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• W2897710147 abstract "Subjective cognitive decline (SCD) could be a predictor of later decline to mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD)(Shu,et.al.2017), (Fernandez-Blazquez,et.al,2016). In this preclinical stage, the subtlety and spatial heterogeneity of white matter (WM) alterations often make it difficult, if not impossible, to test hypotheses using standard group-wise analytical design. In this study, we used a subject-specific approach to detect significant WM changes at the individual level. Seventy-eight subjects were recruited for this study from Indiana Alzheimer Disease Center. All participants underwent Hybrid Diffusion Imaging (HYDI) (Wu,et.al,2007), (Wu,et.al,2008) and detailed neuropsychological assessment (Table 1). Self-perceived decline in cognitive function was assessed via the cognitive change index (CCI) (Saykin,et.al,2006), (Rattanabannakit,et.al,2016), a recently proposed measure of perceived dysfunction in memory, executive, and language performance. Thirty-eight subjects with CCI>20 were considered as SCD and the remaining 40 were considered cognitively normal (CN). HYDI data were used to compute seven diffusion metrics using DTI, neurite orientation dispersion and density imaging (NODDI), and q-space imaging (Kodiweera,et.al,2016). Subject-specific analysis was performed using a “pothole” approach (White,et.al,2009) by z-transforming the diffusion metrics of each individual SCD subject according to the distributions created from the CN group (Figure 1). White-matter voxels with extreme z-scores defined as |z-score|>3 were summarized for each SCD subject. Illustration of subject-specific analysis. For each diffusion metric, a template (mean and standard deviation (SD)) is created from the CN group (step 1). The diffusion metric of an individual (i.e., SCD subject) is z-transformed on a voxel-wise basis using the control template (step 2). By selecting a threshold (in this case, ±2, step 3), an extreme z-score map with z-scores larger than the threshold is generated (step 4). A pothole approach used a fixed threshold whereas a more sophisticated approach such as DisCo-Z(Mayer, et al, 2014) adjusts the threshold according to group size and population distribution. Thirteen out of 38 SCD subjects (34%) were identified to have extreme z-scores suggestive of neurodegeneration (Table 2). White-matter changes in SCD demonstrated higher DTI metrics and NODDI-derived dispersion index (OD), but bi-directional changes in NODDI-derived intra-cellular volume fraction (Vic) and q-space tissue restriction measure (P0). Six out of the 13 significant SCD subjects were confirmed to have at least one AD risk factor (Table 2). In general, within each SCD subject, the locations of voxels with extreme z-scores tended to be overlapping or adjacent across diffusion metrics (Figure 2). The extreme diffusion metrics localized to the superior and posterior corona radiata, and superior longitudinal fasciculus. Anatomical locations of extreme voxels for the diffusion metrics in six SCD subjects labeled by S1 to S6. Subject-specific analysis can detect subtle white matter integrity changes in SCD. Future goals are to optimize the pothole analysis with DsiCo-Z (Mayer,et.al,2014) adjusting group size and population distributions and to correlate the extreme-voxel counts with outcome measures." @default.
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• W2897710147 date "2018-07-01" @default.
• W2897710147 modified "2023-10-12" @default.
• W2897710147 title "IC‐P‐157: ALTERATIONS IN WHITE‐MATTER DIFFUSION METRICS IN PRECLINICAL ALZHEIMER'S DISEASE: A SUBJECT‐SPECIFIC ANALYSIS" @default.
• W2897710147 doi "https://doi.org/10.1016/j.jalz.2018.06.2224" @default.
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