18F-FDG PET Imaging Analysis of Antiepileptic Drug Response in BECTS
18F-FDG PET Imaging Analysis of Antiepileptic Drug Response in Benign Epilepsy With Centrotemporal Spikes Patients
研究概览
地位
条件
详细说明
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.
研究类型
注册 (实际的)
联系人和位置
学习地点
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Zhejiang
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Hangzhou、Zhejiang、中国、310009
- Department of Nuclear Medicine and PET/CT Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University
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参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
取样方法
研究人群
描述
Inclusion Criteria:
- 1.clinical diagnosis of BECTS; 2. aging between 6 and 18 years ; 3.taking MRI and EEG examination; 4. taking AEDs as prescribed; 5. 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
Exclusion Criteria:
- 1.any history of neurological disorders, such as head trauma, tumor or infarct
学习计划
研究是如何设计的？
设计细节
队列和干预
团体/队列 |
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实验组
实验组接受18F-FDG PET检查
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控制组
对照组接受18F-FDG PET检查
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研究衡量的是什么？
主要结果指标
结果测量 |
措施说明 |
大体时间 |
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The 'area under curve' (AUC ) of our model in classification performance
大体时间：Through study completion, about 6 months
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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.
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Through study completion, about 6 months
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合作者和调查者
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (实际的)
研究完成 (实际的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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