PurposeDetermine whether white matter signal fluctuation on T2* weighted BOLD contrast images are associated with aging and cerebral small vessel disease (SVD).MethodologyResting state BOLD data were collected with a 250 ms repetition time (TR) to achieve unaliased, ungated cardiac sampled BOLD (cs-BOLD) images on 11 young adult controls, 10 healthy older adult controls and 7 adults with extensive white matter hyperintensities (WMH) from SVD. Tissue classes (WM and GM) were segmented on T1 images. WMH were identified on FLAIR images in the SVD group. Raw physiological noise (σphysio) and cardiac pulsatility (i.e. fluctuations at the cardiac frequency) were calculated voxel wise and group differences were tested by ANOVA. It was also possible to calculate σphysio in 2s TR cardiac aliased whole-brain BOLD (wb-BOLD) data (N = 84) obtained from the International Consortium for Brain Mapping.ResultsCS-BOLD metrics showed an aging and SVD effects (p<0.0005). Covariates such as thermal noise, WM volume and partial volume did not influence the significant aging effect seen on the cardiac pulsatility metric (p<0.017) but did influence the σphysio (p = 0.184). As a verification of the cs-BOLD findings, the wb-BOLD also showed a linear aging effect of σphysio in WM. In the SVD adults, cardiac pulsatility and σphysio were lower in WMH regions compared to normal appearing white matter (NAWM) regions (p<0.0013 and p<0.002, respectively). Cardiac pulsatility was better able to distinguish WMH regions from NAWM than σphysio as measured by effect size (Cohen’s d 2.2 and 0.88, respectively).ConclusionNAWM was found to have graded increases in cardiac pulsations due to age and SVD, independently. Within SVD participants, WMH lesions had reduced physiological noise compared to NAWM. Cardiac pulsatility in resting BOLD data may provide a complementary dynamic measure of WM integrity to add to static FLAIR anatomical images.

The objective of this study was to determine whether physiological fluctuations in white matter (PFWM) on resting-state functional magnetic resonance images could be used as an index of neurodegeneration and Alzheimer's disease (AD). Using resting-state functional magnetic resonance image data from participants in the Alzheimer's Disease Neuroimaging Initiative, PFWM was compared across cohorts: cognitively healthy, mild cognitive impairment, or probable AD. Secondary regression analyses were conducted between PFWM and neuroimaging, cognitive, and cerebrospinal fluid biomarkers. There was an effect of cohort on PFWM (t = 5.08, degree of freedom [df] = 424, p < 5.7 × 10(-7)), after accounting for nuisance effects from head displacement and global signal (t > 6.16). From the neuroimaging data, PFWM was associated with glucose metabolism (t = -2.93, df = 96, p = 0.004) but not ventricular volume (p < 0.49) or hippocampal volume (p > 0.44). From the cognitive data, PFWM was associated with composite memory (t = -3.24, df = 149, p = 0.0015) but not executive function (p > 0.21). PFWM was not associated with cerebrospinal fluid biomarkers. In one final omnibus model to explain PFWM (n = 124), glucose metabolism (p = 0.04) and cohort (p = 0.008) remained significant, as were global and head motion root-mean-square terms, whereas memory was not (p = 0.64). PFWM likely reflects end-arteriole intracranial pulsatility effects that may provide additional diagnostic potential in the context of AD neurodegeneration.