Advanced [(18)F]FDG and [(11)C]flumazenil PET analysis for individual outcome prediction after temporal lobe epilepsy surgery for hippocampal sclerosis

Details

Serval ID
serval:BIB_CD4F9AEBEE5F
Type
Article: article from journal or magazin.
Collection
Publications
Title
Advanced [(18)F]FDG and [(11)C]flumazenil PET analysis for individual outcome prediction after temporal lobe epilepsy surgery for hippocampal sclerosis
Journal
Neuroimage Clin
Author(s)
Yankam Njiwa J., Gray K. R., Costes N., Mauguiere F., Ryvlin P., Hammers A.
ISSN
2213-1582 (Electronic)
ISSN-L
2213-1582
Publication state
Published
Issued date
2015
Volume
7
Pages
122-31
Language
english
Notes
Yankam Njiwa, J
Gray, K R
Costes, N
Mauguiere, F
Ryvlin, P
Hammers, A
eng
Netherlands
Neuroimage Clin. 2014 Nov 27;7:122-31. doi: 10.1016/j.nicl.2014.11.013. eCollection 2015.
Abstract
PURPOSE: We have previously shown that an imaging marker, increased periventricular [(11)C]flumazenil ([(11)C]FMZ) binding, is associated with failure to become seizure free (SF) after surgery for temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS). Here, we investigated whether increased preoperative periventricular white matter (WM) signal can be detected on clinical [(18)F]FDG-PET images. We then explored the potential of periventricular FDG WM increases, as well as whole-brain [(11)C]FMZ and [(18)F]FDG images analysed with random forest classifiers, for predicting surgery outcome. METHODS: Sixteen patients with MRI-defined HS had preoperative [(18)F]FDG and [(11)C]FMZ-PET. Fifty controls had [(18)F]FDG-PET (30), [(11)C]FMZ-PET (41), or both (21). Periventricular WM signal was analysed using Statistical Parametric Mapping (SPM8), and whole-brain image classification was performed using random forests implemented in R (http://www.r-project.org). Surgery outcome was predicted at the group and individual levels. RESULTS: At the group level, non-seizure free (NSF) versus SF patients had periventricular increases with both tracers. Against controls, NSF patients showed more prominent periventricular [(11)C]FMZ and [(18)F]FDG signal increases than SF patients. All differences were more marked for [(11)C]FMZ. For individuals, periventricular WM signal increases were seen at optimized thresholds in 5/8 NSF patients for both tracers. For SF patients, 1/8 showed periventricular signal increases for [(11)C]FMZ, and 4/8 for [(18)F]FDG. Hence, [(18)F]FDG had relatively poor sensitivity and specificity. Random forest classification accurately identified 7/8 SF and 7/8 NSF patients using [(11)C]FMZ images, but only 4/8 SF and 6/8 NSF patients with [(18)F]FDG. CONCLUSION: This study extends the association between periventricular WM increases and NSF outcome to clinical [(18)F]FDG-PET, but only at the group level. Whole-brain random forest classification increases [(11)C]FMZ-PET's performance for predicting surgery outcome.
Keywords
Adult, Carbon Radioisotopes, Epilepsy, Temporal Lobe/*diagnostic imaging/*surgery, Female, Flumazenil, Fluorodeoxyglucose F18, Hippocampus/diagnostic imaging/pathology/surgery, Humans, Image Interpretation, Computer-Assisted, Male, Middle Aged, Neurosurgical Procedures, Positron-Emission Tomography/*methods, *Radiopharmaceuticals, Sclerosis/pathology, Treatment Outcome, Young Adult, Fdg-pet, Fmz-pet, Hippocampal sclerosis, Periventricular white matter signal increases, Random forests, Surgery outcome
Pubmed
Open Access
Yes
Create date
29/11/2018 12:37
Last modification date
20/08/2019 15:47
Usage data