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[P2–329]: FP‐CIT IMAGING IN MILD NEUROCOGNITIVE DISORDER WITH LEWY BODIES
Author(s) -
Donaghy Paul C.,
O'Brien John T.,
Colloby Sean J.,
Lloyd Jim,
Petrides George,
Taylor JohnPaul,
Thomas Alan
Publication year - 2017
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.2017.06.983
Subject(s) - dementia with lewy bodies , lewy body , parkinsonism , rem sleep behavior disorder , dementia , neurocognitive , psychology , medicine , biomarker , spect imaging , neuropsychology , parkinson's disease , disease , pathology , psychiatry , nuclear medicine , cognition , biochemistry , chemistry
(RSNs) that best discriminate SCI, MCI, and AD groups from each other, and determine the relation of discriminative networks to cognitive functions. Methods: 37 SCI, 26 MCI and 8 AD participants underwent detailed neuropsychological assessment and resting state MRI. RSNs were obtained by using independent component analysis (ICA) in Group-ICA fMRI Toolbox (GIFT). Scores representing the expression level of specific networks in each subject were obtained by calculating the dot product of the subject’s and group spatial maps. Results: Forward conditional binary logistic regression analysis between SCI and MCI groups yielded 2 ICs that could discriminate the groups with an accuracy of 61.9% (p<0.02; R1⁄40.16). In the MCI group, salience network (SN) scores were higher and the posterior default mode network (DMN) scores were lower. Logistic regression analysis between the SCI and AD groups yielded 3 ICs with a discrimination accuracy of 88.9% (p<0.001; R1⁄40.54). The expression of the SN was higher, while the expression of the posterior and parahippocampal sub-components of the DMN were lower in AD group. Finally, logistic regression analysis between MCI and AD groups yielded 2 discriminative ICs with accuracy of 82.4% (p<0.05; R1⁄40.26). Expression scores of both the posterior DMN and the language network were lower in AD group. With regard to the relationship between network expression scores and cognitive scores of the overall sample, a number of positive correlations with the DMN and negative with the SN are found (r values range between -.30 and .37, p<.02). Conclusions: Our findings are in line with previous research showing that connectivity changes within and among the particular ICNs are discriminatory among different stages of the AD continuum; further research is needed to show whether these could be used as a biomarker in the individual level. This study is supported by Turkish Scientific and Technological Research Council (TUBITAK) Project #114E053 and Turkish Ministry of Development Project #2010K120330.