Elsevier

Epilepsy & Behavior

Volume 112, November 2020, 107436
Epilepsy & Behavior

Prefrontal seizure classification based on stereo-EEG quantification and automatic clustering

https://doi.org/10.1016/j.yebeh.2020.107436Get rights and content

Highlights

  • We identified categories of prefrontal seizures based on seizure onset quantification and clinical ictal manifestations

  • Four subgroups were: "pure dorsolateral", "pure ventro-median" group, "pure orbito-frontal" and "global prefrontal"

  • The most common signs were altered consciousness, automatisms, gestural motor behavior and hyperkinetic behaviour

  • No significant difference was observed in the distribution of ictal signs between the different groups

Abstract

Purpose

Frontal seizures are organized according to anatomo-functional subdivisions of the frontal lobe. Prefrontal seizures have been the subject of few detailed studies to date. The objective of this study was to identify subcategories of prefrontal seizures based on seizure onset quantification and to look for semiological differences.

Methods

Consecutive patients who underwent stereoelectroencephalography (SEEG) for drug-resistant prefrontal epilepsy between 2000 and 2018 were included. The different prefrontal regions investigated in our patients were dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), dorsomedial prefrontal cortex (DMPFC), ventromedial prefrontal cortex (VMPFC), and orbitofrontal cortex (OFC). The seizure onset zone (SOZ) was determined from one or two seizures in each patient, using the epileptogenicity index (EI) method. The presence or absence of 16 clinical ictal manifestations was analyzed. Classification of prefrontal networks was performed using the k-means automatic classification method.

Results

A total of 51 seizures from 31 patients were analyzed. The optimal clustering was 4 subgroups of prefrontal seizures: a “pure DLPF” group, a “pure VMPF” group, a “pure OFC” group, and a “global prefrontal” group. The first 3 groups showed a mean EI considered epileptogenic (> 0.4) only in one predominant structure, while the fourth group showed a high mean EI in almost all prefrontal structures. The median number of epileptogenic structures per seizure (prefrontal or extrafrontal) was 5 for the “global prefrontal” group and 2 for the other groups. We found that the most common signs were altered consciousness, automatisms/stereotypies, integrated gestural motor behavior, and hyperkinetic motor behavior. We found no significant difference in the distribution of ictal signs between the different groups.

Conclusion

Our study showed that although most prefrontal seizures manifest as a network of several anatomically distinct structures, we were able to determine a sublobar organization of prefrontal seizure onset with four groups.

Introduction

Frontal lobe seizures represent the second most frequent group of epilepsies in surgical series [1,2]. However, they do not represent a homogeneous group of anatomically well-defined entities [[3], [4], [5]]. Seizures arising from the motor and premotor cortices have been earlier and better delineated compared with prefrontal seizures, both in terms of clinical expression and cortical substrate, since the beginning of the 19th century up until recent years [[6], [7], [8]]. Conversely, descriptions and investigations of prefrontal lobe seizures were elaborated later, particularly after the introduction of intracranial investigations [[9], [10], [11], [12], [13], [14]]. Nonetheless it is commonly accepted that prefrontal seizures are more difficult to characterize in terms of organization of the epileptogenic networks within the prefrontal cortices [4,5,15,16], and such a difficulty to define distinct electroclinical patterns is related to intrinsic characteristics of the lobe.

Indeed, the prefrontal cortex represents a large part of total cortical volume in humans (about 30%) [17] and is subdivided into different cytoarchitectural and functional subregions [18], with complex and multidirectional patterns of connections, both intrinsic and extralobar [19]. The exact boundaries of the different prefrontal areas are not easy to delineate, and this subject is still a matter of debate. However, a rostrocaudal organization together with an orbitomedial and lateral gradient of functional organization have been evidenced, and dorsolateral, dorsomedial, ventrolateral, ventromedial, and orbital prefrontal cortex are common functional divisions [18,20].

The prefrontal cortex with all its subdivisions is involved in various higher cognitive processes and more generally in the control of behavior, either motor or not, including executive functions [21], visual working memory [22], regulation of emotion [23], social cognition [24], or decision-making [25]. It is also a critical part of the frontoparietal system essential for consciousness processing [26].

The large and partially buried volume of the prefrontal cortex, its complex multidirectional, intra- and interlobar connectivity, and the different functions in which it is involved can explain the complexity of the clinical expression of prefrontal seizures [5]. Indeed, the variability in terms of clinical expression from one patient to another makes classification challenging.

In a previous study, electroclinical patterns in the whole frontal lobe and its subregions were identified, in which an aspect of the methodology involved evaluation of “the early spread network” rather than the seizure onset zone (SOZ) only, encompassing motor, premotor, and prefrontal areas [5]. This study showed a rostrocaudal semiological gradient within the frontal lobes. However, a precise sublobar organization of prefrontal seizures using quantified analysis of electrical activity at seizure onset has not been clearly established, and a comprehensive analysis of prefrontal epileptogenic zone (EZ) networks is lacking.

The goal of this study was to determine whether subcategories of prefrontal seizures as determined by stereoelectroencephalography (SEEG) could be identified, in a consecutive series of patients, using a quantification of the EZ by the estimation of the “epileptogenicity index” (EI) [27]. A second objective was to describe the clinical features of each subcategory.

Section snippets

Patient selection and SEEG recording

Patients undergoing presurgical evaluation for drug-resistant epilepsy were selected from a series of 400 patients in whom intracerebral recordings had been performed between 2000 and 2018 (Timone Hospital, Marseille, France). Selection was based on the results of SEEG recordings showing a clear definition of the SOZ within the prefrontal cortex (Table 1).

The institutional review board of the Assitance Publique Hopitaux de Marseille approved this study.

Prior to selection for SEEG, all patients

General characteristics

Thirty-three patients (18 males and 13 females) were selected on the basis of prominent involvement of prefrontal cortex at seizure onset. Two patients were excluded (one because the electrophysiological pattern was too slow to allow calculation of EI; the other because seizures were too brief to be computed using EI, being characterized by very short-lasting spasms). Thus, 31 consecutive patients were finally included in our study, and we analyzed a total of 51 seizures (1 or 2 seizures per

Discussion

The main aim of this study was to estimate the involvement of the different sampled regions within prefrontal cortex in the generation of ictal discharge, in order to establish if a sublobar organization of prefrontal seizures could be demonstrated. By using the EI method, we quantified 51 prefrontal seizures recorded by SEEG, to assess the degree of epileptogenicity of each subregion of the prefrontal cortex. We decided to subdivide the prefrontal cortex into different subregions according to

Declaration of competing interest

The authors have no conflict of interest to declare.

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