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ObjectiveThe disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.MethodsGlobal and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.ResultsDuring a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44–2.23] and FA 0.65 [0.52–0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was −0.04 [−0.07 to −0.01]). Associations were most profound in the projection, association, and limbic system tracts.ConclusionsStructural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population.

Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)‐based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI‐based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild‐AD, and moderate‐AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population‐based cohort with 48 MCI and 617 normal aging subjects. Each model's ability to detect MCI was quantified using area under the receiver operating characteristic curve (AUC) and compared with an MCI detection model trained and applied to the population‐based cohort. The AD‐model and mild‐AD identified MCI from controls better than chance level (AUC = 0.600, p = 0.025; AUC = 0.619, p = 0.008). In contrast, the moderate‐AD‐model was not able to separate MCI from normal aging (AUC = 0.567, p = 0.147). The MCI‐model was able to separate MCI from controls better than chance (p = 0.014) with mean AUC values comparable with the AD‐model (AUC = 0.611, p = 1.0). Within our population‐based cohort, classification models detected MCI better than chance. Nevertheless, classification performance rates were moderate and may be insufficient to facilitate robust MRI‐based MCI detection on an individual basis. Our data indicate that multiparametric MRI‐based classification algorithms, that are effective in clinical cohorts, may not straightforwardly translate to applications in a general population.

Purpose: To determine longitudinally the rate of change in diffusion- tensor imaging (DTI) parameters of white matter microstructure with aging and to investigate whether cardiovascular risk factors influence this longitudinal change. Materials and Methods: This prospective population-based cohort study was approved by a dedicated ethics committee overseen by the national government, and all participants gave written informed consent. Community-dwelling participants without dementia were examined by using a research-dedicated 1.5-T magnetic resonance (MR) imager on two separate visits that were, on average, 2.0 years apart. Among 810 persons who were eligible for imaging at baseline, longitudinal imaging data were available for 501 persons (mean age, 69.9 years; age range, 64.1-91.1 years). Changes in normal-appearing white matter DTI characteristics in the tract centers were analyzed globally to investigate diffuse patterns of change and then locally by using voxelwise multilinear regression. The influence of cardiovascular risk factors was assessed by treating them as additional determinants in both analyses. Results: Over the 2.0-year follow-up interval, global fractional anisotropy (FA) decreased by 0.0042 (P < .001), while mean diffusivity (MD) increased by 8.1 x 10(-6) mm(2)/sec (P < .001). Voxelwise analysis of the brain white matter skeleton showed an average decrease of 0.0082 (P-mean = .002) in FA in 57% of skeleton voxels. The sensorimotor pathway, however, showed an increase of 0.0078 (P-mean = .009) in FA. MD increased by 10.8 x 10(-6) mm(2)/sec (P-mean < .001) on average in 79% of white matter skeleton voxels. Additionally, white matter degeneration was more pronounced in older persons. Cardiovascular risk factors were generally not associated with longitudinal changes in white matter microstructure. Conclusion: Longitudinal diffusion analysis indicates widespread microstructural deterioration of the normal-appearing white matter in normal aging, with relative sparing of sensorimotor fibers. (C) RSNA, 2015

Cognition in adults shows variation due to developmental and degenerative components. A recent genomewide association study identified genetic variants for general cognitive function in 148 independent loci. Here, we aimed to elucidate possible developmental and neurodegenerative pathways underlying these genetic variants by relating them to functional, clinical and neuroimaging outcomes. This study was conducted within the population-based Rotterdam Study (N=11,496, mean age 65.3±9.9 years, 58.0% female). We used lead variants for general cognitive function to construct a polygenic score (PGS), and additionally excluded developmental variants at multiple significance thresholds. A higher PGS was related to more years of education (β=0.29, p=4.3×10 -7 ) and a larger intracranial volume (β=0.05, p=7.5×10 -4 ). To a smaller extent, the PGS was associated with less cognitive decline (βΔG-factor=0.03, p=1.3×10 -3 ), which became non-significant after adjusting for education (p=1.6×10 -2 ). No associations were found with daily functioning, dementia, parkinsonism, stroke or microstructural white matter integrity. Excluding developmental variants attenuated nearly all associations. In conclusion, this study suggests that the genetic variants identified for general cognitive function are acting mainly through the developmental pathway of cognition. Therefore, cognition, assessed cross-sectionally, seems to have limited value as a biomarker for neurodegeneration.

Previous studies have linked global burden of age-related white matter hyperintensities (WMHs) to cognitive impairment. We aimed to determine how WMHs in individual white matter connections relate to measures of cognitive function relative to measures of connectivity which do not take WMHs into account. Brain connectivity and WMH-related disconnectivity were derived from 3714 participants of the population-based Rotterdam Study. Connectivity was represented by the structural connectome, which was defined using diffusion tensor data, whereas the disconnectome represented disconnectivity due to WMH. The relationship between (dis)connectivity and cognitive measures was estimated using linear regression. We found that lower disconnectivity and higher connectivity corresponded to better cognitive function. There were many more significant associations with cognitive function in the disconnectome than in the connectome. Most connectome associations attenuated when disconnection was included in the model. WMH-related disconnectivity was especially related to worse executive functioning. Better cognitive speed corresponded to higher connectivity in specific connections independent of WMH presence. We conclude that WMH-related disconnectivity explains more variation in cognitive function than does connectivity. Efficient wiring in specific connections is important to information processing speed independent of WMH presence.

Background and Purpose— Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) for intracranial aneurysms in clinical samples. In addition, SNPs have been discovered for blood pressure, one of the strongest risk factors for intracranial aneurysms. We studied the role of these genetic variants on occurrence and size of unruptured intracranial aneurysms, discovered incidentally in a general community-dwelling population. Methods— In 4890 asymptomatic participants from the Rotterdam Study, 120 intracranial aneurysms were identified on brain imaging and segmented for maximum diameter and volume. Genetic risk scores (GRS) were calculated for intracranial aneurysms (10 SNPs), systolic blood pressure (33 SNPs), and diastolic blood pressure (41 SNPs). Results— The GRS for intracranial aneurysms was not statistically significantly associated with presence of aneurysms in this population (OR, 1.16; 95% CI, 0.96–1.40; P =0.119), but showed a significant association with both maximum diameter (difference in log-transformed mm per SD increase of GRS, 0.10; 95% CI, 0.02–0.19; P =0.018) and volume (difference in log-transformed µL per SD increase of GRS, 0.21; 95% CI, 0.01–0.41; P =0.040) of aneurysms. GRSs for blood pressures were associated with neither presence nor size of aneurysms. Conclusions— Genetic variants previously identified for intracranial aneurysms in clinical studies relate to the size rather than the presence of incidentally discovered, unruptured intracranial aneurysms in the general population.

Thyroid hormone (TH) is crucial during neurodevelopment, but high levels of TH have been linked to neurodegenerative disorders. No data on the association of thyroid function with brain imaging in the general population are available. We therefore investigated the association of thyroid-stimulating hormone and free thyroxine (FT4) with magnetic resonance imaging (MRI)-derived total intracranial volume, brain tissue volumes, and diffusion tensor imaging measures of white matter microstructure in 4683 dementia- and stroke-free participants (mean age 60.2, range 45.6–89.9 years). Higher FT4 levels were associated with larger total intracranial volumes (β = 6.73 mL, 95% confidence interval = 2.94–9.80). Higher FT4 levels were also associated with larger total brain and white matter volumes in younger individuals, but with smaller total brain and white matter volume in older individuals (p-interaction 0.02). There was a similar interaction by age for the association of FT4 with mean diffusivity on diffusion tensor imaging (p-interaction 0.026). These results are in line with differential effects of TH during neurodevelopmental and neurodegenerative processes and can improve the understanding of the role of thyroid function in neurodegenerative disorders.

BackgroundLittle is known about the natural course of atherosclerotic plaque in the carotid artery bifurcation. This study investigated the growth pattern of calcifications in atherosclerotic carotid arteries and its determinants using serial multi-detector CT angiography (MDCTA).MethodsFrom a cohort of consecutive patients with TIA or ischemic stroke and a baseline MCDTA scan of the carotid arteries, subjects were invited for a follow-up scan after 4–6 years. Calcification volumes were scored semi-automatically on baseline and follow-up scans. Progression of calcification and its determinants were analyzed in two ways: 1. as incidence of newly detectable calcification in patients free of calcification at baseline, using logistic regression analysis; 2. as annual change in calcification volume in all patients, using linear regression analysis.ResultsTwo-hundred-twenty-two patients (aged 61.0 ± 9.6 years, follow-up time 4.7 ± 0.8 years) were included. Calcification volumes increased significantly (median 2.9 mm³ at baseline versus 9.4 mm³ at follow-up, p

Purpose To present an updated prevalence estimate for incidental findings on brain magnetic resonance (MR) images and provide information on clinical relevance, including natural course, over a period of up to 9 years. Materials and Methods This study was approved by the institutional review board and all participants gave informed consent. In a prospective population-based setting, structural brain MR imaging was performed in 5800 participants (mean age, 64.9 years; 3194 women [55.1%]). Trained reviewers recorded abnormalities, which were subsequently evaluated by neuroradiologists. The prevalence with 95% confidence interval (CI) of incidental findings was determined, and clinical management of findings that required the attention of a medical specialist was followed. Follow-up imaging in the study context provided information on the natural course of findings that were not referred. Results In 549 of 5800 participants (9.5% [95% CI: 8.7%, 10.3%]), incidental findings were found, of which meningiomas (143 of 5800; 2.5% [95% CI: 2.1%, 2.9%]) and cerebral aneurysms (134 of 5800; 2.3% [95% CI: 2.0%, 2.7%]) were most common. A total of 188 participants were referred to medical specialists for incidental findings (3.2% [95% CI: 2.8%, 3.7%]). Of these, 144 (76.6% [95% CI: 70.1%, 82.1%]) either underwent a wait-and-see policy or were discharged after the initial clinical visit. The majority of meningiomas and virtually all aneurysms not referred or referred but untreated remained stable in size during follow-up. Conclusion Incidental findings at brain MR imaging that necessitate further diagnostic evaluation occur in over 3% of the general middle-aged and elderly population, but are mostly without direct clinical consequences. © RSNA, 2016.

White matter microstructural integrity has been related to cognition. Yet, the potential role of specific white matter tracts on top of a global white matter effect remains unclear, especially when considering specific cognitive domains. Therefore, we determined the tract-specific effect of white matter microstructure on global cognition and specific cognitive domains. In 4400 nondemented and stroke-free participants (mean age 63.7 years, 55.5% women), we obtained diffusion magnetic resonance imaging parameters (fractional anisotropy and mean diffusivity) in 14 white matter tracts using probabilistic tractography and assessed cognitive performance with a cognitive test battery. Tract-specific white matter microstructure in all supratentorial tracts was associated with poorer global cognition. Lower fractional anisotropy in association tracts, primarily the inferior fronto-occipital fasciculus, and higher mean diffusivity in projection tracts, in particular the posterior thalamic radiation, most strongly related to poorer cognition. Altered white matter microstructure related to poorer information processing speed, executive functioning, and motor speed, but not to memory. Tract-specific microstructural changes may aid in better understanding the mechanism of cognitive impairment and neurodegenerative diseases. (C) 2016 Elsevier Inc. All rights reserved.