Temporal epilepsy lesions may be detected by the voxel-based quantitative analysis of brain FDG-PET images using an original block-matching normalization software.

Introduction: Statistical parametric mapping (SPM) provides useful voxel-by-voxel analyses of brain images from (18)F-fluorodesoxyglucose positron emission tomography (FDG-PET) after an initial step of spatial normalization through an anatomical template model. In the setting of the preoperative workup of patients with temporal epilepsy, this study aimed at assessing a block-matching (BM) normalization method, where most transformations are computed through small blocks, a principle that minimizes artefacts and overcomes additional image-filtering.

Methods: Brain FDG-PET images from 31 patients with well-characterised temporal lobe epilepsy and among whom 22 had common mesial temporal lobe epilepsy were retrospectively analysed using both BM and conventional SPM normalization methods and with PET images from age-adjusted controls.

Age-related changes in FDG brain uptake are more accurately assessed when applying an adaptive template to the SPM method of voxel-based quantitative analysis.

Introduction: The impact of age is crucial and must be taken into account when applying a voxel-based quantitative analysis on brain images from [¹⁸F]-fluorodeoxyglucose Positron Emission Tomography (FDG-PET). This study aimed to determine whether age-related changes in brain FDG-PET images are more accurately assessed when the conventional statistical parametric mapping (SPM) normalization method is used with an adaptive template, obtained from analysed PET images using a Block-Matching (BM) algorithm to fit with the characteristics of these images.

Methods: Age-related changes in FDG-PET images were computed with linear models in 84 neurologically healthy subjects (35 women, 19 to 82-year-old), and compared between results provided by the SPM normalization algorithm applied on its dedicated conventional template or on the adaptive BM template.

Complementarity of visual and voxel-based FDG-PET analysis to detect MCI-like hypometabolic pattern in elderly patients with hypertension and isolated memory complaints.

Background: 18F-FDG PET can be used to aid in the diagnosis of Alzheimer's disease (AD) and clarify the diagnosis and prognosis of patients with mild cognitive impairment (MCI).

Purpose: To compare the results of a quantitative analysis of FDG-PET brain images to a standard visual analysis (SVA) with regards to the detection of MCI-like hypometabolic pattern in elderly patients with hypertension and subjective, isolated memory complaints.

Material And Methods: FDG-PET brain was performed in 71 patients (mean age, 76.