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P2‐439: IDENTIFICATION OF FTD CANDIDATES IN MCI‐SNAP GROUPS BY CORTICAL THICKNESS ANALYSIS
Author(s) -
Esteban Eva,
Buckley Chris J.,
Wilkens Paul J.
Publication year - 2018
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2018.06.1131
Subject(s) - atrophy , frontotemporal dementia , dementia , psychology , audiology , medicine , hippocampal formation , post hoc analysis , cerebral atrophy , biomarker , amyloid (mycology) , pathology , neuroscience , nuclear medicine , disease , chemistry , biochemistry
The global ranking was obtained by averaging the rankings for each label over all the classifiers. Pairwise Pearson correlations between all structures were calculated to assess where the redundancy of information could influence the ranking. Results: High left-right correlation, particularly (r>0.9) in the lateral ventricles, thalami and white matter (frontal, parietal, insula), indicates strong hemispheric symmetry in atrophy patterns. High correlations were also present in some of the highestranking features for detecting disease progression. For example, CSF regions (including lateral ventricles) ranked amongst the most discriminative of features, and the correlation matrix (figure) highlights that these features are strongly correlated with many regions throughout the brain. Conclusions:Our analysis revealed strong correlations across regional atrophy rates. These correlations must be considered when examining the most relevant features extracted by common multivariate techniques.