Enikő Zsoldos

ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging

The identification of resting state networks (RSNs) and the quantification of their functional connectivity in resting-state fMRI (rfMRI) are seriously hindered by the presence of artefacts, many of which overlap spatially or spectrally with RSNs. Moreover, recent developments in fMRI acquisition yield data with higher spatial and temporal resolutions, but may increase artefacts both spatially and/or temporally. Hence the correct identification and removal of non-neural fluctuations is crucial, especially in accelerated acquisitions. In this paper we investigate the effectiveness of three data-driven cleaning procedures, compare standard against higher (spatial and temporal) resolution accelerated fMRI acquisitions, and investigate the combined effect of different acquisitions and different cleanup approaches. We applied single-subject independent component analysis (ICA), followed by automatic component classification with FMRIBs ICA-based X-noiseifier (FIX) to identify artefactual components. We then compared two first-level (within-subject) cleaning approaches for removing those artefacts and motion-related fluctuations from the data. The effectiveness of the cleaning procedures was assessed using time series (amplitude and spectra), network matrix and spatial map analyses. For time series and network analyses we also tested the effect of a second-level cleaning (informed by group-level analysis). Comparing these approaches, the preferable balance between noise removal and signal loss was achieved by regressing out of the data the full space of motion-related fluctuations and only the unique variance of the artefactual ICA components. Using similar analyses, we also investigated the effects of different cleaning approaches on data from different acquisition sequences. With the optimal cleaning procedures, functional connectivity results from accelerated data were statistically comparable or significantly better than the standard (unaccelerated) acquisition, and, crucially, with higher spatial and temporal resolution. Moreover, we were able to perform higher dimensionality ICA decompositions with the accelerated data, which is very valuable for detailed network analyses.

Moderate alcohol consumption as risk factor for adverse brain outcomes and cognitive decline: longitudinal cohort study

Objectives To investigate whether moderate alcohol consumption has a favourable or adverse association or no association with brain structure and function. Design Observational cohort study with weekly alcohol intake and cognitive performance measured repeatedly over 30 years (1985-2015). Multimodal magnetic resonance imaging (MRI) was performed at study endpoint (2012-15). Setting Community dwelling adults enrolled in the Whitehall II cohort based in the UK (the Whitehall II imaging substudy). Participants 550 men and women with mean age 43.0 (SD 5.4) at study baseline, none were “alcohol dependent” according to the CAGE screening questionnaire, and all safe to undergo MRI of the brain at follow-up. Twenty three were excluded because of incomplete or poor quality imaging data or gross structural abnormality (such as a brain cyst) or incomplete alcohol use, sociodemographic, health, or cognitive data. Main outcome measures Structural brain measures included hippocampal atrophy, grey matter density, and white matter microstructure. Functional measures included cognitive decline over the study and cross sectional cognitive performance at the time of scanning. Results Higher alcohol consumption over the 30 year follow-up was associated with increased odds of hippocampal atrophy in a dose dependent fashion. While those consuming over 30 units a week were at the highest risk compared with abstainers (odds ratio 5.8, 95% confidence interval 1.8 to 18.6; P≤0.001), even those drinking moderately (14-21 units/week) had three times the odds of right sided hippocampal atrophy (3.4, 1.4 to 8.1; P=0.007). There was no protective effect of light drinking (1-<7 units/week) over abstinence. Higher alcohol use was also associated with differences in corpus callosum microstructure and faster decline in lexical fluency. No association was found with cross sectional cognitive performance or longitudinal changes in semantic fluency or word recall. Conclusions Alcohol consumption, even at moderate levels, is associated with adverse brain outcomes including hippocampal atrophy. These results support the recent reduction in alcohol guidance in the UK and question the current limits recommended in the US.

Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images

Despite its great potential in studying brain anatomy and structure, diffusion magnetic resonance imaging (dMRI) is marred by artefacts more than any other commonly used MRI technique. In this paper we present a non-parametric framework for detecting and correcting dMRI outliers (signal loss) caused by subject motion. Signal loss (dropout) affecting a whole slice, or a large connected region of a slice, is frequently observed in diffusion weighted images, leading to a set of unusable measurements. This is caused by bulk (subject or physiological) motion during the diffusion encoding part of the imaging sequence. We suggest a method to detect slices affected by signal loss and replace them by a non-parametric prediction, in order to minimise their impact on subsequent analysis. The outlier detection and replacement, as well as correction of other dMRI distortions (susceptibility-induced distortions, eddy currents (EC) and subject motion) are performed within a single framework, allowing the use of an integrated approach for distortion correction. Highly realistic simulations have been used to evaluate the method with respect to its ability to detect outliers (types 1 and 2 errors), the impact of outliers on retrospective correction of movement and distortion and the impact on estimation of commonly used diffusion tensor metrics, such as fractional anisotropy (FA) and mean diffusivity (MD). Data from a large imaging project studying older adults (the Whitehall Imaging sub-study) was used to demonstrate the utility of the method when applied to datasets with severe subject movement. The results indicate high sensitivity and specificity for detecting outliers and that their deleterious effects on FA and MD can be almost completely corrected.

Classification and characterization of periventricular and deep white matter hyperintensities on MRI: A study in older adults

ABSTRACT White matter hyperintensities (WMH) are frequently divided into periventricular (PWMH) and deep (DWMH), and the two classes have been associated with different cognitive, microstructural, and clinical correlates. However, although this distinction is widely used in visual ratings scales, how to best anatomically define the two classes is still disputed. In fact, the methods used to define PWMH and DWMH vary significantly between studies, making results difficult to compare. The purpose of this study was twofold: first, to compare four current criteria used to define PWMH and DWMH in a cohort of healthy older adults (mean age: 69.58 ± 5.33 years) by quantifying possible differences in terms of estimated volumes; second, to explore associations between the two WMH sub‐classes with cognition, tissue microstructure and cardiovascular risk factors, analysing the impact of different criteria on the specific associations. Our results suggest that the classification criterion used for the definition of PWMH and DWMH should not be considered a major obstacle for the comparison of different studies. We observed that higher PWMH load is associated with reduced cognitive function, higher mean arterial pressure and age. Higher DWMH load is associated with higher body mass index. PWMH have lower fractional anisotropy than DWMH, which also have more heterogeneous microstructure. These findings support the hypothesis that PWMH and DWMH are different entities and that their distinction can provide useful information about healthy and pathological aging processes. HIGHLIGHTSClassification criteria for periventricular/deep white matter hyperintensities are compared.The definition of PWMH and DWMH is not a major obstacle for study comparison.PWMH and DWMH have different functional, microstructural and clinical correlates.10 mm distance rule gave best separation in terms of associations with the tested factors.

Associations between self-reported sleep quality and white matter in community-dwelling older adults: A prospective cohort study.

Both sleep disturbances and decline in white matter microstructure are commonly observed in ageing populations, as well as in age‐related psychiatric and neurological illnesses. A relationship between sleep and white matter microstructure may underlie such relationships, but few imaging studies have directly examined this hypothesis. In a study of 448 community‐dwelling members of the Whitehall II Imaging Sub‐Study aged between 60 and 82 years (90 female, mean age 69.2 ± 5.1 years), we used the magnetic resonance imaging technique diffusion tensor imaging to examine the relationship between self‐reported sleep quality and white matter microstructure. Poor sleep quality at the time of the diffusion tensor imaging scan was associated with reduced global fractional anisotropy and increased global axial diffusivity and radial diffusivity values, with small effect sizes. Voxel‐wise analysis showed that widespread frontal‐subcortical tracts, encompassing regions previously reported as altered in insomnia, were affected. Radial diffusivity findings remained significant after additional correction for demographics, general cognition, health, and lifestyle measures. No significant differences in general cognitive function, executive function, memory, or processing speed were detected between good and poor sleep quality groups. The number of times participants reported poor sleep quality over five time‐points spanning a 16‐year period was not associated with white matter measures. In conclusion, these data demonstrate that current sleep quality is linked to white matter microstructure. Small effect sizes may limit the extent to which poor sleep is a promising modifiable factor that may maintain, or even improve, white matter microstructure in ageing. Hum Brain Mapp 38:5465–5473, 2017.

Sub-threshold depressive symptoms and brain structure: A magnetic resonance imaging study within the Whitehall II cohort

Background Late-life sub-threshold depressive symptoms (i.e. depressive symptoms that do not meet the criteria for a diagnosis of major depressive disorder) are associated with impaired physical health and function, and increased risk of major depressive disorder. Magnetic resonance imaging (MRI) studies examining late-life major depressive disorder find structural brain changes in grey and white matter. However, the extent to which late-life sub-threshold depression is associated with similar hallmarks is not well established. Methods Participants with no history of major depressive disorder were selected from the Whitehall Imaging Sub-Study (n=358, mean age 69±5 years, 17% female). Depressive symptoms were measured using the Centre for Epidemiological Studies Depression Scale (CES-D) at three previous Whitehall II Study phases (2003–04, 2007–09 and 2012–13) and at the time of the MRI scan (2012–14). The relationships between current and cumulative depressive symptoms and MRI brain measures were explored using Voxel-Based Morphometry (VBM) for grey matter and Tract Based Spatial Statistics (TBSS) for white matter. Results Current sub-threshold depressive symptoms were associated with significant reductions in fractional anisotropy and increases in axial and radial diffusivity. There were no significant relationships between current depressive symptoms and grey matter measures, or cumulative depressive symptoms and MRI measures. Limitations The prevalence (10%) of sub-threshold depressive symptoms means that analyses may be underpowered to detect subtle differences in brain structure. Conclusions Current sub-threshold depressive symptoms are associated with changes in white matter microstructure, indicating that even mild depressive symptoms are associated with similar MRI hallmarks to those in major depressive disorder.

Associations between Mobility, Cognition, and Brain Structure in Healthy Older Adults

Mobility limitations lead to a cascade of adverse events in old age, yet the neural and cognitive correlates of mobility performance in older adults remain poorly understood. In a sample of 387 adults (mean age 69.0 ± 5.1 years), we tested the relationship between mobility measures, cognitive assessments, and MRI markers of brain structure. Mobility was assessed in 2007–2009, using gait, balance and chair-stands tests. In 2012–2015, cognitive testing assessed executive function, memory and processing-speed; gray matter volumes (GMV) were examined using voxel-based morphometry, and white matter microstructure was assessed using tract-based spatial statistics of fractional anisotropy, axial diffusivity (AD), and radial diffusivity (RD). All mobility measures were positively associated with processing-speed. Faster walking speed was also correlated with higher executive function, while memory was not associated with any mobility measure. Increased GMV within the cerebellum, basal ganglia, post-central gyrus, and superior parietal lobe was associated with better mobility. In addition, better performance on the chair-stands test was correlated with decreased RD and AD. Overall, our results indicate that, even in non-clinical populations, mobility measures can be sensitive to sub-clinical variance in cognition and brain structures.

Occupational stress, bullying and resilience in old age.

Our working years increasingly extend into the late 60s and may soon include the 70s for some people. Thus the question whether work stress has a cumulative effect in older age, and whether older employees are more vulnerable to certain sources of work stress, such as bullying in the work place, is becoming increasingly relevant. We review some of the mechanisms, which translate cumulative stress at work into ill health, particularly in older age, and summarise what is known about the effect of age-specific stress, taking age-related bullying as an example.

Effect of age and the APOE gene on metabolite concentrations in the posterior cingulate cortex

ABSTRACT Proton magnetic resonance spectroscopy (1H‐MRS) has provided valuable information about the neurochemical profile of Alzheimers disease (AD). However, its clinical utility has been limited in part by the lack of consistent information on how metabolite concentrations vary in the normal aging brain and in carriers of apolipoprotein E (APOE) &egr;4, an established risk gene for AD. We quantified metabolites within an 8 cm3 voxel within the posterior cingulate cortex (PCC)/precuneus in 30 younger (20–40 years) and 151 cognitively healthy older individuals (60–85 years). All 1H‐MRS scans were performed at 3 T using the short‐echo SPECIAL sequence and analyzed with LCModel. The effect of APOE was assessed in a sub‐set of 130 volunteers. Older participants had significantly higher myo‐inositol and creatine, and significantly lower glutathione and glutamate than younger participants. There was no significant effect of APOE or an interaction between APOE and age on the metabolite profile. Our data suggest that creatine, a commonly used reference metabolite in 1H‐MRS studies, does not remain stable across adulthood within this region and therefore may not be a suitable reference in studies involving a broad age‐range. Increases in creatine and myo‐inositol may reflect age‐related glial proliferation; decreases in glutamate and glutathione suggest a decline in synaptic and antioxidant efficiency. Our findings inform longitudinal clinical studies by characterizing age‐related metabolite changes in a non‐clinical sample.

Association of Long-Term Diet Quality with Hippocampal Volume: Longitudinal Cohort Study.

BACKGROUND Diet quality is associated with brain aging outcomes. However, few studies have explored in humans the brain structures potentially affected by long-term diet quality. We examined whether cumulative average of the Alternative Healthy Eating Index 2010 (AHEI-2010) score during adult life (an 11-year exposure period) is associated with hippocampal volume. METHODS Analyses were based on data from 459 participants of the Whitehall II imaging sub-study (mean age [standard deviation] (SD) = 59.6 [5.3] years in 2002-2004, 19.2% women). Multimodal magnetic resonance imaging examination was performed at the end of follow-up (2015-2016). Structural images were acquired using a high-resolution 3-dimensional T1-weighted sequence and processed with Functional Magnetic Resonance Imaging of the Brain Software Library (FSL) tools. An automated model-based segmentation and registration tool was applied to extract hippocampal volumes. RESULTS Higher AHEI-2010 cumulative average score (reflecting long-term healthy diet quality) was associated with a larger total hippocampal volume. For each 1 SD (SD = 8.7 points) increment in AHEI-2010 score, an increase of 92.5 mm3 (standard error = 42.0 mm3) in total hippocampal volume was observed. This association was independent of sociodemographic factors, smoking habits, physical activity, cardiometabolic health factors, cognitive impairment, and depressive symptoms, and was more pronounced in the left hippocampus than in the right hippocampus. Of the AHEI-2010 components, no or light alcohol consumption was independently associated with larger hippocampal volume. CONCLUSIONS Higher long-term AHEI-2010 scores were associated with larger hippocampal volume. Accounting for the importance of hippocampal structures in several neuropsychiatric diseases, our findings reaffirm the need to consider adherence to healthy dietary recommendation in multi-interventional programs to promote healthy brain aging.