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In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher order diffusion model that is a straightforward extension of the DTI model. Here, we analyze the physics underlying this method, we report our MRI acquisition protocol with the preprocessing pipeline used and the DKI parametric maps obtained on a 1.5 T scanner, and we review the most relevant clinical applications of this technique in various neurological diseases. [ABSTRACT FROM AUTHOR]

Purpose: An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate modeland algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. Methods: The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value = 0 and b-value = 1000 s/mm2 data while the DKI model was fitted to data comprising b-value = 0, 1000 and 3000/2500 s/mm2 [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition toMK/RK/AK maps,MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. Results: DKI-derivedMD/FA/RD/AD andMOestimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine. Conclusions: Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines. [ABSTRACT FROM AUTHOR]

Background and purpose Parkinson's disease ( PD) is a progressive neurodegenerative disorder with motor and non-motor symptoms, including cognitive deficits. Several magnetic resonance imaging approaches have been applied to investigate brain atrophy in PD. The aim of this study was to detect early structural cortical and subcortical changes in de novo PD whilst distinguishing cognitive status, clinical phenotype and motor laterality. Methods Eighteen de novo PD with mild cognitive impairment ( PD- MCI), 18 de novo PD without MCI ( PD- NC) and 18 healthy control subjects were evaluated. In the PD- MCI group, nine were tremor dominant and nine were postural instability gait disorder ( PIGD) phenotype; 11 had right-sided symptom dominance and seven had left-sided symptom dominance. FreeSurfer was used to measure cortical thickness/folding, subcortical structures and to study group differences as well as the association with clinical and neuropsychological data. Results Parkinson's disease with MCI showed regional thinning in the right frontal, right middle temporal areas and left insula compared to PD- NC. A reduction of the volume of the left and right thalamus and left hippocampus was found in PD- MCI compared to PD- NC. PD- MCI PIGD showed regional thinning in the right inferior parietal area compared to healthy controls. A decreased volume of the left thalamus was reported in PD- MCI with right-sided symptom dominance compared to PD- NC and PD- MCI with left-sided symptom dominance. Conclusions When MCI was present, PD patients showed a fronto-temporo-parietal pattern of cortical thinning. This cortical pattern does not appear to be influenced by motor laterality, although one-sided symptom dominance may contribute to volumetric reduction of specific subcortical structures. [ABSTRACT FROM AUTHOR]

Mechanical interplay between the adjacent ventricles is one of the principal modulators of physiopathological heart function, and the underlying mechanisms of interaction are only partially understood, hence hampering clinically useful interpretation of imaging data. In order to characterize the influence of chamber geometry on ventricular coupling, the ventricles and septum are modeled as portions of ellipsoidal shells, and configuration is derived as a function of pressure gradients by combining shell element equilibrium equations through static boundary conditions applied at the sulcus. Diastolic volume ( v) surfaces are calculated as a function of pressure ( p), contralateral pressure ( clp) and intrathoracic pressure ( p t ) and match literature data where available. Ventricular interaction is characterized in terms of partial derivatives in v–p–clp–p t space both under physiological and altered (selectively stiffened walls) conditions. The model allows prediction of diastolic ventricular v–p–clp–p t interplay in a variety of physiopathological circumstances. [ABSTRACT FROM AUTHOR]

We investigated whether changes in noradrenaline neurotransmission in the hypothalamus could explain the hyporesponsiveness of the hypothalamic-pituitary-adrenal (HPA) axis in late pregnancy. Noradrenaline release within the hypothalamic paraventricular nucleus in response to swim stress, as estimated by microdialysis and high-performance liquid chromatography, was lower in 20-day pregnant rats compared to virgin rats. Driving a central noradrenergic pathway using intravenous cholecystokinin increased adrenocorticotropic hormone (ACTH) secretion in virgin rats, but the response was significantly less in 16-day and 20-day pregnant rats. Thus, the activity of noradrenergic inputs to the paraventricular nucleus and the HPA axis is attenuated in late pregnancy. The sensitivity of the HPA axis to noradrenaline in pregnancy was investigated by intracerebroventricular administration of anα1-receptor antagonist, benoxathian, before and during exposure to swim stress. In virgin rats, benoxathian increased basal and stress-induced ACTH secretion, but in late pregnant rats the benoxathian effects were attenuated, indicating reduced sensitivity of the HPA axis to noradrenaline neurotransmission and/or the inability of the system to become disinhibited at this time.α1A-adrenoreceptor mRNA expression in the parvocellular and magnocellular paraventricular nucleus, measured byin situhybridisation, was decreased in late pregnant compared to virgin rats. Additionally, blocking endogenous opioid inhibition with naloxone pretreatment restored the ACTH secretory response to cholecystokinin in pregnant rats. Thus, in late pregnancy, there is reduced noradrenergic input to the paraventricular nucleus and reducedα1A-receptor expression in the paraventricular nucleus, both of which may contribute to the reduced responsiveness of the HPA axis in pregnancy. [ABSTRACT FROM AUTHOR]

The human brain is characterized by highly dynamic patterns of functional connectivity. However, it is unknown whether this time-variant 'connectome' is related to the individual differences in the behavioural and cognitive traits described in the five-factor model of personality. To answer this question, inter-network time-variant connectivity was computed in n = 818 healthy people via a dynamical conditional correlation model. Next, network dynamicity was quantified throughout an ad-hoc measure (T-index) and the generalizability of the multi-variate associations between personality traits and network dynamicity was assessed using a train/test split approach. Conscientiousness, reflecting enhanced cognitive and emotional control, was the sole trait linked to stationary connectivity across several circuits such as the default mode and prefronto-parietal network. The stationarity in the 'communication' across large-scale networks offers a mechanistic description of the capacity of conscientious people to 'protect' non-immediate goals against interference over-time. This study informs future research aiming at developing more realistic models of the brain dynamics mediating personality differences. [ABSTRACT FROM AUTHOR]