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

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.

Study Overview

• Status: Completed
• Conditions: Benign Epilepsy With Centrotemporal Spikes

Detailed Description

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.

• Study Type: Observational
• Enrollment (Actual): 55

Contacts and Locations

Study Locations

• China
  • Zhejiang
    • Hangzhou, Zhejiang, China, 310009
      • Department of Nuclear Medicine and PET/CT Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 6 years to 18 years (Child, Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Pediatric patients with benign epilepsy with centrotemporal spikes

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Experimental Group; The experimental group received 18F-FDG PET examination
Control Group; The control group received 18F-FDG PET examination

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The 'area under curve' (AUC ) of our model in classification performance	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.	Through study completion, about 6 months

Collaborators and Investigators

• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University

Study record dates

Study Major Dates

• Study Start (Actual): June 1, 2019
• Primary Completion (Actual): March 30, 2020
• Study Completion (Actual): April 20, 2020

Study Registration Dates

• First Submitted: April 20, 2020
• First Submitted That Met QC Criteria: April 20, 2020
• First Posted (Actual): April 22, 2020

Study Record Updates

• Last Update Posted (Actual): April 22, 2020
• Last Update Submitted That Met QC Criteria: April 20, 2020
• Last Verified: April 1, 2020

More Information

Terms related to this study

• Keywords: machine learning; positron emission tomography; glucose metabolism; Benign Epilepsy with Centrotemporal Spikes
• Additional Relevant MeSH Terms: Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Epileptic Syndromes; Epilepsies, Partial; Epilepsy; Epilepsy, Rolandic
• Other Study ID Numbers: 2019-437

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No