It has been hypothesized that air pollution and ambient noise might impact neurocognitive function. Early studies mostly investigated the associations of air pollution and ambient noise exposure with ...cognitive development in children. More recently, several studies investigating associations with neurocognitive function, mood disorders, and neurodegenerative disease in adult populations were published, yielding inconsistent results. The purpose of this review is to summarize the current evidence on air pollution and noise effects on mental health in adults. We included studies in adult populations (≥18 years old) published in English language in peer-reviewed journals. Fifteen articles related to long-term effects of air pollution and eight articles on long-term effects of ambient noise were extracted. Both exposures were separately shown to be associated with one or several measures of global cognitive function, verbal and nonverbal learning and memory, activities of daily living, depressive symptoms, elevated anxiety, and nuisance. No study considered both exposures simultaneously and few studies investigated progression of neurocognitive decline or psychological factors. The existing evidence generally supports associations of environmental factors with mental health, but does not suffice for an overall conclusion about the independent effect of air pollution and noise. There is a need for studies investigating simultaneously air pollution and noise exposures in association mental health, for longitudinal studies to corroborate findings from cross-sectional analyses, and for parallel toxicological and epidemiological studies to elucidate mechanisms and pathways of action.
Wearable sensors are rapidly gaining influence in the diagnostics, monitoring, and treatment of disease, thereby improving patient outcomes. In this review, we aim to explore how these advances can ...be applied to magnetic resonance imaging (MRI). We begin by (i) introducing limitations in current flexible/stretchable RF coils and then move to the broader field of flexible sensor technology to identify translatable technologies. To this goal, we discuss (ii) emerging materials currently used for sensor substrates, (iii) stretchable conductive materials, (iv) pairing and matching of conductors with substrates, and (v) implementation of lumped elements such as capacitors. Applicable (vi) fabrication methods are presented, and the review concludes with a brief commentary on (vii) the implementation of the discussed sensor technologies in MRI coil applications. The main takeaway of our research is that a large body of work has led to exciting new sensor innovations allowing for stretchable wearables, but further exploration of materials and manufacturing techniques remains necessary, especially when applied to MRI diagnostics.
Detection and diagnosis of early and subclinical stages of Alzheimer's Disease (AD) play an essential role in the implementation of intervention and prevention strategies. Neuroimaging techniques ...predominantly provide insight into anatomic structure changes associated with AD. Deep learning methods have been extensively applied towards creating and evaluating models capable of differentiating between cognitively unimpaired, patients with Mild Cognitive Impairment (MCI) and AD dementia. Several published approaches apply information fusion techniques, providing ways of combining several input sources in the medical domain, which contributes to knowledge of broader and enriched quality. The aim of this paper is to fuse sociodemographic data such as age, marital status, education and gender, and genetic data (presence of an apolipoprotein E (APOE)-ε4 allele) with Magnetic Resonance Imaging (MRI) scans. This enables enriched multi-modal features, that adequately represent the MRI scan visually and is adopted for creating and modeling classification systems capable of detecting amnestic MCI (aMCI). To fully utilize the potential of deep convolutional neural networks, two extra color layers denoting contrast intensified and blurred image adaptations are virtually augmented to each MRI scan, completing the Red-Green-Blue (RGB) color channels. Deep convolutional activation features (DeCAF) are extracted from the average pooling layer of the deep learning system Inception_v3. These features from the fused MRI scans are used as visual representation for the Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) classification model. The proposed approach is evaluated on a sub-study containing 120 participants (aMCI = 61 and cognitively unimpaired = 59) of the Heinz Nixdorf Recall (HNR) Study with a baseline model accuracy of 76%. Further evaluation was conducted on the ADNI Phase 1 dataset with 624 participants (aMCI = 397 and cognitively unimpaired = 227) with a baseline model accuracy of 66.27%. Experimental results show that the proposed approach achieves 90% accuracy and 0.90 F1-Score at classification of aMCI vs. cognitively unimpaired participants on the HNR Study dataset, and 77% accuracy and 0.83 F1-Score on the ADNI dataset.
Investigations of adverse effects of air pollution (AP) and ambient noise on cognitive functions are apparently scarce, and findings seem to be inconsistent. The aim of this study was to examine the ...associations of long-term exposure to AP and traffic noise with cognitive performance. At the second examination of the population-based Heinz Nixdorf Recall study (2006-2008), cognitive performance was evaluated in 4086 participants. Long-term residential exposure to size-specific particulate matter (PM) and nitrogen oxides (NOx) with land use regression, to and traffic noise (weighted 24-h (L
DEN
) and nighttime (L
NIGHT
) means), was assessed according to the European Union (EU) Directive 2002/49/EC. Multiple regression models were calculated for the relationship of environmental exposures with a global cognitive score (GCS) and in five cognitive subtests, using single- and two-exposure models. In fully adjusted models, several AP metrics were negatively associated with four of five subtests and with GCS. For example, an interquartile range increase in PM
2.5
was correlated with verbal fluency, labyrinth test, and immediate and delayed verbal recall. A 10 dB(A) elevation in L
DEN
and L
NIGHT
was associated with GCS. Similar but not significant associations were found for the cognitive subtests. In two-exposure models including noise and air pollution simultaneously, the associations did not change markedly for air pollution, but attenuated numerically for noise. Long-term exposures to AP and traffic noise are negatively correlated with subtests related to memory and executive functions. There appears to be little evidence for mutual confounding.
Magnetic resonance imaging (MRI) gradient coils produce acoustic noise due to coil conductor vibrations caused by large Lorentz forces. Accurate sound pressure levels and modeling of heating are ...essential for the assessment of gradient coil safety. This work reviews the state-of-the-art numerical methods used in accurate gradient coil modeling and prediction of sound pressure levels (SPLs) and temperature rise. We review several approaches proposed for noise level reduction of high-performance gradient coils, with a maximum noise reduction of 20 decibels (dB) demonstrated. An efficient gradient cooling technique is also presented.
Possible joint effects of subjective cognitive decline (SCD) and apolipoprotein E (APOE) ε4 genotype on incident mild cognitive impairment (MCI) were examined for men and women separately.
...Cognitively normal participants with and without SCD were included from the first follow-up examination of the population-based Heinz Nixdorf Recall study. Sex-stratified logistic regression models estimated main effects and interactions (additive, multiplicative) of SCD at the first follow-up (yes+/no−) and APOE ε4 (positive+/negative−) groups for MCI 5 years later.
Odds for MCI 5 years later were higher in SCD/APOE ε4 group +/+ than the sum of groups +/− and −/+ in women, with a trend for positive interaction. Odds for incident MCI in men was highest in group +/−, with no interaction effect.
Our findings indicate that APOE ε4 may play an important role in the association of SCD and incident MCI, especially considering sex. Further studies need to examine these associations with larger sample sizes.
Flexible and stretchable radiofrequency coils for magnetic resonance imaging represent an emerging and rapidly growing field. The main advantage of such coil designs is their conformal nature, ...enabling a closer anatomical fit, patient comfort, and freedom of movement. Previously, we demonstrated a proof-of-concept single element stretchable coil design with a self-tuning smart geometry. In this work, we evaluate the feasibility of scaling this coil concept to a multi-element coil array and the associated engineering and manufacturing challenges. To this goal, we study a dual-channel coil array using full-wave simulations, bench testing, in vitro, and in vivo imaging in a 3 T scanner. We use three fabrication techniques to manufacture dual-channel receive coil arrays: (1) single-layer casting, (2) double-layer casting, and (3) direct-ink-writing. All fabricated arrays perform equally well on the bench and produce similar sensitivity maps. The direct-ink-writing method is found to be the most advantageous fabrication technique for fabrication speed, accuracy, repeatability, and total coil array thickness (0.6 mm). Bench tests show excellent frequency stability of 128 ± 0.6 MHz (0% to 30% stretch). Compared to a commercial knee coil array, the stretchable coil array is more conformal to anatomy and provides 50% improved signal-to-noise ratio in the region of interest.
Recent developments in the field of radiofrequency (RF) coils for magnetic resonance imaging (MRI) offer flexible and patient-friendly solutions. Previously, we demonstrated a proof-of-concept ...single-element stretchable coil design based on liquid metal and a self-tuning smart geometry. In this work, we numerically analyze and experimentally study a multi-channel stretchable coil array and demonstrate its application in dynamic knee imaging. We also compare our flexible coil array to a commonly used commercial rigid coil array. Our numerical analysis shows that the proposed coil array maintains its resonance frequency (<1% variation) and sensitivity (<6%) at various stretching configurations from 0% to 30%. We experimentally demonstrate that the signal-to-noise ratio (SNR) of the acquired MRI images is improved by up to four times with the stretchable coil array due to its conformal and therefore tight-fitting nature. This stretchable array allows for dynamic knee imaging at different flexion angles, infeasible with traditional, rigid coil arrays. These findings are significant as they address the limitations of current rigid coil technology, offering a solution that enhances patient comfort and image quality, particularly in applications requiring dynamic imaging.
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