Strategic Candidate Selection For Invasive Monitoring In Temporal Lobe Epilepsy : Analysing Predictors of Surgical Outcome
Manisha Karamala Yalapalli1, Jayakumari Nandana1, RAMSHEKHAR MENON1, George Vilanilam2, Bejoy Thomas3, Chandrasekharan Kesavadas3, Ashalatha Radhakrishnan1
1Neurology, 2Neurosurgery, 3Department of imaging sciences and interventional radiology, R Madhavan Nayar Center for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute for Medical Sciences & Technology
Objective:
We aimed to evaluate the effectiveness of invasive EEG monitoring in identifying the epileptogenic zone in TLE and to identify predictors of surgical outcomes for patients undergoing resective surgery.
Background:
Temporal lobe epilepsy(TLE) accounts for 30% of drug-resistant epilepsy(DRE) cases, with around 25% of DRE patients requiring invasive monitoring to identify the epileptogenic zone when non-invasive data fail to recognise it.
Design/Methods:
We conducted a detailed analysis of prospectively collected data from our archive of patients who underwent invasive monitoring followed by surgical intervention for refractory TLE between 2003 and 2022. Electroclinical and imaging data, surgical approaches, and postoperative outcomes were reviewed. Yield of invasive monitoring was ascertained,univariate and multivariate regression analyses were used to determine predictors of surgical outcome
Results:
Out of 2100 patients with refractory TLE who underwent presurgical evaluation, 58 underwent invasive EEG monitoring (depth electrodes, subdural grid, or both). This included bitemporal epileptogenesis(34.4%), discordant data(24.1%), temporal plus(17.3%), nonlesional epilepsy (10.3%), dual pathology(6.8%), and overlapping causes(5.17%). A definite hypothesis was reached in 35 patients(61.1%) who underwent resective surgery with 26( 74.2% )achieving favorable outcomes(Engel Class1 and 2). Poor outcome predictors included nonlesional epilepsy(p=0.02), temporal plus(p=0.04), posterior cortex networks (p=0.004), irritative zones with fast ripples(p=0.012), and high frequency oscillations (p=0.048). Good outcomes were associated with bitemporal epileptogenesis (p<0.001), lesional low-grade epilepsy-associated tumors(LEATs)(p=0.004), ictal patterns of low voltage fast activity(p=0.018), and mesial networks compared to lateral networks (p<0.001).
Conclusions:
Invasive monitoring is crucial for accurately localizing the epileptogenic zone in 5% of refractory TLE patients with high yield(61%). Key predictors of favorable surgical outcomes include bitemporal epileptogenesis, lesional(LEATs) and specific ictal patterns, while nonlesional epilepsy, temporal plus, and involvement of posterior cortex networks are associated with poor outcomes. Future research should focus on predictive models to enhance the effectiveness of invasive monitoring in achieving optimal surgical results.
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