Self-rated executive dysfunction in adults with epilepsy and effects of a cognitive-behavioral intervention (HOBSCOTCH)

Moncrief, Grant G.; Aita, Stephen L.; Tyson, Brad; Abecassis, Maurissa; Roth, Robert M.; Caller, Tracie A.; Schmidt, Samantha; Jobst, Barbara C.

doi:10.1016/j.yebeh.2021.108042

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…To date, automated approaches have not been successful in the classification of RSN, noise, and SOZ, in rs-fMRI for pediatric patients with DRE due to the following challenges: (1) Lack of normalized pathological rs-fMRI RSN data for children (Zhang et al, 2019 ); (2) databases with balanced instances of RSN, SOZ, and noise, large enough for DL techniques to effectively recognize the three IC categories that are not available; (3) the potentially inadequate performance of SOZ identification in children with DRE can indicate a high risk of developmental disorders post-surgery. Given that each patient only has 5% ICs as SOZ, a 40% sensitivity (Hunyadi et al, 2014 ) indicates that only two out of five SOZ ICs are correctly identified but 14 of them are wrongly identified as SOZ; and (4) fMRI-based pre-surgical mapping is more complicated for children with DRE due to developmental changes during cognitive maturation (Jiang et al, 2018 ; Bouyssi-Kobar et al, 2019 ), the impairment experienced due to DRE, and the normal representation of memory function during development (Michels et al, 2012 ; Darki and Klingberg, 2015 ; Cui et al, 2018 ; Kasradze et al, 2021 ), which may differ from adults (Faghiri et al, 2017 ; Lee et al, 2019 ; DeGeorge et al, 2021 ; Moncrief et al, 2021 ). Hence, the efficacy of fMRI classification techniques on adults needs to be reexamined for children with DRE.…”

Section: Introductionmentioning

confidence: 99%

Automated seizure onset zone locator from resting-state functional MRI in drug-resistant epilepsy

Banerjee

Kamboj²,

Wyckoff³

et al. 2023

Front. Neuroimaging

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ObjectiveAccurate localization of a seizure onset zone (SOZ) from independent components (IC) of resting-state functional magnetic resonance imaging (rs-fMRI) improves surgical outcomes in children with drug-resistant epilepsy (DRE). Automated IC sorting has limited success in identifying SOZ localizing ICs in adult normal rs-fMRI or uncategorized epilepsy. Children face unique challenges due to the developing brain and its associated surgical risks. This study proposes a novel SOZ localization algorithm (EPIK) for children with DRE.MethodsEPIK is developed in a phased approach, where fMRI noise-related biomarkers are used through high-fidelity image processing techniques to eliminate noise ICs. Then, the SOZ markers are used through a maximum likelihood-based classifier to determine SOZ localizing ICs. The performance of EPIK was evaluated on a unique pediatric DRE dataset (n = 52). A total of 24 children underwent surgical resection or ablation of an rs-fMRI identified SOZ, concurrently evaluated with an EEG and anatomical MRI. Two state-of-art techniques were used for comparison: (a) least squares support-vector machine and (b) convolutional neural networks. The performance was benchmarked against expert IC sorting and Engel outcomes for surgical SOZ resection or ablation. The analysis was stratified across age and sex.ResultsEPIK outperformed state-of-art techniques for SOZ localizing IC identification with a mean accuracy of 84.7% (4% higher), a precision of 74.1% (22% higher), a specificity of 81.9% (3.2% higher), and a sensitivity of 88.6% (16.5% higher). EPIK showed consistent performance across age and sex with the best performance in those < 5 years of age. It helped achieve a ~5-fold reduction in the number of ICs to be potentially analyzed during pre-surgical screening.SignificanceAutomated SOZ localization from rs-fMRI, validated against surgical outcomes, indicates the potential for clinical feasibility. It eliminates the need for expert sorting, outperforms prior automated methods, and is consistent across age and sex.

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Section: Introductionmentioning

confidence: 99%

Automated seizure onset zone locator from resting-state functional MRI in drug-resistant epilepsy

Banerjee

Kamboj²,

Wyckoff³

et al. 2023

Front. Neuroimaging

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“…Whereas some univariate correlations between attention SCI and OCI have been identified, 11,24,25 other studies have demonstrated that attention complaints and scores were unrelated, especially after controlling for confounders. 26,27 Even though difficulties in executive functions are frequently reported in PWE, 28,29 overlap with objective executive function has rarely been studied. Only single studies report bivariate correlations with test results.…”

Section: Introductionmentioning

confidence: 99%

Domain‐specific relationships of subjective and objective cognition in epilepsy

et al. 2023

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Objective: Many people with epilepsy report subjective cognitive impairment (SCI), i.e., problems with memory, attention, or executive functions, reducing quality of life. Nevertheless, overlap with objective cognitive impairment (OCI) is often weak. One reason may be a domain-specific mismatch between subjective reports and objective tests. We aimed to evaluate relations between SCI and OCI of corresponding domains and to assess whether these differ between persons who over-or underestimate their performance. Methods:In this prospective, cross-sectional sample of 104 adult inpatients with epilepsy, we performed multiple regression analyses predicting SCI in the domains attention, memory, and executive functions. We tested relationships with measures of psychomotor speed, short-term memory, verbal learning, verbal delayed recall, and word fluency while controlling for age, sex, seizure frequency, structural lesions, mono-versus polytherapy and adverse events of antiseizure medication (ASM), depressive and anxiety symptoms, level of education, and employment status. Furthermore, we tested whether these relationships differed between realistic raters and over-and underestimators. Results:We found domain-specific relations for attention and executive functions for the full sample, explaining a small proportion of variance of SCI (general dominance index = .03 and .004), whereas ASM adverse events and psychological variables were more important predictors. When dividing the sample according to the concordance of SCI and OCI, we found high frequencies of both over-(23%-46%) and underestimation (31%-35%) depending on the domain. The explanatory power of OCI for SCI was stronger within the subgroups compared to the full sample, suggesting nonlinear relationships and different underlying mechanisms for realistic raters, underestimators, and overestimators.Significance: Domain-specific SCI and OCI are related, and both should be assessed with standardized instruments. These relationships differ between overand underestimators as well as realistic raters. Based on the concordance of

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Higher education level as a protective factor against executive dysfunction in patients with epilepsy in Mataram, Indonesia

Harahap

Ferdiana

Mahardika

et al. 2023

Clinical Neurology and Neurosurgery

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Self-rated executive dysfunction in adults with epilepsy and effects of a cognitive-behavioral intervention (HOBSCOTCH)

Cited by 5 publications

References 44 publications

Automated seizure onset zone locator from resting-state functional MRI in drug-resistant epilepsy

Automated seizure onset zone locator from resting-state functional MRI in drug-resistant epilepsy

Domain‐specific relationships of subjective and objective cognition in epilepsy

Higher education level as a protective factor against executive dysfunction in patients with epilepsy in Mataram, Indonesia

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