18F-FDG PET Imaging Analysis of Antiepileptic Drug Response in BECTS

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.

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Key information

Conditions

Benign Epilepsy With Centrotemporal Spikes Brain Diseases Central Nervous System Diseases Epilepsies, Partial Epilepsy Epilepsy, Rolandic Epileptic Syndromes Nervous System Diseases

Age range

6 year–18 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Department of Nuclear Medicine and PET/CT Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University

Hangzhou, Zhejiang, 310009, China

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Primary outcomes

The 'area under curve' (AUC ) of our model in classification performance

Time frame: 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.

Sponsors and collaborators

Lead sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Other

Registry information

Official study title

18F-FDG PET Imaging Analysis of Antiepileptic Drug Response in Benign Epilepsy With Centrotemporal Spikes Patients

Important dates

Study start: 2019
Primary completion: 2020
Study completion: 2020
First posted: Apr 22, 2020
Registry last updated: Apr 22, 2020

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Completed