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Clinical Trials/NCT04357236
NCT04357236CompletedNot Applicable

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

Second Affiliated Hospital, School of Medicine, Zhejiang University1 site in 1 country55 target enrollmentStarted: June 1, 2019Last updated:
Conditions

Trial Snapshot

Phase
Not Applicable
Status
Completed
Sponsor
Enrollment
55
Locations
1
Primary Endpoint
The 'area under curve' (AUC ) of our model in classification performance

Study Overview

Brief Summary

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.

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 Design

Study Type
Observational
Observational Model
Cohort
Time Perspective
Retrospective

Eligibility Criteria

Ages
6 Years to 18 Years (Child, Adult)
Sex
All
Accepts Healthy Volunteers
No

Inclusion Criteria

  • •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

Exclusion Criteria

  • •1.any history of neurological disorders, such as head trauma, tumor or infarct

Outcomes

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.

Secondary Outcomes

No secondary outcomes reported

Investigators

Sponsor
Second Affiliated Hospital, School of Medicine, Zhejiang University
Sponsor Class
Other
Responsible Party
Sponsor

Study Sites (1)

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