238 research outputs found
Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI
The neuroimage analysis community has neglected the automated segmentation of
the olfactory bulb (OB) despite its crucial role in olfactory function. The
lack of an automatic processing method for the OB can be explained by its
challenging properties. Nonetheless, recent advances in MRI acquisition
techniques and resolution have allowed raters to generate more reliable manual
annotations. Furthermore, the high accuracy of deep learning methods for
solving semantic segmentation problems provides us with an option to reliably
assess even small structures. In this work, we introduce a novel, fast, and
fully automated deep learning pipeline to accurately segment OB tissue on
sub-millimeter T2-weighted (T2w) whole-brain MR images. To this end, we
designed a three-stage pipeline: (1) Localization of a region containing both
OBs using FastSurferCNN, (2) Segmentation of OB tissue within the localized
region through four independent AttFastSurferCNN - a novel deep learning
architecture with a self-attention mechanism to improve modeling of contextual
information, and (3) Ensemble of the predicted label maps. The OB pipeline
exhibits high performance in terms of boundary delineation, OB localization,
and volume estimation across a wide range of ages in 203 participants of the
Rhineland Study. Moreover, it also generalizes to scans of an independent
dataset never encountered during training, the Human Connectome Project (HCP),
with different acquisition parameters and demographics, evaluated in 30 cases
at the native 0.7mm HCP resolution, and the default 0.8mm pipeline resolution.
We extensively validated our pipeline not only with respect to segmentation
accuracy but also to known OB volume effects, where it can sensitively
replicate age effects
Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging
Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high b-value acquisitions, such as CHARMED modeling and biomarkers from the diffusion propagator
Incidence, risk, and case fatality of first ever stroke in the elderly population. The Rotterdam Study
OBJECTIVE: To estimate the incidence, survival, and lifetime risk of
stroke in the elderly population. METHODS: The authors conducted a study
in 7,721 participants from the population based Rotterdam Study who were
free from stroke at baseline (1990-1993) and were followed up for stroke
until 1 January 1999. Age and sex specific incidence, case fatality rates,
and lifetime risks of stroke were calculated. RESULTS: Mean follow up was
6.0 years and 432 strokes occurred. The incidence rate of stroke per 1,000
person years increased with age and ranged from 1.7 (95% CI 0.4 to 6.6) in
men aged 55 to 59 years to 69.8 (95% CI 22.5 to 216.6) in men aged 95
years or over. Corresponding figures for women were 1.2 (95% CI 0.3 to
4.7) and 33.1 (95% CI 17.8 to 61.6). Men and women had similar absolute
lifetime risks of stroke (21% for those aged 55 years). The survival after
stroke did not differ according to sex. CONCLUSIONS: Stroke incidence
increases with age, also in the very old. Although the incidence rate is
higher in men than in women over the entire age range, the lifetime risks
were similar for both sexes
FastSurfer-HypVINN: Automated sub-segmentation of the hypothalamus and adjacent structures on high-resolutional brain MRI
The hypothalamus plays a crucial role in the regulation of a broad range of
physiological, behavioural, and cognitive functions. However, despite its
importance, only a few small-scale neuroimaging studies have investigated its
substructures, likely due to the lack of fully automated segmentation tools to
address scalability and reproducibility issues of manual segmentation. While
the only previous attempt to automatically sub-segment the hypothalamus with a
neural network showed promise for 1.0 mm isotropic T1-weighted (T1w) MRI, there
is a need for an automated tool to sub-segment also high-resolutional (HiRes)
MR scans, as they are becoming widely available, and include structural detail
also from multi-modal MRI. We, therefore, introduce a novel, fast, and fully
automated deep learning method named HypVINN for sub-segmentation of the
hypothalamus and adjacent structures on 0.8 mm isotropic T1w and T2w brain MR
images that is robust to missing modalities. We extensively validate our model
with respect to segmentation accuracy, generalizability, in-session test-retest
reliability, and sensitivity to replicate hypothalamic volume effects (e.g.
sex-differences). The proposed method exhibits high segmentation performance
both for standalone T1w images as well as for T1w/T2w image pairs. Even with
the additional capability to accept flexible inputs, our model matches or
exceeds the performance of state-of-the-art methods with fixed inputs. We,
further, demonstrate the generalizability of our method in experiments with 1.0
mm MR scans from both the Rhineland Study and the UK Biobank. Finally, HypVINN
can perform the segmentation in less than a minute (GPU) and will be available
in the open source FastSurfer neuroimaging software suite, offering a
validated, efficient, and scalable solution for evaluating imaging-derived
phenotypes of the hypothalamus.Comment: Submitted to Imaging Neuroscienc
Homocysteine and brain atrophy on MRI of non-demented elderly
Patients with Alzheimer's disease have higher plasma homocysteine levels
than controls, but it is uncertain whether higher plasma homocysteine
levels are involved in the early pathogenesis of the disease. Hippocampal,
amygdalar and global brain atrophy on brain MRI have been proposed as
early markers of Alzheimer's disease. In the Rotterdam Scan Study, a
population-based study of age-related brain changes in 1077 non-demented
people aged 60-90 years, we investigated the association between plasma
homocysteine levels and severity of hippocampal, amygdalar and global
brain atrophy on MRI. We used axial T(1)-weighted MRIs to visualize global
cortical brain atrophy (measured semi-quantitatively; range 0-15) and a 3D
HASTE (half-Fourier acquisition single-shot turbo spin echo) sequence in
511 participants to measure hippocampal and amygdalar volumes. We had
non-fasting plasma homocysteine levels in 1031 of the participants and in
505 of the participants with hippocampal and amygdalar volumes.
Individuals with higher plasma homocysteine levels had, on average, more
cortical atrophy [0.23 units (95% CI 0.07-0.38 units) per standard
deviation increase in plasma homocysteine levels] and more hippocampal
atrophy [difference in left hippocampal volume -0.05 ml (95% CI -0.09 to
-0.01) and in right hippocampal volume -0.03 ml (95% CI -0.07 to 0.01) per
standard deviation increase in plasma homocysteine levels]. No association
was observed between plasma homocysteine levels and amygdalar atrophy.
These results support the hypothesis that higher plasma homocysteine
levels are associated with more atrophy of the hippocampus and cortical
regions in elderly at risk of Alzheimer's disease
Aortic atherosclerosis at middle age predicts cerebral white matter lesions in the elderly
BACKGROUND AND PURPOSE: MRI scans of the brains of elderly people
frequently show white matter lesions. Clinically, these lesions are
associated with cognitive impairment and dementia. A relation between
atherosclerosis and white matter lesions was found in some small
cross-sectional studies. However, atherosclerosis is a gradual process
that starts early in life. We investigated the longitudinal association
between aortic atherosclerosis assessed during midlife and late life and
cerebral white matter lesions. METHODS: We randomly sampled subjects
between 60 and 90 years old from 2 population-based follow-up studies in
which subjects had their baseline examinations in 1975 to 1978 (midlife)
and in 1990 to 1993 (late life). In 1995 to 1996, subjects underwent 1.5-T
MRI scanning; white matter lesions were rated in the deep subcortical and
periventricular regions separately. Aortic atherosclerosis was assessed on
abdominal radiographs that were obtained from 276 subjects in midlife and
531
Carotid plaques increase the risk of stroke and subtypes of cerebral infarction in asymptomatic elderly: the Rotterdam study
BACKGROUND: Few studies have quantified the relation between carotid
plaques and stroke in asymptomatic patients, and limited data exist on the
importance of location of plaques or the association with subtypes of
cerebral infarction. We investigated the relationship between carotid
plaques, measured at different locations, and risk of stroke and subtypes
of cerebral infarction in a population-based study. Methods and Results-
The study was based on the Rotterdam Study and included 4217
neurologically asymptomatic subjects aged 55 years or older. Presence of
carotid plaques at 6 locations in the carotid arteries was assessed at
baseline. Severity was categorized according to the number of affected
sites. After a mean follow-up of 5.2 years, 160 strokes had occurred. Data
were analyzed using Cox proportional hazards regression. Plaques increased
the risk of stroke and cerebral infarction approximately 1.5-fold,
irrespective of plaque location. Severe carotid plaques increased the risk
of nonlacunar infarction in anterior (RR 3.2 [95% CI, 1.1 to 9.7]) but not
in posterior circulation (RR 0.6 [95% CI, 0.1 to 4.9]). A >10-fold
increased risk of lacunar infarction was found in subjects with severe
plaques (RR 10.8 [95% CI, 1.7 to 69.7]). No clear difference in risk
estimates was seen between ipsilateral and contralateral infarction.
CONCLUSIONS: Carotid plaques increase the risk of stroke and cerebral
infarction, irrespective of their location. Plaques increase the risk of
infarctions in the anterior but not in the posterior circulation. It is
likely that carotid plaques in neurologically asymptomatic subjects are
both markers of generalized atherosclerosis and sources of thromboemboli
Cerebral microbleeds a guide to detection and interpretation
Cerebral microbleeds (CMB) are increasingly recognized neuroimaging findings, occurring with cerebrovascular disease, dementia, and normal aging. Recent years have seen substantial progress, particularly in developing newer MRI methodologies for CMB detection and applying them to population-based elderly samples. This review focuses on these recent developments and their impact on two major questions: how CMB are detected, and how they should be interpreted. There is now ample evidence that prevalence and number of detected CMB varies with MRI characteristics such as pulse sequence, sequence parameters, spatial resolution, magnetic field strength, and post-processing, underlining the importance of MRI technique in interpreting studies. Recent investigations using sensitive techniques find the prevalence of CMB detected in community-dwelling elderly to be surprisingly high. We propose procedural guidelines for identifying CMB and suggest possible future approaches for elucidating the role of these common lesions as markers for, and potential contributors to, small vessel brain disease
Is carotid intima-media thickness useful in cardiovascular disease risk assessment? The Rotterdam Study
BACKGROUND AND PURPOSE: We determined the contribution of common carotid
intima-media thickness (IMT) in the prediction of future coronary heart
disease and cerebrovascular disease when added to established risk
factors. METHODS: We used data from a nested case-control study comprising
374 subjects with either an incident stroke or a myocardial infarction and
1496 controls.
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