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Amyloid deposition and CBF patterns predict conversion of mild cognitive impairment to dementia

Overview of attention for article published in Neurological Sciences, June 2018
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Title
Amyloid deposition and CBF patterns predict conversion of mild cognitive impairment to dementia
Published in
Neurological Sciences, June 2018
DOI 10.1007/s10072-018-3477-0
Pubmed ID
Authors

Takayuki Kikukawa, Takato Abe, Suzuka Ataka, Haruna Saito, Itsuki Hasegawa, Toshikazu Mino, Jun Takeuchi, Joji Kawabe, Yasuhiro Wada, Yasuyoshi Watanabe, Yoshiaki Itoh

Abstract

Mild cognitive impairment (MCI) can include the transition from a normal state to dementia. To explore biomarkers for the development of dementia, we performed an 18-month follow-up study in 28 patients with amnestic MCI. Amyloid deposition was examined using PiB PET, and cerebral blood flow (CBF) was examined using SPECT. Cognitive function was periodically assessed. The rate of conversion to dementia was higher in the PiB-positive/equivocal group (74%) than in the PiB-negative group (33%) (p = 0.041). Perfusion SPECT was performed in 16 patients. MCI patients with an AD-characteristic pattern of reduced CBF had a higher PiB-positive/equivocal rate (82%) than those with a non-AD pattern (20%) (p = 0.018), and patients with an AD pattern had a higher conversion rate (82%) than those with a non-AD pattern (40%) (p = 0.094). Clinically, all PiB-positive converters were diagnosed as having Alzheimer's disease (AD), whereas PiB-negative converters were thought to have some form of dementia other than AD. Amyloid PET is useful for predicting conversion to AD in MCI patients. A pattern analysis of perfusion SPECT findings might also be helpful for predicting conversion to AD, but with a lower specificity.

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The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 15%
Researcher 4 10%
Other 3 7%
Unspecified 2 5%
Student > Ph. D. Student 2 5%
Other 3 7%
Unknown 21 51%
Readers by discipline Count As %
Medicine and Dentistry 8 20%
Psychology 3 7%
Unspecified 2 5%
Environmental Science 1 2%
Linguistics 1 2%
Other 3 7%
Unknown 23 56%