Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.

Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21-88 years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.

Demyelination of superficial white matter in early Alzheimer's disease: a magnetization transfer imaging study.

Assuming selective vulnerability of short association U-fibers in early Alzheimer's disease (AD), we quantified demyelination of the surface white matter (dSWM) with magnetization transfer ratio (MTR) in 15 patients (Clinical Dementia Rating Scale [CDR] 0.5-1; Functional Assessment Staging [FAST]: 3-4) compared with 15 controls. MTRs were computed for 39 areas in each hemisphere. We found a bilateral MTR decrease in the temporal, cingulate, parietal, and prefrontal areas. With linear discriminant analysis, we successfully classified all the participants with 3 variates including the cuneus, parahippocampal, and superior temporal regions of the left hemisphere. The pattern of dSWM changed with the age of AD onset. In early onset patients, we found bilateral posterior demyelination spreading to the temporal areas in the left hemisphere. The late onset patients showed a distributed bilateral pattern with the temporal and cingulate areas strongly affected. A correlation with Mini Mental State Examination (MMSE), Lexis, and memory tests revealed the dSWM impact on cognition. A specific landscape of dSWM in early AD shows the potential of MTR imaging as an in vivo biomarker superior to currently used techniques.

Correction of through-plane deformation artifacts in stimulated echo acquisition mode cardiac imaging.

Attempts to use a stimulated echo acquisition mode (STEAM) in cardiac imaging are impeded by imaging artifacts that result in signal attenuation and nulling of the cardiac tissue. In this work, we present a method to reduce this artifact by acquiring two sets of stimulated echo images with two different demodulations. The resulting two images are combined to recover the signal loss and weighted to compensate for possible deformation-dependent intensity variation. Numerical simulations were used to validate the theory. Also, the proposed correction method was applied to in vivo imaging of normal volunteers (n = 6) and animal models with induced infarction (n = 3). The results show the ability of the method to recover the lost myocardial signal and generate artifact-free black-blood cardiac images.

MP2RAGE Multiple Sclerosis Magnetic Resonance Imaging at 3 T.

OBJECTIVES: Lesion detection and characterization in multiple sclerosis (MS) are an essential part of its clinical diagnosis and an important research field. In this pilot study, we applied the recently introduced two inversion-contrast magnetization-prepared rapid gradient echo sequence (MP2RAGE) to patients with early-stage MS.¦MATERIALS AND METHODS: The MP2RAGE is a 3-dimensional (3D) magnetization-prepared rapid gradient echo derivative providing homogeneous T1 weighting and simultaneous T1 mapping. The MP2RAGE performance was compared with that of 2 clinical routine sequences (2D fluid-attenuated inversion recovery [FLAIR] and 3D magnetization-prepared rapid gradient echo [MP-RAGE]) and 2 state-of-the art clinical research sequences (the 3D FLAIR-SPACE [sampling perfection with application-optimized contrasts by using different flip-angle evolutions], a fluid-attenuated variable flip-angle fast spin echo technique, and the 3D double-inversion recovery SPACE). A cohort of 10 early-stage female MS patients (age, 31.6 ± 4.7 years; disease duration, 3.8 ± 1.9 years; median expanded disability status scale score, 1.75) and 10 age- and gender-matched controls were enrolled after approval of the local institutional review board was obtained. Multiple sclerosis lesions were identified and assigned to brain locations and tissue types by two experienced physicians in all 5 contrasts. Subsequently, lesions were manually delineated for comparison and statistical analysis of lesion count, volume and quantitative measures.¦RESULTS AND CONCLUSIONS: The results show that the 3D T1-weighted high-resolution MP2RAGE contrast provides a sensitive means for MS lesion assessment. The additional quantitative T1 relaxation time maps obtained with the MP2RAGE provide further potential diagnostic and prognostic information that could help (a) to better discriminate lesion subtypes and (b) to stage and predict the activity and the evolution of MS. Results also indicate that the T2-weighted double-inversion recovery and FLAIR-SPACE contrasts are attractive complements to the MP2RAGE for lesion detection.

Predictors of onset of cannabis and other drug use in male young adults: results from a longitudinal study.

BACKGROUND: The use of cannabis and other illegal drugs is particularly prevalent in male young adults and is associated with severe health problems. This longitudinal study explored variables associated with the onset of cannabis use and the onset of illegal drug use other than cannabis separately in male young adults, including demographics, religion and religiosity, health, social context, substance use, and personality. Furthermore, we explored how far the gateway hypothesis and the common liability to addiction model are in line with the resulting prediction models. METHODS: The data were gathered within the Cohort Study on Substance Use Risk Factors (C-SURF). Young men aged around 20 years provided demographic, social, health, substance use, and personality-related data at baseline. Onset of cannabis and other drug use were assessed at 15-months follow-up. Samples of 2,774 and 4,254 individuals who indicated at baseline that they have not used cannabis and other drugs, respectively, in their life and who provided follow-up data were used for the prediction models. Hierarchical logistic stepwise regressions were conducted, in order to identify predictors of the late onset of cannabis and other drug use separately. RESULTS: Not providing for oneself, having siblings, depressiveness, parental divorce, lower parental knowledge of peers and the whereabouts, peer pressure, very low nicotine dependence, and sensation seeking were positively associated with the onset of cannabis use. Practising religion was negatively associated with the onset of cannabis use. Onset of drug use other than cannabis showed a positive association with depressiveness, antisocial personality disorder, lower parental knowledge of peers and the whereabouts, psychiatric problems of peers, problematic cannabis use, and sensation seeking. CONCLUSIONS: Consideration of the predictor variables identified within this study may help to identify young male adults for whom preventive measures for cannabis or other drug use are most appropriate. The results provide evidence for both the gateway hypothesis and the common liability to addiction model and point to further variables like depressiveness or practising of religion that might influence the onset of drug use.

Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity.

The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

Associations of physical activity and sport and exercise with at-risk substance use in young men: a longitudinal study.

OBJECTIVE: This study aims to measure the associations of physical activity and one of its components, sport and exercise, with at-risk substance use in a population of young men. METHOD: Baseline (2010-2012) and follow-up (2012-2013) data of 4748 young Swiss men from the Cohort Study on Substance Use Risk Factors (C-SURF) were used. Cross-sectional and prospective associations between at-risk substance use and both sport and exercise and physical activities were measured using Chi-squared tests and logistic regression models adjusting for covariates. RESULTS: At baseline, logistic regression indicated that sport and exercise is negatively associated with at-risk use of cigarettes and cannabis. A positive association was obtained between physical activity and at-risk alcohol use. At baseline, sport and exercise was negatively associated with at-risk use of cigarettes and cannabis at follow-up. Adjusted for sport and exercise, physical activity was positively associated with at-risk use of cigarettes and cannabis. CONCLUSION: Sport and exercise is cross-sectionally and longitudinally associated with a low prevalence of at-risk use of cigarettes and cannabis. This protective effect was not observed for physical activity broadly defined. Taking a substance use prevention perspective, the promotion of sport and exercise among young adults should be encouraged.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

FluxEXPLORER: a new high-speed laser Doppler imaging system for the assessment of burn injuries.

BACKGROUND: Deep burn assessment made by clinical evaluation has an accuracy varying between 60% and 80% and will determine if a burn injury will need tangential excision and skin grafting or if it will be able to heal spontaneously. Laser Doppler Imaging (LDI) techniques allow an improved burn depth assessment but their use is limited by the time-consuming image acquisition which may take up to 6 min per image. METHODS: To evaluate the effectiveness and reliability of a newly developed full-field LDI technology, 15 consecutive patients presenting with intermediate depth burns were assessed both clinically and by FluxExplorer LDI technology. Comparison between the two methods of assessment was carried out. RESULTS: Image acquisition was done within 6 s. FluxEXPLORER LDI technology achieved a significantly improved accuracy of burn depth assessment compared to the clinical judgement performed by board certified plastic and reconstructive surgeons (P < 0.05, 93% of correctly assessed burns injuries vs. 80% for clinical assessment). CONCLUSION: Technological improvements of LDI technology leading to a decreased image acquisition time and reliable burn depth assessment allow the routine use of such devices in the acute setting of burn care without interfering with the patient's treatment. Rapid and reliable LDI technology may assist clinicians in burn depth assessment and may limit the morbidity of burn patients through a minimization of the area of surgical debridement. Future technological improvements allowing the miniaturization of the device will further ease its clinical application.

A multi-center study: intra-scan and inter-scan variability of diffusion spectrum imaging.

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.