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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 (p(discovery) = 4.0 × 10(-9) ; p(replication) = 1.3 × 10(-7) ; p(combined) = 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. [ABSTRACT FROM AUTHOR]

Metopic synostosis patients are at risk for neurodevelopmental disorders despite a negligible risk of intracranial hypertension. To gain insight into the underlying pathophysiology of metopic synostosis and associated neurodevelopmental disorders, we aimed to investigate brain volumes of non-syndromic metopic synostosis patients using preoperative MRI brain scans. MRI brain scans were processed with HyperDenseNet to calculate total intracranial volume (TIV), total brain volume (TBV), total grey matter volume (TGMV), total white matter volume (TWMV) and total cerebrospinal fluid volume (TCBFV). We compared global brain volumes of patients with controls corrected for age and sex using linear regression. Lobe-specific grey matter volumes were assessed in secondary analyses. We included 45 metopic synostosis patients and 14 controls (median age at MRI 0.56 years [IQR 0.36] and 1.1 years [IQR 0.47], respectively). We found no significant differences in TIV, TBV, TGMV or TCBFV in patients compared to controls. TWMV was significantly smaller in patients (-62,233 mm 3 [95% CI = -96,968; -27,498], Holm-corrected p = 0.004), and raw data show an accelerated growth pattern of white matter in metopic synostosis patients. Grey matter volume analyses per lobe indicated increased cingulate (1378 mm 3 [95% CI = 402; 2355]) and temporal grey matter (4747 [95% CI = 178; 9317]) volumes in patients compared to controls. To conclude, we found smaller TWMV with an accelerated white matter growth pattern in metopic synostosis patients, similar to white matter growth patterns seen in autism. TIV, TBV, TGMV and TCBFV were comparable in patients and controls. Secondary analyses suggest larger cingulate and temporal lobe volumes. These findings suggest a generalized intrinsic brain anomaly in the pathophysiology of neurodevelopmental disorders associated with metopic synostosis., (© 2024 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.)

Objective: Objective differentiation between unilateral coronal synostosis (UCS) and positional posterior plagiocephaly (PPP) based on 3D photogrammetry according to Utrecht Cranial Shape Quantificator (UCSQ)., Design: Retrospective study., Setting: Primary craniofacial center., Patients, Participants: Thirty-two unoperated patients (17 UCS; 15 PPP) (age < 1 year)., Interventions: Extraction of variables from sinusoid curves derived using UCSQ: asymmetry ratio forehead and occiput peak, ratio of gradient forehead and occiput peak, location forehead and occiput peak., Main Outcome Measure(s): Variables, derived using 3D photogrammetry, were analyzed for differentiation between UCS and PPP., Results: Frontal peak was shifted to the right side of the head in left-sided UCS (mean x -value 207 [192-220]), and right-sided PPP (mean x -value 210 [200-216]), and to the left in right-sided UCS (mean x -value 161 [156-166]), and left-sided PPP (mean x -value 150 [144-154]). Occipital peak was significantly shifted to the right side of the head in left-sided PPP (mean x -value 338 [336-340]) and to the left in right-sided PPP (mean x -value 23 [14-32]). Mean x -value of occipital peak was 9 (354-30) in left- and 2 (350-12) in right-sided UCS. Calculated ratio of gradient of the frontal peak is, in combination with the calculated asymmetry ratio of the frontal peak, a distinctive finding., Conclusions: UCSQ objectively captures shape of synostotic and positional plagiocephaly using 3D photogrammetry, we therefore developed a suitable method to objectively differentiate UCS from PPP using radiation-free methods.

Higher vascular disease burden increases the likelihood of developing dementia, including Alzheimer's disease. Better understanding the association between vascular risk factors and Alzheimer's disease pathology at the predementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of six vascular risk factors on the presence and severity of in vivo measured brain amyloid-beta (Aβ) plaques in participants from the population-based Rotterdam Study. Vascular risk factors (hypertension, hypercholesterolaemia, diabetes, obesity, physical inactivity and smoking) were assessed 13 (2004-2008) and 7 years (2009-2014) prior to 18F-florbetaben PET (2018-2021) in 635 dementia-free participants. Vascular risk factors were associated with binary amyloid PET status or continuous PET readouts (standard uptake value ratios, SUVrs) using logistic and linear regression models, respectively, adjusted for age, sex, education, APOE4 risk allele count and time between vascular risk and PET assessment. Participants' mean age at time of amyloid PET was 69 years (range: 60-90), 325 (51.2%) were women and 190 (29.9%) carried at least one APOE4 risk allele. The adjusted prevalence estimates of an amyloid-positive PET status markedly increased with age [12.8% (95% CI 11.6; 14) in 60-69 years versus 35% (36; 40.8) in 80-89 years age groups] and APOE4 allele count [9.7% (8.8; 10.6) in non-carriers versus 38.4% (36; 40.8) to 60.4% (54; 66.8) in carriers of one or two risk allele(s)]. Diabetes 7 years prior to PET assessment was associated with a higher risk of a positive amyloid status [odds ratio (95% CI) = 3.68 (1.76; 7.61), P < 0.001] and higher standard uptake value ratios, indicating more severe Aβ pathology [standardized beta = 0.40 (0.17; 0.64), P = 0.001]. Hypertension was associated with higher SUVr values in APOE4 carriers (mean SUVr difference of 0.09), but not in non-carriers (mean SUVr difference 0.02; P = 0.005). In contrast, hypercholesterolaemia was related to lower SUVr values in APOE4 carriers (mean SUVr difference -0.06), but not in non-carriers (mean SUVr difference 0.02). Obesity, physical inactivity and smoking were not related to amyloid PET measures. The current findings suggest a contribution of diabetes, hypertension and hypercholesterolaemia to the pathophysiology of Alzheimer's disease in a general population of older non-demented adults. As these conditions respond well to lifestyle modification and drug treatment, further research should focus on the preventative effect of early risk management on the development of Alzheimer's disease neuropathology., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Implementation of the Utrecht Cranial Shape Quantificator (UCSQ) classification method on 3D photogrammetry in patients with different types of craniosynostosis is the aim of the present study. Five children (age <1 year) of every group of the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, right-sided and left-sided anterior plagiocephaly) were randomly included. The program 3-Matic (v13.0) was used to import and analyze the included 3dMD photos. Three external landmarks were placed. Using the landmarks, a base plane was created, as well as a plane 4 cm superior to the base plane. Using UCSQ, we created sinusoid curves of the patients, the resulting curves were analyzed and values were extracted for calculations. Results per patient were run through a diagnostic flowchart in order to determine correctness of the flowchart when using 3D photogrammetry. Each of the patients (n=25) of the different craniosynostosis subgroups is diagnosed correctly based on the different steps in the flowchart. This study proposes and implements a diagnostic approach of craniosynostosis based on 3D photogrammetry. By using a diagnostic flowchart based on specific characteristics for every type of craniosynostosis related to specific skull deformities, diagnosis can be established. All variables are expressed in number and are therefore objective., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 by Mutaz B. Habal, MD.)

Background: Intracranial stenosis (ICS) and brain amyloid-beta (Aβ) have been associated with cognition and dementia. We aimed to investigate the association between ICS and brain Aβ and their independent and joint associations with cognition., Methods: We conducted a cross-sectional study of 185 patients recruited from a memory clinic. ICS was measured on 3-dimensional time-of-flight magnetic resonance angiography and defined as stenosis ≥50%. Brain Aβ was measured with [ 11 C] Pittsburgh compound B-positron emission tomography imaging. Cognition was assessed with a locally validated neuropsychological battery., Results: A total of 17 (9.2%) patients had ICS, and the mean standardized uptake value ratio was 1.4 (±0.4 SD). ICS was not significantly associated with brain Aβ deposition. ICS was significantly associated with worse global cognition (β: -1.26, 95% CI: -2.25; -0.28, P =0.013), executive function (β: -1.04, 95% CI: -1.86; -0.22, P =0.015) and visuospatial function (β: -1.29, 95% CI: -2.30; -0.27, P =0.015). Moreover, in ICS patients without dementia (n=8), the presence of Aβ was associated with worse performance on visuomotor speed., Conclusions: ICS was significantly associated with worse cognition and showed interaction with brain Aβ such that patients with both pathologies performed worse on visuomotor speed specifically in those without dementia. Further studies may clarify if ICS and brain Aβ deposition indeed have a synergistic association with cognition., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Children with trigonocephaly are at risk for neurodevelopmental disorders. The aim of this study is to investigate white matter properties of the frontal lobes in young, unoperated patients with metopic synostosis as compared to healthy controls using diffusion tension imaging (DTI)., Methods: Preoperative DTI data sets of 46 patients with trigonocephaly with a median age of 0.49 (interquartile range: 0.38) years were compared with 21 controls with a median age of 1.44 (0.98) years. White matter metrics of the tracts in the frontal lobe were calculated using FMRIB Software Library (FSL). The mean value of tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were estimated for each subject and compared to healthy controls. By linear regression, FA and MD values per tract were assessed by trigonocephaly, sex, and age., Results: The mean FA and MD values in the frontal lobe tracts of untreated trigonocephaly patients, younger than 3 years, were not significantly different in comparison to controls, where age showed to be a significant associated factor., Conclusions: Microstructural parameters of white matter tracts of the frontal lobe of patients with trigonocephaly are comparable to those of controls aged 0-3 years., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aim: To assess the relationship of surface area of the cerebral cortex to intracranial volume (ICV) in syndromic craniosynostosis., Method: Records of 140 patients (64 males, 76 females; mean age 8y 6mo [SD 5y 6mo], range 1y 2mo-24y 2mo) with syndromic craniosynostosis were reviewed to include clinical and imaging data. Two hundred and three total magnetic resonance imaging (MRI) scans were evaluated in this study (148 patients with fibroblast growth factor receptor [FGFR], 19 patients with TWIST1, and 36 controls). MRIs were processed via FreeSurfer pipeline to determine total ICV and cortical surface area (CSA). Scaling coefficients were calculated from log-transformed data via mixed regression to account for multiple measurements, sex, syndrome, and age. Educational outcomes were reported by syndrome., Results: Mean ICV was greater in patients with FGFR (1519cm 3 , SD 269cm 3 , p=0.016) than in patients with TWIST1 (1304cm 3 , SD 145cm 3 ) or controls (1405cm 3 , SD 158cm 3 ). CSA was related to ICV by a scaling law with an exponent of 0.68 (95% confidence interval [CI] 0.61-0.76) in patients with FGFR compared to 0.81 (95% CI 0.50-1.12) in patients with TWIST1 and 0.77 (95% CI 0.61-0.93) in controls. Lobar analysis revealed reduced scaling in the parietal (0.50, 95% CI 0.42-0.59) and occipital (0.67, 95% CI 0.54-0.80) lobes of patients with FGFR compared with controls. Modified learning environments were needed more often in patients with FGFR., Interpretation: Despite adequate ICV in FGFR-mediated craniosynostosis, CSA development is reduced, indicating maldevelopment, particularly in parietal and occipital lobes. Modified education is also more common in patients with FGFR., (© 2021 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.)

Trigonocephaly is the result of premature fusion of the metopic suture and its severity can vary widely. However, there is no gold standard for quantification of the severity. This study was performed to quantify severity using the Utrecht Cranial Shape Quantifier (UCSQ) and to assess forehead symmetry. Nineteen preoperative non-syndromic trigonocephaly patients (age ≤1 year) were included for the analysis of severity and symmetry. Severity according to the UCSQ was based on the following combined variables: forehead width and relative skull elongation. The UCSQ was compared to the most established quantification methods. A high correlation was found between the UCSQ and visual score (r=0.71). Moderate to negligible correlation was found between the UCSQ and frontal angle, binocular distance, inter-ocular distance, and frontal stenosis. Additionally, correlation between the visual score and these established quantification methods was negligible. Assessment of the frontal peak (a)symmetry (ratio of right to left triangle area in the curve) showed a mean right versus left triangle area ratio of 1.4 (range 0.9-2.4). The results suggest that the UCSQ is appropriate for the quantification of severity based on the high correlation with clinical judgement. Furthermore, a larger triangle area right than left was unexpectedly found, indicating forehead asymmetry., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objectives: Severity of unilateral coronal synostosis (UCS) can vary. Quantification is important for treatment, expectations of treatment and natural outcome, and education of the patient and parents., Design: Retrospective study., Setting: Primary craniofacial center., Patients, Participants: Twenty-three preoperative patients with unilateral coronal craniosynostosis (age < 2 years)., Intervention: Utrecht Cranial Shape Quantifier (UCSQ) was used to quantify severity using the variables: asymmetry ratio of frontal peak and ratio of frontal peak gradient., Main Outcome Measures(s): The UCSQ variables were combined and related to visual score using Pearson correlation coefficient; UCSQ and visual score were additionally compared to Di Rocco classification by one-way analysis of variance or Kruskal-Wallis test. All measurements were made on computed tomography scans., Results: Good correlation between UCSQ and visual score was found ( r = 0.67). No statistically significant differences were found between group means of UCSQ in the 3 categories of Di Rocco classification ( F 2,20 = 0.047; P > .05). Kruskal-Wallis test showed no significant differences between group means of visual score in the 3 categories of Di Rocco classification (Kruskal-Wallis H (2) = 0.871; P > .05)., Conclusions: Using UCSQ, we can quantify UCS according to severity using characteristics, it outperforms traditional methods and captures the whole skull shape. In future research, we can apply UCSQ to 3D-photogrammetry due to the utilization of external landmarks.

In this study, we diagnose skull shape deformities by analysing sinusoid curves obtained from standardized computed tomography (CT) slices of the skull for the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, right- and left-sided anterior plagiocephaly). Scaphocephaly has a high forehead peak and low troughs, in contrast to brachycephaly. Anterior plagiocephaly has asymmetry and shifting of the forehead peak. Trigonocephaly has a high and narrow frontal peak. Control patients have a symmetrical skull shape with low troughs and a high and broader frontal peak. Firstly, we included 5 children of every group of the common craniosynostoses and additionally 5 controls for extraction and calculation of characteristics. A diagnostic flowchart was developed. Secondly, we included a total of 51 craniosynostosis patients to validate the flowchart. All patients were correctly classified using the flowchart.Conclusion: Our study proposes and implements a new diagnostic approach of craniosynostosis. We describe a diagnostic flowchart based on specific characteristics for every type of craniosynostosis related to the specific skull deformities and control patients. All variables are expressed in number; therefore, we are able to use these variables in future research to quantify the different types of craniosynostosis. What is Known: • Premature fusion of one or more cranial sutures results in a specific cranial shape. • Clinical diagnosis is relatively simple; however, objective diagnosis based on distinctive values is difficult. What is New: • Using external landmarks and curve analysis, distinctive variables, and values for every type of craniosynostosis related to the specific skull deformities were determined and used to create a diagnostic flowchart for diagnosis. • Validation with an independent data set of 51 patients showed that all patients were correctly classified.

We present a novel technique for classification of skull deformities due to most common craniosynostosis. We included 5 children of every group of the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, and right- and left-sided anterior plagiocephaly) and additionally 5 controls. Our outline-based classification method is described, using the software programs OsiriX, MeVisLab, and Matlab. These programs were used to identify chosen landmarks (porion and exocanthion), create a base plane and a plane at 4 cm, segment outlines, and plot resulting graphs. We measured repeatability and reproducibility, and mean curves of groups were analyzed. All raters achieved excellent intraclass correlation scores (0.994-1.000) and interclass correlation scores (0.989-1.000) for identifying the external landmarks. Controls, scaphocephaly, trigonocephaly, and brachycephaly all have the peak of the forehead in the middle of the curve (180°). In contrary, in anterior plagiocephaly, the peak is shifted (to the left of graph in right-sided and vice versa). Additionally, controls, scaphocephaly, and trigonocephaly have a high peak of the forehead; scaphocephaly has the lowest troughs; in brachycephaly, the width/frontal peak ratio has the highest value with a low frontal peak.Conclusion: We introduced a preliminary study showing an objective and reproducible methodology using CT scans for the analysis of craniosynostosis and potential application of our method to 3D photogrammetry. What is Known: • Diagnosis of craniosynostosis is relatively simple; however, classification of craniosynostosis is difficult and current techniques are not widely applicable. What is New: • We introduce a novel technique for classification of skull deformities due to craniosynostosis, an objective and reproducible methodology using CT scans resulting in characteristic curves. The method is applicable to all 3D-surface rendering techniques. • Using external landmarks and curve analysis, specific and characteristic curves for every type of craniosynostosis related to the specific skull deformities are found.

Aim: To evaluate the impact of risk factors for intracranial hypertension (ICH) on cerebral cortex thickness in syndromic craniosynostosis., Method: ICH risk factors including papilloedema, hydrocephalus, obstructive sleep apnea (OSA), cerebellar tonsillar position, occipitofrontal circumference (OFC) curve deflection, age, and sex were collected from the records of patients with syndromic craniosynostosis (Apert, Crouzon, Pfeiffer, Muenke, Saethre-Chotzen syndromes) and imaging. Magnetic resonance images were analysed and exported for statistical analysis. A linear mixed model was developed to determine correlations with cerebral cortex thickness changes., Results: In total, 171 scans from 107 patients (83 males, 88 females [including repeated scans], mean age 8y 10mo, range 1y 1mo-34y, SD 5y 9mo) were evaluated. Mean cortical thickness in this cohort was 2.78mm (SD 0.17). Previous findings of papilloedema (p=0.036) and of hydrocephalus (p=0.007) were independently associated with cortical thinning. Cortical thickness did not vary significantly by sex (p=0.534), syndrome (p=0.896), OSA (p=0.464), OFC (p=0.375), or tonsillar position (p=0.682)., Interpretation: Detection of papilloedema or hydrocephalus in syndromic craniosynostosis is associated with significant changes in cortical thickness, supporting the need for preventative rather than reactive treatment strategies., What This Paper Adds: Papilloedema is associated with thinning of the cerebral cortex in syndromic craniosynostosis, independently of hydrocephalus., (© 2020 Mac Keith Press.)

Background: Episodes of intracranial hypertension are associated with reductions in cerebral cortical thickness (CT) in syndromic craniosynostosis. Here we focus on Crouzon-Pfeiffer syndrome patients to measure CT and evaluate associations with type of primary cranial vault expansion and synostosis pattern., Methods: Records from 34 Crouzon-Pfeiffer patients were reviewed along with MRI data on CT and intracranial volume to examine associations. Patients were grouped according to initial cranial vault expansion (frontal/occipital). Data were analyzed by multiple linear regression controlled for age and brain volume to determine an association between global/lobar CT and vault expansion type. Synostosis pattern effect sizes on global/lobar CT were calculated as secondary outcomes., Results: Occipital expansion patients demonstrated 0.02 mm thicker cortex globally ( P = 0.81) with regional findings, including: thicker cortex in frontal (0.02 mm, P = 0.77), parietal (0.06 mm, P = 0.44) and occipital (0.04 mm, P = 0.54) regions; and thinner cortex in temporal (-0.03 mm, P = 0.69), cingulate (-0.04 mm, P = 0.785), and, insula (-0.09 mm, P = 0.51) regions. Greatest effect sizes were observed between left lambdoid synostosis and the right cingulate (d = -1.00) and right lambdoid synostosis and the left cingulate ( d = -1.23). Left and right coronal synostosis yielded effect sizes of d = -0.56 and d = -0.42 on respective frontal lobes., Conclusions: Both frontal and occipital primary cranial vault expansions correlate to similar regional CT in Crouzon-Pfeiffer patients. Lambdoid synostosis appears to be associated with cortical thinning, particularly in the cingulate gyri., Competing Interests: Disclosure: The authors have no financial interest to declare in relation to the content of this article., (Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons.)

Structural brain markers are studied extensively in the field of neurodegeneration, but are thought to occur rather late in the process. Functional measures such as functional connectivity are gaining interest as potentially more subtle markers of neurodegeneration. However, brain structure and function are also affected by 'normal' brain ageing. More information is needed on how functional connectivity relates to aging, particularly in the absence of overt neurodegenerative disease. We investigated the association of age with resting-state functional connectivity in 2878 non-demented persons between 50 and 95 years of age (54.1% women) from the population-based Rotterdam Study. We obtained nine well-known resting state networks using data-driven methodology. Within the anterior default mode network, ventral attention network, and sensorimotor network, functional connectivity was significantly lower with older age. In contrast, functional connectivity was higher with older age within the visual network. Between resting state networks, we found patterns of both increases and decreases in connectivity in approximate equal proportions. Our results reinforce the notion that the aging brain undergoes a reorganization process, and serves as a solid basis for exploring functional connectivity as a preclinical marker of neurodegenerative disease., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI)., Method: MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus., Results: We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors., Conclusions: Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI., Key Points: • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

Background and Purpose: Vulnerable carotid plaque components are reported to increase the risk of cerebrovascular events. Yet, the relation between plaque composition and subclinical ischemic brain disease is not known. We studied, in the general population, the association between carotid atherosclerotic plaque characteristics and ischemic brain disease on MR imaging., Materials and Methods: From the population-based Rotterdam Study, 951 participants underwent both carotid MR imaging and brain MR imaging. The presence of intraplaque hemorrhage, lipid core, and calcification and measures of plaque size was assessed in both carotid arteries. The presence of plaque characteristics in relation to lacunar and cortical infarcts and white matter lesion volume was investigated and adjusted for cardiovascular risk factors. Stratified analyses were conducted to explore effect modification by sex. Additional analyses were conducted per carotid artery in relation to vascular brain disease in the ipsilateral hemisphere., Results: Carotid intraplaque hemorrhage was significantly associated with the presence of cortical infarcts (OR, 1.9; 95% confidence interval, 1.1-3.3). None of the plaque characteristics were related to the presence of lacunar infarcts. Calcification was the only characteristic that was associated with higher white matter lesion volume. There was no significant interaction by sex., Conclusions: The presence of carotid intraplaque hemorrhage on MR imaging is independently associated with MR imaging-defined cortical infarcts, but not with lacunar infarcts. Plaque calcification, but not vulnerable plaque components, is related to white matter lesion volume., (© 2017 by American Journal of Neuroradiology.)

Background: Cortical brain infarcts are defined as infarcts involving cortical gray matter, but may differ considerably in size. It is unknown whether small cortical infarcts have a similar clinical phenotype as larger counterparts. We investigated prevalence, determinants, and cognitive correlates of small cortical infarcts in the general population and compared these with large cortical infarcts and lacunar infarcts., Methods: Four thousand nine hundred five nondemented individuals (age 63·95 ± 10·99) from a population-based study were included. Infarcts were rated on magnetic resonance imaging and participants were classified according to mean infarct diameter into small (≤15 mm in largest diameter) or large (>15 mm) cortical infarcts, lacunar infarcts, or a combination of subtypes. Spatial distribution maps were created for manually labeled small and large infarcts. Participants underwent cognitive testing. Analyses were performed using multinomial regression and analysis of covariance., Results: Three hundred eighty-one (7·8%) persons had any infarct on magnetic resonance imaging, among whom 54 with small (1·1%) and 77 (1·6%) with large cortical infarcts. Small cortical infarcts were mainly localized in external watershed areas, whereas large cortical infarcts were localized primarily in large arterial territories. Age (odds ratio = 1·06; 95% confidence interval = 1·02, 1·09), male gender (1·98; 1·01, 3·92), and smoking (2·55; 1·06, 6·14) were determinants of small cortical infarcts. Participants with these infarcts had worse scores in delayed memory, processing speed, and attention tests than persons without infarcts, even after adjustment for cardiovascular risk factors., Conclusions: In the elderly, small cortical infarcts appear as frequent as large infarcts but in different localization. Our results suggest that small cortical infarcts share cardiovascular risk factors and cognitive correlates with large cortical, but also with lacunar infarcts., (© 2015 World Stroke Organization.)

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65-80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.

Extracranial carotid artery disease has been shown to be related to cognitive deficits. However, limited data are available on intracranial stenosis (ICS) and cognitive impairment. We investigate the association between ICS and cognitive impairment in Chinese. Subjects (n=278), recruited from the Epidemiology of Dementia in Singapore Study, underwent comprehensive clinical evaluation, neuropsychological testing, and brain magnetic resonance imaging (MRI), including 3-dimensional-time-of-flight magnetic resonance angiography (MRA). Cognitive function was expressed as composite and domain-specific Z-scores. Cognitive impairment no dementia and dementia were diagnosed according to internationally accepted diagnostic criteria. Linear and logistic regression models were adjusted for age, sex, education, vascular risk factors, and other MRI markers. A total of 29 (10.4%) persons had ICS on MRA, which was significantly associated with both composite cognitive Z-scores [mean difference in Z-score, presence vs. absence of ICS: -0.37 (95% confidence interval: -0.63, -0.12)] and specific domains including executive function, language, visuomotor speed, verbal memory, and visual memory. ICS was also related to significant cognitive impairment (odds ratio: 5.10 [1.24 to 21.02]). With respect to other MRI markers, adjusted for the presence of lacunar infarcts, the associations of ICS with both composite and domain-specific Z-scores, and significant cognitive impairment became nonsignificant; however, adjustment for other MRI markers did not alter these associations. In this Chinese population, presence of ICS was associated with cognitive impairment independent of vascular risk factors. These associations may be mediated through the presence of infarcts.

We propose an infrastructure for the automated anonymization, extraction and processing of image data stored in clinical data repositories to make routinely acquired imaging data available for research purposes. The automated system, which was tested in the context of analyzing routinely acquired MR brain imaging data, consists of four modules: subject selection using PACS query, anonymization of privacy sensitive information and removal of facial features, quality assurance on DICOM header and image information, and quantitative imaging biomarker extraction. In total, 1,616 examinations were selected based on the following MRI scanning protocols: dementia protocol (246), multiple sclerosis protocol (446) and open question protocol (924). We evaluated the effectiveness of the infrastructure in accessing and successfully extracting biomarkers from routinely acquired clinical imaging data. To examine the validity, we compared brain volumes between patient groups with positive and negative diagnosis, according to the patient reports. Overall, success rates of image data retrieval and automatic processing were 82.5 %, 82.3 % and 66.2 % for the three protocol groups respectively, indicating that a large percentage of routinely acquired clinical imaging data can be used for brain volumetry research, despite image heterogeneity. In line with the literature, brain volumes were found to be significantly smaller (p-value <0.001) in patients with a positive diagnosis of dementia (915 ml) compared to patients with a negative diagnosis (939 ml). This study demonstrates that quantitative image biomarkers such as intracranial and brain volume can be extracted from routinely acquired clinical imaging data. This enables secondary use of clinical images for research into quantitative biomarkers at a hitherto unprecedented scale.

Background: Frontotemporal lobar degeneration is a neurodegenerative disease characterized by brain atrophy of the frontal and anterior temporal lobes. The associated frontotemporal dementia syndromes are clinically heterogeneous, and the pattern of affected cortical regions varies among subtypes. The TMEM106B rs1990622 polymorphism is associated with frontotemporal lobar degeneration, but little is known about how it affects the brain., Methods: We investigated the rs1990622 polymorphism in relation to regional brain volumes to identify potential structures through which TMEM106B confers risk for frontotemporal lobar degeneration. In 4413 nondemented and stroke-free participants from the population-based Rotterdam Study, 150 cortical brain structures and 6 commissural regions were segmented from magnetic resonance imaging., Results: A distinct pattern of association was found between rs1990622 and gray matter volume of left-sided temporal brain regions important for language processing, including the superior temporal gyrus (β=-88.8 μL per risk allele, p=7.64×10(-5)), which contains Wernicke's area. The risk allele was also associated with a smaller anterior commissure cross-sectional area (β=-.167 mm2 per risk allele, p=4.90×10(-5)) and posterior part of the corpus callosum (β=-15.3 μL per risk allele, p=1.23×10(-5)), both of which contain temporal lobe commissural tracts., Conclusions: The asymmetric, predominantly left-sided involvement suggests an effect of TMEM106B on functions lateralized to the dominant hemisphere, such as language. These results show that, in nondemented persons, TMEM106B influences the volume of temporal brain regions that are important for language processing., (Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

In cerebral amyloid angiopathy patients, microbleeds often cluster, mostly occipital, and are associated with apolipoprotein E (APOE) genotype. Microbleeds also frequently occur in the asymptomatic, general population. In this population, we investigated spatial distribution of microbleeds and whether this is influenced by APOE genotype. In 292 persons with microbleeds, we labeled microbleeds on baseline and follow-up magnetic resonance images. We calculated distance between incident and prevalent microbleeds within and between persons and performed lobar segmentation on the magnetic resonance images. Subsequently, we investigated proximity and lobar distribution in strata of APOE genotype. Microbleeds occurred closer within persons than between persons (-42.2 mm, 95% confidence interval, -44.6 to -39.9; p < 0.001). Microbleeds within APOE ε2 and ε4 carriers occurred closer than those in persons with ε3ε3 genotype (-11.9 mm, 95% confidence interval, -24.4 to 0.6; p = 0.06). Persons with ε2 and ε4 alleles had a larger proportion of microbleeds in the occipital lobe than persons with ε3ε3 genotype. Similar to cerebral amyloid angiopathy patients, microbleeds in the general population cluster and the distribution is affected by APOE genotype., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Cerebral microbleeds (CMBs) are considered to be a novel marker of cerebral small vessel disease. However, the link with cognitive impairment remains unclear. We investigated whether CMBs-independent of other traditional markers of cerebral small vessel disease-are related to cognition. Chinese subjects from the population-based Singapore Chinese Eye Study, who failed an initial cognitive screening and were recruited into the ongoing Epidemiology of Dementia in Singapore Study, underwent neuropsychological testing and 3 T brain magnetic resonance imaging. The presence and number of CMBs were graded using Brain Observer Microbleed Scale on susceptibility-weighted images. Other magnetic resonance imaging lesions that were graded included presence of lacunes, white matter lesion, and total brain volumes. A comprehensive neuropsychological battery was administered and cognitive function was summarized as composite and domain-specific Z-scores. Among 282 subjects, 91 had any CMBs (32.3%), of whom 36 (12.8%) had multiple CMBs. CMBs were-independent of cardiovascular risk factors and other markers of cerebral small vessel disease-significantly associated with poorer cognitive function as reflected by composite Z-score (mean difference per CMB increase: -0.06; 95% confidence interval: -0.11, -0.01] and with domain-specific Z-scores including executive function, attention, and visuoconstruction. Among Chinese subjects CMBs were, independent of other concomitant markers of cerebral small vessel disease, associated with poorer cognitive function.

Cortical thickness is considered a potentially relevant marker for neurodegenerative diseases. However, the relationship of demographic and vascular risk factors with cortical thickness remains unclear. In a population-based sample of 1022 non-demented elderly persons (mean age 68.4±7.3 years), we examined aging effects on global and lobar cortical thickness and the relationship with demographic variables and cardiovascular risk factors. We used a validated model-based approach to calculate mean cortical thickness (μm) in brain MR-images. We found that women had a significant thicker cortex than men (p<0.01). Further, with increasing age, cortical thickness decreased (approximately 0.2% per year), with the largest age effects for the occipital and temporal lobes, and the decrease in the frontal lobe being more apparent in men than in women (p-interaction<0.001). Additionally, higher education, higher diastolic blood pressure and larger intra-cranial volume were related to a larger cortical thickness, whilst diabetes mellitus and higher HDL cholesterol levels were related to a thinner cortex., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

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 © 2013 S. Karger AG, Basel.)

Background: Increasing evidence suggests a role of atherosclerosis in the pathogenesis of cognitive impairment and dementia. Calcification volume measured with computed tomography (CT) is a valid marker of atherosclerosis. This study investigates associations of atherosclerosis (measured using CT) at four locations with cognition and brain changes on magnetic resonance imaging (MRI)., Methods: To quantify calcification volume, 2414 nondemented people from the Rotterdam Study underwent CT of the coronary arteries, aortic arch, extracranial carotid arteries, and intracranial carotid arteries. To assess global cognition and performance on memory, executive function, information processing speed, and motor speed, they also underwent neuropsychological tests. In a random subgroup of 844 participants, brain MRI was performed. Automated segmentation and quantification of brain MRI scans yielded brain tissue volumes in milliliters. Diffusion tensor imaging was used to measure the microstructural integrity of the white matter. Relationships of atherosclerotic calcification with cognition, brain tissue volumes, and diffusion tensor imaging measures were assessed with linear regression models and adjusted for relevant confounders., Results: With larger calcification volumes, lower cognitive scores were observed. When calcification volumes were larger, total brain volumes were also smaller. Specifically, larger coronary artery calcification volumes related to smaller gray matter volumes, and extracranial and intracranial carotid calcification volumes related to smaller white matter volumes. Larger calcification volume in all vessel beds was accompanied by worse microstructural integrity of the white matter., Conclusions: Larger calcification volume is associated with worse cognitive performance. It also relates to smaller brain tissue volumes and worse white matter microstructural integrity, revealing possible mechanisms through which atherosclerosis may lead to poorer cognition., (Copyright © 2012 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

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) ɛ4 allele had lower hippocampal volumes than persons with the ɛ3/ɛ3 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 ɛ4 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., (Copyright © 2012 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 × 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 × 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 × 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 × 10(-3) for 6q22 and 1.2 × 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.

It has been hypothesized that white matter lesions at different locations may have different etiology and clinical consequences. Several approaches for the quantification of local white matter lesion load have been proposed in the literature, most of which rely on a distinction between lesions in a periventricular region close to the ventricles and a subcortical zone further away. In this work we present a novel automated method for local white matter lesion volume quantification in magnetic resonance images. The method segments and measures the white matter lesion volume in 43 regions defined by orientation and distance to the ventricles, which allows a more spatially detailed study of lesion load. The potential of the method was demonstrated by analyzing the effect of blood pressure on the regional white matter lesion volume in 490 elderly subjects taken from a longitudinal population study. The method was also compared to two commonly used techniques to assess the periventricular and subcortical lesion load. The main finding was that high blood pressure was primarily associated with lesion load in the vascular watershed area that forms the border between the periventricular and subcortical regions. It explains the associations found for both the periventricular and subcortical load computed for the same data, and that were reported in the literature. But the proposed method can localize the region of association with greater precision than techniques that distinguish between periventricular and subcortical lesions only., (Copyright © 2011 Elsevier Inc. All rights reserved.)

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: We found that lobar cerebral microbleeds occurred significantly more often in the temporal lobe, a region known to be more affected in cerebral amyloid angiopathy., Conclusion: This study corroborates the presumed association of lobar microbleeds with cerebral amyloid angiopathy.

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., (Copyright © 2010 Elsevier Inc. All rights reserved.)

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., (Copyright (c) 2010 Elsevier Inc. All rights reserved.)

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., (Copyright 2008 Elsevier Inc. All rights reserved.)

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.

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.

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 neuropsychological 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.

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.

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.

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 (beta=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.

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.

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.

The aim of the study was to evaluate a new method for automated definition of a center lumen line in vessels in cardiovascular image data. This method, called VAMPIRE, is based on improved detection of vessel-like structures. A multiobserver evaluation study was conducted involving 40 tracings in clinical CTA data of carotid arteries to compare VAMPIRE with an established technique. This comparison showed that VAMPIRE yields considerably more successful tracings and improved handling of stenosis, calcifications, multiple vessels, and nearby bone structures. We conclude that VAMPIRE is highly suitable for automated definition of center lumen lines in vessels in cardiovascular image data.

Noninvasive temperature measurement is feasible with MRI to monitor changes in thermal therapy. Phase shift based MR thermometry gives an estimate of the relative temperature variation between thermal and baseline images. This technique is limited, however, when applied on targets under inter-frame motion. Simple image registration and subtraction are not adequate to recover the temperature properly since the phase shift due to temperature changes is corrupted by an unwanted phase shift. In this work, the unwanted phase shift is predicted from the raw registered phase shift map itself. To estimate the unwanted phase shift, a thin plate smoothing spline is fitted to the values outside the heated region. The spline value in the heated area serves as an estimate for the offset. The estimation result is applied to correct errors in the temperature maps of an ex-vivo experiment.

Attaching tantalum markers to prostheses for Roentgen stereophotogrammetry (RSA) may be difficult and is sometimes even impossible. In this study, a model-based RSA method that avoids the attachment of markers to prostheses is presented and validated. This model-based RSA method uses a triangulated surface model of the implant. A projected contour of this model is calculated and this calculated model contour is matched onto the detected contour of the actual implant in the RSA radiograph. The difference between the two contours is minimized by variation of the position and orientation of the model. When a minimal difference between the contours is found, an optimal position and orientation of the model has been obtained. The method was validated by means of a phantom experiment. Three prosthesis components were used in this experiment: the femoral and tibial component of an Interax total knee prosthesis (Stryker Howmedica Osteonics Corp., Rutherfort, USA) and the femoral component of a Profix total knee prosthesis (Smith & Nephew, Memphis, USA). For the prosthesis components used in this study, the accuracy of the model-based method is lower than the accuracy of traditional RSA. For the Interax femoral and tibial components, significant dimensional tolerances were found that were probably caused by the casting process and manual polishing of the components surfaces. The largest standard deviation for any translation was 0.19mm and for any rotation it was 0.52 degrees. For the Profix femoral component that had no large dimensional tolerances, the largest standard deviation for any translation was 0.22mm and for any rotation it was 0.22 degrees. From this study we may conclude that the accuracy of the current model-based RSA method is sensitive to dimensional tolerances of the implant. Research is now being conducted to make model-based RSA less sensitive to dimensional tolerances and thereby improving its accuracy.