Vrooman, H.A.

The Relation of Uric Acid to Brain Atrophy and Cognition: The Rotterdam Scan Study. (Article)

2013-03-19T00:00:00Z

Background: Uric acid has been associated with focal vascular brain disease. However, it is unknown whether uric acid also relates to global brain changes such as brain atrophy. We therefore studied the relation of uric acid to brain atrophy and whether this is accompanied by worse cognitive function. Methods: In 814 persons of the population-based Rotterdam Study (mean age 62.0 years), we studied the relation of uric acid levels to brain tissue atrophy and cognition using linear regression models adjusted for age, sex and putative confounders. Brain atrophy was assessed using automated processing of magnetic resonance imaging. Cognition was assessed using a validated neuropsychological test battery and we computed compound scores of cognitive domains. Results: Higher uric acid levels were associated with white matter atrophy [difference in Z-score of white matter volume per standard deviation increase in uric acid: -0.07 (95% CI: -0.12; -0.01)], but not with gray matter atrophy. This was particularly marked when comparing hyperuricemic to normouricemic persons [Z-score difference: -0.27 (-0.43; -0.11)]. Worse cognition was primarily found in persons with hyperuricemia [-0.28 (-0.48; -0.08)]. Conclusions: Hyperuricemia is related to white matter atrophy and worse cognition. Copyright

Vascular risk factors, apolipoprotein E, and hippocampal decline on magnetic resonance imaging over a 10-year follow-up (Article)

2012-01-12T00:00:00Z

Background: Decline of hippocampal volume on magnetic resonance imaging (MRI) may be considered as a surrogate biomarker of accumulating Alzheimer disease (AD) pathology. Previously, we showed in the prospective population-based Rotterdam Scan Study that a higher rate of decline of hippocampal volume on MRI precedes clinical AD or memory decline. We studied potential risk factors for decline of hippocampal volume. Methods: At baseline (1995-1996), 518 nondemented elderly subjects were included, and the cohort was re-examined in 1999 and in 2006. At each examination, hippocampal volume was determined using an automated segmentation procedure. In all, 301 persons had at least two three-dimensional MRI scans to assess decline in hippocampal volume. Results: Persons carrying the apolipoprotein E (APOE) e{open}4 allele had lower hippocampal volumes than persons with the e{open}3/e{open}3 genotype, but the rate of decline was not influenced by APOE genotype. In persons who did not use antihypertensive treatment, both a high (>90 mm Hg) and a low (<70 mm Hg) diastolic blood pressure were associated with a faster decline in hippocampal volume. Also, white matter lesions on baseline MRI were associated with a higher rate of decline in hippocampal volume. Conclusions: In a nondemented elderly population, persons with the APOE e{open}4 allele have a smaller hippocampal volume but not a higher rate of decline. Rate of decline of hippocampal volume was influenced by white matter lesions and diastolic blood pressure, supporting their hypothesized role in the pathogenesis of AD.

Global and focal brain volume in long-term breast cancer survivors exposed to adjuvant chemotherapy (Article)

2011-12-28T00:00:00Z

A limited number of studies have associated adjuvant chemotherapy with structural brain changes. These studies had small sample sizes and were conducted shortly after cessation of chemotherapy. Results of these studies indicate local gray matter volume decrease and an increase in white matter lesions. Up till now, it is unclear if non-CNS chemotherapy is associated with long-term structural brain changes. We compared focal and total brain volume (TBV) of a large set of non-CNS directed chemotherapy-exposed breast cancer survivors, on average 21 years post-treatment, to that of a population-based sample of women without a history of cancer. Structural MRI (1.5T) was performed in 184 chemotherapy-exposed breast cancer patients, mean age 64.0 (SD = 6.5) years, who had been diagnosed with cancer on average 21.1 (SD = 4.4) years before, and 368 age-matched cancer-free reference subjects from a population-based cohort study. Outcome measures were: TBV and total gray and white matter volume, and hippocampal volume. In addition, voxel based morphometry was performed to analyze differences in focal gray matter. The chemotherapy-exposed breast cancer survivors had significantly smaller TBV (-3.5 ml, P = 0.019) and gray matter volume (-2.9 ml, P = 0.003) than the reference subjects. No significant differences were observed in white matter volume, hippocampal volume, or local gray matter volume. This study shows that adjuvant chemotherapy for breast cancer is associated with long-term reductions in TBV and overall gray matter volume in the absence of focal reductions. The observed smaller gray matter volume in chemotherapy-exposed survivors was comparable to the effect of almost 4 years of age on gray matter volume reduction. These volume differences might be associated with the slightly worse cognitive performance that we observed previously in this group of breast cancer survivors.

Genome-wide association studies of cerebral white matter lesion burden (Article)

2011-07-01T00:00:00Z

Objective: White matter hyperintensities (WMHs) detectable by magnetic resonance imaging are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMHs are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified. Methods: We performed a meta-analysis of genome-wide association studies (GWASs) for WMH burden in 9,361 stroke-free individuals of European descent from 7 community-based cohorts. Significant findings were tested for replication in 3,024 individuals from 2 additional cohorts. Results: We identified 6 novel risk-associated single nucleotide polymorphisms (SNPs) in 1 locus on chromosome 17q25 encompassing 6 known genes including WBP2, TRIM65, TRIM47, MRPL38, FBF1, and ACOX1. The most significant association was for rs3744028 (pdiscovery= 4.0 × 10-9; preplication= 1.3 × 10-7; pcombined= 4.0 × 10-15). Other SNPs in this region also reaching genome-wide significance were rs9894383 (p = 5.3 × 10-9), rs11869977 (p = 5.7 × 10-9), rs936393 (p = 6.8 × 10-9), rs3744017 (p = 7.3 × 10-9), and rs1055129 (p = 4.1 × 10-8). Variant alleles at these loci conferred a small increase in WMH burden (4-8% of the overall mean WMH burden in the sample). Interpretation: This large GWAS of WMH burden in community-based cohorts of individuals of European descent identifies a novel locus on chromosome 17. Further characterization of this locus may provide novel insights into the pathogenesis of cerebral WMH.

Lobar distribution of cerebral microbleeds: The Rotterdam Scan Study (Article)

2011-05-01T00:00:00Z

Objective: To investigate the distribution of lobar microbleeds over the different lobes, taking into account lobar volume and clustering effects of multiple microbleeds. Design: Population-based, cross-sectional analysis. Setting: The Rotterdam Scan Study. Participants: A total of 198 persons (age range, 61-95 years) with lobar microbleeds. Main Outcome Measures: Distribution of microbleeds over different lobes. Results:Wefoundthat lobar cerebralmicrobleedsoccurred significantlymoreoften inthetemporallobe, aregionknown to be more affected in cerebral amyloid angiopathy. Conclusion: This study corroborates the presumed association of lobar microbleeds with cerebral amyloid angiopathy.

Statistical analysis of minimum cost path based structural brain connectivity (Article)

2011-03-15T00:00:00Z

Diffusion MRI can be used to study the structural connectivity within the brain. Brain connectivity is often represented by a binary network whose topology can be studied using graph theory. We present a framework for the construction of weighted structural brain networks, containing information about connectivity, which can be effectively analyzed using statistical methods. Network nodes are defined by segmentation of subcortical structures and by cortical parcellation. Connectivity is established using a minimum cost path (mcp) method with an anisotropic local cost function based directly on diffusion weighted images. We refer to this framework as Statistical Analysis of Minimum cost path based Structural Connectivity (SAMSCo) and the weighted structural connectivity networks as mcp-networks. In a proof of principle study we investigated the information contained in mcp-networks by predicting subject age based on the mcp-networks of a group of 974 middle-aged and elderly subjects. Using SAMSCo, age was predicted with an average error of 3.7. years. This was significantly better than predictions based on fractional anisotropy or mean diffusivity averaged over the whole white matter or over the corpus callosum, which showed average prediction errors of at least 4.8. years. Additionally, we classified subjects, based on the mcp-networks, into groups with low and high white matter lesion load, while correcting for age, sex and white matter atrophy. The SAMSCo classification outperformed the classification based on the diffusion measures with a classification accuracy of 76.0% versus 63.2%. We also performed a classification in groups with mild and severe atrophy, correcting for age, sex and white matter lesion load. In this case, mcp-networks and diffusion measures yielded similar classification accuracies of 68.3% and 67.8% respectively. The SAMSCo prediction and classification experiments indicate that the mcp-networks contain information regarding age, white matter lesion load and white matter atrophy, and that in case of age and white matter lesion load the mcp-network based models outperformed the predictions based on diffusion measures.

Genetic risk factors for cerebral small-vessel disease in hypertensive patients from a genetically isolated population (Article)

2011-01-01T00:00:00Z

Background: Asymptomatic cerebral lesions on MRI such as white matter lesions (WML), lacunes and microbleeds are commonly seen in older people. We examined the role of a series of candidate genes involved in blood pressure regulation and amyloid metabolism. Materials and Methods: The study was embedded in a family-based cohort sampled from a Dutch genetically isolated population. We selected individuals between 55 and 75 years of age with hypertension (N=129). Volumes of WML and presence of lacunes and microbleeds were assessed with MRI. We studied three genes involved in blood pressure regulation (angiotensin, angiotensin II type 1 receptor, α-adducin) and two genes involved in the amyloid pathway (apolipoprotein E (APOE) and sortilin-related receptor gene (SORL1)). Results: All participants had WML (median volume, 3.1 ml; interquartile range, 1.5e6.5 ml); lacunar infarcts were present in 15.5% and microbleeds in 23.3%. Homozygosity for the APOE ε4 allele was associated with lacunes (OR, 4.8; 95% CI, 1.2 to 19.3). Individuals carrying two copies of the variant allele of four single nucleotide polymorphism (SNPs) located at the 3'-end of SORL1 (rs1699102, rs3824968, rs2282649, rs1010159) had significantly more often microbleeds (highest OR, 6.87; 95% CI, 1.78 to 26.44). Conclusion: The association of SORL1 with microbleeds suggests that the amyloid cascade is involved in the aetiology of microbleeds in populations with hypertension.

Statistical analysis of structural brain connectivity (Article)

2010-11-22T00:00:00Z

We present a framework for statistical analysis in large cohorts of structural brain connectivity, derived from diffusion weighted MRI. A brain network is defined between subcortical gray matter structures and a cortical parcellation obtained with FreeSurfer. Connectivity is established through minimum cost paths with an anisotropic local cost function and is quantified per connection. The connectivity network potentially encodes important information about brain structure, and can be analyzed using multivariate regression methods. The proposed framework can be used to study the relation between connectivity and e.g. brain function or neurodegenerative disease. As a proof of principle, we perform principal component regression in order to predict age and gender, based on the connectivity networks of 979 middle-aged and elderly subjects, in a 10-fold cross-validation. The results are compared to predictions based on fractional anisotropy and mean diffusivity averaged over the white matter and over the corpus callosum. Additionally, the predictions are performed based on the best predicting connection in the network. Principal component regression outperformed all other prediction models, demonstrating the age and gender information encoded in the connectivity network.

Accuracy and reproducibility study of automatic MRI brain tissue segmentation methods (Article)

2010-07-01T00:00:00Z

The ability to study changes in brain morphometry in longitudinal studies majorly depends on the accuracy and reproducibility of the brain tissue quantification. We evaluate the accuracy and reproducibility of four previously proposed automatic brain tissue segmentation methods: FAST, SPM5, an automatically trained k-nearest neighbor (kNN) classifier, and a conventional kNN classifier based on a prior training set. The intensity nonuniformity correction and skull-stripping mask were the same for all methods. Evaluations were performed on MRI scans of elderly subjects derived from the general population. Accuracy was evaluated by comparison to two manual segmentations of MRI scans of six subjects (mean age 65.9 ± 4.4. years). Reproducibility was assessed by comparing the automatic segmentations of 30 subjects (mean age 57.0 ± 3.7. years) who were scanned twice within a short time interval. All methods showed good accuracy and reproducibility, with only small differences between methods. The conventional kNN classifier was the most accurate method with similarity indices of 0.82/0.90/0.94 for cerebrospinal fluid/gray matter/white matter, but it showed the lowest reproducibility. FAST yielded the most reproducible segmentation volumes with volume difference standard deviations of 0.55/0.49/0.38 (percentage of intracranial volume) respectively. The results of the reproducibility experiment can be used to calculate the required number of subjects in the design of a longitudinal study with sufficient power to detect changes over time in brain (tissue) volume. Example sample size calculations demonstrate a rather large effect of the choice of segmentation method on the required number of subjects.

Brain tissue volumes in relation to cognitive function and risk of dementia (Article)

2010-03-01T00:00:00Z

We investigated in a population-based cohort study the association of global and lobar brain tissue volumes with specific cognitive domains and risk of dementia. Participants (n = 490; 60-90 years) were non-demented at baseline (1995-1996). From baseline brain MRI-scans we obtained global and lobar volumes of CSF, GM, normal WM, white matter lesions and hippocampus. We performed neuropsychological testing at baseline to assess information processing speed, executive function, memory function and global cognitive function. Participants were followed for incident dementia until January 1, 2005. Larger volumes of CSF and WML were associated with worse performance on all neuropsychological tests, and an increased risk of dementia. Smaller WM volume was related to poorer information processing speed and executive function. In contrast, smaller GM volume was associated with worse memory function and increased risk of dementia. When investigating lobar GM volumes, we found that hippocampal volume and temporal GM volume were most strongly associated with risk of dementia, even in persons without objective and subjective cognitive deficits at baseline, followed by frontal and parietal GM volumes.

White Matter microstructural integrity and cognitive function in a general elderly population (Article)

2009-05-01T00:00:00Z

Context: The role of macrostructural white matter changes, such as atrophy and white matter lesions, in cognitive decline is increasingly being recognized. However, in the elderly population, these macrostructural changes do not account for all variability in cognition. Measures reflecting white matter microstructural integrity may provide additional information to investigate the relation between white matter changes and cognition. Objective: To study the relation between white matter integrity and cognition in the general elderly population, using diffusion tensor imaging and taking into account macrostructural white matter changes. Design: Cross-sectional population-based study. Setting: A general community in the Netherlands. Participants: A population-based sample of 860 persons, older than 60 years, free of dementia. We performed multisequence magnetic resonance imaging, which included diffusion tensor imaging, and extensive neuropsychological testing. Fractional anisotropy, mean diffusivity, and directional diffusivities were measured globally in white matter lesions and normal-appearing white matter. Main Outcome Measures: Performance on neuro- psychological tests in the following cognitive domains: memory, executive function, information processing speed, global cognition, and motor speed. Results: Regardless of macrostructural white matter changes, a higher mean diffusivity or higher axial and radial diffusivities within white matter lesions or normal- appearing white matter were related to worse performance on tasks assessing information processing speed and global cognition. In addition, diffusivity within white matter lesions related to memory, while in normal-appearing white matter, it furthermore related to executive function. Lower mean fractional anisotropy in white matter lesions or normal-appearing white matter related to worse information processing speed and motor speed. Conclusions: Microstructural integrity of both white matter lesions and normal-appearing white matter is associated with cognitive function, regardless of white matter atrophy and white matter lesion volume. This suggests that measuring white matter integrity has added value beyond macrostructural assessment of white matter changes to study the relation between white matter and cognition.

White matter lesion extension to automatic brain tissue segmentation on MRI (Article)

2009-05-01T00:00:00Z

A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.

Brain tissue volumes and small vessel disease in relation to the risk of mortality (Article)

2009-03-01T00:00:00Z

Brain atrophy and small vessel disease increase the risk of dementia and stroke. In a population-based cohort study (n = 490; 60-90 years) we investigated how volumetric measures of atrophy and small vessel disease were related to mortality and whether this was independent of incident dementia or stroke. Brain volume and hippocampal volume were considered as measures of atrophy, whereas white matter lesions (WML) and lacunar infarcts reflected small vessel disease. We first investigated all-cause mortality in the whole cohort. In subsequent analyses we censored persons at incident dementia or incident stroke. Finally, we separately investigated cardiovascular mortality. The average follow-up was 8.4 years, during which 191 persons died. Brain atrophy and hippocampal atrophy, as well as WML increased the risk of death. The risks associated with hippocampal atrophy attenuated when censoring persons at incident dementia, but not at incident stroke. Censoring at either incident dementia or stroke did not change the risk associated with brain atrophy and WML. Moreover, WML were particularly associated with cardiovascular mortality.

Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study (Article)

2008-10-01T00:00:00Z

BACKGROUND AND PURPOSE: Cerebral white matter lesions and lacunar infarcts are small vessel disease-related lesions, which are associated with cognitive decline and dementia. We aimed to assess the relationship between risk factors, effect modifiers, and progression of these lesions. Furthermore, we studied the cognitive consequences of lesion progression. METHODS: Six hundred sixty-eight people, aged 60 to 90 years, underwent repeated MRI scanning and neuropsychological testing within 3-year follow-up. We rated incident lacunar infarcts and change in periventricular and subcortical white matter lesion severity with a semiquantitative scale. We assessed the relationships between age, sex, baseline lesion load, risk factors, lesion progression, and change in cognitive function by multivariate regression analyses and additional stratified analyses. RESULTS: Baseline lesion load, higher age, high blood pressure, and current smoking were independently associated with progression of white matter lesions. Women had more marked progression of subcortical white matter lesions and incident lacunar infarcts compared with men. Carotid atherosclerosis was associated with incident lacunar infarcts. Higher blood pressure did not contribute to lesion progression in people with already severe lesions at baseline nor in the very old. Lesion progression was associated with a paralleled decline in general cognitive function and in particular with a decreased information processing speed. CONCLUSIONS: Higher age, female sex, cigarette smoking, elevated blood pressure, and baseline lesion load were associated with small vessel disease progression. Age and baseline lesion load influenced the risk relations with blood pressure. Progression of small vessel disease was related to a paralleled decline in cognitive function.

Brain tissue volumes in the general elderly population. The Rotterdam Scan Study (Article)

2008-06-01T00:00:00Z

We investigated how volumes of cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) varied with age, sex, small vessel disease and cardiovascular risk factors in the Rotterdam Scan Study. Participants (n = 490; 60-90 years) were non-demented and 51.0% had hypertension, 4.9% had diabetes mellitus, 17.8% were current smoker and 54.0% were former smoker. We segmented brain MR-images into GM, normal WM, white matter lesion (WML) and CSF. Brain infarcts were rated visually. Volumes were expressed as percentage of intra-cranial volume. With increasing age, volumes of total brain, normal WM and total WM decreased; that of GM remained unchanged; and that of WML increased, in both men and women. Excluding persons with infarcts did not alter these results. Persons with larger load of small vessel disease had smaller brain volume, especially normal WM volume. Diastolic blood pressure, diabetes mellitus and current smoking were also related to smaller brain volume. In the elderly, higher age, small vessel disease and cardiovascular risk factors are associated with smaller brain volume, especially WM volume.

Foetal growth determines cerebral ventricular volume in infants. The Generation R Study (Article)

2008-02-15T00:00:00Z

The cerebral ventricular system is a marker of brain development and a predictor of neurodevelopmental outcome. In premature or dysmature neonates, neuroanatomical structures including the ventricular system appear to be altered. The present study aims to provide information on the association between foetal growth and neonatal cerebral ventricular size in the normal population. Within the Generation R Study, a population-based cohort study, we used three-dimensional cranial ultrasound to determine lateral ventricular volume in 778 term infants aged 4-12 weeks. Foetal growth characteristics were repeatedly measured in early, mid- and late pregnancy and analysed in relation to ventricular volume divided by head circumference. Results revealed positive associations between foetal head circumference in late pregnancy and log-transformed ventricular volume (β = 0.077, 95% confidence interval (0.017; 0.136), equivalent to a 7.7% increase in ventricular volume per standard deviation of head circumference). Similarly, in a per week-longer gestational duration, ventricular volume in infancy was 6.0% larger. Multilevel modelling demonstrated that reduced growth of foetal head circumference and biparietal diameter during pregnancy were associated with decreased ventricular volume in infancy. In conclusion, foetal maturation is positively associated to cerebral ventricular size in term infants. Larger ventricular size in term infants needs to be distinguished from ventricular enlargement due to intraventricular haemorrhage or white matter damage in premature or dysmature infants. Moreover, the naturally occurring enlargement of ventricles during infancy should be considered in interpreting reports on increased ventricular volumes in several neuropsychiatric disorders.

Total cerebral blood flow and total brain perfusion in the general population: The Rotterdam Scan Study (Article)

2008-02-01T00:00:00Z

Reduced cerebral perfusion may contribute to the development of cerebrovascular and neurodegenerative diseases. Little is known on cerebral perfusion in the general population, as most measurement techniques are too invasive for application in large groups of healthy individuals. Total cerebral blood flow (tCBF) can be noninvasively measured by magnetic resonance imaging (MRI) but is highly correlated with brain volume. We calculated total brain perfusion by dividing tCBF by brain volume, and we investigated determinants of total brain perfusion in comparison with tCBF. Secondly, we studied whether persons with a low tCBF or low total brain perfusion have a larger volume of white matter lesions (WML). This study is based on 892 persons aged 60 to 91 years from the Rotterdam Study, a population-based cohort study. We performed two-dimensional (2D) phase-contrast MRI for tCBF measurement. Brain volume and WML volume were quantitatively assessed. Cardiovascular determinants were assessed by interview and physical examination. We assessed associations between cardiovascular determinants and flow measures with linear regression models, adjusted for age and sex. Associations between tCBF or total brain perfusion and WML volume were assessed using general linear models. We found that determinants of tCBF and total brain perfusion differed largely due to the large influence of brain volume on tCBF values. Persons with low total brain perfusion had a significantly larger WML volume compared with those with high total brain perfusion. Prospective studies are required to unravel whether hypoperfusion contributes to WML formation or that tissue damage, manifested by WML, leads to brain hypoperfusion.

Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification (Article)

2007-08-01T00:00:00Z

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.

C-reactive protein and cerebral small-vessel disease: the Rotterdam Scan Study. (Article)

2005-08-09T00:00:00Z

BACKGROUND: Inflammatory processes are involved in the development and consequences of atherosclerosis. Whether these processes are also involved in cerebral small-vessel disease is unknown. Cerebral white matter lesions and lacunar brain infarcts are caused by small-vessel disease and are commonly observed on MRI scans in elderly people. These lesions are associated with an increased risk of stroke and dementia. We assessed whether higher C-reactive protein (CRP) levels were related to white matter lesion and lacunar infarcts. METHODS AND RESULTS: We based our study on 1033 participants of the population-based Rotterdam Scan Study for whom complete data on CRP levels were available and who underwent brain MRI scanning. Subjects were 60 to 90 years of age and free of dementia at baseline. Six hundred thirty-six subjects had a second MRI scan on average 3.3 years later. We used multivariate regression models to assess the associations between CRP levels and markers of small-vessel disease. Higher CRP levels were associated with presence and progression of white matter lesions, particularly with marked lesion progression (ORs for highest versus lowest quartile of CRP 3.1 [95% CI 1.3 to 7.2] and 2.5 [95% CI 1.1 to 5.6] for periventricular and subcortical white matter lesion progression, respectively). These associations persisted after adjustment for cardiovascular risk factors and carotid atherosclerosis. Persons with higher CRP levels tended to have more prevalent and incident lacunar infarcts. CONCLUSIONS: Inflammatory processes may be involved in the pathogenesis of cerebral small-vessel disease, in particular, the development of white matter lesions.

Suitability of texture features to assess changes in trabecular bone architecture (Article)

2002-03-19T00:00:00Z