White matter lesion extension to automatic brain tissue segmentation on MRI

Boer, Renske de; Vrooman, Henri A.; Lijn, Fedde van der; Vernooij, Meike W.; Ikram, M. Arfan; Lugt, Aad van der; Breteler, Monique M.B.; Niessen, Wiro J.

doi:10.1016/j.neuroimage.2009.01.011

Cited by 283 publications

(208 citation statements)

References 34 publications

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“…T1-weighted images were segmented into white matter, cortex, and deep gray matter using FreeSurfer software (http://surfer.nmr.mgh.harvard.edu) 17 and FSL (Version 5.0; http://www.fmrib.ox.ac.uk/fsl). 18 Subsequently, the normalappearing white matter (NAWM) was separated from the white matter hyperintensities on FLAIR using a semiautomated segmentation algorithm 19 followed by visual checks. Visible vascular lesions were identified (n ϭ 4) by a neuroradiologist (Ͼ20 years of experience).…”

Section: Image Analysismentioning

confidence: 99%

On the Reproducibility of Inversion Recovery Intravoxel Incoherent Motion Imaging in Cerebrovascular Disease

Wong¹,

Backes²,

Zhang

et al. 2017

AJNR Am J Neuroradiol

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Section: Image Analysismentioning

confidence: 99%

On the Reproducibility of Inversion Recovery Intravoxel Incoherent Motion Imaging in Cerebrovascular Disease

Wong¹,

Backes²,

Zhang

et al. 2017

AJNR Am J Neuroradiol

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“…22 For the assessment of brain volume measurements, we used an automated tissue segmentation that has been described elsewhere. 23 It is based on a k-nearest-neighbor brain tissue classifier extended with white matter lesion (WML) segmentation. Total brain volume (TBV) was defined as the sum of gray matter (GM) volume and total white matter (WM) volume.…”

Section: Magnetic Resonance Imaging Acquisition and Postprocessingmentioning

confidence: 99%

The Bidirectional Association between Reduced Cerebral Blood Flow and Brain Atrophy in the General Population

Zonneveld

Loehrer

Hofman

et al. 2015

J Cereb Blood Flow Metab

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The question remains whether reduced cerebral blood flow (CBF) leads to brain atrophy or vice versa. We studied the longitudinal relation between CBF and brain volume in a community-dwelling population. In the Rotterdam Study, 3011 participants (mean age 59.6 years (s.d. 8.0)) underwent repeat brain magnetic resonance imaging to quantify brain volume and CBF at two time points. Adjusted linear regression models were used to investigate the bidirectional relation between CBF and brain volume. We found that smaller brain volume at baseline was associated with a steeper decrease in CBF in the whole population (standardized change per s.d. increase of total brain volume (TBV) = 0.296 (95% confidence interval (CI) 0.200; 0.393)). Only in persons aged ⩾ 65 years, a lower CBF at baseline was associated with steeper decline of TBV (standardized change per s.d. increase of CBF = 0.003 (95% CI − 0.004; 0.010) in the whole population and 0.020 (95% CI 0.004; 0.036) in those aged ⩾ 65 years of age). Our results indicate that brain atrophy causes CBF to decrease over time, rather than vice versa. Only in persons aged 465 years of age did we find lower CBF to also relate to brain atrophy.

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“…They are quantified using visual rating scales or automated segmentation methods [73][74][75] . They are predominantly supratentorial in distribution, although are also common in the pons, and have a predilection for the frontal lobes.…”

Section: Structural Imagingmentioning

confidence: 99%

What can imaging tell us about cognitive impairment and dementia?

Narayanan

Murray

2016

WJR

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Dementia is a contemporary global health issue with far reaching consequences, not only for affected individuals and their families, but for national and global socioeconomic conditions. The hallmark feature of dementia is that of irreversible cognitive decline, usually affecting memory, and impaired activities of daily living. Advances in healthcare worldwide have facilitated longer life spans, increasing the risks of developing cognitive decline and dementia in late life. Dementia remains a clinical diagnosis. The role of structural and molecular neuroimaging in patients with dementia is primarily supportive role rather than diagnostic, American and European guidelines recommending imaging to exclude treatable causes of dementia, such as tumor, hydrocephalus or intracranial haemorrhage, but also to distinguish between different dementia subtypes, the commonest of which is Alzheimer's disease. However, this depends on the availability of these imaging techniques at individual centres. Advanced magnetic resonance imaging (MRI) techniques, such as functional connectivity MRI, diffusion tensor imaging and magnetic resonance spectroscopy, and molecular imaging techniques, such as 18F fluoro-deoxy glucose positron emission tomography (PET), amyloid PET, tau PET, are currently within the realm of dementia research but are available for clinical use. Increasingly the research focus is on earlier identification of at risk preclinical individuals, for example due to family history. Intervention at the preclinical stages before irreversible brain damage occurs is currently the best hope of reducing the impact of dementia.

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White matter lesion extension to automatic brain tissue segmentation on MRI

Cited by 283 publications

References 34 publications

On the Reproducibility of Inversion Recovery Intravoxel Incoherent Motion Imaging in Cerebrovascular Disease

On the Reproducibility of Inversion Recovery Intravoxel Incoherent Motion Imaging in Cerebrovascular Disease

The Bidirectional Association between Reduced Cerebral Blood Flow and Brain Atrophy in the General Population

What can imaging tell us about cognitive impairment and dementia?

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