Prognostic value of the second ictal intracranial pattern for the outcome of epilepsy surgery

Jiménez‐Jiménez, Diego; Martín-López, David; Masood, Mojtaba A.; Selway, Richard; Valentı́n, Antonio; Alarcón, Gonzalo

doi:10.1016/j.clinph.2015.07.001

Cited by 6 publications

(4 citation statements)

References 30 publications

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“…Currently, to our knowledge, neither our model, nor any other model has provided a mechanistic insight regarding this pattern. Particularly, as it may not only be a seizure onset pattern, but can occur in the middle of a seizure [34]. The spatial scale of this pattern is also generally diffuse, often involving most of the recording electrodes [18], making it a difficult event to study for our model.…”

Section: Modelling Of Onset Patternsmentioning

confidence: 99%

Mechanisms underlying different onset patterns of focal seizures

et al. 2017

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Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types—low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the “healthy” surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome.

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Section: Modelling Of Onset Patternsmentioning

confidence: 99%

Mechanisms underlying different onset patterns of focal seizures

et al. 2017

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“…The patterns differ in frequency, amplitude, and waveform of the oscillations and in their temporal evolution. Several studies attempted to classify these patterns in an effort to distinguish between local onset and propagated seizures and to link the early patterns with different pathologies or with the outcome of a resective surgery [3][4][5][6][7][8][9][10].…”

Section: Intracranial Eeg and Early Electrographic Patternsmentioning

confidence: 99%

Evidence for spreading seizure as a cause of theta-alpha activity electrographic pattern in stereo-EEG seizure recordings

et al. 2021

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Intracranial electroencephalography is a standard tool in clinical evaluation of patients with focal epilepsy. Various early electrographic seizure patterns differing in frequency, amplitude, and waveform of the oscillations are observed. The pattern most common in the areas of seizure propagation is the so-called theta-alpha activity (TAA), whose defining features are oscillations in the θ − α range and gradually increasing amplitude. A deeper understanding of the mechanism underlying the generation of the TAA pattern is however lacking. In this work we evaluate the hypothesis that the TAA patterns are caused by seizures spreading across the cortex. To do so, we perform simulations of seizure dynamics on detailed patient-derived cortical surfaces using the spreading seizure model as well as reference models with one or two homogeneous sources. We then detect the occurrences of the TAA patterns both in the simulated stereo-electroencephalographic signals and in the signals of recorded epileptic seizures from a cohort of fifty patients, and we compare the features of the groups of detected TAA patterns to assess the plausibility of the different models. Our results show that spreading seizure hypothesis is qualitatively consistent with the evidence available in the seizure recordings, and it can explain the features of the detected TAA groups best among the examined models.

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“…Two epileptologists independently reviewed the SEEG data and the discrepancies were solved after discussion with a professional neuroelectrophysiologist. If the rhythmic discharge lasts for longer than 1.5 s, the sustained pattern is identified [5]. The seizure onset was defined as the earliest sustained rhythmic activity of SEEG discharge and subsequent appearance of the seizure symptom [7].…”

Section: Signal Analysismentioning

confidence: 99%

Multiple ictal onset patterns underlie seizure generation in seizure-free patients with temporal lobe epilepsy surgery: an SEEG study

Zhang

Yan

et al. 2021

Acta Neurochir

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Purpose Seizure originates from different pathological substrate; however, the same pathologies may have distinct mechanisms underlying seizure generation. We aimed to improve the understanding of such mechanisms in patients with temporal lobe epilepsy (TLE) by investigating the stereoelectroencephalography (SEEG) ictal onset patterns (IOPs). Methods We analyzed data from a cohort of 19 consecutive patients explored by SEEG and had 1–3-year seizure-freedom following temporal lobe resection. Results Six IOPs were identified. They were low voltage fast activity (LVFA) (36.5%), rhythmic spikes or spike-waves at low frequency and with high amplitude (34.1%), runs of spikes (10.6%), rhythmic sharp waves (8.2%), low frequency high amplitude repetitive spiking (LFRS) (7.1%), and delta activity (3.5%). All six patterns were found in patients with mesial temporal onset and only two patterns were found in patients with temporal neocortical onset. The most prevalent patterns for patients with mesial temporal onset were rhythmic spikes or spike-waves, followed by LVFA with a mean discharge rate 74 Hz. For patients with temporal neocortical onset, the most prevalent IOP pattern was LVFA with a mean discharge rate 35 Hz, followed by runs of spikes. Compared with Lateral TLE (LTLE), the duration between the onset of the IOPs to the onset of the symptom was longer for patients with MTLE (Mesial TLE) (MTLE:55.7 ± 50.6 s vs LTLE:19.5 ± 16.4 s). Conclusion Multiple IOPs underlie seizure generation in patients with TLE. However, the mesial and lateral temporal lobes share distinct IOPs.

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Prognostic value of the second ictal intracranial pattern for the outcome of epilepsy surgery

Cited by 6 publications

References 30 publications

Mechanisms underlying different onset patterns of focal seizures

Mechanisms underlying different onset patterns of focal seizures

Evidence for spreading seizure as a cause of theta-alpha activity electrographic pattern in stereo-EEG seizure recordings

Multiple ictal onset patterns underlie seizure generation in seizure-free patients with temporal lobe epilepsy surgery: an SEEG study

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