Neuroimagerie de la maladie d’Alzheimer : synthèse et apport à la compréhension des mécanismes physiopathologiques

Abstract

Alzheimer's disease has become a major public health issue for occidental societies. Since animal models of Alzheimer's disease currently fail to perfectly mimic pathophysiological mechanisms or the manifestations of the disease, in vivo neuroimaging has a key role in better understanding the pathophysiology of Alzheimer's disease. The diversity of anatomical and functional neuroimaging techniques - anatomical (T1-MRI), functional (fMRI) and diffusion tensor imaging (DTI) via magnetic resonance imaging (MRI) as well as position emission tomography coupled to fluorodeoxyglucose ((18)FDG-PET) - offers a large possibility of investigation of brain alterations in Alzheimer's disease. These techniques have thus provided morphological and functional brain alterations mapping of Alzheimer's disease: on one hand grey matter atrophy first concerns the medial temporal lobe before extending to the temporal neocortex and then other neocortical areas; on the other hand, metabolic alterations are first located within the posterior cingulate cortex and then reach the temporo-parietal area as well as the prefrontal cortex, especially in its medial part. Assessments of white matter alterations with DTI have highlighted a variety of tract alterations including the cingulum bundle, a white matter tract connecting the medial temporal lobe to the posterior cingulate cortex. Finally fMRI activation studies have evidenced compensatory mechanisms through hyperactivations in Alzheimer's disease patients. Altogether these results have led to the hypothesis of two major pathophysiological mechanisms in Alzheimer's disease: on one hand compensatory mechanisms in regions where atrophy exceeds metabolic alterations, on the other disconnection between medial temporal lobe and posterior cingulate cortex through the cingulum bundle, accounting for higher metabolic than structural alterations in the posterior cingulate cortex. Our work has extensively contributed to this disconnection hypothesis thanks to the use of cross-sectional and longitudinal multi-modal neuroimaging approaches. It has underlined the relevance of distant over local mechanisms in the pathophysiology of Alzheimer's disease and offers new perspectives to the exploration of the neural bases of cognitive impairments in this disorder.

Biomarkers of Cognitive Training Effects in Aging

“…Compensatory recruitment can involve the hemispheric homologues (see HAROLD model [hemispheric asymmetry reduction in older adults] proposed by Cabeza [20]) or anterior recruitment (see PASA [posterior–anterior shift in aging] in Davis et al [21]). Functional brain imaging also shows impairments early in the development of AD [22–24]. Reduced activation is found in the medial temporal areas but also in some regions of the prefrontal cortex of AD patients.…”

Three-Dimensional Face Recognition in Mild Cognitive Impairment: A Psychophysical and Structural MR Study

“…Of interest, the neural substrates of SFM perception in MCI patients were found to predominantly relate to aberrant patterns of activation in fusiform face area/occipital face area (FFA/OFA) in the presence of normal recruitment of motion selective areas, suggesting the activation pattern within the ventral visual stream as a putative biomarker for MCI (Graewe et al, 2013). The study of visuospatial perception in the MCI group using an experimental paradigm requiring integration of dorsal and ventral processing may be important to clarify the role of these two visual pathways in the prediction of AD and better understand its pathophysiology, in addition to medial temporal lobe areas already known to be affected in this disorder (Jacobs et al, 2012;McKee et al, 2006;Villain, Chetelat, Desgranges, & Eustache, 2010;Villain, Fouquet, et al, 2010).…”

A large scale multivariate parallel ICA method reveals novel imaging–genetic relationships for Alzheimer's disease in the ADNI cohort

“…MRI captures robust phenotypic neuroanatomical LOAD biomarkers, most consistently implicating posterior cingulate and entorhinal cortices, hippocampus and other medial temporal structures (Jack et al, 2010a; Jack et al, 2010b; Smith, 2010; Villain et al, 2010) corresponding to sites of early, severe LOAD-related neuropathology. Imaging genetics attempts to bridge genetic variations with phenotypic trait markers, relating genotypic variations to underlying biological disease etiologies and increasing statistical power, thereby requiring smaller sample sizes (Potkin et al, 2009).…”