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Determinants of cerebellar and cerebral volume in the general elderly population

Yoo Young Hoogendam, Jos N. van der Geest, Fedde van der Lijn, Aad van der Lugt, Wiro J. Niessen, Gabriel P. Krestin, Albert Hofman, Meike W. Vernooij, Monique M.B. Breteler, M. Arfan Ikram
2012 Neurobiology of Aging  
., 2008; van Harten et al., 2006) , but the strong relationship between diabetes and cerebellar volume in older adults has not been described elsewhere.  ... 
doi:10.1016/j.neurobiolaging.2012.02.012 pmid:22405042 fatcat:uvzqyskvajg3jgr4gyyi54z6m4

Statistical Analysis of Structural Brain Connectivity [chapter]

Renske de Boer, Michiel Schaap, Fedde van der Lijn, Henri A. Vrooman, Marius de Groot, Meike W. Vernooij, M. Arfan Ikram, Evert F. S. van Velsen, Aad van der Lugt, Monique M. B. Breteler, Wiro J. Niessen
2010 Lecture Notes in Computer Science  
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
more » ... sing 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.
doi:10.1007/978-3-642-15745-5_13 fatcat:ghqqu3yg25aynhkhzco7lchztu

Statistical analysis of minimum cost path based structural brain connectivity

Renske de Boer, Michiel Schaap, Fedde van der Lijn, Henri A. Vrooman, Marius de Groot, Aad van der Lugt, M. Arfan Ikram, Meike W. Vernooij, Monique M.B. Breteler, Wiro J. Niessen
2011 NeuroImage  
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
more » ... hed 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. NeuroImage 55 (2011) 557-565 ⁎ Corresponding author. Biomedical Imaging Group Rotterdam,
doi:10.1016/j.neuroimage.2010.12.012 pmid:21147237 fatcat:5jyocrid6ngmno52qxfanpeebi

Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts

Fedde van der Lijn, Tom den Heijer, Monique M.B. Breteler, Wiro J. Niessen
2008 NeuroImage  
A preliminary version of the proposed method was presented at a conference (van der Lijn et al., 2007) , but with a limited crossvalidation experiment on 20 manually segmented images.  ...  Unlike techniques used to optimize comparable models (for example Fischl et al., 2002 and van Leemput et al., 1999) , this optimizer finds the global minimum.  ... 
doi:10.1016/j.neuroimage.2008.07.058 pmid:18761411 fatcat:mtztnjhqlrathf2ttmcvtj5uze

Automated Brain Structure Segmentation Based on Atlas Registration and Appearance Models

Fedde van der Lijn, Marleen de Bruijne, Stefan Klein, Tom den Heijer, Yoo Y. Hoogendam, Aad van der Lugt, Monique M. B. Breteler, Wiro J. Niessen
2012 IEEE Transactions on Medical Imaging  
Hoogendam) under supervision of a neurologist (T. den Heijer) and a neuro-radiologist (A. van der Lugt).  ... 
doi:10.1109/tmi.2011.2168420 pmid:21937346 fatcat:3wbcuchrq5flrbo7br4fqnldpq

Older Age Relates to Worsening of Fine Motor Skills: A Population-Based Study of Middle-Aged and Elderly Persons

Yoo Young Hoogendam, Fedde van der Lijn, Meike W. Vernooij, Albert Hofman, Wiro J. Niessen, Aad van der Lugt, M. Arfan Ikram, Jos N. van der Geest
2014 Frontiers in Aging Neuroscience  
Citation: Hoogendam YY, van der Lijn F, Vernooij MW, Hofman A, Niessen WJ, van der Lugt A, Ikram MA and van der Geest JN (2014) Older age relates to worsening of fine motor skills: a population-based study  ...  Vernooij, Albert Hofman, Aad van der Lugt, M. Arfan Ikram, and Jos N. van der Geest) or the acquisition (Yoo Young Hoogendam, Fedde van der Lijn, Wiro J.  ...  Niessen, and Jos N. van der Geest), analysis (Yoo Young Hoogendam, M. Arfan Ikram, and Jos N. van der Geest), or interpretation of data for the work (Yoo Young Hoogendam, Fedde van der Lijn, M.  ... 
doi:10.3389/fnagi.2014.00259 pmid:25309436 pmcid:PMC4174769 fatcat:oroycypfh5butdecmmal36xsya

The influence of cerebral small vessel disease on default mode network deactivation in mild cognitive impairment

Janne M. Papma, Tom den Heijer, Inge de Koning, Francesco U. Mattace-Raso, Aad van der Lugt, Fedde van der Lijn, John C. van Swieten, Peter J. Koudstaal, Marion Smits, Niels D. Prins
2013 NeuroImage: Clinical  
Introduction: Cerebral small vessel disease (CSVD) is thought to contribute to cognitive dysfunction in patients with mild cognitive impairment (MCI). The underlying mechanisms, and more specifically, the effects of CSVD on brain functioning in MCI are incompletely understood. The objective of the present study was to examine the effects of CSVD on brain functioning, activation and deactivation, in patients with MCI using task-related functional MRI (fMRI). Methods: We included 16 MCI patients
more » ... ith CSVD, 26 MCI patients without CSVD and 25 controls. All participants underwent a physical and neurological examination, neuropsychological testing, structural MRI, and fMRI during a graded working memory paradigm. Results: MCI patients with and without CSVD had a similar neuropsychological profile and task performance during fMRI, but differed with respect to underlying (de)activation patterns. MCI patients with CSVD showed impaired deactivation in the precuneus/posterior cingulate cortex, a region known to be involved in the default mode network. In MCI patients without CSVD, brain activation depended on working memory load, as they showed relative 'hyperactivation' during vigilance, and 'hypoactivation' at a high working memory load condition in working memory related brain regions. Conclusions: We present evidence that the potential underlying mechanism of CSVD affecting cognition in MCI is through network interference. The observed differences in brain activation and deactivation between MCI patients with and without CSVD, who had a similar 'clinical phenotype', support the view that, in patients with MCI, different types of pathology can contribute to cognitive impairment through different pathways.
doi:10.1016/j.nicl.2012.11.005 pmid:24179756 pmcid:PMC3778258 fatcat:e6rwxfjedrcrjkzlxyg45q3c6a

IT Infrastructure to Support the Secondary Use of Routinely Acquired Clinical Imaging Data for Research

Kai Yan Eugene Leung, Fedde van der Lijn, Henri A. Vrooman, Miriam C. J. M. Sturkenboom, Wiro J. Niessen
2014 Neuroinformatics  
Furthermore, computer tools are being developed to automate these measurements (Adame et al. 2004; Tang et al. 2012; Isgum et al. 2007; Shahzad et al. 2013; Fischl et al. 2002; van der Lijn et al. 2008  ... 
doi:10.1007/s12021-014-9240-7 pmid:25129841 pmcid:PMC4303741 fatcat:i6qo3npysvfopfkvlgealori5y

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

Vincent Koppelmans, Michiel B. de Ruiter, Fedde van der Lijn, Willem Boogerd, Caroline Seynaeve, Aad van der Lugt, Henri Vrooman, Wiro J. Niessen, Monique M. B. Breteler, Sanne B. Schagen
2011 Breast Cancer Research and Treatment  
The institutional review boards of the two participating institutions (the Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital and the Erasmus University Medical Center) approved the study.  ...  Chemotherapy-exposed subjects We selected consecutive female patients with unilateral invasive breast cancer from the registries of the Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital and  ... 
doi:10.1007/s10549-011-1888-1 pmid:22205140 fatcat:gwc4rnh6u5fe5o6yy66xz2pz4y

Estimating the impulse response of buried objects from ground-penetrating radar signals

Fedde van der Lijn, Friedrich Roth, Michel Verhaegen, Russell S. Harmon, John H. Holloway, Jr., J. T. Broach
2003 Detection and Remediation Technologies for Mines and Minelike Targets VIII  
This paper presents a novel deconvolution algorithm designed to estimate the impulse response of buried objects based on ground penetrating radar (GPR) signals. The impulse response is a rich source of information about the buried object and therefore very useful for intelligent signal processing of GPR data. For example, it can be used in a target classification scheme to reduce the false alarm rate in demining operations. Estimating the target impulse response from the incident and scattered
more » ... adar signals is a basic deconvolution problem. However, noise sensitivity and ground dispersion prevent the use of simple deconvolution methods like linear least squares deconvolution. Instead, a new deconvolution algorithm has been developed that computes estimates adhering to a physical impulse response model and that can be characterized by a limited number of parameters. It is shown that the new algorithm is robust with respect to noise and that it can deal with ground dispersion. The general performance of the algorithm has been tested on data generated by finite-difference time-domain (FDTD) simulations. The results demonstrate that the algorithm can distinguish between different dielectric and metal targets, making it very suitable for use in a classification scheme. Moreover, since the estimated impulse responses have physical meaning they can be related to target characteristics such as size and material properties. A direct application of this is the estimation of the permittivity of a dielectric target from its impulse response and that of a calibration target.
doi:10.1117/12.486979 fatcat:luo4tdkutjdd3ejjezmuhn7aym

Genetic determination of human facial morphology: links between cleft-lips and normal variation

Stefan Boehringer, Fedde van der Lijn, Fan Liu, Manuel Günther, Stella Sinigerova, Stefanie Nowak, Kerstin U Ludwig, Ruth Herberz, Stefan Klein, Albert Hofman, Andre G Uitterlinden, Wiro J Niessen (+8 others)
2011 European Journal of Human Genetics  
Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and other previous studies showed distinctly differing facial distance measurements when comparing unaffected relatives of NSCL/P patients with normal controls. Here, we test the hypothesis that genetic loci involved in NSCL/P also influence normal variation in facial morphology. We tested 11 SNPs from 10 genomic regions
more » ... iously showing replicated evidence of association with NSCL/P for association with normal variation of nose width and bizygomatic distance in two cohorts from Germany (N¼529) and the Netherlands (N¼2497). The two most significant associations found were between nose width and SNP rs1258763 near the GREM1 gene in the German cohort (P¼6Â10 À4 ), and between bizygomatic distance and SNP rs987525 at 8q24.21 near the CCDC26 gene (P¼0.017) in the Dutch sample. A genetic prediction model explained 2% of phenotype variation in nose width in the German and 0.5% of bizygomatic distance variation in the Dutch cohort. Although preliminary, our data provide a first link between genetic loci involved in a pathological facial trait such as NSCL/P and variation of normal facial morphology. Moreover, we present a first approach for understanding the genetic basis of human facial appearance, a highly intriguing trait with implications on clinical practice, clinical genetics, forensic intelligence, social interactions and personal identity.
doi:10.1038/ejhg.2011.110 pmid:21694738 pmcid:PMC3198142 fatcat:jkku5ij5sfg65glscsi5hnfbya

The Thyroid Hormone Receptor Alpha Locus and White Matter Lesions: A Role for the Clock Gene REV-ERBα

Marco Medici, M. Arfan Ikram, Fedde van der Lijn, Tom den Heijer, Meike W. Vernooij, Albert Hofman, Wiro J. Niessen, Theo J. Visser, Monique M.B. Breteler, Robin P. Peeters
2012 Thyroid  
Thyroid disorders are associated with an increased risk of cognitive impairment and Alzheimer's disease. Both small vessel disease and neurodegeneration have a role in the pathogenesis of cognitive impairment and Alzheimer's disease. Thyroid hormone receptor alpha (TRa) is the predominant TR in brain. The circadian clock gene REV-ERBa overlaps with the TRa gene and interferes with TRa expression. Limited data are available on the role of the TRa/REV-ERBa locus in small vessel disease and
more » ... generation. We therefore studied genetic variation in the TRa/REV-ERBa locus in relation to brain imaging data, as early markers for small vessel disease and neurodegeneration. Methods: Fifteen polymorphisms, covering the TRa/REV-ERBa locus, were studied in relation to white matter lesion (WML), total brain, and hippocampal volumes in the Rotterdam Study I (RS-I, n = 454). Associations that remained significant after multiple testing correction were subsequently studied in an independent population for replication (RS-II, n = 607). Results: No associations with total brain or hippocampal volumes were detected. A haplotype block in REV-ERBa was associated with WML volumes in RS-I. Absence of this haplotype was associated with larger WML volumes in women (0.38% -0.18% [b -SE], p = 0.007), but not in men (0.04% -0.11%, p = 0.24), which was replicated in RS-II (women: 0.15% -0.05%, p = 0.04; men: 0.05% -0.07%, p = 0.80). Meta-analysis of the two populations showed that women lacking this haplotype have a 1.9 times larger WML volume ( p = 0.001). Conclusion: Our results suggest a role for REV-ERBa in the pathogenesis of WMLs.
doi:10.1089/thy.2012.0198 pmid:23083441 pmcid:PMC3487114 fatcat:crdxlzdirreefppdy24zlvtffm

A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans

Fan Liu, Fedde van der Lijn, Claudia Schurmann, Gu Zhu, M. Mallar Chakravarty, Pirro G. Hysi, Andreas Wollstein, Oscar Lao, Marleen de Bruijne, M. Arfan Ikram, Aad van der Lugt, Fernando Rivadeneira (+23 others)
2012 PLoS Genetics  
Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on
more » ... andmark data obtained from three-dimensional head magnetic resonance images (MRIs) and twodimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes-PRDM16, PAX3, TP63, C5orf50, and COL17A1-in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.
doi:10.1371/journal.pgen.1002932 pmid:23028347 pmcid:PMC3441666 fatcat:x7kccwsq2zedtgjiwrxnuezw4y

MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Adriënne M. Mendrik, Koen L. Vincken, Hugo J. Kuijf, Marcel Breeuwer, Willem H. Bouvy, Jeroen de Bresser, Amir Alansary, Marleen de Bruijne, Aaron Carass, Ayman El-Baz, Amod Jog, Ranveer Katyal (+18 others)
2015 Computational Intelligence and Neuroscience  
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
more » ... ated 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.
doi:10.1155/2015/813696 pmid:26759553 pmcid:PMC4680055 fatcat:uhsmxrfz65ahtc7fciqt6v3fem

Mathematical Methods in Biomedical Image Analysis (MMBIA 2007)

2007 2007 IEEE 11th International Conference on Computer Vision  
van der Lijn, Tom den Heijer, Monique Breteler, Wiro Niessen "Fuzzy classification of brain MRI using a priori knowledge: weighted fuzzy C-means" Olivier Salvado, Pierrick Bourgeat, Oscar Acosta Tamayo  ...  Localization Certainty in Level Set Segmentation" Jenny Folkesson, Carl-Fred rik Westin "Combining graph cuts, atlas registration, and voxel classification for hippocampus segmentation in MR images" Fedde  ... 
doi:10.1109/iccv.2007.4408823 fatcat:dcdpjaymqve75lxshxmbhif24m
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