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  • Lateralization of Temporal Lobe Epilepsy by Imaging-Based Response-Driven Multinomial Multivariate Models

    Final Number:
    116

    Authors:
    Jason M. Schwalb MD , FACS; Mohammad-Reza Nazem-Zadeh PhD; Hassan Bagher-Ebadian; Fariborz Mahmoudi; Hamid Soltanian-Zadeh

    Study Design:
    Other

    Subject Category:
    Epilepsy

    Meeting: 2014 ASSFN Biennial Meeting

    Introduction:

    Multiple modalities are used in determining laterality in temporal lobe epilepsy. It is unclear how much different imaging modalities should be weighted in decision-making.

    Methods:

    Volumetrics, mean and standard deviation of FLAIR intensity, and mean of normalized ictal–interictal SPECT intensity on left and right hippocampi were extracted from preoperative images of forty-five retrospective TLE patients with surgical outcome of Engel class I. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated.

    Results:

    Among univariate response models, for the response model with mean SPECT attributes the lowest fit deviance of 65.1±0.1. A false alarm probability of 0 and 0.04 for the left and right epileptogenic sides were achieved respectively. However, the response model with mean FLAIR attributes resulted in highest probability of detection 0.93 and 0.94 for left and right epileptogenic sides, respectively. The multivariate response model with incorporating all attributes of volumetrics, mean and standard deviation FLAIR, and mean SPECT intensity, reached to a significantly lower fit deviance than for other response models (12.3±0.1, p < 0.001). It reached probability of detection of 1 with no false alarms. We were able to correctly lateralize the fifteen TLE patients who had undergone phase II intracranial monitoring. Therefore, phase II intracranial monitoring might have been avoided for this set of patients. Based on this lateralization response model, the side of epileptogenicity was also detected for all thirty patients who had proceeded to resection with only phase I of EEG monitoring

    Conclusions:

    The proposed multinomial multivariate response-driven model for lateralization of epileptogenicity in TLE patients can help in decision-making prior the surgical resection and may reduce the need for implantation of intracranial monitoring electrodes.

    Patient Care:

    By potentially reducing the need for Phase II monitoring and the associated complications

    Learning Objectives:

    By the conclusion of this section participants should be able to 1) Understand response-driven models and how they can help in lateralizing temporal lobe epilepsy (TLE) patients 2) Identify which imaging characteristics are most associated with Engel 1 outcomes

    References:

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