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

Autor: K.R. Gray, François Mauguière, Alexander Hammers, Nicolas Costes, Philippe Ryvlin, J. Yankam Njiwa
Rok vydání: 2015
Předmět:
Adult
Flumazenil
Male
Cognitive Neuroscience
Hippocampus
FMZ-PET
Periventricular white matter signal increases
lcsh:Computer applications to medicine. Medical informatics
lcsh:RC346-429
Neurosurgical Procedures
Temporal lobe
Epilepsy
Young Adult
Fluorodeoxyglucose F18
Image Interpretation
Computer-Assisted
medicine
Humans
Radiology
Nuclear Medicine and imaging
Epilepsy surgery
Carbon Radioisotopes
Young adult
FDG-PET
lcsh:Neurology. Diseases of the nervous system
Hippocampal sclerosis
Sclerosis
Surgery outcome
medicine.diagnostic_test
business.industry
Regular Article
Middle Aged
Random forests
medicine.disease
nervous system diseases
Treatment Outcome
Neurology
Epilepsy
Temporal Lobe
Positron emission tomography
Positron-Emission Tomography
lcsh:R858-859.7
Female
Neurology (clinical)
Radiopharmaceuticals
Nuclear medicine
business
Psychology
medicine.drug
Zdroj: NeuroImage : Clinical
NeuroImage: Clinical, Vol 7, Iss C, Pp 122-131 (2015)
ISSN: 2213-1582
DOI: 10.1016/j.nicl.2014.11.013
Popis: Purpose We have previously shown that an imaging marker, increased periventricular [11C]flumazenil ([11C]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 [18F]FDG-PET images. We then explored the potential of periventricular FDG WM increases, as well as whole-brain [11C]FMZ and [18F]FDG images analysed with random forest classifiers, for predicting surgery outcome. Methods Sixteen patients with MRI-defined HS had preoperative [18F]FDG and [11C]FMZ-PET. Fifty controls had [18F]FDG-PET (30), [11C]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 [11C]FMZ and [18F]FDG signal increases than SF patients. All differences were more marked for [11C]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 [11C]FMZ, and 4/8 for [18F]FDG. Hence, [18F]FDG had relatively poor sensitivity and specificity. Random forest classification accurately identified 7/8 SF and 7/8 NSF patients using [11C]FMZ images, but only 4/8 SF and 6/8 NSF patients with [18F]FDG. Conclusion This study extends the association between periventricular WM increases and NSF outcome to clinical [18F]FDG-PET, but only at the group level. Whole-brain random forest classification increases [11C]FMZ-PET's performance for predicting surgery outcome.
Graphical abstract
Databáze: OpenAIRE
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