Evaluation of noise regression techniques in resting-state fMRI studies using data of 434 older adults

Subject motion is a well-known confound in resting-state functional MRI (rs-fMRI) and the analysis of functional connectivity. Consequently, several clean-up strategies have been established to minimize the impact of subject motion. Physiological signals in response to cardiac activity and respiration are also known to alter the apparent rs-fMRI connectivity. Comprehensive comparisons of common noise regression techniques showed that the Independent Component Analysis based strategy for Automatic Removal of Motion Artifacts (ICA-AROMA) was a preferred pre-processing technique for teenagers and adults. However, motion and physiological noise characteristics may differ substantially for older adults. Here, we present a comprehensive comparison of noise-regression techniques for older adults from a large multi-site clinical trial of exercise and intensive pharmacological vascular risk factor reduction. The Risk Reduction for Alzheimer\u27s Disease (rrAD) trial included hypertensive older adults (60-84 years old) at elevated risk of developing Alzheimer\u27s Disease (AD). We compared the performance of censoring, censoring combined with global signal regression, non-aggressive and aggressive ICA-AROMA, as well as the Spatially Organized Component Klassifikator (SOCK) on the rs-fMRI baseline scans from 434 rrAD subjects. All techniques were rated based on network reproducibility, network identifiability, edge activity, spatial smoothness, and loss of temporal degrees of freedom (tDOF). We found that non-aggressive ICA-AROMA did not perform as well as the other four techniques, which performed table with marginal differences, demonstrating the validity of these techniques. Considering reproducibility as the most important factor for longitudinal studies, given low false-positive rates and a better preserved, more cohesive temporal structure, currently aggressive ICA-AROMA is likely the most suitable noise regression technique for rs-fMRI studies of older adults

Rationale and Methods for a Multicenter Clinical Trial Assessing Exercise and Intensive Vascular Risk Reduction in Preventing Dementia (rrAD Study)

Alzheimer\u27s Disease (AD) is an age-related disease with modifiable risk factors such as hypertension, hypercholesterolemia, obesity, and physical inactivity influencing the onset and progression. There is however, no direct evidence that reducing these risk factors prevents or slows AD. The Risk Reduction for Alzheimer\u27s Disease (rrAD) trial is designed to study the independent and combined effects of intensive pharmacological control of blood pressure and cholesterol and exercise training on neurocognitive function. Six hundred and forty cognitively normal older adults age 60 to 85 years with hypertension and increased risk for dementia will be enrolled. Participants are randomized into one of four intervention group for two years: usual care, Intensive Reduction of Vascular Risk factors (IRVR) with blood pressure and cholesterol reduction, exercise training (EX), and IRVR+EX. Neurocognitive function is measured at baseline, 6, 12, 18, and 24 months; brain MRIs are obtained at baseline and 24 months. We hypothesize that both IRVR and EX will improve global cognitive function, while IRVR+EX will provide a greater benefit than either IRVR or EX alone. We also hypothesize that IRVR and EX will slow brain atrophy, improve brain structural and functional connectivity, and improve brain perfusion. Finally, we will explore the mechanisms by which study interventions impact neurocognition and brain. If rrAD interventions are shown to be safe, practical, and successful, our study will have a significant impact on reducing the risks of AD in older adults. NCT Registration: NCT02913664