Intensive Blood Pressure Management Preserves Functional Connectivity in Patients with Hypertension from the Systolic Blood Pressure Intervention Randomized Trial.

BACKGROUND AND PURPOSE: The Systolic Blood Pressure Intervention (SPRINT) randomized trial demonstrated that intensive blood pressure management resulted in slower progression of cerebral white matter hyperintensities, compared with standard therapy. We assessed longitudinal changes in brain functional connectivity to determine whether intensive treatment results in less decline in functional connectivity and how changes in brain functional connectivity relate to changes in brain structure. MATERIALS AND METHODS: Five hundred forty-eight participants completed longitudinal brain MR imaging, including resting-state fMRI, during a median follow-up of 3.84 years. Functional brain networks were identified using independent component analysis, and a mean connectivity score was calculated for each network. Longitudinal changes in mean connectivity score were compared between treatment groups using a 2-sample t test, followed by a voxelwise t test. In the full cohort, adjusted linear regression analysis was performed between changes in the mean connectivity score and changes in structural MR imaging metrics. RESULTS: Four hundred six participants had longitudinal imaging that passed quality control. The auditory-salience-language network demonstrated a significantly larger decline in the mean connectivity score in the standard treatment group relative to the intensive treatment group (P = .014), with regions of significant difference between treatment groups in the cingulate and right temporal/insular regions. There was no treatment group difference in other networks. Longitudinal changes in mean connectivity score of the default mode network but not the auditory-salience-language network demonstrated a significant correlation with longitudinal changes in white matter hyperintensities (P = .013). CONCLUSIONS: Intensive treatment was associated with preservation of functional connectivity of the auditory-salience-language network, while mean network connectivity in other networks was not significantly different between intensive and standard therapy. A longitudinal increase in the white matter hyperintensity burden is associated with a decline in mean connectivity of the default mode network.

White Matter Lesion Penumbra Shows Abnormalities on Structural and Physiologic MRIs in the Coronary Artery Risk Development in Young Adults Cohort.

BACKGROUND AND PURPOSE: White matter lesions are 1 age-related manifestation of cerebrovascular disease, but subthreshold abnormalities have been identified in nonlesional WM. We hypothesized that structural and physiologic MR imaging findings of early cerebrovascular disease can be measured in middle-aged subjects in tissue adjacent to WM lesions, termed "penumbra." MATERIALS AND METHODS: WM lesions were defined using automated segmentation in 463 subjects, 43-56 years of age, from the Coronary Artery Risk Development in Young Adults (CARDIA) longitudinal observational cohort study. We described 0- to 2-mm and 2- to 4-mm-thick spatially defined penumbral WM tissue ROIs as rings surrounding WM lesions. The remaining WM was defined as distant normal-appearing WM. Mean signal intensities were measured for FLAIR, T1-, and T2-weighted images, and from fractional anisotropy, mean diffusivity, CBF, and vascular reactivity maps. Group comparisons were made using Kruskal-Wallis and pair-wise t tests. RESULTS: Lesion volumes averaged 0.738 ± 0.842 cm3 (range, 0.005-7.27 cm3). Mean signal intensity for FLAIR, T2, and mean diffusivity was increased, while T1, fractional anisotropy, and CBF were decreased in white matter lesions versus distant normal-appearing WM, with penumbral tissues showing graded intermediate values (corrected P < .001 for all group/parameter comparisons). Vascular reactivity was significantly elevated in white matter lesions and penumbral tissue compared with distant normal-appearing white matter (corrected P ≤ .001). CONCLUSIONS: Even in relatively healthy 43- to 56-year-old subjects with small white matter lesion burden, structural and functional MR imaging in penumbral tissue reveals significant signal abnormalities versus white matter lesions and other normal WM. Findings suggest that the onset of WM injury starts by middle age and involves substantially more tissue than evident from focal white matter lesions visualized on structural imaging.

A prospective study of focal brain atrophy, mobility and fitness.

BACKGROUND: The parallel decline of mobility and cognition with ageing is explained in part by shared brain structural changes that are related to fitness. However, the temporal sequence between fitness, brain structural changes and mobility loss has not been fully evaluated. METHODS: Participants were from the Baltimore Longitudinal Study of Aging, aged 60 or older, initially free of cognitive and mobility impairments, with repeated measures of fitness (400-m time), mobility (6-m gait speed) and neuroimaging markers over 4 years (n = 332). Neuroimaging markers included volumes of total brain, ventricles, frontal, parietal, temporal and subcortical motor areas, and corpus callosum. Autoregressive models were used to examine the temporal sequence of each brain volume with mobility and fitness, adjusted for age, sex, race, body mass index, height, education, intracranial volume and APOE ɛ4 status. RESULTS: After adjustment, greater volumes of total brain and selected frontal, parietal and temporal areas, and corpus callosum were unidirectionally associated with future faster gait speed over and beyond cross-sectional and autoregressive associations. There were trends towards faster gait speed being associated with future greater hippocampus and precuneus. Higher fitness was unidirectionally associated with future greater parahippocampal gyrus and not with volumes in other areas. Smaller ventricle predicted future higher fitness. CONCLUSION: Specific regional brain volumes predict future mobility impairment. Impaired mobility is a risk factor for future atrophy of hippocampus and precuneus. Maintaining fitness preserves parahippocampal gyrus volume. Findings provide new insight into the complex and bidirectional relationship between the parallel decline of mobility and cognition often observed in older persons.

Modifiable vascular risk factors, white matter disease and cognition in early Parkinson's disease.

BACKGROUND AND PURPOSE: Dementia in Parkinson's disease (PD) is common and disabling. Identification of modifiable risk factors for it is essential. Vascular risk factors (VRFs) may be associated with cognitive decline in early PD. Biomarkers that serve as surrogates of the long-term effect of VRFs on PD are needed. To that end, we aimed to quantitate white matter hyperintensities (WMH) in early PD, measure associations with VRFs and examine relationships between WMH and longitudinal cognition. METHODS: Participants in the Parkinson's Progression Markers Initiative study (141 patients with PD, 63 healthy controls) with adequate baseline structural brain magnetic resonance imaging data were included. Hypertension and diabetes history, and body mass index were combined to create a vascular risk score. WMH were quantitated via automated methods. Cognition was assessed annually with a comprehensive test battery. RESULTS: In the PD group, vascular risk score was associated with WMH for total brain (ß = 0.210; P = 0.021), total white matter (ß = 0.214; P = 0.013), frontal (ß = 0.220; P = 0.002) and temporal (ß = 0.212; P = 0.002) regions. Annual rate of change in global cognition was greater in those with higher vascular risk score (ß = -0.040; P = 0.007) and greater WMH (ß = -0.029; P = 0.049). Higher temporal WMH burden was associated with great decline over time in verbal memory (ß = -0.034; P = 0.031). CONCLUSIONS: In early PD, modifiable VRFs are associated with WMH on brain magnetic resonance imaging. Temporal WMH burden predicts decline in verbal memory. WMH may serve as a surrogate marker for the effect of VRFs on cognitive abilities in PD.

Neurobiological support to the diagnosis of ADHD in stimulant-naïve adults: pattern recognition analyses of MRI data.

OBJECTIVE: In adulthood, the diagnosis of attention-deficit/hyperactivity disorder (ADHD) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first time, machine learning-based pattern classification methods to structural MRI and diffusion tensor imaging (DTI) data obtained from stimulant-naïve adults with childhood-onset ADHD and healthy controls (HC). METHOD: Sixty-seven ADHD patients and 66 HC underwent high-resolution T1-weighted and DTI acquisitions. A support vector machine (SVM) classifier with a non-linear kernel was applied on multimodal image features extracted on regions of interest placed across the whole brain. RESULTS: The discrimination between a mixed-gender ADHD subgroup and individually matched HC (n = 58 each) yielded area-under-the-curve (AUC) and diagnostic accuracy (DA) values of up to 0.71% and 66% (P = 0.003) respectively. AUC and DA values increased to 0.74% and 74% (P = 0.0001) when analyses were restricted to males (52 ADHD vs. 44 HC). CONCLUSION: Although not at the level of clinically definitive DA, the neuroanatomical signature identified herein may provide additional, objective information that could influence treatment decisions in adults with ADHD spectrum symptoms.

State-dependent microstructural white matter changes in drug-naïve patients with first-episode psychosis.

BACKGROUND: Diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) microstructural abnormalities in schizophrenia. Whether or not such alterations could vary depending on clinical status (i.e. acute psychosis v. remission) remains to be investigated. METHODS: Twenty-five treatment-naïve first-episode psychosis (FEP) patients and 51 healthy-controls (HC) underwent MRI scanning at baseline. Twenty-one patients were re-scanned as soon as they achieved sustained remission of symptoms; 36 HC were also scanned twice. Rate-of-change maps of longitudinal DTI changes were calculated for in order to examine WM alterations associated with changes in clinical status. We conducted voxelwise analyses of fractional anisotropy (FA) and trace (TR) maps. RESULTS: At baseline, FEP presented reductions of FA in comparison with HC [p < 0.05, false-discovery rate (FDR)-corrected] affecting fronto-limbic WM and associative, projective and commissural fasciculi. After symptom remission, patients showed FA increase over time (p < 0.001, uncorrected) in some of the above WM tracts, namely the right anterior thalamic radiation, right uncinate fasciculus/inferior fronto-occipital fasciculus, and left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. We also found significant correlations between reductions in PANSS scores and FA increases over time (p < 0.05, FDR-corrected). CONCLUSIONS: WM changes affecting brain tracts critical to the integration of perceptual information, cognition and emotions are detectable soon after the onset of FEP and may partially reverse in direct relation to the remission of acute psychotic symptoms. Our findings reinforce the view that WM abnormalities in brain tracts are a key neurobiological feature of acute psychotic disorders, and recovery from such WM pathology can lead to amelioration of symptoms.

Relationship between APOE Genotype and Structural MRI Measures throughout Adulthood in the Study of Health in Pomerania Population-Based Cohort.

BACKGROUND AND PURPOSE: The presence of the apolipoprotein E ε4 allele is the strongest sporadic Alzheimer disease genetic risk factor. We hypothesized that apolipoprotein E ε4 carriers and noncarriers may already differ in imaging patterns in midlife. We therefore sought to identify the effect of apolipoprotein E genotype on brain atrophy across almost the entire adult age span by using advanced MR imaging-based pattern analysis. MATERIALS AND METHODS: We analyzed MR imaging scans of 1472 participants from the Study of Health in Pomerania (22-90 years of age). We studied the association among age, apolipoprotein E ε4 carrier status, and brain atrophy, which was quantified by using 2 MR imaging-based indices: Spatial Pattern of Atrophy for Recognition of Brain Aging (summarizing age-related brain atrophy) and Spatial Pattern of Abnormality for Recognition of Early Alzheimer Disease (summarizing Alzheimer disease-like brain atrophy patterns), as well as the gray matter volumes in several Alzheimer disease- and apolipoprotein E-related ROIs (lateral frontal, lateral temporal, medial frontal, and hippocampus). RESULTS: No significant association was found between apolipoprotein E ε4 carrier status and the studied ROIs or the MR imaging-based indices in linear regression models adjusted for age, sex, and education, including an interaction term between apolipoprotein E and age. CONCLUSIONS: Our study indicates that measurable apolipoprotein E-related brain atrophy does not occur in early adulthood and midlife and suggests that such atrophy may only occur more proximal to the onset of clinical symptoms of dementia.

Advanced brain aging: relationship with epidemiologic and genetic risk factors, and overlap with Alzheimer disease atrophy patterns.

We systematically compared structural imaging patterns of advanced brain aging (ABA) in the general-population, herein defined as significant deviation from typical BA to those found in Alzheimer disease (AD). The hypothesis that ABA would show different patterns of structural change compared with those found in AD was tested via advanced pattern analysis methods. In particular, magnetic resonance images of 2705 participants from the Study of Health in Pomerania (aged 20-90 years) were analyzed using an index that captures aging atrophy patterns (Spatial Pattern of Atrophy for Recognition of BA (SPARE-BA)), and an index previously shown to capture atrophy patterns found in clinical AD (Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease (SPARE-AD)). We studied the association between these indices and risk factors, including an AD polygenic risk score. Finally, we compared the ABA-associated atrophy with typical AD-like patterns. We observed that SPARE-BA had significant association with: smoking (P<0.05), anti-hypertensive (P<0.05), anti-diabetic drug use (men P<0.05, women P=0.06) and waist circumference for the male cohort (P<0.05), after adjusting for age. Subjects with ABA had spatially extensive gray matter loss in the frontal, parietal and temporal lobes (false-discovery-rate-corrected q<0.001). ABA patterns of atrophy were partially overlapping with, but notably deviating from those typically found in AD. Subjects with ABA had higher SPARE-AD values; largely due to the partial spatial overlap of associated patterns in temporal regions. The AD polygenic risk score was significantly associated with SPARE-AD but not with SPARE-BA. Our findings suggest that ABA is likely characterized by pathophysiologic mechanisms that are distinct from, or only partially overlapping with those of AD.

Multiple Sclerosis Lesions in the Brain: Computer-Assisted Assessment of Lesion Load Dynamics on 3D FLAIR MR Images.

The detection and monitoring of brain lesions caused by multiple sclerosis is commonly performed with the use of magnetic resonance imaging. Analysis of a large number of images is a time-consuming challenge to the neuroradiologist, that can be accelerated with the assistance of computer-detection software. In 98 baseline and follow-up brain magnetic resonance studies from 88 patients with a diagnosis of multiple sclerosis, we employed locally developed lesion-detection software to assess temporal change in the load of brain lesions and compared its results to routine clinical reports. Analyzing the differences between the follow-up study and the baseline study, the software displays the results in the form of a scrollable axial volume, with the changed lesions highlighted in different colors and superimposed on the baseline reference scan. Disagreements between the software and the clinical readers in the detection of changed lesions were observed only in 11 (11.2%) cases, and the difference did not reach statistical significance (p=0.07). The mean interpretation time with assistance of the software was 2.7±2.2 minutes. We conclude that the performance of the software-assisted interpretation in the analysis of change over time in multiple sclerosis brain lesions is comparable to the performance of clinical readers, with a possibly shorter assessment time. Our study demonstrates the potential of including lesion-detection software in the workflow of neuroradiology practice.

Errata Corrige: The Neuroradiology Journal 25: 17-21, 2012. Multiple Sclerosis Lesions in the Brain: Computer-Assisted Assessment of Lesion Load Dynamics on 3D FLAIR MR Images.

The detection and monitoring of brain lesions caused by multiple sclerosis is commonly performed with the use of magnetic resonance imaging. Analysis of a large number of images is a time-consuming challenge to the neuroradiologist, that can be accelerated with the assistance of computer-detection software. In 98 baseline and follow-up brain magnetic resonance studies from 88 patients with a diagnosis of multiple sclerosis, we employed locally developed lesion-detection software to assess temporal change in the load of brain lesions and compared its results to routine clinical reports. Analyzing the differences between the follow-up study and the baseline study, the software displays the results in the form of a scrollable axial volume, with the changed lesions highlighted in different colors and superimposed on the baseline reference scan. Although disagreements between the software and the clinical readers in the detection of changed lesions were observed only in 12 (12.2%) cases, the difference reached statistical significance (p=0.04). The mean interpretation time with assistance of the software was 2.7±2.2 minutes. We conclude that the performance of the software-assisted interpretation in the analysis of change over time in multiple sclerosis brain lesions is different from the performance of clinical readers, with a possibly shorter assessment time. The software detected more changes from baseline than clinical readers, suggesting a higher sensitivity, which will have to be confirmed on further analysis.