In dynamic magnetic resonance imaging (MRI) studies, the motion kinetics or the contrast variability are often hard to predict, hampering an appropriate choice of the image update rate or the temporal resolution. A constant azimuthal profile spacing (111.246 degrees), based on the Golden Ratio, is investigated as optimal for image reconstruction from an arbitrary number of profiles in radial MRI. The profile order is evaluated and compared with a uniform profile distribution in terms of signal-to-noise ratio (SNR) and artifact level. The favorable characteristics of such a profile order are exemplified in two applications on healthy volunteers. First, an advanced sliding window reconstruction scheme is applied to dynamic cardiac imaging, with a reconstruction window that can be flexibly adjusted according to the extent of cardiac motion that is acceptable. Second, a contrast-enhancing k-space filter is presented that permits reconstructing an arbitrary number of images at arbitrary time points from one raw data set. The filter was utilized to depict the T1-relaxation in the brain after a single inversion prepulse. While a uniform profile distribution with a constant angle increment is optimal for a fixed and predetermined number of profiles, a profile distribution based on the Golden Ratio proved to be an appropriate solution for an arbitrary number of profiles.

The electric conductivity can potentially be used as an additional diagnostic parameter, e.g., in tumor diagnosis. Moreover, the electric conductivity, in connection with the electric field, can be used to estimate the local SAR distribution during MR measurements. In this study, a new approach, called electric properties tomography (EPT) is presented. It derives the patient's electric conductivity, along with the corresponding electric fields, from the spatial sensitivity distributions of the applied RF coils, which are measured via MRI. Corresponding numerical simulations and initial experiments on a standard clinical MRI system underline the principal feasibility of EPT to determine the electric conductivity and the local SAR. In contrast to previous methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or RF probes, thus enhancing the practicality of the approach. Furthermore, in contrast to previous methods, EPT circumvents the solution of an inverse problem, which might lead to significantly higher spatial image resolution.

The electric properties of human tissue can potentially be used as an additional diagnostic parameter, e.g., in tumor diagnosis. In the framework of radiofrequency safety, the electric conductivity of tissue is needed to correctly estimate the local specific absorption rate distribution during MR measurements. In this study, a recently developed approach, called electric properties tomography (EPT) is adapted for and applied to in vivo imaging. It derives the patient's electric conductivity and permittivity from the spatial sensitivity distributions of the applied radiofrequency coils. In contrast to other methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or radiofrequency probes, which enhances the practicability of the approach. This work shows that conductivity distributions can be reconstructed from phase images and permittivity distributions can be reconstructed from magnitude images of the radiofrequency transmit field. Corresponding numerical simulations using finite-difference time-domain methods support the feasibility of this phase-based conductivity imaging and magnitude-based permittivity imaging. Using this approximation, three-dimensional in vivo conductivity and permittivity maps of the human brain are obtained in 5 and 13 min, respectively, which can be considered a step toward clinical feasibility for EPT. Magn Reson Med 66:456-466, 2011. V C 2011 Wiley-Liss, Inc.Key words: permittivity; conductivity; electric properties tomography; quantitative MRI; patient-specific SAR MR provides a vast variety of possible image contrasts. Because of reasons of reproducibility and comparability, contrasts comprising quantitative parameters are of particular clinical interest. Current examples of quantitative MRI techniques are diffusion, perfusion, and permeability imaging; however, electric conductivity and permittivity are also possible candidates for quantitative parameters. The idea of extracting these electric properties from MR images was already proposed in 1991 (1). However, only recently, the electric properties of the human body have been introduced as a quantitative image contrast in standard MRI via electric properties tomography (EPT) (2). EPT allows the determination of the conductivity and permittivity using the radiofrequency (RF) transmit field map of a standard MR scan (3).The task of imaging electric properties has been addressed by a variety of imaging modalities. Among these modalities, electric impedance tomography is probably the most prominent one. It is performed by applying low frequency currents through multiple electrodes and reconstructing electric properties by solving the resulting inverse problem (4-7). Magnetic induction tomography is a similar approach, however, using RF coils for current induction and reception of the resulting fields (8,9). MR electric impedance tomography is a method initially based on electric impedance tomography, including electrode mounting, however, taking advantage of the spatial encodin...

Investigating the mechanisms underlying the genesis and conduction of electrical excitation in the atria at physiological and pathological states is of great importance. To provide knowledge concerning the mechanisms of excitation, we constructed a biophysical detailed and anatomically accurate computer model of human atria that incorporates both structural and electrophysiological heterogeneities. The three-dimensional geometry was extracted from the visible female dataset. The sinoatrial node (SAN) and atrium, including crista terminalis (CT), pectinate muscles (PM), appendages (APG) and Bachmann's bundle (BB) were segmented in this work. Fibre orientation in CT, PM and BB was set to local longitudinal direction. Descriptions for all used cell types were based on modifications of the Courtemanche et al. model of a human atrial cell. Maximum conductances of Ito, IKr and ICa,L were modified for PM, CT, APG and atrioventricular ring to reproduce measured action potentials (AP). Pacemaker activity in the human SAN was reproduced by removing IK1, but including If, ICa,T, and gradients of channel conductances as described in previous studies for heterogeneous rabbit SAN. Anisotropic conduction was computed with a monodomain model using the finite element method. The transversal to longitudinal ratio of conductivity for PM, CT and BB was 1:9. Atrial working myocardium (AWM) was set to be isotropic. Simulation of atrial electrophysiology showed initiation of APs in the SAN centre. The excitation spread afterwards to the periphery near to the region of the CT and preferentially towards the atrioventricular region. The excitation extends over the right atrium along PM. Both CT and PM activated the right AWM. Earliest activation of the left atrium was through BB and excitation spread over to the APG. The conduction velocities were 0.6ms-1 for AWM, 1.2ms-1 for CT, 1.6ms-1 for PM and 1.1ms-1 for BB at a rate of 63bpm. The simulations revealed that bundles form dominant pathways for atrial conduction. The preferential conduction towards CT and along PM is comparable with clinical mapping. Repolarization is more homogeneous than excitation due to the heterogeneous distribution of electrophysiological properties and hence the action potential duration.

The specific absorption rate (SAR) is a limiting constraint in sequence design for high-field MRI. SAR estimation is typically performed by numerical simulations using generic human body models. This entails an intrinsic uncertainty in present SAR prediction. This study first investigates the required detail of human body models in terms of spatial resolution and the number of soft tissue classes required, based on finite-differences timedomain simulations of a 3 T body coil. The numerical results indicate that a resolution of 5 mm is sufficient for local SAR estimation. Moreover, a differentiation between fatty tissues, water-rich tissues, and the lungs was found to be essential to represent eddy current paths inside the human body. This study then proposes a novel approach for generating individualized body models from whole-body water-fat-separated MR data and applies it to volunteers. The SAR hotspots consistently occurred in the arms due to proximity to the body coil as well as