Multiple motion encoding in phase-contrast MRI: A general theory and application to elastography imaging.

While MRI allows to encode the motion of tissue in the magnetization's phase, it remains yet a challenge to obtain high fidelity motion images due to wraps in the phase for high encoding efficiencies. Therefore, we propose an optimal multiple motion encoding method (OMME) and exemplify it in Magnetic Resonance Elastography (MRE) data. OMME is formulated as a non-convex least-squares problem for the motion using an arbitrary number of phase-contrast measurements with different motion encoding gradients (MEGs). The mathematical properties of OMME are proved in terms of standard deviation and dynamic range of the motion's estimate for arbitrary MEGs combination which are confirmed using synthetically generated data. OMME's performance is assessed on MRE data from in vivo human brain experiments and compared to dual encoding strategies. The unwrapped images are further used to reconstruct stiffness maps and compared to the ones obtained using conventional unwrapping methods. OMME allowed to successfully combine several MRE phase images with different MEGs, outperforming dual encoding strategies in either motion-to-noise ratio (MNR) or number of successfully reconstructed voxels with good noise stability. This lead to stiffness maps with greater resolution of details than obtained with conventional unwrapping methods. The proposed OMME method allows for a flexible and noise robust increase in the dynamic range and thus provides wrap-free phase images with high MNR. In MRE, the method may be especially suitable when high resolution images with high MNR are needed.

A simplified homogenization model applied to viscoelastic behavior of cortical bone at ultrasonic frequencies.

Cortical bone is a complex multiscale medium and its study is of importance for clinical fracture prevention. In particular, cortical attenuation is known to be linked with shock energy absorption and ability to resist fracture. However, the links between cortical bone absorption and its multiscale structure are still not well understood. This work is about the use of homogenized tensors in order to characterize the viscoelastic behavior of cortical bone at ultrasonic frequencies, i.e., about 0.1 to 10 MHz. Such tensors are derived from the cell problem via two-scale homogenization theory for linear elastic and Kelvin-Voigt viscoelastic descriptions. The elliptic formulations obtained from the cell problems are implemented within the range of medically-observed porosities. Microstructure is assessed considering cubic cells with cylindrical inclusion and transverse isotropic assumption. A simplified model, adding one temporal parameter τ per phase, allows a good agreement with experimental data. The corresponding attenuation is proportional to the square of the frequency, in agreement with Kramer-Kronig relations. This development is proposed in the context of robust clinical inverse problem approaches using a restricted number of parameter. Two main properties for the material filling the pores are adjusted and discussed: absorption and shear contribution. Best agreement with experimental data is observed for material inside the pores being solid and highly attenuating.

Validation of 4D Flow based relative pressure maps in aortic flows.

While the clinical gold standard for pressure difference measurements is invasive catheterization, 4D Flow MRI is a promising tool for enabling a non-invasive quantification, by linking highly spatially resolved velocity measurements with pressure differences via the incompressible Navier-Stokes equations. In this work we provide a validation and comparison with phantom and clinical patient data of pressure difference maps estimators. We compare the classical Pressure Poisson Estimator (PPE) and the new Stokes Estimator (STE) against catheter pressure measurements under a variety of stenosis severities and flow intensities. Specifically, we use several 4D Flow data sets of realistic aortic phantoms with different anatomic and hemodynamic severities and two patients with aortic coarctation. The phantom data sets are enriched by subsampling to lower resolutions, modification of the segmentation and addition of synthetic noise, in order to study the sensitivity of the pressure difference estimators to these factors. Overall, the STE method yields more accurate results than the PPE method compared to catheterization data. The superiority of the STE becomes more evident at increasing Reynolds numbers with a better capacity of capturing pressure gradients in strongly convective flow regimes. The results indicate an improved robustness of the STE method with respect to variation in lumen segmentation. However, with heuristic removal of the wall-voxels, the PPE can reach a comparable accuracy for lower Reynolds' numbers.

Optimal Dual-VENC Unwrapping in Phase-Contrast MRI.

Dual-VENC strategies have been proposed to improve the velocity-to-noise ratio in phase-contrast MRI. However, they are based on aliasing-free high-VENC data. The aim of this paper is to propose a dual-VENC velocity estimation method allowing high-VENC aliased data. For this purpose, we reformulate the phase-contrast velocity as a least squares estimator, providing a natural framework for including multiple encoding gradient measurements. By analyzing the mathematical properties of both single- and dual-VENC problems, we can justify theoretically high/low-VENC ratios such that the aliasing velocity can be minimized. The resulting reconstruction algorithm was assessed using three types of data: numerical, experimental, and volunteers. In clinical practice, this method would allow shorter examination times by avoiding tedious adaptation of VENC values by repeated scans.

Relative pressure estimation from velocity measurements in blood flows: State-of-the-art and new approaches.

The relative pressure difference across stenotic blood vessels serves as an important clinical index for the diagnosis of many cardiovascular diseases. While the clinical gold standard for relative pressure difference measurements is invasive catheterization, Phase-Contrast Magnetic Resonance Imaging has emerged as a promising tool for enabling a noninvasive quantification, by linking highly spatially resolved velocity measurements with relative pressures via the incompressible Navier-Stokes equations. In this work, we provide a review and analysis of current methods for relative pressure estimation and propose 3 additional techniques. Methods are compared using synthetic data from numerical examples, and sensitivity to subsampling and noise was explored. Through our analysis, we verify that the newly proposed approaches are more robust with respect to spatial subsampling and less sensitive to noise and therefore provide improved means for estimating relative pressure differences noninvasively.

Modeling heterocyst pattern formation in cyanobacteria.

BACKGROUND: To allow the survival of the population in the absence of nitrogen, some cyanobacteria strains have developed the capability of differentiating into nitrogen fixing cells, forming a characteristic pattern. In this paper, the process by which cyanobacteria differentiates from vegetative cells into heterocysts in the absence of nitrogen and the elements of the gene network involved that allow the formation of such a pattern are investigated. METHODS: A simple gene network model, which represents the complexity of the differentiation process, and the role of all variables involved in this cellular process is proposed. Specific characteristics and details of the system's behavior such as transcript profiles for ntcA, hetR and patS between consecutive heterocysts were studied. RESULTS: The proposed model is able to capture one of the most distinctive features of this system: a characteristic distance of 10 cells between two heterocysts, with a small standard deviation according to experimental variability. The system's response to knock-out and over-expression of patS and hetR was simulated in order to validate the proposed model against experimental observations. In all cases, simulations show good agreement with reported experimental results. CONCLUSION: A simple evolution mathematical model based on the gene network involved in heterocyst differentiation was proposed. The behavior of the biological system naturally emerges from the network and the model is able to capture the spacing pattern observed in heterocyst differentiation, as well as the effect of external perturbations such as nitrogen deprivation, gene knock-out and over-expression without specific parameter fitting.