18F-FDG PET Imaging Analysis of Antiepileptic Drug Response in Benign Epilepsy With Centrotemporal Spikes Patients
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 55
- 试验地点
- 1
- 主要终点
- The 'area under curve' (AUC ) of our model in classification performance
研究概览
简要总结
This original article is a novel investigation on the metabolic characteristics of different patterns of antiepileptic drug (AED) responses in benign epilepsy with centrotemporal spikes (BECTS) patients using 18F-FDG PET imaging. In this study, we demonstrated remitting-relapsing group showed more widespread hypo-metabolism regions than AED responders. Results indicated that metabolic differences had the ability to distinguish the remitting-relapsing patients from AED responders. 18F-FDG PET could be used as a marker to infer the current seizure activity of BECTS. We think that the established hybrid model based on PET and clinical features may be a critical reference for better personalized medication in patients with BECTS.
详细描述
Purpose The current drug treatment of benign epilepsy with centrotemporal spikes (BECTS) mainly depends on the clinical experience of physicians. This study aimed to investigate different patterns of antiepileptic drug (AED) responses in patients with BECTS using 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging for better personalized medication.
Methods A total of 55 patients with BECTS (36 AED responders, 19 remitting-relapsing patients) and 23 pseudo-controls who underwent 18F-FDG PET imaging were retrospectively included. The group comparison was performed to investigate metabolic differences among AED responders, remitting-relapsing patients and pseudo-controls. Three different logistic regression models were employed to distinguish remitting-relapsing patients from AED responders based on clinical features, 18F-FDG PET images and a hybrid of both. Ten AED responders who reduced AED dose and one remitting-relapsing patient who relapsed within one month after PET examination were included in the model evaluation.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 6 Years 至 18 Years（Child, Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •1.clinical diagnosis of BECTS;
- •aging between 6 and 18 years ; 3.taking MRI and EEG examination;
- •taking AEDs as prescribed;
- •continuous 12-month clinical follow-up after 18F-FDG PET examination; 6.the last seizure occurring earlier than 24 h before 18F-FDG PET study
排除标准
- •1.any history of neurological disorders, such as head trauma, tumor or infarct
结局指标
主要结局
The 'area under curve' (AUC ) of our model in classification performance
时间窗: Through study completion, about 6 months
To evaluate the performance of our model, the investigators calculated the AUC of three different logistic regression models based on clinical features, 18F-FDG PET images and a hybrid of both.
次要结局
未报告次要终点