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.