Research ReportLongitudinal white matter changes in Alzheimer's disease: A tractography-based analysis study
Introduction
Alzheimer's disease (AD) is the most common cause of dementia, and the number of AD patients have been increasing in recent years. AD shows symptoms of memory impairment and disturbance in orientation in its early stage, and then shows further higher brain dysfunction, such as visuospatial disturbance and executive dysfunction with disease progression. AD shows brain atrophy with disease progression. In imaging studies of AD, it has been shown that the medial temporal lobe (MTL) structures become atrophied in the early stage, and further atrophy progressively spreads to the neocortical regions. Although AD is considered to affect mainly the cortical gray matter, pathological changes are also observed in the white matter, such as the loss of axons and oligodendrocytes together with reactive astrocytosis (Kobayashi et al., 2002, Roth et al., 2005). The executive function is consequent on activating the interaction across the several cortical regions, and it is considered that white matter abnormalities are related to the various cognitive dysfunction (Delbeuck et al., 2007, Fellgiebel et al., 2008, Bozzali et al., 2011). Therefore, the neural connectivities across brain regions are important to comprehend the pathophysiology of AD.
Diffusion tensor imaging (DTI) is based on evaluating the random motion of water molecules, and can noninvasively examine neural microstructural tissue organization. In region of interest (ROI) analysis, microstructural damage is shown in the frontal, temporal regions or in the hippocampus in AD (Chen et al., 2009; Hong et al., 2010). The voxel-based morphometric analysis (VBA) in AD is known to show abnormality in the medial temporal structure and the hippocampus (Di. Paola et al., 2007, Rose et al., 2008). Furthermore, the tract-based analysis, which extracts the diffusion parameters along the reconstructed white matter bundles, shows microstructural damage in the uncinate fasciculus, cingulated fasciculus, and the corpus callosum (Kiuchi et al., 2009, Nakata et al., 2008, Pievani et al., 2010; Yasmin et al., 2008). Also, AD is a progressive neurodegenerative disease and shows atrophic changes and various clinical symptoms with disease progression. Matsuda et al. (2002) reported that progressive medial temporal lobe atrophy in a 3 dimension-magnetic resonance imaging (MRI) follow-up study was investigated in AD patients. Taken together, the research on longitudinal white matter changes would be important to understand AD pathophysiology. However, to the best of our knowledge, a follow-up DTI study for white matter changes in AD has not been conducted.
In this study, we followed AD patients from the early stage to the moderate, and investigated their longitudinal white matter changes with disease progression. In the course of AD, pathological neuronal change begins in the medial temporal regions such as enthorhinal cortex, hippocampus and parahippocampus, which subsequently spreads to the neocortical regions with temporal, parietal and frontal cortex (Braak and Braak, 1995). Thus, pathological alterations in AD occur in temporal regions of the brain. Therefore, in recent study, we investigated three major white matter bundles, the uncinate fasciculus (UNC), the inferior longitudinal fasciculus (ILF) and the inferior occipitofrontal fasciculus (IOFF). The UNC is considered to play an important role in memory and cognition (Highley et al., 2002), and the ILF and IOFF are related to executive functions such as emotional process, object cognition, verbal and visual memory and visuospatial cognition (Chanraud et al., 2010, Kiuchi et al., 2010, Kringelbach, 2005). We hypothesized that the disruption in major white matter bundles can cause memory impairment or high cognitive impairments, and the connectivity of white matter tracts is impaired with disease progression.
In this study, we employed tract-based analysis to examine microstructural white matter changes with several major tracts in AD patients. Tract based analysis assembles the local diffusion tensor data into tracts using scalar metrics, such as fractional anisotropy (FA) and apparent diffusion coefficient (ADC). Furthermore, the coordinates of the tensor matrix can be diagonalized to extract the three eigenvalues; λ1, λ2, and λ3 derived from the main eigenvectors of diffusion elements. The combination of these eigenvalues defines diffusion parameters, the axial diffusivity (DA), in parallel with axon fibers, and radial diffusivity (DR), perpendicular to axon fibers (Basser and Pierpaoli, 1998, Song et al., 2002, Sun et al., 2005). Thus, tract-based analysis can evaluate the specific anatomical localization of a single tract and allow measurement throughout the length of the bundles.
Section snippets
demographic data
The demographic and neuropsychological characteristics are shown in Table 1. No significant differences were noted in age and educational level between AD patients and normal controls. Between baseline and follow-up, AD patients showed significant decline in Mini Mental state Examination (MMSE) and Alzheimer's Disease Assessment Scale-cognitive component-Japanese version (ADAS-Cog.) scores (p<0.005).
FA and ADC
Table 2 shows the FA and ADC values of the UNC, ILF and IOFF for all the groups. Among the AD
Discussion
The present study explored the white matter microstructural abnormalities in AD patients with disease progression using tractography-based analysis. To the best of our knowledge, this is the first study where AD patients were followed and assessed for longitudinal changes of their white matter bundles. In this study, we found mean FA reduction of the bilateral UNC in the course of clinical follow-up among AD patients. In addition, compared with normal controls, white matter microstructural
Subjects
The subjects in this study were 35 AD patients (11 males and 24 females) with probable AD and age-matched 29 normal controls (12 males and 17 females), recruited from the Department of Psychiatry, Nara Medical University, Kashihara, Japan. Probable AD was diagnosed according to the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria (McKhann et al., 1984). Among the AD patients, 26 took 5
Acknowledgment
We thank Mr. Jose M. Morales who kindly assist with reading of the abstract. We also thank all colleagues and participants in the recent study.
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