No abstract

Prior studies have demonstrated decreasing cerebral blood flow (CBF) in normal aging, but the full spatial pattern and potential mechanism of changes in CBF remain to be elucidated. Specifically, existing data have not been entirely consistent regarding the spatial distribution of such changes, potentially a result of neglecting the effect of age-related tissue atrophy in CBF measurements. In this work, we use pulsed arterial-spin labelling to quantify regional CBF in 86 cognitively and physically healthy adults, aged 23 to 88 years. Surface-based analyses were utilized to map regional decline in CBF and cortical thickness with advancing age, and to examine the spatial associations and dissociations between these metrics. Our results demonstrate regionally selective age-related reductions in cortical perfusion, involving the superior-frontal, orbito-frontal, superior-parietal, middle-inferior temporal, insular, precuneus, supramarginal, lateral-occipital and cingulate regions, while subcortical CBF was relatively preserved in aging. Regional effects of age on CBF differed from that of grey-matter atrophy. In addition, the pattern of CBF associations with age displays an interesting similarity with the default-mode network. These findings demonstrate the dissociation between regional CBF and structural alterations specific to normal aging, and augment our understanding of mechanisms of pathology in older adults.

The effect of carbon dioxide (CO 2 ) on cerebral metabolism is of tremendous interest to functional imaging. In particular, mild-to-moderate hypercapnia is routinely used in calibrated blood oxygenlevel dependent (BOLD)-functional magnetic resonance imaging (fMRI)-based quantification of cerebral oxidative metabolism changes (DCMRO 2 ), and relies on the assumption of a stable CMRO 2 during CO 2 challenges. However, this assumption has been challenged by certain animal studies, necessitating its verification in humans and under conditions customary to fMRI. We report, for the first time, on global DCMRO 2 measurements made noninvasively in humans during graded hypercapnia and hypocapnia. We used computerized end-tidal CO 2 modulation to minimize undesired concurrent changes in oxygen pressure, and our findings suggest that no significant change in global CMRO 2 is expected at the levels of end-tidal CO 2 changes customary to calibrated BOLD.

To understand and predict the blood-oxygenation level-dependent (BOLD) fMRI signal, an accurate knowledge of the relationship between cerebral blood flow (DeltaCBF) and volume (DeltaCBV) changes is critical. Currently, this relationship is widely assumed to be characterized by Grubb's power-law, derived from primate data, where the power coefficient (alpha) was found to be 0.38. The validity of this general formulation has been examined previously, and an alpha of 0.38 has been frequently cited when calculating the cerebral oxygen metabolism change (DeltaCMRo(2)) using calibrated BOLD. However, the direct use of this relationship has been the subject of some debate, since it is well established that the BOLD signal is primarily modulated by changes in 'venous' CBV (DeltaCBV(v), comprising deoxygenated blood in the capillary, venular, and to a lesser extent, in the arteriolar compartments) instead of total CBV, and yet DeltaCBV(v) measurements in humans have been extremely scarce. In this work, we demonstrate reproducible DeltaCBV(v) measurements at 3 T using venous refocusing for the volume estimation (VERVE) technique, and report on steady-state DeltaCBV(v) and DeltaCBF measurements in human subjects undergoing graded visual and sensorimotor stimulation. We found that: (1) a BOLD-specific flow-volume power-law relationship is described by alpha = 0.23 +/- 0.05, significantly lower than Grubb's constant of 0.38 for total CBV; (2) this power-law constant was not found to vary significantly between the visual and sensorimotor areas; and (3) the use of Grubb's value of 0.38 in gradient-echo BOLD modeling results in an underestimation of DeltaCMRo(2).

No abstract

Recent studies have demonstrated alterations in cortical gray to white matter tissue contrast with nondemented aging and in individuals with Alzheimer’s disease (AD). However, little information exists about the clinical relevance of such changes. It is possible that changes in MRI tissue contrast occur via independent mechanisms from those traditionally used in the assessment of AD associated degeneration such as hippocampal degeneration measured by more traditional volumetric magnetic resonance imaging (MRI). We created cortical surface models of 95 cognitively healthy individuals and 98 individuals with AD to characterize changes in regional gray and white matter T1-weighted signal intensities in dementia, and in normal aging and to evaluate how such measures related to classically described hippocampal and cortical atrophy. We found a reduction in gray matter to white matter tissue contrast throughout portions of medial and lateral temporal cortical regions as well as in anatomically associated regions including the posterior cingulate, precuneus, and medial frontal cortex. Decreases in tissue contrast were associated with hippocampal volume, however, the regional patterns of these associations differed for demented and nondemented individuals. In nondemented controls, lower hippocampal volume was associated with decreased gray/white matter tissue contrast globally across the cortical mantle. In contrast, in individuals with AD, selective associations were found between hippocampal volume and tissue contrast in temporal and limbic tissue. These results demonstrate that there are strong regional changes in neural tissue properties in AD which follow a spatial pattern including regions known to be affected from pathology studies. Such changes are associated with traditional imaging metrics of degeneration and may provide a unique biomarker of the tissue loss that occurs as a result of AD.

Diffusion tensor imaging (DTI) has been used extensively to investigate white matter (WM) microstructural changes during healthy adult aging. However, WM fibers are known to shrink throughout the lifespan, leading to larger interstitial spaces with age. This could allow more extracellular free water molecules to bias DTI metrics, which are relied upon to provide WM microstructural information. Using a cohort of 212 participants, we demonstrate that WM microstructural changes in aging are potentially less pronounced than previously reported once the free water compartment is eliminated. After free water elimination, DTI parameters show age-related differences that match histological evidence of myelin degradation and debris accumulation. The fraction of free water is further shown to associate better with age than any of the conventional DTI parameters. Our findings suggest that DTI analyses involving free water are likely to yield novel insight into retrospective re-analysis of data and to answer new questions in ongoing DTI studies of brain aging.

Previous studies have found that aperiodic, systemic low-frequency oscillations (sLFOs) are present in blood-oxygen-level-dependent (BOLD) data. These signals are in the same low frequency band as the "resting state" signal; however, they are distinct signals which represent non-neuronal, physiological oscillations. The same sLFOs are found in the periphery (i.e. finger tips) as changes in oxy/deoxy-hemoglobin concentration using concurrent near-infrared spectroscopy. Together, this evidence points toward an extra-cerebral origin of these sLFOs. If this is the case, it is expected that these sLFO signals would be found in the carotid arteries with time delays that precede the signals found in the brain. To test this hypothesis, we employed the publicly available MyConnectome dataset (a two-year longitudinal study of a single subject) to extract the sLFOs in the internal carotid arteries (ICAs) with the help of the T1/T2-weighted images. Significant, but negative, correlations were found between the LFO BOLD signals from the ICAs and (1) the global signal (GS), (2) the superior sagittal sinus, and (3) the jugulars. We found the consistent time delays between the sLFO signals from ICAs, GS and veins which coincide with the blood transit time through the cerebral vascular tree.