ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
|Principal Investigator's Name:||Emily Trittschuh|
|Institution:||Northwestern University, Feinberg School of Medicine|
|Department:||GRECC/Dept of Psychiatry and Behavioral Science|
|Country:||United States of America|
|Proposed Analysis:||Cortical Thickness Mapping Training Set ADNI Project Proposal – Emily H. Trittschuh I am currently a post-doctoral fellow at the Cognitive Neurology and Alzheimer’s Disease Center at Northwestern University’s Feinberg School of Medicine. My dissertation and previous research focused on how spatial attention, working memory, and oculomotor programming interact during visual search in younger and older adults. We found very interesting results regarding the planning of visual search and the differential involvement of posterior parietal cortices, especially along the intraparietal sulcus, and in frontal cortices at the junction of the superior frontal sulcus and precentral gyrus, an area referred to as the human frontal eye field. My previous research was based on neuropsychological assessment and fMRI methodologies. As part of my post-doctoral training, I have proposed to expand my studies by learning cortical thickness mapping techniques to investigate changes in the substrates of visual search in older adults, those with a diagnosis of MCI, and those with early AD. To this end, I am requesting that I be allowed access to the ADNI database of T1 images acquired from 3-Tesla magnets for a set of pilot images (4 Older Adult controls, 4 MCI, and 4 AD patients; n=12 total) with basic demographic information (gender, age, education) to be utilized for a future project feasibility assessment. Background: Cognitively-intact older individuals evidence structural changes in the brain with increasing age, indicating smaller grey, white, and total brain volumes (Good et al., 2001; Gur et al., 1991). In particular, grey matter volume decreases linearly with age and its loss appears to be accelerated bilaterally in the superior parietal lobe, the anterior frontal lobe, the insula, and the cingulate gyri (Good et al., 2001; Raz, 2000). Approaches to measuring in vivo cortical structural loss have included manual measurements of the cortex as well as automated techniques. Manual techniques are time-consuming and often rely on a single individual’s judgment. In these studies, single or multiple regions of interest are selected as whole brain measurements are not viable. However, manual tracing preserves individual sulcal and gyral pattern differences. Automated measures require that individual scans be pulled into a common brain coordinate system, a process called “normalization.” The warping this entails allows for whole brain or lobar studies, but limits spatial resolution and universal conclusions. Larger numbers of subjects can be studied with automated techniques such as voxel-based morphometry (Ashburner & Friston, 2000). Dale and Fischl (1999) developed an alternative approach to previous methods of measuring atrophy (FreeSurfer program). Their techniques utilize an automated method with good reliability and accuracy (intersubject standard deviation < 0.5mm) to create cortical thickness maps that follow the natural curvature and variations of the cerebral cortex. In addition to offering obvious advantages over manual methods, this technique offers the ability to correlate better the functional activation patterns with regional differences in cortical thickness (Fischl & Dale, 2000). In recent years, this type of mapping technique has been extended to investigate alterations of cortical thickness in patient populations such as individuals with multiple sclerosis providing further support for grey matter changes in addition to the hallmark white matter lesions (Sailer et al., 2003). Applications in schizophrenia show selected regions of cortical thinning (Kuperberg et al., 2003) that can also be demonstrated in patients’ non-schizophrenic relatives (Goghari, Rehm, Carter, & Macdonald, 2006). In healthy controls, cortical thickness mapping has been used to explore hemispheric asymmetry differences between genders (Luders et al., 2005). The Present Study: The goal of the present study is to investigate if the Freesurfer-based cortical thickness mapping methodology will allow for the accurate estimation of cortical thickness differences between older normal controls, MCI, and AD subjects. In particular, we wish to use this methodology to investigate cortical differences in brain regions that were previously difficult to accurately estimate based on prior volumetric techniques (e.g., voxel-based morphometry) I plan to pre-process the images using Freesurfer and then take the data to the Fischl lab in Boston at MGH to learn advanced techniques for group comparison and correlation with other factors of interest such as age. Should this training be successful, I will create a more specific and detailed project proposal for application with a larger set of ADNI subjects and with the additional goal of making correlations between structural changes in key brain regions associated with visual search with subjects’ performance on neuropsychological measures of working memory, attention, and visuomotor sequencing. References: Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry--the methods. Neuroimage, 11(6 Pt 1), 805-821. Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A, 97(20), 11050-11055. Goghari, V. M., Rehm, K., Carter, C. S., & Macdonald, A. W., 3rd. (2006). Regionally Specific Cortical Thinning and Gray Matter Abnormalities in the Healthy Relatives of Schizophrenia Patients. Cereb Cortex. Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N., Friston, K. J., & Frackowiak, R. S. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage, 14(1 Pt 1), 21-36. Gur, R. C., Mozley, P. D., Resnick, S. M., Gottlieb, G. L., Kohn, M., Zimmerman, R., et al. (1991). Gender differences in age effect on brain atrophy measured by magnetic resonance imaging. Proc Natl Acad Sci U S A, 88(7), 2845-2849. Kuperberg, G. R., Broome, M. R., McGuire, P. K., David, A. S., Eddy, M., Ozawa, F., et al. (2003). Regionally localized thinning of the cerebral cortex in schizophrenia. Arch Gen Psychiatry, 60(9), 878-888. Luders, E., Narr, K. L., Thompson, P. M., Rex, D. E., Jancke, L., & Toga, A. W. (2005). Hemispheric Asymmetries in Cortical Thickness. Cereb Cortex. Raz, N. (2000). Aging of the brain and its impact on cognitive performance: integration of structural and functional findings. In F. I. Craik & T. A. Salthouse (Eds.), The Handbook of Aging and Cognition (Second ed.). Mahwah, NJ: Lawrence Erlbaum Associates. Sailer, M., Fischl, B., Salat, D., Tempelmann, C., Schonfeld, M. A., Busa, E., et al. (2003). Focal thinning of the cerebral cortex in multiple sclerosis. Brain, 126(Pt 8), 1734-1744.|