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Epilepsy is the most common chronic neurological disorder in the world, affecting more than 50 million people worldwide.
Approximately 35% of patients with epilepsy are refractory to all available antiepileptic drugs. Focal Hypometabolism on interictal [18F]-FDG PET is a hallmark of the Seizure Onset Zone as well as surrounding areas. Using [18F]-FDG PET is thus particularly useful to determine the seizure onset zone of epileptic patients and thus to guide surgical treatment when antiepileptic drugs fail.
Interpretation of PET images primarily relies on standard visual analysis, but statistical analysis, with the widely used Statistical Parametric Mapping (SPM) software improves the diagnostic yield of PET. Over the past years, some authors have thus reported that the use of SPM can result in greater sensitivity and specificity of PET imaging in patients with partial epilepsy.
In order to perform statistical analysis of PET images to compare brain metabolism of epileptic patients and healthy controls, it is necessary to collect a normative database of [18F]-FDG PET images in healthy controls.
The purpose of this study is (i) collect a normative database of [18F]-FDG PET images in healthy adults controls to evaluate rigorously the diagnostic value of multimodal imaging for non-invasive localization of the EZ and (ii) to evaluate the test-retest reliability of [18F]-FDG PET scanning.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| PET [18F] FDG | Active Comparator | Each subject will have a PET scan at [18F] FDG.The raw imaging data obtained from these controls will be post-processed using the Statistical Parametric Mapping software. Schematically, the data of each control will be normalized in the same anatomical space, then smoothed and averaged between the different controls. This will make it possible to constitute the normative database. |
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| Review test-retest | Sham Comparator | Of the 40 volunteers included, 10 will have test-retest exams (2 separate exams every 15 days). |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| PET [18F] FDG | Other | Measurement of carbohydrate metabolism at the individual level. Standardization of the individual imaging data in a standard anatomical space and then calculation of an average image through the group-level controls. |
| Measure | Description | Time Frame |
|---|---|---|
| Glucose Metabolism of the whole brain estimated with [18F]-FDG PET in healthy controls. | 40 healthy controls (age range 20-65 years) will undergo [18F]-FDG PET. The Glucose Metabolism for whole brain will be determined with [18F]-FDG PET for each subject. | Day 1 |
| Measure | Description | Time Frame |
|---|---|---|
| Test-reliability | For each subject, we will measure Glucose Metabolism of the whole brain estimated with [18F]-FDG PET for the first PET scan and for the second PET scan and evaluate the potential difference of Glucose Metabolism between the two scans. | Week 2 |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Julien JUNG, MD | Hospices Civils de Lyon | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hospices Civils de Lyon | Bron | 69500 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40187100 | Background | Zotova D, Pinon N, Trombetta R, Bouet R, Jung J, Lartizien C. GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models. Comput Methods Programs Biomed. 2025 Jun;265:108727. doi: 10.1016/j.cmpb.2025.108727. Epub 2025 Mar 31. | |
| 34529159 | Result |
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| ID | Term |
|---|---|
| C062942 | 2-phenyl-6-(2'-(4'-(ethoxycarbonyl)thiazolyl))thiazolo(3,2-b)(1,2,4)triazole |
| D019788 | Fluorodeoxyglucose F18 |
| ID | Term |
|---|---|
| D003847 | Deoxyglucose |
| D003837 | Deoxy Sugars |
| D002241 | Carbohydrates |
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| Anatomical MRI | Other | All subjects will benefit from a 3D anatomical MRI to control the normality of their MRI and an automatic segmentation of 73 brain regions by multi-atlas segmentation. |
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| Merida I, Jung J, Bouvard S, Le Bars D, Lancelot S, Lavenne F, Bouillot C, Redoute J, Hammers A, Costes N. CERMEP-IDB-MRXFDG: a database of 37 normal adult human brain [18F]FDG PET, T1 and FLAIR MRI, and CT images available for research. EJNMMI Res. 2021 Sep 16;11(1):91. doi: 10.1186/s13550-021-00830-6. |