Epileptogenic zone localization using a new automatic quantitative analysis based on normal brain glucose metabolism database

Abstract

Objectives

To assess the clinical value of voxel-based automatic quantitative analysis using a normal brain glucose metabolism database in the preoperative localization of focal intractable temporal lobe epilepsy patients.

Methods

Patients with refractory temporal lobe epilepsy who underwent 18F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) imaging were retrospectively enrolled from January to June 2017. Visual analysis was performed by two nuclear medicine radiologists, and the automatic quantitative analysis was carried out using MIMneuro software based the age- and gender-stratified normal brain glucose metabolism database. Setting postoperative outcomes as reference, the consistency between visual analysis and automatic quantitative analysis was tested by Cohen’s kappa coefficient, and differences in localization of epileptic foci of the two methods were compared by Chi-square test.

Results

A total of 32 patients intractable temporal lobe epilepsy were included in this study. There was a moderate agreement between the automatic quantitative analysis based on MIMneuro software and visual analysis (kappa coefficient = 0.472, p = 0.002). In terms of the efficiency of focus localization, the voxel-based automatic quantitative analysis was higher than that of visual analysis (Chi-square value = 6.969, p = 0.008).

Conclusions

The voxel-based automatic quantitative analysis combined with normal brain glucose metabolism database had a certain clinical application value for detection temporal lobe epilepsy.

Keywords:

• Epilepsy
• localization
• ¹⁸F-FDG PET
• quantitative analysis

Disclosure statement

No potential conflict of interest was reported by the author(s).

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Funding

This study was supported by the Project of New Technology in the Second Affiliated Hospital of Air Force Medical University and Beijing Municipal Administration of the Hospitals’ Ascent Plan, Code: DFL20180802.