# MRI Diffusion Connectomics-Based Characterization of Progression in Alzheimer's Disease
## 2 Materials and Methods
### Statistics  
We applied whole-brain deterministic tractography techniques to generate a high-dimensional dataset across 434 exams. Each subject had approximately 1.3 million feature measurements on average being evaluated for potential as a biomarker for characterizing AD, depending on the number of visits a subject participated in. The ADNI3 dataset includes detailed clinical biomarkers for most participants at each imaging session, providing tremendous benefit, as they offer potential indicators of early decline in the preclinical stages or for those with mild cognitive impairment (MCI). We targeted 16 neurosychological and neurobiological phenotypic characteristics (see Table 3) as response variables in our analysis of white matter tract features. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Phenotypic Characteristic** & **Range** & **Description** \\ \hline ADAS-11 (neuropsychological) & 0–70 & A rating scale to assess the severity of cognitive and non-cognitive dysfunction from mild to severe AD, ADAS-11 assesses the cognitive domains of memory, language, and praxis. Specific tasks include Word Recall, Naming Objects and Engineers, Commands, Constructional Praxis, Ideational Praxis, Orientation, Word Recognition, and Language \\ \hline ADAS-13 (neuropsychological) & 0–85 & A rating scale to assess cognitive domains hypothesized to be important treatment targets of antidementia drugs that are not assessed by the ADAS-11: attention and concentration, planning and executive function, verbal memory, nonverbal memory, and praxis. \\ \hline AV45 (PET image analysis) & & An imaging biomarker for amyloid plaque accumulation in subjects with cognitive impairment that may be attributed to the presence of Alzheimer’s disease. Average AV45 regional standardized uptake values of frontal, anterior cingulate, precuneus, and parietal cortex relative to the cerebellum. \\ \hline BRAIN VOLUME (MR image analysis) & Volume (mm\({}^{3}\)) of brain \\ \hline Diagnosis & [CN,MLCAD] & Diagnosis classification at scan \\ \hline ENTORHINAL VOLUME (MR image analysis) & Volume (mm\({}^{3}\)) of entorhinal cortex \\ \hline FDG (PET scan information) & Average fluorodeoxyglucose PET of angular, temporal, and posterior cingulate. It reflects loss of neuropil, loss of synapse, and functional impairment of neurons. Lower FDG-PET was regarded as a signal of neuronal hypometabolism due to neurodegeneration. \\ \hline FUSIFORM VOLUME (MR image analysis) & Volume (mm\({}^{3}\)) of fusiform \\ \hline HIPPCAMFUS VOLUME (MR image analysis) & Volume (mm\({}^{3}\)) of hippocampus \\ \hline ICV (MR image analysis) & Intracranial volume. In patients with dementia, but not in MCI, severity of cognitive impairment and ICV were moderately correlated. The effect of ICV on cognition was not mediated by hippocampal atrophy. \\ \hline MIDTEMPORAL VOLUME (MR image analysis) & Volume (mm\({}^{3}\)) of mid temporal \\ \hline VENTRICLE VOLUME (MR image analysis) & Volume (mm\({}^{3}\)) of ventricles \\ \hline CDR SB (neuropsychological) & 0–36 & Clinical Dementia Rating scale Sum of Boxes (CDR-SB) score. This score has been used to accurately stage severity of Alzheimer dementia and mild cognitive impairment (MCI). \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Table of ADNI biomarkers available per scan/session. We performed a univariate statistical analysis on each feature derived within our dataset to understand range, central tendency, standard deviation, and correlation to each of the 16 selected phenotypic characteristics provided by the ADNI as they related to cognitive decline. Cognitive decline is presented in ADNI data as a categorical variable representing diagnosis. Using our dataframe containing diffusion measurements derived from dMRI and T1-weighted images, we sought to answer the following research questions. * Do phenotypic characteristics predict cognitive decline within our current dataset?