Julien Senegas

Compressed sensing reconstruction for magnetic resonance parameter mapping

Compressed sensing (CS) holds considerable promise to accelerate the data acquisition in magnetic resonance imaging by exploiting signal sparsity. Prior knowledge about the signal can be exploited in some applications to choose an appropriate sparsifying transform. This work presents a CS reconstruction for magnetic resonance (MR) parameter mapping, which applies an overcomplete dictionary, learned from the data model to sparsify the signal. The approach is presented and evaluated in simulations and in in vivo T1 and T2 mapping experiments in the brain. Accurate T1 and T2 maps are obtained from highly reduced data. This model‐based reconstruction could also be applied to other MR parameter mapping applications like diffusion and perfusion imaging. Magn Reson Med, 2010.

Dynamic and simultaneous MR measurement of R1 and R2* changes during respiratory challenges for the assessment of blood and tissue oxygenation

This work presents a novel method for the rapid and simultaneous measurement of R1 and R2* relaxation rates. It is based on a dynamic short repetition time steady‐state spoiled multigradient‐echo sequence and baseline R1 and B1 measurements. The accuracy of the approach was evaluated in simulations and a phantom experiment. The sensitivity and specificity of the method were demonstrated in one volunteer and in four patients with intracranial tumors during carbogen inhalation. We utilized (ΔR2*, ΔR1) scatter plots to analyze the multiparametric response amplitude of each voxel within an area of interest. In normal tissue R2* decreased and R1 increased moderately in response to the elevated blood and tissue oxygenation. A strong negative ΔR2* and ΔR1 response was observed in veins and some tumor areas. Moderate positive ΔR2* and ΔR1 response amplitudes were found in fluid‐rich tissue as in cerebrospinal fluid, peritumoral edema, and necrotic areas. The multiparametric approach was shown to increase the specificity and sensitivity of oxygen‐enhanced MRI compared to measuring ΔR2* or ΔR1 alone. It is thus expected to provide an optimal tool for the identification of tissue areas with low oxygenation, e.g., in tumors with compromised oxygen supply. Magn Reson Med, 2013.

Accelerated T2 Mapping for Characterization of Prostate Cancer

Prostate T2 mapping was performed in 34 consecutive patients using an accelerated multiecho spin‐echo sequence with 4‐fold k‐space undersampling leading to a net acceleration factor of 3.3 on a 3T scanner. The mean T2 values from the accelerated and conventional, unaccelerated sequences demonstrated a very high correlation (r = 0.99). Different prostate segments demonstrated similarly good interscan reproducibility (p = not significant) with slightly larger difference at base: 2.0% ± 1.6% for left base and 2.1% ± 1.1% for right base. In patients with subsequent targeted biopsy, T2 values of histologically proven malignant tumor areas were significantly lower than the suspicious looking but nonmalignant lesions (p < 0.05) and normal areas (p < 0.001): 100 ± 10 ms for malignant tumors, 114 ± 23 ms for suspicious lesions and 149 ± 32 ms for normal tissues. The proposed method can provide an effective approach for accelerated T2 quantification for prostate patients. Magn Reson Med, 2011.

Iterative Off-Resonance and Signal Decay Estimation and Correction for Multi-Echo MRI

Signal dephasing due to field inhomogeneity and signal decay due to transverse relaxation lead to perturbations of the Fourier encoding commonly applied in magnetic resonance imaging. Hence, images acquired with long readouts suffer from artifacts such as blurring, distortion, and intensity variation. These artifacts can be removed in reconstruction, usually based on separately collected information in form of field and relaxation maps. In this work, a recently proposed gridding-based algorithm for off-resonance correction is extended to also address signal decay. It is integrated into a new fixed-point iteration, which permits the joint estimation of an image and field and relaxation maps from multi-echo acquisitions. This approach is then applied in simulations and in vivo experiments and demonstrated to improve both images and maps. The rapid convergence of the fixed-point iteration in combination with the efficient gridding-based correction promises to render the running time of such a joint estimation acceptable.

Positive visualization of implanted devices with susceptibility gradient mapping using the original resolution

In magnetic resonance imaging, implantable devices are usually visualized with a negative contrast. Recently, positive contrast techniques have been proposed, such as susceptibility gradient mapping (SGM). However, SGM reduces the spatial resolution making positive visualization of small structures difficult. Here, a development of SGM using the original resolution (SUMO) is presented. For this, a filter is applied in k‐space and the signal amplitude is analyzed in the image domain to determine quantitatively the susceptibility gradient for each pixel. It is shown in simulations and experiments that SUMO results in a better visualization of small structures in comparison to SGM. SUMO is applied to patient datasets for visualization of stent and prostate brachytherapy seeds. In addition, SUMO also provides quantitative information about the number of prostate brachytherapy seeds. The method might be extended to application for visualization of other interventional devices, and, like SGM, it might also be used to visualize magnetically labelled cells. Magn Reson Med, 2011.

Concurrent MR blood volume and vessel size estimation in tumors by robust and simultaneous ΔR2 and ΔR2* quantification

This work presents a novel method for concurrent estimation of the fractional blood volume and the mean vessel size of tumors based on a multi‐gradient‐echo‐multi‐spin‐echo sequence and the injection of a super‐paramagnetic blood‐pool agent. The approach further comprises a post‐processing technique for simultaneous estimation of changes in the transverse relaxation rates R2 and R  2* , which is robust against global B0 and B1 field inhomogeneities and slice imperfections. The accuracy of the simultaneous ΔR2 and ΔR  2* quantification approach is evaluated in a phantom. The simultaneous blood volume and vessel size estimates, obtained with MR, compare well to the immunohistological findings in a preclinical experiment (HT1080 cells, implanted in nude mice). Clinical translation is achieved in a patient with a pleomorphic sarcoma in the left pubic bone. The latter demonstrates the robustness of the technique against changes in the contrast agent concentration in blood during washout. Magn Reson Med, 2011.

Segmentation of Medical Images with a Shape and Motion Model: A Bayesian Perspective

This paper describes a Bayesian framework for the segmentation of a temporal sequence of medical images, where both shape and motion prior information are integrated into a stochastic model. With this approach, we aim to take into account all the information available to compute an optimum solution, thus increasing the robustness and accuracy of the shape and motion reconstruction. The segmentation algorithm we develop is based on sequential Monte Carlo sampling methods previously applied in tracking applications. Moreover, we show how stochastic shape models can be constructed using a global shape description based on orthonormal functions. This makes our approach independent of the dimension of the object (2D or 3D) and on the particular shape parameterization used. Results of the segmentation method applied to cardiac cine MR images are presented.

Fast T2 relaxometry with an accelerated multi-echo spin-echo sequence

A new method has been developed to reduce the number of phase‐encoding steps in a multi‐echo spin‐echo imaging sequence allowing fast T2 mapping without loss of spatial resolution. In the proposed approach, the k‐space data at each echo time were undersampled and a reconstruction algorithm that exploited the temporal correlation of the MR signal in k‐space was used to reconstruct alias‐free images. A specific application of this algorithm with multiple‐receiver acquisition, offering an alternative to existing parallel imaging methods, has also been introduced. The fast T2 mapping method has been validated in human brain T2 measurements in a group of nine volunteers with acceleration factors up to 3.4. The results demonstrated that the proposed method exhibited excellent linear correlation with the regular T2 mapping with full sampling and achieved better image reconstruction and T2 mapping with respect to SNR and reconstruction artifacts than the selected reference acceleration techniques. The new method has also been applied for quantitative tracking of injected magnetically labeled breast cancer cells in the rat brain with acceleration factors of 1.8 and 3.0. The proposed technique can provide an effective approach for accelerated T2 quantification, especially for experiments with single‐channel coil when parallel imaging is not applicable. Copyright

Model-based segmentation of cardiac MRI cine sequences: a Bayesian formulation

The quantitative analysis of cardiac cine MRI sequences requires automated, robust, and fast image processing algorithms for the 4D (3D + time) segmentation of the heart chambers. The use of shape models has proven efficient in extracting the cardiac volumes for single phases, but less attention has been focused on incorporating prior knowledge about the cardiac motion. To explicitly address the temporal aspect of the segmentation problem, this paper proposes a full Bayesian model, where the prior information is represented by a cardiac shape and motion model. In this framework, the solution of the segmentation is defined by means of a probability distribution over the parameters of the space-time problem. The computed solution, obtained by means of sequential Monte Carlo techniques, has the advantage of being both spatially and temporally coherent. Furthermore, the method does not require any particular representation of the shape or of the motion model; it is therefore generic and highly flexible.

Optimal high b-value for diffusion weighted MRI in diagnosing high risk prostate cancers in the peripheral zone

To retrospectively determine the optimal b‐value(s) of diffusion‐weighted imaging (DWI) associated with intermediate–high risk cancer in the peripheral zone (PZ) of the prostate.