Florent Aubry

Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve

Brain atrophy measured by magnetic resonance structural imaging has been proposed as a surrogate marker for the early diagnosis of Alzheimers disease. Studies on large samples are still required to determine its practical interest at the individual level, especially with regards to the capacity of anatomical magnetic resonance imaging to disentangle the confounding role of the cognitive reserve in the early diagnosis of Alzheimers disease. One hundred and thirty healthy controls, 122 subjects with mild cognitive impairment of the amnestic type and 130 Alzheimers disease patients were included from the ADNI database and followed up for 24 months. After 24 months, 72 amnestic mild cognitive impairment had converted to Alzheimers disease (referred to as progressive mild cognitive impairment, as opposed to stable mild cognitive impairment). For each subject, cortical thickness was measured on the baseline magnetic resonance imaging volume. The resulting cortical thickness map was parcellated into 22 regions and a normalized thickness index was computed using the subset of regions (right medial temporal, left lateral temporal, right posterior cingulate) that optimally distinguished stable mild cognitive impairment from progressive mild cognitive impairment. We tested the ability of baseline normalized thickness index to predict evolution from amnestic mild cognitive impairment to Alzheimers disease and compared it to the predictive values of the main cognitive scores at baseline. In addition, we studied the relationship between the normalized thickness index, the education level and the timeline of conversion to Alzheimers disease. Normalized thickness index at baseline differed significantly among all the four diagnosis groups (P < 0.001) and correctly distinguished Alzheimers disease patients from healthy controls with an 85% cross-validated accuracy. Normalized thickness index also correctly predicted evolution to Alzheimers disease for 76% of amnestic mild cognitive impairment subjects after cross-validation, thus showing an advantage over cognitive scores (range 63–72%). Moreover, progressive mild cognitive impairment subjects, who converted later than 1 year after baseline, showed a significantly higher education level than those who converted earlier than 1 year after baseline. Using a normalized thickness index-based criterion may help with early diagnosis of Alzheimers disease at the individual level, especially for highly educated subjects, up to 24 months before clinical criteria for Alzheimers disease diagnosis are met.

Testing for the dual-route cascade reading model in the brain: an fMRI effective connectivity account of an efficient reading style

Neuropsychological data about the forms of acquired reading impairment provide a strong basis for the theoretical framework of the dual-route cascade (DRC) model which is predictive of reading performance. However, lesions are often extensive and heterogeneous, thus making it difficult to establish precise functional anatomical correlates. Here, we provide a connective neural account in the aim of accommodating the main principles of the DRC framework and to make predictions on reading skill. We located prominent reading areas using fMRI and applied structural equation modeling to pinpoint distinct neural pathways. Functionality of regions together with neural network dissociations between words and pseudowords corroborate the existing neuroanatomical view on the DRC and provide a novel outlook on the sub-regions involved. In a similar vein, congruent (or incongruent) reliance of pathways, that is reliance on the word (or pseudoword) pathway during word reading and on the pseudoword (or word) pathway during pseudoword reading predicted good (or poor) reading performance as assessed by out-of-magnet reading tests. Finally, inter-individual analysis unraveled an efficient reading style mirroring pathway reliance as a function of the fingerprint of the stimulus to be read, suggesting an optimal pattern of cerebral information trafficking which leads to high reading performance.

Piecemeal recruitment of left-lateralized brain areas during reading: a spatio-functional account.

Neuroimaging studies of reading converge to suggest that linguistically elementary stimuli are confined to the activation of bilateral posterior regions, whereas linguistically complex stimuli additionally recruit left hemispheric anterior regions, raising the hypotheses of a gradual bilateral-to-left and a posterior-to-anterior recruitment of reading related areas. Here, we tested these two hypotheses by contrasting a repertoire of eight categories of stimuli ranging from simple orthographic-like characters to words and pseudowords in a single experiment, and by measuring BOLD signal changes and connectivity while 16 fluent readers passively viewed the stimuli. Our results confirm the existence of a bilateral-to-left and posterior-to-anterior recruitment of reading related areas, straightforwardly resulting from the increase in stimulis linguistic processing load, which reflects reading processes: visual analysis, orthographic encoding and phonological decoding. Connectivity analyses strengthened the validity of these observations and additionally revealed an enhancement of the left parieto-frontal information trafficking for higher linguistic processing. Our findings clearly establish the notion of a gradual spatio-functional recruitment of reading areas and demonstrate, to the best of our knowledge, the first evidence of a robust and staged link between the level of linguistic processing, the spatial distribution of brain activity and its information trafficking.

Brain Gray Matter Mri Morphometry for Neuroprognostication After Cardiac Arrest

Objectives: We hypothesize that the combined use of MRI cortical thickness measurement and subcortical gray matter volumetry could provide an early and accurate in vivo assessment of the structural impact of cardiac arrest and therefore could be used for long-term neuroprognostication in this setting. Design: Prospective cohort study. Setting: Five Intensive Critical Care Units affiliated to the University in Toulouse (France), Paris (France), Clermont-Ferrand (France), Liège (Belgium), and Monza (Italy). Patients: High-resolution anatomical T1-weighted images were acquired in 126 anoxic coma patients (“learning” sample) 16u2009±u20098 days after cardiac arrest and 70 matched controls. An additional sample of 18 anoxic coma patients, recruited in Toulouse, was used to test predictive model generalization (“test” sample). All patients were followed up 1 year after cardiac arrest. Interventions: None. Measurements and Main Results: Cortical thickness was computed on the whole cortical ribbon, and deep gray matter volumetry was performed after automatic segmentation. Brain morphometric data were employed to create multivariate predictive models using learning machine techniques. Patients displayed significantly extensive cortical and subcortical brain volumes atrophy compared with controls. The accuracy of a predictive classifier, encompassing cortical and subcortical components, has a significant discriminative power (learning area under the curve = 0.87; test area under the curve = 0.96). The anatomical regions which volume changes were significantly related to patient’s outcome were frontal cortex, posterior cingulate cortex, thalamus, putamen, pallidum, caudate, hippocampus, and brain stem. Conclusions: These findings are consistent with the hypothesis of pathologic disruption of a striatopallidal-thalamo-cortical mesocircuit induced by cardiac arrest and pave the way for the use of combined brain quantitative morphometry in this setting.

Cortical Imaging on a Head Template: A Simulation Study Using a Resistor Mesh Model (RMM)

The T1 head template model used in Statistical Parametric Mapping Version 2000 (SPM2), was segmented into five layers (scalp, skull, CSF, grey and white matter) and implemented in 2xa0mm voxels. We designed a resistor mesh model (RMM), based on the finite volume method (FVM) to simulate the electrical properties of this head model along the three axes for each voxel. Then, we introduced four dipoles of high eccentricity (about 0.8) in this RMM, separately and simultaneously, to compute the potentials for two sets of conductivities. We used the direct cortical imaging technique (CIT) to recover the simulated dipoles, using 60 or 107 electrodes and with or without addition of Gaussian white noise (GWN). The use of realistic conductivities gave better CIT results than standard conductivities, lowering the blurring effect on scalp potentials and displaying more accurate position areas when CIT was applied to single dipoles. Simultaneous dipoles were less accurately localized, but good qualitative and stable quantitative results were obtained up to 5% noise level for 107 electrodes and up to 10% noise level for 60 electrodes, showing that a compromise must be found to optimize both the number of electrodes and the noise level. With the RMM defined in 2xa0mm voxels, the standard 128-electrode cap and 5% noise appears to be the upper limit providing reliable source positions when direct CIT is used. The admittance matrix defining the RMM is easy to modify so as to adapt to different conductivities. The next step will be the adaptation of individual real head T2 images to the RMM template and the introduction of anisotropy using diffusion imaging (DI).

IC-P2-126: MRI-based cortical thickness measurement improves the prediction of MCI to AD conversion

grey matter (GM) probability in the MTL were obtained. Neuropsychological testing was performed at baseline for all subjects, and during follow-up between 1-3.5 years in MCI patients. Conversion to AD was defined based upon clinical and neuropsychological evaluation and change in Clinical Dementia Rating (CDR) scale score from 0.5 to 1.0. Subjects were reclassified to four cognitive status levels: 1 control, 2 MCI-Nonconverter, 3 MCI-Converter, and 4 AD. An ordinal regression model was created with MTL structural and PMC fMRI measures, age and MMSE as the independent variables. Results: Both imaging and follow-up data were available in 32 MCI subjects, 10 of whom converted to AD (total sample 28 controls, 22 MCI-Nonconverters, 10 MCI-Converters, and 13 AD). In our regression model, the main effects of all four factors were statistically significant (p 0.05), independent of one another. Contributions to model variance (highest to lowest) were as follows: MTL GM probability, MMSE, Age, and PMC signal change. Conclusions: PMC deactivation and MTL GM probability measures contribute independently to diagnostic classification, including prognosis in MCI patients. Combined use of structural and functional MRI information may serve as adjuncts to neuropsychological testing in early identification and monitoring of disease progression.

U - 12 Analyse longitudinale de l’atrophie cérébrale en IRM : limites des méthodes et perspectives

Resume Introduction L’imagerie par Resonance Magnetique anatomique est un candidat pour la detection precoce et le suivi longitudinal de la maladie d’Alzheimer a travers l’etude de l’atrophie cerebrale. Objectifs Les algorithmes permettant l’etude de l’atrophie cerebrale doivent etre testes pour eprouver leur capacite de localisation et de quantification en termes de robustesse et de precision. Methodes Nous avons developpe un algorithme permettant d’introduire, sur des images reelles, des atrophies de localisation et de quantification controlables. Nous avons simule differents degres d’atrophie sur douze images de sujets sains, puis teste un representant de chacune des deux grandes classes d’algorithmes de la litterature : VBM (detection voxel a voxel en analyse transverse de groupes) et SIENA (mesure du deplacement de la frontiere cerebrale en analyse individuelle longitudinale). Resultats Selon les parametrages utilises lors des tests statistiques, soit VBM n’a pas permis de detecter les atrophies simulees, soit la detection a ete entachee de nombreux faux positifs. SIENA a permis de calculer pour chaque atrophie un indice global. Cependant, cet indice a sous estime l’atrophie ; il etait de plus biaise par les pretraitements des images et presentait une forte variabilite entre individus. Discussion L’utilisation clinique fait appel a une methode fournissant une localisation et une quantification la plus locale possible de l’atrophie et presentant un parametrage simple. VBM souffre d’un parametrage complexe et ne permet que la localisation. SIENA permet la localisation et la quantification, mais cette derniere est globale, imprecise et variable entre individus. Conclusion Aucune des methodes testees n’est entierement adaptee aux besoins cliniques. Nous developpons donc une methode originale, basee sur l’epaisseur corticale, fournissant des informations quantitatives locales de l’atrophie.

N - 4 Le mouvement dans la perception du temps : étude en IRMf

Introduction La perception du temps est une faculte importante pour l’homme. Elle fait partie de la vie courante, permet de planifier, controler et realiser des actions dans un environnement en mouvement. Objectifs Dans notre etude nous cherchons a montrer, grâce a l’imagerie cerebrale (IRMf), la modulation, due a la presence de mouvement, de l’activation des aires impliquees dans la perception du temps. Methodes Des stimuli visuels, fixes (condition controle) ou en mouvement, etaient presentes par couple et le sujet devait estimer si la duree du second stimulus etait egale ou differente de celle du premier. Les sept sujets etaient de sexe feminin, droitiers, avec une moyenne d’âge de 24 ans (± 1,56 ans). Les donnees d’imagerie ont ete analysees avec le logiciel SPM. Nous avons choisi de contraster les conditions avec mouvement a la condition controle. Resultats Nos resultats montraient que les conditions presentant du mouvement activaient les aires connues dans la perception du temps : aires corticales (cortex frontal, cortex parietal, aires motrices et aires cingulaires) et sous corticales (ganglions de la base et noyaux gris centraux). Le contraste condition avec mouvement versus condition fixe suractivait preferentiellement des zones sous corticales. Le jugement des sujets sur la duree d’un evenement etait aussi influence par la presence du mouvement. Discussion Les etudes sur la perception du temps montrent le role important des ganglions de la base. D’apres plusieurs auteurs, ils supporteraient le « pacemaker » du modele de l’horloge interne dont la frequence peut etre influencee par des elements exogenes. Les suractivations sous corticales peuvent donc etre expliquees par une influence du mouvement sur le rythme du pacemaker. Conclusion Nous rejoignons les etudes qui montrent que le rythme du pacemaker peut etre module par les caracteristiques du stimulus, ici le mouvement, influencant ainsi le jugement du sujet.