MR parameter quantification with magnetization-prepared double echo steady-state (MP-DESS).

PURPOSE: The mapping of MR relaxation times and proton density has been the subject of research in medical imaging for many years, as it offers the possibility for longitudinal investigation of disease and the correlation with related biochemical processes. The purpose of this study is to provide a fast mapping protocol, which simultaneously acquires MR relaxation times and relative proton density without compromising accuracy and precision. METHODS: This work presents a novel magnetization-prepared double echo steady-state (MP-DESS) sequence, which was designed to be sensitive to parameter variations of interest, and insensitive to variations of confounding variables. It provides high sensitivity against variations of the MR relaxation times, high acquisition efficiency, and it is insensitive to off-resonance. Accurate phase graph modeling of the MP-DESS signal is used to obtain unbiased parameter estimates. RESULTS: The approach is validated in phantom and in vivo measurements. A whole-brain acquisition of 1.4-mm isotropic resolution was acquired in 15 min. Comparisons to gold-standard methods suggest a mapping precision of 5% for T1 and M0 , and below 10% for T2. CONCLUSION: A new quantitative imaging technique is introduced that allows fast and isotropic simultaneous MR parameter mapping of T1, T2, and M0.

Parallel imaging acceleration of EPIK for reduced image distortions in fMRI.

EPI with Keyhole (EPIK) is a hybrid imaging technique used to improve the performance of EPI in dynamic MRI applications. The method had been previously validated at 1.5 T with both phantom and in vivo images; EPIK was able to provide a higher temporal resolution and less image distortions than single-shot EPI. The data presented here demonstrate that the performance of EPIK can be further improved by accelerating it with the parallel imaging. For this work, this combination was tested at 3 T. After initial evaluation using phantom images, use of the method in functional MRI was verified with visual fMRI measurements as well as MRI simulation results. The results showed that accelerated EPIK had increased temporal resolution with favorable robustness against susceptibility artifacts when compared with EPI or non-accelerated EPIK.

Zonal rate model for axial and radial flow membrane chromatography. Part I: knowledge transfer across operating conditions and scales.

The zonal rate model (ZRM) has previously been applied for analyzing the performance of axial flow membrane chromatography capsules by independently determining the impacts of flow and binding related non-idealities on measured breakthrough curves. In the present study, the ZRM is extended to radial flow configurations, which are commonly used at larger scales. The axial flow XT5 capsule and the radial flow XT140 capsule from Pall are rigorously analyzed under binding and non-binding conditions with bovine serum albumin (BSA) as test molecule. The binding data of this molecule is much better reproduced by the spreading model, which hypothesizes different binding orientations, than by the well-known Langmuir model. Moreover, a revised cleaning protocol with NaCl instead of NaOH and minimizing the storage time has been identified as most critical for quantitatively reproducing the measured breakthrough curves. The internal geometry of both capsules is visualized by magnetic resonance imaging (MRI). The flow in the external hold-up volumes of the XT140 capsule was found to be more homogeneous as in the previously studied XT5 capsule. An attempt for model-based scale-up was apparently impeded by irregular pleat structures in the used XT140 capsule, which might lead to local variations in the linear velocity through the membrane stack. However, the presented approach is universal and can be applied to different capsules. The ZRM is shown to potentially help save valuable material and time, as the experiments required for model calibration are much cheaper than the predicted large-scale experiment at binding conditions.

High-performance computing MRI simulations.

A new open-source software project is presented, JEMRIS, the Jülich Extensible MRI Simulator, which provides an MRI sequence development and simulation environment for the MRI community. The development was driven by the desire to achieve generality of simulated three-dimensional MRI experiments reflecting modern MRI systems hardware. The accompanying computational burden is overcome by means of parallel computing. Many aspects are covered that have not hitherto been simultaneously investigated in general MRI simulations such as parallel transmit and receive, important off-resonance effects, nonlinear gradients, and arbitrary spatiotemporal parameter variations at different levels. The latter can be used to simulate various types of motion, for instance. The JEMRIS user interface is very simple to use, but nevertheless it presents few limitations. MRI sequences with arbitrary waveforms and complex interdependent modules are modeled in a graphical user interface-based environment requiring no further programming. This manuscript describes the concepts, methods, and performance of the software. Examples of novel simulation results in active fields of MRI research are given.

Model-based analysis and quantitative prediction of membrane chromatography: extreme scale-up from 0.08 ml to 1200 ml.

A model-based approach is presented for quantitatively decoupling the impacts of non-ideal flow and non-ideal binding in membrane chromatography (MC) capsules at different scales. The internal geometry of Sartobind capsules with 0.08 ml and 1200 ml membrane volume is reconstructed from MRI measurements and manufacturer data. Based on this information, computational fluid dynamics (CFD) simulations are used for computing internal flow patterns of both capsules. Measured breakthrough curves (BTC) under non-binding conditions are used for calibrating PFR and CSTR models of the holdup volumes in the Äkta systems. A suitable binding model is determined and the binding parameters are estimated from binding BTC data of the 0.08 ml capsule. Due to the decoupling of non-idealities, the binding parameters can be directly transferred between the CFD models of both capsules. This advantage is used for quantitatively predicting BTC data of the 1200 ml capsule under binding conditions. The model-based prediction excellently matches with independently measured BTC data, facilitating an extreme scale-up factor of 15,000. The presented approach has previously been shown to be universally applicable to capsules from other vendors with different flow configurations and membrane types.

Computational fluid dynamic simulation of axial and radial flow membrane chromatography: mechanisms of non-ideality and validation of the zonal rate model.

Membrane chromatography (MC) is increasingly being used as a purification platform for large biomolecules due to higher operational flow rates. The zonal rate model (ZRM) has previously been applied to accurately characterize the hydrodynamic behavior in commercial MC capsules at different configurations and scales. Explorations of capsule size, geometry and operating conditions using the model and experiment were used to identify possible causes of inhomogeneous flow and their contributions to band broadening. In the present study, the hydrodynamics within membrane chromatography capsules are more rigorously investigated by computational fluid dynamics (CFD). The CFD models are defined according to precisely measured capsule geometries in order to avoid the estimation of geometry related model parameters. In addition to validating the assumptions and hypotheses regarding non-ideal flow mechanisms encoded in the ZRM, we show that CFD simulations can be used to mechanistically understand and predict non-binding breakthrough curves without need for estimation of any parameters. When applied to a small-scale axial flow MC capsules, CFD simulations identify non-ideal flows in the distribution (hold-up) volumes upstream and downstream of the membrane stack as the major source of band broadening. For the large-scale radial flow capsule, the CFD model quantitatively predicts breakthrough data using binding parameters independently determined using the small-scale axial flow capsule, identifying structural irregularities within the membrane pleats as an important source of band broadening. The modeling and parameter determination scheme described here therefore facilitates a holistic mechanistic-based method for model based scale-up, obviating the need of performing expensive large-scale experiments under binding conditions. As the CFD model described provides a rich mechanistic analysis of membrane chromatography systems and the ability to explore operational space, but requires detailed knowledge of internal capsule geometries and has much greater computational requirements, it is complementary to the previously described strengths and uses of the ZRM for process analysis and design.

Advances in multimodal neuroimaging: hybrid MR-PET and MR-PET-EEG at 3 T and 9.4 T.

Multi-modal MR-PET-EEG data acquisition in simultaneous mode confers a number of advantages at 3 T and 9.4 T. The three modalities complement each other well; structural-functional imaging being the domain of MRI, molecular imaging with specific tracers is the strength of PET, and EEG provides a temporal dimension where the other two modalities are weak. The utility of hybrid MR-PET at 3 T in a clinical setting is presented and critically discussed. The potential problems and the putative gains to be accrued from hybrid imaging at 9.4 T, with examples from the human brain, are outlined. Steps on the road to 9.4 T multi-modal MR-PET-EEG are also illustrated. From an MR perspective, the potential for ultra-high resolution structural imaging is discussed and example images of the cerebellum with an isotropic resolution of 320 µm are presented, setting the stage for hybrid imaging at ultra-high field. Further, metabolic imaging is discussed and high-resolution images of the sodium distribution are presented. Examples of tumour imaging on a 3 T MR-PET system are presented and discussed. Finally, the perspectives for multi-modal imaging are discussed based on two on-going studies, the first comparing MR and PET methods for the measurement of perfusion and the second which looks at tumour delineation based on MRI contrasts but the knowledge of tumour extent is based on simultaneously acquired PET data.

On the numerically predicted spatial BOLD fMRI specificity for spin echo sequences.

This work utilises general numerical magnetic resonance imaging MRI simulations to predict the spatial specificity of the blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signal. A Monte Carlo simulation approach was utilized on a microvascular structure consisting of randomly oriented cylinders representing blood vessels. This framework was employed to numerically investigate the spatial specificity, defined as ratio of pial vessel to microvascular signal, of the spin echo BOLD fMRI signal as a function of field strength, echo time and tissue types [grey matter (GM) and cerebrospinal fluid (CSF), respectively]. Spatial specificity of spin echo BOLD fMRI signal was determined to increase with field strength up to 16 T and with maximal specificity for echo time shorter than tissue T(2). In addition, it was found that, for large pial vessels, the extravascular signal decay could not be described using the oversimplified but nevertheless commonly employed mono-exponential signal decay approximation (MEA). Consequently, a recently proposed model relying on the MEA deviates substantially from our results on the spatial specificity. A refinement of this model is proposed based on an available, more detailed signal description. Finally, the effect of CSF on the spatial specificity was investigated. While a large spatial specificity of the spin echo BOLD fMRI signal is observed if a pial vessel is surrounded by grey matter, this is greatly reduced for a pial vessel situated on a GM/CSF interface, rendering the suppression of pial vessels on the cortex surface unlikely.