White Matter Signal Abnormalities Volume Research Articles

In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging.

Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.

White matter abnormalities and cognition in patients with conflicting diagnoses and CSF profiles.

To determine whether white matter changes influence progression of cognitive decline in individuals with clinically diagnosed Alzheimer disease (AD) and differing biomarker profiles. Two hundred thirty-six individuals from the Alzheimer's Disease Neuroimaging Initiative database with clinical diagnoses of cognitively normal older adult (older controls [OCs]), mild cognitive impairment, and AD were studied. Support vector machine experiments were first performed to determine the utility of various biomarkers for classifying individuals by clinical diagnosis. General linear models were implemented to assess the relationships between CSF measures of β-amyloid 1-42, phosphorylated tau181p, and MRI-based white matter signal abnormality (WMSA) volumes and cognitive decline. Analyses were performed across all patients as well as within subgroups of individuals that were defined by clinical cutoff points for both CSF measures. CSF biomarkers alone classified individuals with AD vs OCs with 82% accuracy, and the addition of WMSA did not enhance this. Both CSF biomarkers as well as WMSA volume significantly contributed to predicting cognitive decline in executive and memory domains when assessed across all 236 individuals. In individuals with pathologic levels of both CSF biomarkers, WMSA only significantly contributed to models of future executive function decline. In individuals with subpathologic CSF biomarker levels (levels similar to those in OC individuals), WMSA significantly contributed to prediction of memory decline and were the sole significant predictor of executive function decline. WMSA hold additional predictive power regarding cognitive progression in older individuals and are most effective as biomarkers in individuals who are cognitively impaired but do not fit the expected CSF biomarker profile of AD.

White matter signal abnormalities in former National Football League players

IntroductionLater-life brain alterations in former tackle football players are poorly understood, particularly regarding their relationship with repetitive head impacts (RHIs) and clinical function. We examined white matter signal abnormalities (WMSAs) and their association with RHIs and clinical function in former National Football League (NFL) players. MethodsEighty-six clinically symptomatic former NFL players and 23 same-age reportedly asymptomatic controls without head trauma exposure underwent magnetic resonance imaging and neuropsychological testing. FreeSurfer calculated WMSAs. A cumulative head impact index quantified RHIs. ResultsIn former NFL players, increased volume of WMSAs was associated with higher cumulative head impact index scores (P = .043) and worse psychomotor speed and executive function (P = .015). Although former NFL players had greater WMSA volume than controls (P = .046), these findings are inconclusive due to recruitment of controls based on lack of clinical symptoms and head trauma exposure. DiscussionIn former NFL players, WMSAs may reflect long-term microvascular and nonmicrovascular pathologies from RHIs that negatively impact cognition.

The functional connectome of cognitive reserve.

Cognitive Reserve (CR) designates the brain's capacity to actively cope with insults through a more efficient use of its resources/networks. It was proposed in order to explain the discrepancies between the observed cognitive ability and the expected capacity for an individual. Typical proxies of CR include education and Intelligence Quotient but none totally account for the variability of CR and no study has shown if the brain's greater efficiency associated with CR can be measured. We used a validated model to estimate CR from the residual variance in memory and general executive functioning, accounting for both brain anatomical (i.e., gray matter and white matter signal abnormalities volume) and demographic variables (i.e., years of formal education and sex). Functional connectivity (FC) networks and topological properties were explored for associations with CR. Demographic characteristics, mainly accounted by years of formal education, were associated with higher FC, clustering, local efficiency and strength in parietal and occipital regions and greater network transitivity. Higher CR was associated with a greater FC, local efficiency and clustering of occipital regions, strength and centrality of the inferior temporal gyrus and higher global efficiency. Altogether, these findings suggest that education may facilitate the brain's ability to form segregated functional groups, reinforcing the view that higher education level triggers more specialized use of neural processing. Additionally, this study demonstrated for the first time that CR is associated with more efficient processing of information in the human brain and reinforces the existence of a fine balance between segregation and integration. Hum Brain Mapp 37:3310–3322, 2016.. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

White matter signal abnormality quality differentiates mild cognitive impairment that converts to Alzheimer's disease from nonconverters

The objective of this study was to assess how longitudinal change in the quantity and quality of white matter signal abnormalities (WMSAs) contributes to the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The Mahalanobis distance of WMSA from normal-appearing white matter using T1-, T2-, and proton density–weighted MRI was defined as a quality measure for WMSA. Cross-sectional analysis of WMSA volume in 104 cognitively healthy older adults, 116 individuals with MCI who converted to AD within 3 years (mild cognitive impairment converter [MCI-C]), 115 individuals with MCI that did not convert in that time (mild cognitive impairment nonconverter [MCI-NC]), and 124 individuals with AD from the Alzheimer's Disease Neuroimaging Initiative revealed that WMSA volume was substantially greater in AD relative to the other groups but did not differ between MCI-NC and MCI-C. Longitudinally, MCI-C exhibited faster WMSA quality progression but not volume compared with matched MCI-NC beginning 18 months before MCI-C conversion to AD. The strongest difference in rate of change was seen in the time period starting 6 months before MCI-C conversion to AD and ending 6 months after conversion (p < 0.001). The relatively strong effect in this time period relative to AD conversion in the MCI-C was similar to the relative rate of change in hippocampal volume, a traditional imaging marker of AD pathology. These data demonstrate changes in white matter tissue properties that occur within WMSA in individuals with MCI that will subsequently obtain a clinical diagnosis of AD within 18 months. Individuals with AD have substantially greater WMSA volume than all MCI suggesting that there is a progressive accumulation of WMSA with progressive disease severity, and that quality change predates changes in this total volume. Given the timing of the changes in WMSA tissue quality relative to the clinical diagnosis of AD, these findings suggest that WMSAs are a critical component for this conversion and are a critical component of this clinical syndrome.

Dirty-Appearing White Matter in the Brain is Associated with Altered Cerebrospinal Fluid Pulsatility and Hypertension in Individuals without Neurologic Disease.

Aging of the healthy brain is characterized by focal or nonfocal white matter (WM) signal abnormality (SA) changes, which are typically detected as leukoaraiosis (LA). Hypertension is a risk factor for WM lesion formation. This study investigated whether LA might be associated with increased cerebrospinal fluid (CSF) pulsatility linked to arterial hypertension. A total of 101 individuals without neurologic diseases (53 females and 48 males) aged between 18 and 75 years underwent 3T brain MRI with cine phase contrast imaging for CSF flow estimation, after providing their informed consent. LA was defined as the presence of focal T2 WM SA changes and/or nonfocal uniform areas of signal increase termed dirty appearing white matter (DAWM). Relevant information relating to cardiovascular risk factors was also collected. When controlled for age and hypertension, significant partial correlations were observed between: DAWM volume and: net negative flow (r = -.294, P = .014); net positive flow (NPF) (r = .406, P = .001); and peak positive velocity (r = .342, P = .004). Multiple linear regression analysis revealed DAWM volume to be significantly correlated with CSF NPF (P = .019) and hypertension (P = .007), whereas T2 WM SA volume was only significantly correlated with age (P = .002). Combined DAWM and T2 WM SA volumes were significantly related with age (P = .001) and CSF peak negative velocity (P = .041). Rarefaction of WM leading to LA is a multifactorial process, in which formation of DAWM induced by hypertension and increased aqueductal CSF pulsatility, may play a contributory role. These two factors appear to act independently of each other in a process that is independent of age.

Macro- and micro-structural white matter differences correlate with cognitive performance in healthy aging.

Studies have shown that white matter (WM) volumetric reductions and overall degradation occur with aging. Nonetheless little is known about the WM alterations that may underlie different cognitive status in older individuals. The main goal of the present work was to identify and characterize possible macro and microstructural WM alterations that could distinguish between older healthy individuals with contrasting cognitive profiles (i.e., "poor" vs "good" cognitive performers). Structural and diffusion magnetic resonance imaging was performed in order to quantify local WM volumes, white matter signal abnormalities (WMSA) volume (a measure of lesion burden) and diffusion tensor imaging scalar maps known to probe WM microstructure. A battery of neurocognitive/psychological tests was administered to assess the cognitive performance. Poor performers showed a higher slope for the positive association between WMSA volume and age compared to good performers. Even when controlling for WMSA volume, poor performers also evidenced lower fractional anisotropy, as well as positive associations with age with higher slopes of regression parameters in radial and axial diffusivity. Altogether results suggest that cognitive performance is related to differences in WM, with poor cognitive performers displaying signs of faster aging in WM.

Effects of insulin resistance on white matter microstructure in middle-aged and older adults.

To investigate the potential relationship between insulin resistance (IR) and white matter (WM) microstructure using diffusion tensor imaging in cognitively healthy middle-aged and older adults. Diffusion tensor imaging was acquired from 127 individuals (age range 41-86 years). IR was evaluated by the homeostasis model assessment of IR (HOMA-IR). Participants were divided into 2 groups based on HOMA-IR values: "high HOMA-IR" (≥2.5, n = 27) and "low HOMA-IR" (<2.5, n = 100). Cross-sectional voxel-based comparisons were performed using Tract-Based Spatial Statistics and anatomically defined regions of interest analysis. The high HOMA-IR group demonstrated decreased axial diffusivity broadly throughout the cerebral WM in areas such as the corpus callosum, corona radiata, cerebral peduncle, posterior thalamic radiation, and right superior longitudinal fasciculus, and WM underlying the frontal, parietal, and temporal lobes, as well as decreased fractional anisotropy in the body and genu of corpus callosum and parts of the superior and anterior corona radiata, compared with the low HOMA-IR group, independent of age, WM signal abnormality volume, and antihypertensive medication status. These regions additionally demonstrated linear associations between diffusion measures and HOMA-IR across all subjects, with higher HOMA-IR values being correlated with lower axial diffusivity. In generally healthy adults, greater IR is associated with alterations in WM tissue integrity. These cross-sectional findings suggest that IR contributes to WM microstructural alterations in middle-aged and older adults.

Atlas-Guided Quantification of White Matter Signal Abnormalities on Term-Equivalent Age MRI in Very Preterm Infants: Findings Predict Language and Cognitive Development at Two Years of Age

The developmental significance of the frequently encountered white matter signal abnormality (WMSA) findings on MRI around term-equivalent age (TEA) in very preterm infants, remains in question. The use of conventional qualitative analysis methods is subjective, lacks sufficient reliability for producing accurate and reproducible WMSA diagnosis, and possibly contributes to suboptimal neurodevelopmental outcome prediction. The advantages of quantitative over qualitative diagnostic approaches have been widely acknowledged and demonstrated. The purpose of this study is to objectively and accurately quantify WMSA on TEA T2-weighted MRI in very preterm infants and to assess whether such quantifications predict 2-year language and cognitive developmental outcomes. To this end, we constructed a probabilistic brain atlas, exclusively for very preterm infants to embed tissue distributions (i.e. to encode shapes, locations and geometrical proportion of anatomical structures). Guided with this atlas, we then developed a fully automated method for WMSA detection and quantification using T2-weighted images. Computer simulations and experiments using in vivo very preterm data showed very high detection accuracy. WMSA volume, particularly in the centrum semiovale, on TEA MRI was a significant predictor of standardized language and cognitive scores at 2 years of age. Independent validation of our automated WMSA detection algorithm and school age follow-up are important next steps.

Association between white matter microstructure, executive functions, and processing speed in older adults: The impact of vascular health

Cerebral white matter damage is not only a commonly reported consequence of healthy aging, but is also associated with cognitive decline and dementia. The aetiology of this damage is unclear; however, individuals with hypertension have a greater burden of white matter signal abnormalities (WMSA) on MR imaging than those without hypertension. It is therefore possible that elevated blood pressure (BP) impacts white matter tissue structure which in turn has a negative impact on cognition. However, little information exists about whether vascular health indexed by BP mediates the relationship between cognition and white matter tissue structure. We used diffusion tensor imaging to examine the impact of vascular health on regional associations between white matter integrity and cognition in healthy older adults spanning the normotensive to moderate-severe hypertensive BP range (43-87 years; N = 128). We examined how white matter structure was associated with performance on tests of two cognitive domains, executive functioning (EF) and processing speed (PS), and how patterns of regional associations were modified by BP and WMSA. Multiple linear regression and structural equation models demonstrated associations between tissue structure, EF and PS in frontal, temporal, parietal, and occipital white matter regions. Radial diffusivity was more prominently associated with performance than axial diffusivity. BP only minimally influenced the relationship between white matter integrity, EF and PS. However, WMSA volume had a major impact on neurocognitive associations. This suggests that, although BP and WMSA are causally related, these differential metrics of vascular health may act via independent pathways to influence brain structure, EF and PS.

Regional White Matter Signal Abnormalities and Cognitive Correlates Among Geriatric Patients with Treated Cardiovascular Disease

The purpose of this study was to investigate the relations between regional white matter signal abnormalities (WMSA) and cognitive functioning among individuals being treated for cardiovascular risk factors and/or clinical events. Forty-one participants with cardiovascular disease underwent a comprehensive neuropsychological assessment and MRI. Total WMSAs were quantified using a semi-automated thresholding technique. Unique to this study, total WMSA volume was divided into three separate anatomically related regions: WMSA in the periventricular (PERIWMSA) region, WMSA adjacent to subcortical nuclei (SUBWMSA), and WMSA in the deep white matter (DEEPWMSA). A ratio of these measures to total cerebral brain volume was compared to cognitive measures assessing attention, executive functioning, psychomotor speed, immediate and delayed memory, language, and visuospatial functioning. PERIWMSA, SUBWMSA, and total WMSA were significantly associated with performance on measures of attention/processing speed. No other significant relationships between WMSA and cognition were noted. Secondary analyses suggested that PERIWMSA volume was increased in individuals with clinical evidence of atherosclerosis. These results emphasize the utility of studying the associations between regional WMSA and cognitive/functional performance in patients undergoing cardiovascular treatment.

Accrual of MRI white matter abnormalities in elderly with normal and impaired mobility

White matter signal abnormality (WMSA) is often present in the MRIs of older persons with mobility impairment. We examined the relationship between impaired mobility and the progressive accrual of WMSA. Mobility was assessed with the Short Physical Performance Battery (SPPB) and quantitative measures of gait and balance. Fourteen subjects had baseline and follow-up MRI scans performed 20 months apart. WMSA was detected and quantified using automated computer algorithms. In the control subjects, WMSA volume increased by 0.02±0.05% ICCV (percent intracranial cavity volume)/year while the WMSA of mobility impaired subjects increased five-times faster (0.10±0.10 ICCV/year, p=0.03). WMSA volume was related to some of the mobility measures and was sensitive to change which was not true of the other MRI variables. The study demonstrates the sensitivity of longitudinal automated volumetric analysis of WMSA to differentiate differences in the accrual rate of WMSA in groups selected on the basis of mobility. Based on these results, we propose that a subset of subjects with mobility impairment have accelerated, disease related WMSA accrual, thus explaining the rapid progression of mobility impairment in some older persons without apparent cause. This study demonstrates that quantitative MRI and performance measures can provide valuable insight into the rate of progression and pathophysiologic abnormalities underlying mobility impairment.