The Rotterdam Scan Study: design and update up to 2012

Neuroimaging plays an important role in etiologic research on neurological diseases in the elderly. The Rotterdam Scan Study was initiated as part of the ongoing Rotterdam Study with the aim to unravel causes of neurological disease by performing neuroimaging in a population-based longitudinal setting. In 1995 and 1999 random subsets of the Rotterdam Study underwent neuroimaging, whereas from 2005 onwards MRI has been implemented into the core protocol of the Rotterdam Study. In this paper, we discuss the background and rationale of the Rotterdam Scan Study. We also describe the imaging protocol and post-processing techniques, and highlight the main findings to date. Finally, we make recommendations for future research, which will also be the main focus of investigation in the Rotterdam Scan Study

The Rotterdam Study: 2012 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods

Retinal neurodegeneration on optical coherence tomography and cerebral atrophy

Neurodegeneration in dementia is mainly evaluated by assessing cerebral atrophy, while retinal neurodegeneration can be quantified in vivo using optical coherence tomography (OCT). We examined the association of retinal nerve fibre layer (RNFL) and ganglion cell-inner plexiform layer (GC-IPL) thinning with global and regional cerebral atrophy on magnetic resonance imaging (MRI). Malay participants aged 60-80 years from the Epidemiology of Dementia in Singapore Study underwent comprehensive examinations, including 3-Tesla cranial MRI. RNFL and GC-IPL thicknesses were obtained from spectral domain-OCT; and cerebral grey and white matter volumes were obtained from MRI scans using a validated segmentation tool. Linear regression models were constructed with adjustment for age and sex; and additionally for vascular risk factors and MM markers including intracranial volume. 164 participants without glaucoma with gradable quality MRI and OCT scans were included for analysis. GC-IPL thinning was associated with reduction in total brain volume in the occipital (mean change in GC-IPL per standard deviation (SD) decrease in occipital lobe volume: -1.77 mu m, 95% confidence interval (CI) -6.55 to 0.01 mu m) and temporal lobes (mean change in GC-IPL per SD decrease in temporal lobe volume: -3.45 mu m, 95%CI-5.40 to -1.49 mu m) in multivariate adjusted models. In particular, GC-IPL thinning was primarily associated with grey matter volume, whereas no association was found with white matter changes. Retinal neuronal damage, as reflected by GC-IPL thinning, was independently associated with grey matter loss in the occipital and temporal lobes, suggesting that retinal OCT may provide insights for assessing neurodegeneration in the brain. (C) 2014 Elsevier Ireland Ltd. All rights reserved

Learning Classifiers for Multimodal Image Detection

Learning Classifiers are essential analysis tools in today's era due to the rapid expansion in data-intensive applications. Every type of the classifier has own distinct architectural properties which allow to apply them in various application-specific requirements. Here, experimental work is performed to analyse the performance and accuracy of most commonly used learning classifiers applied within the scope of multimodal image classification problem space. The purpose of this study is to investigate the usefulness of the learning-classifiers with the multimodal datasets which are in many cases have the curse of dimensionality and may contain a very high volume of noise. Validation is conducted over multimodal datasets with the proposed classification algorithms operating in a parallel manner. Finally, results are discussed to explore possible ways to apply every learning classifier in multi-modal image classification applications

Intracranial Stenosis, Cerebrovascular Diseases, and Cognitive Impairment in Chinese

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