Regional rates of neocortical atrophy from normal aging to early Alzheimer disease  

Oleh:

McDonald, C. R. ; McEvoy, L. K. ; Gharapetian, L.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Neurology (Official Journal of The American Academy of Neurology) vol. 73 no. 06 (Aug. 2009), page 457-465.
Topik: MILD COGNITIVE IMPAIRMENT; MINI-MENTAL STATE EXAMINATION

Ketersediaan

Perpustakaan FK Nomor Panggil: N11.K.2009.06 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Objective: To evaluate the spatial pattern and regional rates of neocortical atrophy from normal aging to early Alzheimer disease (AD). Methods: Longitudinal MRI data were analyzed using high-throughput image analysis procedures for 472 individuals diagnosed as normal, mild cognitive impairment (MCI), or AD. Participants were divided into 4 groups based on Clinical Dementia Rating Sum of Boxes score (CDR-SB). Annual atrophy rates were derived by calculating percent cortical volume loss between baseline and 12-month scans. Repeated-measures analyses of covariance were used to evaluate group differences in atrophy rates across regions as a function of impairment. Planned comparisons were used to evaluate the change in atrophy rates across levels of disease severity. Results: In patients with MCI–CDR-SB 0.5–1, annual atrophy rates were greatest in medial temporal, middle and inferior lateral temporal, inferior parietal, and posterior cingulate. With increased impairment (MCI–CDR-SB 1.5–2.5), atrophy spread to parietal, frontal, and lateral occipital cortex, followed by anterior cingulate cortex. Analysis of regional trajectories revealed increasing rates of atrophy across all neocortical regions with clinical impairment. However, increases in atrophy rates were greater in early disease within medial temporal cortex, whereas increases in atrophy rates were greater at later stages in prefrontal, parietal, posterior temporal, parietal, and cingulate cortex. Conclusions: Atrophy is not uniform across regions, nor does it follow a linear trajectory. Knowledge of the spatial pattern and rate of decline across the spectrum from normal aging to Alzheimer disease can provide valuable information for detecting early disease and monitoring treatment effects at different stages of disease progression.

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