Application of an Imaging-Based Sum Score for Cerebral Amyloid Angiopathy to the General Population: Risk of Major Neurological Diseases and Mortality

Objective: To assess the relation between a sum score of imaging markers indicative of cerebral amyloid angiopathy (CAA) and cognitive impairment, stroke, dementia, and mortality in a general population. Methods: One thousand six hundred twenty-two stroke-free and dementia-free participants of the population-based Rotterdam Study (mean age 73.1 years, 54.3% women) underwent brain MRI (1.5 tesla) in 2005–2011 and were followed for stroke, dementia and death until 2016–2017. Four MRI markers (strictly lobar cerebral microbleeds, cortical superficial siderosis, centrum semiovale perivascular spaces, and white matter hyperintensities) were combined to construct the CAA sum score, ranging from 0 to 4. Neuropsychological testing measured during the research visit closest to scan date were used to assess general cognitive function and cognitive domains. The associations of the CAA sum score with cognition cross-sectionally and with stroke, dementia, and mortality longitudinally were determined using linear regression and Cox proportional hazard modeling adjusted for age, sex, hypertension, cholesterol, lipid lowering medication, atrial fibrillation, antithrombotic medication and APOE-ε2/ε4 carriership. Additionally, we accounted for competing risks of death due to other causes for stroke and dementia, and calculated absolute risk estimates. Results: During a mean follow-up of 7.2 years, 62 participants suffered a stroke, 77 developed dementia and 298 died. Participants with a CAA score of 1 showed a lower Mini-Mental-State-Exam (fully-adjusted mean difference −0.21, 9

The Impact of Incidental Findings Detected During Brain Imaging on Research Participants of the Rotterdam Study: An Interview Study

This interview study investigates the short- and long-term implications of incidental findings detected through brain imaging on research participants’ lives and their surroundings. For this study, nine participants of the Rotterdam Scan Study with an incidental finding were approached and interviewed. When examining research participants’ narratives on the impact of the disclosure of incidental findings, the authors identified five sets of tensions with regard to motivations for and expectations of research participation, preferences regarding disclosure, short- and long-term impacts and impacts on self and others. The paper shows: (1) that the impact of incidental findings may be greater than participants at first let on; (2) incidental findings can have significant effects on participants’ social environment; and (3) participants may not feel prepared for disclosure even if incidental findings have been discussed during the informed consent process. The authors call for investigators to be aware of research participants’ experiences and these short- and long-term impacts when designing suitable courses of action for the detection and management of incidental findings in research settings

Transfer learning by feature-space transformation: A method for Hippocampus segmentation across scanners

Many successful approaches in MR brain segmentation use supervised voxel classification, which requires manually labeled training images that are representative of the test images to segment. However, the performance of such methods often deteriorates if training and test images are acquired with different scanners or scanning parameters, since this leads to differences in feature representations between training and test data. In this paper we propose a feature-space transformation (FST) to overcome such differences in feature representations. The proposed FST is derived from unlabeled images of a subject that was scanned with both the source and the target scan protocol. After an affine registration, these images give a mapping between source and target voxels in the feature space. This mapping is then used to map all training samples to the feature representation of the test samples. We evaluated the benefit of the proposed FST on hippocampus segmentation. Experiments were performed on two datasets: one with relatively small differences between training and test images and one with large differences. In both cases, the FST significantly improved the performance compared to using only image normalization. Additionally, we showed that our FST can be used to improve the performance of a state-of-the-art patch-based-atlas-fusion technique in case of large differences between scanners

Predicting Global Cognitive Decline in the General Population Using the Disease State Index

Background: Identifying persons at risk for cognitive decline may aid in early detection of persons at risk of dementia and to select those that would benefit most from therapeutic or preventive measures for dementia. Objective: In this study we aimed to validate whether cognitive decline in the general population can be predicted with multivariate data using a previously proposed supervised classification method: Disease State Index (DSI). Methods: We included 2,542 participants, non-demented and without mild cognitive impairment at baseline, from the population-based Rotterdam Study (mean age 60.9 ± 9.1 years). Participants with significant global cognitive decline were defined as the 5% of participants with the largest cognitive decline per year. We trained DSI to predict occurrence of significant global cognitive decline using a large variety of baseline features, including magnetic resonance imaging (MRI) features, cardiovascular risk factors, APOE-ε4 allele carriership, gait features, education, and baseline cognitive function as predictors. The prediction performance was assessed as area under the receiver operating characteristic curve (AUC), using 500 repetitions of 2-fold cross-validation experiments, in which (a randomly selected) half of the data was used for training and the other half for testing. Results: A mean AUC (95% confidence interval) for DSI prediction was 0.78 (0.77–0.79) using only age as input feature. When using all available features, a mean AUC of 0.77 (0.75–0.78) was obtained. Without age, and with age-corrected features and feature selection on MRI features, a mean AUC of 0.70 (0.63–0.76) was obtained, showing the potential of other features besides age. Conclusion: The best performance in the prediction of global cognitive decline in the general population by DSI was obtained using only age as input feature. Other features showed potential, but did not improve prediction. Future studies should evaluate whether the performance could be improved by new features, e.g., longitudinal features, and other prediction methods

The value of hippocampal volume, shape, and texture for 11-year prediction of dementia: a population-based study

Hippocampal volume and shape are known magnetic resonance imaging biomarkers of neurodegeneration. Recently, hippocampal texture has been shown to improve prediction of dementia in patients with mild cognitive impairment, but it is unknown whether texture adds prognostic information beyond volume and shape and whether the predictive value extends to cognitively healthy individuals. Using 510 subjects from the Rotterdam Study, a prospective, population-based cohort study, we investigated if hippocampal volume, shape, texture, and their combination were predictive of dementia and determined how predictive performance varied with time to diagnosis and presence of early clinical symptoms of dementia. All features showed significant predictive performance with the area under the receiver operating characteristic curve ranging from 0.700 for texture alone to 0.788 for the combination of volume and texture. Although predictive performance extended to those without objective cognitive complaints or mild cognitive impairment, performance decreased with increasing follow-up time. We conclude that a combination of multiple hippocampal features on magnetic resonance imaging performs better in predicting dementia in the general population than any feature by itself

Atherosclerotic calcification in major vessel beds in chronic obstructive pulmonary disease: The Rotterdam Study

Background and aims: COPD is associated with an increased risk of cardiovascular morbidity and mortality, potentially by mechanisms of atherosclerosis. Insight into location-specific vulnerability to atherosclerosis in COPD, including intracranial arteries, is lacking. We aimed to investigate the relation between COPD and atherosclerosis in multiple vessel beds within a large population-based cohort study. Methods: From 2003 to 2006, a random sample of 2187 elderly participants (mean age, 69.6 ± 6.8 years; 50.9% female; 11.7% COPD) from the population-based Rotterdam Study underwent computed tomography to quantify atherosclerotic coronary artery calcification (CAC), aortic arch calcification (AAC), extracranial carotid artery calcification (ECAC), and intracranial carotid artery calcification (ICAC). We investigated the association of COPD [ratio of forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) < 70%] with the presence of calcification and with calcification volumes in each vessel bed using logistic and linear regression, with adjustments for cardiovascular risk factors including smoking. Results: The prevalence of CAC, AAC and ECAC was significantly higher in subjects with COPD compared to those without. After adjusting for age and smoking, COPD remained associated with the presence of ECAC (odds ratio 1.46 [95% confidence interval, 1.02–2.07, p = 0.037]). COPD was significantly associated with larger calcification volumes in all four vessel beds in people in whom calcification was present. Conclusions: The results of this study suggest that COPD plays a role in extracranial carotid artery atherosclerosis initiation and systemic atherosclerosis aggravation

Migraine Genetic Variants Influence Cerebral Blood Flow

Objective: To investigate the association of migraine genetic variants with cerebral blood flow (CBF). Background: Migraine is a common disorder with many genetic and non-genetic factors affecting its occurrence. The exact pathophysiological mechanisms underlying the disease remain unclear, but are known to involve hemodynamic and vascular disruptions. Recent genome-wide association studies have identified 44 genetic variants in 38 genetic loci that affect the risk of migraine, which provide the opportunity to further disentangle these mechanisms. Methods: We included 4665 participants of the population-based Rotterdam Study (mean age 65.0 ± 10.9 years, 55.6% women). Cross-sectional area (mm2), flow velocity (mm/s), and blood flow (mL/min) were measured in both carotids and the basilar artery using 2-dimensional phase-contrast magnetic resonance imaging. We analyzed 43 previously identified migraine variants separately and calculated a genetic risk score (GRS). To assess the association with CBF, we used linear regression models adjusted for age, sex, and total brain volume. Hierarchical clustering was performed based on the associations with CBF measures and tissue enrichment. Results: The rs67338227 risk allele was associated with higher flow velocity and smaller cross-sectional area in the carotids (Pminimum = 3.7 × 10−8). Other variants were related to CBF with opposite directions of effect, but not significantly after multiple testing adjustments (P < 1.4 × 10−4). The migraine GRS was not associated with CBF after multiple testing corrections. Migraine risk variants were found to be enriched for flow in the basilar artery (λ = 2.39). Conclusions: These findings show that genetic migraine risk is complexly associated with alterations in cerebral hemodynamics

Klotho gene polymorphism, brain structure and cognition in early-life development

Variation in the klotho gene is linked to differences in health outcomes: klotho allele KL-VS heterozygosity is associated with longevity, better cognition and greater right frontal grey matter volume in late life. Contradicting reports, however, suggest that KL-VS’s effect on health might be age-dependent. Here we examine the relationship between KL-VS genotype, cognition and brain structure in childhood and adolescence. We hypothesized that KL-VS has early influences on cognitive and brain development. We investigated the associations of KL-VS carrier status with cognition and brain morphology in a cohort of 1387 children and adolescents aged 3–21 years, examining main effects and interactions between age, sex and socioeconomic circumstance. KL-VS had no main effect on either cognition or brain structure, though there was a significant KL-VS × age interaction for cognition (specifically executive function, attention, episodic memory, and general cognition), total grey matter and total brain volume. KL-VS heterozygotes had better cognition than non-carriers before age 11, but lower cognition after age 11. Heterozygotes had smaller brains than non-carriers did in early childhood. Sex moderated the association between KL-VS and white matter volume. Among girls, KL-VS heterozygotes had smaller white matter volumes than non-carriers. Among boys, heterozygotes had greater white matter volumes than non-carriers. However, a replication in a cohort of 2306 children aged 6–12 years showed no significant associations. In contrast to findings in late life, these results show that KL-VS does not have a main effect on cognition and brain structure. Furthermore, KL-VS’s influence may depend on age and sex

Normative brain volumetry derived from different reference populations: Impact on single-subject diagnostic assessment in dementia

Brain imaging data are increasingly made publicly accessible and volumetric imaging measures derived from population-based cohorts may serve as normative data for individual patient diagnostic assessment. Yet, these normative cohorts are usually not a perfect reflection of a patient’s base population, nor are imaging parameters such as field strength or scanner type similar. In this proof of principle study, we assessed differences between reference curves of subcortical structure volumes of normal controls derived from two population-based studies and a case-control study. We assessed the impact of any differences on individual assessment of brain structure volumes. Percentile curves were fitted on the three healthy cohorts. Next, percentile values for these subcortical structures for individual patients from these three cohorts, 91 mild cognitive impairment (MCI) and 95 Alzheimer’s Disease (AD) cases and patients from the Alzheimer Center (AC) were calculated, based on the distributions of each of the three cohorts. Overall we found that the subcortical volume normative data from these cohorts is highly interchangeable, suggesting more flexibility in clinical implementation

Normative brain volumetry derived from different reference populations: Impact on single-subject diagnostic assessment in dementia

Brain imaging data are increasingly made publicly accessible and volumetric imaging measures derived from population-based cohorts may serve as normative data for individual patient diagnostic assessment. Yet, these normative cohorts are usually not a perfect reflection of a pat