Prior work has shown that white matter fiber integrity decreases in Alzheimer's disease (AD) and mild cognitive impairment (MCI). This integrity can be quantified using diffusion tensor imaging techniques, which describe the anisotropic water movement in the brain. It is important to identify features that can predict the chance of conversion from MCI to AD within a certain time frame. In this study we applied tract-based spatial statistics (TBSS) in order to perform this task, overcoming limitations that are commonly associated with ROI-based approaches and voxel-based morphometry (VBM). Diffusion weighted images were taken from 15 healthy controls, 15 AD patients and 17 MCI patients. 8 MCI patients remained stable during 3 year follow-up investigations (“non-converters”, MCI-nc) and 9 converted to AD (“converters”, MCI-c). Significant differences between the MCI-nc and MCI-c groups were found in a large part of the corpus callosum using fractional anisotropy (FA) and radial diffusivity. In comparison, the MCI-c group did not differ significantly from the AD group and the MCI-nc group exhibited similar measurements as the control group. These results demonstrate that, although MCI-c and MCI-nc patients were clinically similar at time of inclusion, the MCI-c group already exhibited pathologic features associated with AD. This finding could lead to more powerful techniques in the early identification of AD and thus support an earlier and more successful treatment.
Diffusion tensor imaging (DTI) is an advanced MRI technique that provides
information about the fiber architecture of the brain by measuring the movement
of water protons. In white matter, the diffusion perpendicular to the fibers is
lower than parallel to the fibers. The degree of anisotropy can be related to
the tract integrity. Assuming that the displacement distribution is Gaussian,
diffusion can be described by a tensor, a 3 3 matrix that describes the
diffusion in 3D space. The direction of maximum diffusion, the principal direction,
corresponds to the first eigenvector, which is the direction parallel to the fiber
direction. Together with the eigenvalues the eigenvectors describe the properties
of the tensor. The eigenvalues are ordered as 1 2 3 [
Recent studies demonstrated a decrease of white matter integrity in MCI and
AD patients compared to healthy controls [
Materials and Methods 47 subjects were recruited, including 15 controls, 18 MCI patients and 15 AD patients with mean ages of 66 ( 7) years, 70 ( 5) years, and 72 ( 7) years, respectively. The clinical evaluation of all subjects included ascertainment of personal and family history as well as physical, neurological, and neuropsychological examination. Those with a history of ischemic heart disease, cancer, and cerebrovascular risk factors were excluded. MCI was defined by Levy’s criteria of Aging-associated cognitive decline. Mild to moderate Alzheimer’s disease was defined by the NINCDS-ADRDA-criteria. A clinical follow-up of the patients was done within three years after inclusion. From the MCI patients 8 remained stable and 9 converted to AD in this period. At the time of inclusion, the MMS of the AD group was 19.2, that of the healthy control group was 29.3, and that of the whole MCI group was 26.4. The MCI-nc group and the MCI-c group showed a comparable MMS of 26.8 and 26.2. After three years, the MME of the MCI-nc was 26.9. The MME of the MCI-c group, however, decreased significantly to 23.3 (Mann-Whitney: p=0.006). Diffusion weighed imaging was performed on a 1.5T whole body clinical scanner and a quadrature head coil (Magnetom Symphony, Siemens Medical Solutions, Erlangen, Germany) with a gradient strength of 40 mT/m. A single shot echoplanar imaging technique with a twice refocused spin echo diffusion preparation was employed using the following parameters: TR/Echo Time (TE) 4700/78 ms, field of view 240 mm, data matrix of 96 96 yielding an in plane resolution of 2.5 mm, 50 axial slices with a thickness of 2.5 mm and no gap, N = 12 gradient directions and two b-values (0 and 1000 s/mm2). In order to increase the stability, 5 subsequent Diffusion Tensor Imaging (DTI) datasets were acquired, spatially matched and averaged. Diffusion tensors were estimated using a linear least squares fit and FA values were calculated for all subjects, using
F A =
√ 3 √
2
where is the mean of the eigenvectors. Also the axial 1 and radial 2 +2 3
diffusivity were calculated. [
Figure 2a-c show the mean FA values, the axial diffusivities, and radial diffusivities on the corpus callosum in the anterior-posterior direction. The results of the t-tests are summarized in diagrams under each respective graph as well (Fig. 2d-f). The results are reported for the group comparisons controls/MCI-nc, MCI-nc/MCI-c and the MCI-c/AD, since these are adjacent pairs when ordering the groups by disease severity. When looking at the FA and radial diffusivity, the healthy controls and the MCI-nc group have similar values and the MCI-c and the AD group also. for the axial diffusivity this distinction is less clear. The MCI-nc/MCI-c group comparison shows significant differences in FA and radial diffusivity on many positions along the corpus callosum and only very few positions with significant differences for both other comparisons. However, for the axial diffusivity there are much less positions showing a significant difference on the MCI-nc/MCI-c group comparison and more on the controls/MCI-nc group comparison.
In this work we performed tract-specific analysis of diffusion on the corpus callosum, which is a structure that plays an important role in neurodegenerative diseases. In addition to other studies that focus on the differences between AD patients and healthy controls, we retrospectively looked at MCI data, trying to find early markers for the development of AD. Significant differences between MCI-nc and MCI-c were found at nearly all positions from splenium to genu of the corpus callosum when using FA and radial diffusivity as a measurement for tract integrity, indicating that these provide early pathologic hallmarks of AD that are clearly manifested in the diffusion images of MCI-c patients and are absent in those of MCI-nc patients. This is an important result since current clinical tests fail to separate the converting and non-converting MCI subjects at the time of inclusion. Furthermore, hardly any differences in FA or radial diffusivity appeared when comparing the MCI-c group with the AD group, indicating that these groups have similar fiber integrity. The same counts when comparing the healthy control group with the MCI-nc group. When using axial diffusivity as a measure the number of significant positions for the MCI-nc/MCI-c comparison was lower, whereas the number of significant positions for the controls/MCI-nc comparison increased, suggesting that this property is affected even earlier in the course of the disease progression. The results presented in this paper demonstrate the possibility of defining early predictors for Alzheimer’s disease. We showed that radial diffusivity and fractional anisotropy carry information that can help to predict the chances of conversion from MCI to AD, which is very important for early treatment and therapy planning.