References of "Salmon, Eric"
     in
Bookmark and Share    
Peer Reviewed
See detailRetirement and the onset of Alzheimer's disease: The ICTUS study
Grotz, Catherine ULg; Letenneur, luc; Bonsang, Eric et al

Conference (2013, October 03)

Detailed reference viewed: 24 (3 ULg)
Peer Reviewed
See detailAge estimation from faces in Alzheimer disease
Moyse, Evelyne ULg; Brédart, Serge ULg; Salmon, Eric ULg et al

Poster (2013, July)

Although studies on age estimation showed that the performance of estimation is fairly accurate, this performance can be influenced by group biases such as the own-age bias (George & Hole, 1995). Moreover ... [more ▼]

Although studies on age estimation showed that the performance of estimation is fairly accurate, this performance can be influenced by group biases such as the own-age bias (George & Hole, 1995). Moreover this bias occurs both in young and older adults (Moyse & Brédart, 2012). Because difficulties in face processing have been reported in Alzheimer disease (Della Sala et al., 1995), the aim of this study was to examine the performance of age estimation from faces in patients with Alzheimer disease (mild to moderate) compared with normal aging persons. Moreover to test the preservation of the occurrence of an own-age bias, stimuli belonging to different age groups (young, middle age and older adults) were used. We observed a main effect of Group indicating that patients were less accurate than control whatever the age of faces. In addition a main effect of Age of faces was obtained; the percentage of accuracy was better for older faces than for the two other age groups of faces. Consequently although patients’ performance in age estimation of faces is impaired, an own-age bias was still present. These results have two main interests: a clinical interest (expanding the diagnostic criteria of the Alzheimer disease) and a forensic interest (assessing the credibility of eyewitness testimony in older adults with a possible Alzheimer disease). [less ▲]

Detailed reference viewed: 49 (9 ULg)
Full Text
Peer Reviewed
See detailBrain metabolic dysfunction in Capgras syndrome during Alzheimer’s disease: a positron emission tomography study
Jedidi, Haroun ULg; Daury, Noémy; Cappa, Rémi et al

Poster (2013, June)

Detailed reference viewed: 48 (16 ULg)
Full Text
Peer Reviewed
See detailPreclinical radiation dosimetry for the novel SV2A radiotracer [18F]UCB-H
Bretin, Florian ULg; Warnock, Geoffrey; Bahri, Mohamed Ali ULg et al

in European Journal of Nuclear Medicine and Molecular Imaging Research (2013), 3(1), 35

Background: [18F]UCB-H was developed as a novel radiotracer with a high affinity for synaptic vesicle protein 2A, the binding site for the antiepileptic levetiracetam. The objectives of this study were to ... [more ▼]

Background: [18F]UCB-H was developed as a novel radiotracer with a high affinity for synaptic vesicle protein 2A, the binding site for the antiepileptic levetiracetam. The objectives of this study were to evaluate the radiation dosimetry of [18F]UCB-H in a preclinical trial and to determine the maximum injectable dose according to guidelines for human biomedical research. The radiation dosimetry was derived by organ harvesting and dynamic micro positron emission tomography (PET) imaging in mice, and the results of both methods were compared. Methods: Twenty-four male C57BL-6 mice were injected with 6.96 ± 0.81 MBq of [18F]UCB-H, and the biodistribution was determined by organ harvesting at 2, 5, 10, 30, 60, and 120 min (n = 4 for each time point). Dynamic microPET imaging was performed on five male C57BL-6 mice after the injection of 9.19 ± 3.40 MBq of [18F]UCB-H. A theoretical dynamic bladder model was applied to simulate urinary excretion. Human radiation dose estimates were derived from animal data using the International Commission on Radiological Protection 103 tissue weighting factors. Results: Based on organ harvesting, the urinary bladder wall, liver and brain received the highest radiation dose with a resulting effective dose of 1.88E-02 mSv/MBq. Based on dynamic imaging an effective dose of 1.86E-02 mSv/MBq was calculated, with the urinary bladder wall and liver (brain was not in the imaging field of view) receiving the highest radiation. Conclusions: This first preclinical dosimetry study of [18F]UCB-H showed that the tracer meets the standard criteria for radiation exposure in clinical studies. The dose-limiting organ based on US Food and Drug Administration (FDA) and European guidelines was the urinary bladder wall for FDA and the effective dose for Europe with a maximum injectable single dose of approximately 325 MBq was calculated. Although microPET imaging showed significant deviations from organ harvesting, the Pearson’s correlation coefficient between radiation dosimetry derived by either method was 0.9666. [less ▲]

Detailed reference viewed: 49 (16 ULg)
Full Text
Peer Reviewed
See detailBinary classification of (1)(8)F-flutemetamol PET using machine learning: comparison with visual reads and structural MRI
Vandenberghe, R.; Nelissen, N.; Salmon, Eric ULg et al

in NeuroImage (2013), 64

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high ... [more ▼]

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high clinical relevance. We evaluated whether a supervised machine learning technique, support vector machines (SVM), can replicate the assignments made by visual readers blind to the clinical diagnosis, which image components have highest diagnostic value according to SVM and how (18)F-flutemetamol-based classification using SVM relates to structural MRI-based classification using SVM within the same subjects. By means of SVM with a linear kernel, we analyzed (18)F-flutemetamol scans and volumetric MRI scans from 72 cases from the (18)F-flutemetamol phase 2 study (27 clinically probable Alzheimer's disease (AD), 20 amnestic mild cognitive impairment (MCI), 25 controls). In a leave-one-out approach, we trained the (18)F-flutemetamol based classifier by means of the visual reads and tested whether the classifier was able to reproduce the assignment based on visual reads and which voxels had the highest feature weights. The (18)F-flutemetamol based classifier was able to replicate the assignments obtained by visual reads with 100% accuracy. The voxels with highest feature weights were in the striatum, precuneus, cingulate and middle frontal gyrus. Second, to determine concordance between the gray matter volume- and the (18)F-flutemetamol-based classification, we trained the classifier with the clinical diagnosis as gold standard. Overall sensitivity of the (18)F-flutemetamol- and the gray matter volume-based classifiers were identical (85.2%), albeit with discordant classification in three cases. Specificity of the (18)F-flutemetamol based classifier was 92% compared to 68% for MRI. In the MCI group, the (18)F-flutemetamol based classifier distinguished more reliably between converters and non-converters than the gray matter-based classifier. The visual read-based binary classification of (18)F-flutemetamol scans can be replicated using SVM. In this sample the specificity of (18)F-flutemetamol based SVM for distinguishing AD from controls is higher than that of gray matter volume-based SVM. [less ▲]

Detailed reference viewed: 5 (0 ULg)
Peer Reviewed
See detailImpairment of two memory cerebral networks in Alzheimer's disease
Bastin, Christine ULg; Bahri, Mohamed Ali ULg; Collette, Fabienne ULg et al

in Proceedings of the Annual Meeting of the Belgian Association for Psychological Sciences (2013)

Detailed reference viewed: 8 (3 ULg)
Peer Reviewed
See detailCognitive reserve, recollection and familiarity in normal aging, Mild Cognitive Impairment and Alzheimer's disease
Laisney, Mickaël; Salmon, Eric ULg; Bastin, Christine ULg

in Proceedings of the Annual Meeting of the Belgian Association for Psychological Sciences (2013)

Detailed reference viewed: 4 (0 ULg)
Peer Reviewed
See detailEffects of aging on task- and stimulus-related attention during a working memory task
Kurth, Sophie ULg; Hagelstein, Catherine ULg; Collette, Fabienne ULg et al

in Proceedings of the Annual Meeting of the Belgian Association for Psychological Sciences (2013)

Detailed reference viewed: 15 (0 ULg)
Full Text
Peer Reviewed
See detailClassification of positron emission tomography images using multiple kernel learning
Segovia-Román, Fermín ULg; Bastin, Christine ULg; Salmon, Eric ULg et al

in Proceeding of 3rd NIPS 2013 Workshop on Machine Learning and Interpretation in NeuroImaging (2013)

Over the last years, several approaches to analyze nuclear medicine imaging using computer systems have been proposed with the aim of assisting the diagnosis of neurodegenerative disorders. Probably one ... [more ▼]

Over the last years, several approaches to analyze nuclear medicine imaging using computer systems have been proposed with the aim of assisting the diagnosis of neurodegenerative disorders. Probably one of the most complex challenges facing these approaches is to deal with the huge amount of data provided by brain images. In this work, we propose an original approach based on multiple kernel learning. First the images were parcellated (according to the structure of the brain) by means of the automatic anatomical labeling atlas. Then, the importance of each region for the assisted diagnosis was estimated using a classifi- cation procedure. Finally, all the regions were combined in a multiple kernel method in which one kernel per region was computed and all the kernels were weighted according to the importance of the region they represented. For testing purposes, a database with 46 PET images from stable mild cognitive impairment subjects and early Alzheimer’s disease converter patients was used. An accuracy rate of 73.91% was achieved when differentiating between both groups. [less ▲]

Detailed reference viewed: 35 (11 ULg)