Epilepsy Research最新文献

Background: Regional gray matter volume (GMV) reductions have been observed across epilepsy syndromes. This study aimed to investigate the association between global GMV and clinical outcomes in a regional cohort of adults with epilepsy.

Method: A cross-sectional analysis of a regional cohort study (PREDICT, clinicaltrials.gov, NCT04559919) was performed. Adults with epilepsy were recruited from five neurology outpatient clinics. Clinical data were collected from patient records and patient-report questionnaires. The latest MRI including T1 sequence was selected per participant and segmented using SPM 12 for MATLAB. GMV and whole brain volume (WBV) were analyzed across groups with seizures or seizure-freedom using logistic regression models adjusting for age, epilepsy duration and total intracranial volume (ICV). Clinical associations with global GMV were analyzed in MRI negative patients using multiple linear regression.

Results: In the total cohort of 171 participants, median (IQR) age at MRI was 36 (27) years, and epileptogenic lesions on MRI were observed in n (%) = 59 (34.5). The GMV and WBV (cm³) were normally distributed with mean (SD) of 745.9 (104.2) and 1192.8(161.5), respectively. No difference was observed between patients with active epilepsy compared to seizure-free patients in total GMV (mean (SD)) 744.5 (97.3) versus 740.8 (115.7) cm³, p = 0.60), or WBV (1191.9 (154.7) versus 1193.7), p = 0.30). Patients with polypharmacy (≥3 ASM) (n (%)= 46 (26.9)) had lower GMV compared to patients with only 1-2 ASM, (n (%)= 125 (73.1), (mean (SD) 720.983 (88.208) versus 755.097 (108.410), p = 0.04). In MRI negative patients (n = 106), longer epilepsy duration (years) was associated with greater GMV volume (1.32, 95%CI 0.00-2.63, p = 0.05).

Conclusions: Global GMV and/or WBV were not associated with seizures, suggesting that not all patients with active epilepsy will develop generalized gray matter atrophy. Polypharmacy and late-onset epilepsy were associated with lower GMV, suggesting neurodegeneration related to epilepsy also in a regional cohort study.

Objective: This study was conducted to determine the levels of stigma and concealment of disease in individuals with epilepsy and the factors affecting them.

Methods: This descriptive and cross-sectional study was conducted with 140 individuals with epilepsy who were followed at the neurology outpatient clinic of Ardahan State Hospital. The data were collected using a personal information form, a felt stigma scale, and a concealment of epilepsy scale.

Results: The mean stigma score of individuals with epilepsy was found to be 27.26 (SD = 7.56), and their mean concealment score was found to be 34.78 (SD = 10.91). A positive significant correlation was found between stigma and concealment scores (p < 0.001). The mean stigma and concealment scores were higher for the individuals who were single, had suffered an injury during a seizure and had a family history of epilepsy (p < 0.05). Multivariate linear regression analysis was carried out to examine the factors related to concealment scores. The model was found to be statistically significant (p < 0.001). Stigma score (p < 0.001), age (p < 0.05) and level of education (p < 0.05) were found to be significantly associated with concealment scores.

Conclusions: Concealment of disease was significantly associated with higher felt stigma, younger age and higher education level. Felt stigma was more prevalent among single participants, those with a family history of epilepsy and those who had had injuries during seizures.

The purpose of this study is to perform an independent assessment of three state-of-the-art tools for the detection of focal cortical dysplasia (FCD) from Magnetic Resonance images (MRI). These tools include DeepFCD, the Multi-center Epilepsy Lesion Detection (MELD) Classifier, and MELDGraph. T1-weighted and fluid-attenuated inversion recovery MRIs from 101 epilepsy patients with FCD and 101 epilepsy patients without FCD were retrospectively included. Classifiers were evaluated at patient-level by their ability to correctly identify the presence of any FCD lesions, and at lesion-level by their capacity to identify lesions within regions delineated by neuroradiologists in MRI reports. A calibrated threshold for DeepFCD prediction probabilities was empirically determined to improve classifier specificity. Classifier test-retest consistency was measured using the Dice coefficient on repeated MRI scans of 21 individuals. At patient-level, MELDClassifier achieved 52% accuracy (sensitivity=91%, specificity=14%), MELDGraph reached 61% accuracy (sensitivity=76%, specificity=47%) and DeepFCD performed with 56% accuracy (sensitivity=62%, specificity=50%) at an empirically determined threshold of 0.90. At lesion-level, MELDClassifier performed with a sensitivity of 70% and a positive predictive value (PPV) of 13%. MELDGraph reached 53% sensitivity and PPV of 36%, whereas the DeepFCD performed with 30% sensitivity and PPV of 19%. Test-retest reliability was low, with an average [min, max] Dice coefficient of 0.28 [0.0, 1.0] for MELDClassifier, 0.38 [0.0, 1.0] for MELDGraph, and 0.35 [0.05, 0.54] for DeepFCD. This study highlights the current limitations of using deep learning models in FCD diagnosis and emphasizes the need to enhance the tools' accuracy, reliability, and interpretability to improve clinical utility.