability to profile structural and functional brain networks in DRE patients. Here, we performed a systematic review on existing DRE network biomarker candidates and their contribution to three key application areas: (1) modeling of cognitive impairments, (2) localization of the surgical target, and (3) prediction of clinical and cognitive outcomes after surgery. Although network biomarkers hold promise for a range of clinical applications, translation of neuroimaging biomarkers to the patient's bedside has been challenged by a lack of clinical and prospective studies. We therefore close by highlighting conceptual and methodological strategies to improve the evaluation and accessibility of network biomarkers, and ultimately guide clinically actionable decisions.

Precision Medicine: Academic dreaming or clinical reality?

Precision medicine can be distilled into a concept of accounting for an individual's unique collection of clinical, physiologic, genetic, and sociodemographic characteristics to provide patient-level predictions of disease course and response to therapy. Abundant evidence now allows us to determine how an average person with epilepsy will respond to specific medical and surgical treatments. This is useful, but not readily applicable to an individual patient. This has brought into sharp focus the desire for a more individualized approach through which we counsel people based on individual characteristics, as opposed to population-level data. We are now accruing data at unprecedented rates, allowing us to convert this ideal into reality. In addition, we have access to growing volumes of administrative and electronic health records data, biometric, imaging, genetics data, microbiome, and other "omics" data, thus paving the way toward phenome-wide association studies and "the epidemiology of one." Despite this, there are many challenges ahead. The collating, integrating, and storing sensitive multimodal data for advanced analytics remains difficult as patient consent and data security issues increase in complexity. Agreement on many aspects of epilepsy remains imperfect, rendering models sensitive to misclassification due to a lack of "ground truth." Even with existing data, advanced analytics models are prone to overfitting and often failure to generalize externally. Finally, uptake by clinicians is often hindered by opaque, "black box" algorithms. Systematic approaches to data collection and model generation, and an emphasis on education to promote uptake and knowledge translation, are required to propel epilepsy-based precision medicine from the realm of the theoretical into routine clinical practice.

Contributions of electrophysiology for identifying cortical language systems in patients with epilepsy

A crucial element of the surgical treatment of medically refractory epilepsy is to delineate cortical areas that must be spared in order to avoid clinically relevant neurological and neuropsychological deficits postoperatively. For each patient, this typically necessitates determining the language lateralization between hemispheres and language localization within hemisphere. Understanding cortical language systems is complicated by two primary challenges: the extent of the neural tissue involved and the substantial variability across individuals, especially in pathological populations. We review the contributions made through the study of electrophysiological activity to address these challenges. These contributions are based on the techniques of magnetoencephalography (MEG), intracerebral recordings, electrical-cortical stimulation (ECS), and the electrovideo analyses of seizures and their semiology. We highlight why no single modality alone is adequate to identify cortical language systems and suggest avenues for improving current practice.

Outcomes of resections that spare vs remove an MRI-normal hippocampus

OBJECTIVE

To characterize seizure and cognitive outcomes of sparing vs removing an magnetic resonance imaging (MRI)-normal hippocampus in patients with temporal lobe epilepsy.

METHODS

In this retrospective cohort study, we reviewed clinical, imaging, surgical, and histopathological data on 152 individuals with temporal lobe epilepsy and nonlesional hippocampi categorized into hippocampus-spared (n = 74) or hippocampus-resected (n = 78). Extra-hippocampal lesions were allowed. Pre- and postoperative cognitive data were available on 86 patients. Predictors of seizure and cognitive outcomes were identified using Cox-proportional hazard modeling followed by treatment-specific model reduction according to Akaike information criterion, and built into an online risk calculator.

RESULTS

Seizures recurred in 40% within one postoperative year, and in 63% within six postoperative years. Male gender (P = .03), longer epilepsy duration (P < .01), normal MRI (P = .04), invasive evaluation (P = .02), and acute postoperative seizures (P < .01) were associated with a higher risk of recurrence. We found no significant difference in postoperative seizure freedom rates at 5 years between those whose hippocampus was spared and those whose hippocampus was resected (P = .17). Seizure outcome models built with pre- and postoperative data had bootstrap validated concordance indices of 0.65 and 0.72. The dominant hippocampus-spared group had lower rates of decline in verbal memory (39% vs 70%; P = .03) and naming (41% vs 79%; P = .01) compared to the hippocampus-resected group. Partial hippocampus sparing had the same risk of verbal memory decline as for complete removal.

SIGNIFICANCE

Sparing or removing an MRI-normal hippocampus yielded similar long-term seizure outcome. A more conservative approach, sparing the hippocampus, only partially shields patients from postoperative cognitive deficits. Risk calculators are provided to facilitate clinical counseling.

Concurrent EEG monitoring helps interpret neuropsychological testing results in patients with epilepsy

OBJECTIVE

We sought to determine if global cognitive function in patients with epilepsy (PWE) differs when electroencephalographic (EEG) abnormalities are present during concurrent neuropsychological (NP) evaluation.

METHODS

We explored the association between subclinical epileptiform discharges (sEDs) and interictal epileptiform discharges (IEDs) and global aspects of cognition in 79 consecutive PWE who underwent continuous EEG monitoring during NP evaluation for diagnostic (15%) or presurgical (85%) purposes while on their standard antiseizure medication (ASM) regimens. As some researchers have suggested that the apparent link between IEDs and cognition represent epiphenomena of an underlying damaged neural substrate, we used functional status as a stratifying covariate to allow us to address this position.

RESULTS

Despite being on their standard ASM regimen, EEG was abnormal in 68% of patients. Epileptiform abnormalities (IEDs, sEDs, or both) were seen in isolation or coupled with diffuse or focal slowing in 38% of patients. Individuals with IEDs occurring during their NP evaluation demonstrated poorer scores in attention/working memory (forward and backward digit span), processing speed (symbol searching and coding), and speeded components of language (semantic fluency) tests compared with those with normal EEG tracings matched by their real-world, functional status. In two high functioning patients, performance was significantly better when these individuals were tested in the absence of IEDs, with performances appearing invalid when tested during periods of IED activity. No significant association was found between NP performance and nonepileptiform EEG abnormalities.

SIGNIFICANCE

A substantial proportion of PWE undergoing NP evaluation manifest concurrent EEG abnormalities, with epileptiform abnormalities associated with poorer global cognitive performance. As this pattern was observed regardless of functional status, this association appears to represent more than unrelated features coincidentally shared by the lowest functioning cohort. Coupled with our individual case data, our findings suggest that NP testing may be adversely affected by IEDs and sEDs going unrecognized in the absence of simultaneous EEG recordings, and set the stage for future studies to definitively establish this possible relationship.

Algorithms in clinical epilepsy practice: Can they really help us predict epilepsy outcomes?

Significant technological advances have improved our ability to localize epilepsy and investigate the electrophysiology in patients undergoing preparation for epilepsy surgery. Conversely, our process of decision-making and outcome prediction has remained essentially restricted to subjective clinical judgment. This may have hindered our ability to improve outcomes. In this review, we highlight the cognitive biases that interfere with medical decision-making and present data on the use of algorithms and statistical models in general health care, before pivoting to discuss applications in the context of epilepsy.

Cognitive and behavioral outcome of stereotactic laser amydalohippocampotomy in a pediatric setting

We present neuropsychological and functional outcome data in a teenager undergoing stereotactic laser amygdalohippocampotomy (SLAH) who had drug-resistant mesial temporal lobe epilepsy due to left hippocampal sclerosis. Given strong baseline cognitive performance, there was concern for post-operative declines in language and verbal memory were this patient to undergo open resection. She was evaluated pre- and post-ablation with clinical and experimental neuropsychological measures including semantic memory, category-specific object/face recognition and naming, spatial learning, and socio-emotional processing. The patient became seizure-free following SLAH and experienced significant improvements in school performance and social engagement. She experienced improvement in recognition and naming of multiple object categories, memory functions, and verbal fluency. In contrast, the patient declined significantly in her ability to recognize emotional tone from facial expressions, a socio-emotional process that had been normal prior to surgery. We believe this decline was related to surgical disruption of the limbic system, an area highly involved in emotional processing, and suspect such deficits are an under-assessed and unrecognized risk for all surgeries involving the amygdalohippocampal complex and broader limbic system regions. We hope this positive SLAH outcome will serve as impetus for group level research to establish its safety and efficacy in the pediatric setting.

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Stereotactic laser ablation can be used successfully in pediatric epilepsy.

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At risk cognitive abilities did not decline after focal ablation in this teenager.

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Functional improvement was observed that paralleled gains in seizure status and cognition.

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Deficits still occurred in select areas related to focal structures ablated.

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Socio-emotional deficits can result from surgeries restricted to the amygdalohippocampal complex.

Cognitive rehabilitation and prehabilitation in people with epilepsy

Epilepsy is now recognized as a network disorder of the brain that can impact cognition beyond the periictal disturbance associated with seizures. While there is a large literature on the assessment of cognitive functions, particularly memory, in people with epilepsy, there are far fewer studies looking at the efficacy of treatments for cognitive dysfunction in this population. Reviews of the cognitive rehabilitation literature in epilepsy have begun to outnumber original studies. This paper examines the possible reasons for this unsatisfactory ratio in the literature and examines the unique challenges and opportunities for cognitive rehabilitation in this population, with a particular focus on epilepsy surgical candidates. The concept of prehabilitation in this population is described. While traditional cognitive rehabilitation is implemented after a patient has developed a neuropsychological deficit, in surgical candidates, prehabilitation uses intact functions before they are lost to establish compensatory strategies and routines prior to surgery in preparation for postoperative changes. The likely postoperative neuropsychological profile for individual patients can now be modeled using preoperative data. These predictions can guide and inform the prehabilitation process. Rather than concluding with a generic call for more research, the paper presents a framework for a rehabilitation program with practical solutions to address cognitive difficulties in both surgical and nonsurgical populations of people with epilepsy.

Changes in description naming for common and proper nouns after left anterior temporal lobectomy

Numerous studies have shown that surgical resection of the left anterior temporal lobe (ATL) is associated with a decline in object naming ability (Hermann et al., 1999). In contrast, few studies have examined the effects of left ATL surgery on auditory description naming (ADN) or category-specific naming. Compared with object naming, which loads heavily on visual recognition processes, ADN provides a more specific measure of concept retrieval. The present study examined ADN declines in a large group of patients who were tested before and after left ATL surgery, using a 2 × 2 × 2 factorial manipulation of uniqueness (common vs. proper nouns), taxonomic category (living vs. nonliving things), and time (pre- vs. postsurgery). Significant declines occurred across all categories but were substantially larger for proper living (PL) concepts, i.e., famous individuals. The disproportionate decline in PL noun naming relative to other conditions is consistent with the notion that the left ATL is specialized not only for retrieval of unique entity concepts, but also plays a role in processing social concepts and person-specific features.

The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy

OBJECTIVE

The distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.

METHODS

T1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.

RESULTS

The SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance.

CONCLUSION

The SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance.

Naming decline after epilepsy surgery is associated with subjective language complaints

OBJECTIVE

This retrospective, observational study investigated the relationship between objective naming decline and patient report of subjective decline in language functioning following epilepsy surgery. The role of depression in this relationship was also examined.

METHODS

A total of 429 adults with pharmacoresistant epilepsy completed the Boston Naming Test (BNT) and Memory Assessment Clinics Self-Rating Scale (MAC-S) before and after resective surgery. Multiple regression analyses were used to examine the relationship between objective naming decline and subjective language functioning, while controlling for the confounding effect of depression.

RESULTS

Individuals who experienced moderate to severe naming decline (≥11 raw points on BNT) following surgery reported a decline in subjective language functioning (p < .001) and endorsed problems with word-retrieval as well as more general semantic abilities. Those who experienced mild naming decline (5-10 raw points) also reported an increase in subjective language problems (p = .006). Complaints in this group were less severe than in those with more marked naming declines and were primarily related to word-retrieval. Both of these relationships remained significant after controlling for the confounding effect of depression (p < .005-.014).

CONCLUSIONS

Individuals with epilepsy who experience naming decline following surgery perceive these declines in their daily life, regardless of whether or not they are depressed. Findings support the utilization of risk models to predict naming outcome and the importance of counseling patients regarding the risk for naming decline following surgery.