Open Access Series of Imaging Studies: Longitudinal MRI Data in Nondemented and Demented Older Adults

TLDR

The Open Access Series of Imaging Studies provides publicly available neuroimaging datasets for research. The study demonstrates automated whole‑brain volume calculation to assess differences between normal aging and Alzheimer’s disease. The dataset includes 150 right‑handed adults (60–96 yr) scanned longitudinally on a single scanner with identical T1‑weighted protocols, yielding 373 sessions and high‑contrast images for automated analysis. Among the 150 participants, 72 remained nondemented, 64 were demented from the start (51 with CDR 0.5), and 14 progressed from nondemented to demented, illustrating the dataset’s utility for volume‑based aging and Alzheimer’s comparisons.

Abstract

Abstract The Open Access Series of Imaging Studies is a series of neuroimaging data sets that are publicly available for study and analysis. The present MRI data set consists of a longitudinal collection of 150 subjects aged 60 to 96 years all acquired on the same scanner using identical sequences. Each subject was scanned on two or more visits, separated by at least 1 year for a total of 373 imaging sessions. Subjects were characterized using the Clinical Dementia Rating (CDR) as either nondemented or with very mild to mild Alzheimer's disease. Seventy-two of the subjects were characterized as nondemented throughout the study. Sixty-four of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with CDR 0.5 similar level of impairment to individuals elsewhere considered to have “mild cognitive impairment.” Another 14 subjects were characterized as nondemented at the time of their initial visit (CDR 0) and were subsequently characterized as demented at a later visit (CDR > 0). The subjects were all right-handed and include both men (n = 62) and women (n = 88). For each scanning session, three or four individual T1-weighted MRI scans were obtained. Multiple within-session acquisitions provide extremely high contrast to noise, making the data amenable to a wide range of analytic approaches including automated computational analysis. Automated calculation of whole-brain volume is presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.