Tobias Wech

Accelerating cine-MR Imaging in Mouse Hearts Using Compressed Sensing

To combine global cardiac function imaging with compressed sensing (CS) in order to reduce scan time and to validate this technique in normal mouse hearts and in a murine model of chronic myocardial infarction.

Model-based Acceleration of Parameter mapping (MAP) for saturation prepared radially acquired data

A reconstruction technique called Model‐based Acceleration of Parameter mapping (MAP) is presented allowing for quantification of longitudinal relaxation time and proton density from radial single‐shot measurements after saturation recovery magnetization preparation. Using a mono‐exponential model in image space, an iterative fitting algorithm is used to reconstruct one well resolved and consistent image for each of the projections acquired during the saturation recovery relaxation process. The functionality of the algorithm is examined in numerical simulations, phantom experiments, and in‐vivo studies. MAP reconstructions of single‐shot acquisitions feature the same image quality and resolution as fully sampled reference images in phantom and in‐vivo studies. The longitudinal relaxation times obtained from the MAP reconstructions are in very good agreement with the reference values in numerical simulations as well as phantom and in‐vivo measurements. Compared to available contrast manipulation techniques, no averaging of projections acquired at different time points of the relaxation process is required in MAP imaging. The proposed technique offers new ways of extracting quantitative information from single‐shot measurements acquired after magnetization preparation. The reconstruction simultaneously yields images with high spatiotemporal resolution fully consistent with the acquired data as well as maps of the effective longitudinal relaxation parameter and the relative proton density. Magn Reson Med 70:1524–1534, 2013.

High resolution myocardial first-pass perfusion imaging with extended anatomic coverage

To evaluate and to compare Parallel Imaging and Compressed Sensing acquisition and reconstruction frameworks based on simultaneous multislice excitation for high resolution contrast‐enhanced myocardial first‐pass perfusion imaging with extended anatomic coverage.

Resolution evaluation of MR images reconstructed by iterative thresholding algorithms for compressed sensing

PURPOSE Magnetic resonance imaging systems usually feature linear and shift-invariant (stationary) transform characteristics. The point spread function or equivalently the modulation transfer function may thus be used for an objective quality assessment of imaging modalities. The recently introduced theory of compressed sensing, however, incorporates nonlinear and nonstationary reconstruction algorithms into the magnetic resonance imaging process which prohibits the usage of the classical point spread function and therefore the according evaluation. METHODS In this work, alocal point spread function concept was applied to assess the quality of magnetic resonance images which were reconstructed by an iterative soft thresholding algorithm for compressed sensing. The width of the main lobe of the local point spread function was used to perform studies on the spatial and temporal resolution properties of both numerical phantom and in vivo images. The impact of k-space sampling patterns as well as additional sparsifying transforms on the local spatial image resolution was investigated. In addition, the local temporal resolution of image series, which were reconstructed by exploiting spatiotemporal sparsity, was determined. Finally, the dependency of the local resolution on the thresholding parameter of the algorithm was examined. RESULTS The sampling patterns as well as the additional sparsifying transform showed a distinct impact on the local image resolution of the phantom image. The reconstructions, which were usingx-f-space as a sparse transform domain showed slight temporal blurring for dynamic parts of the imaged object. The local image resolution had a dependence on the thresholding parameter, which allowed for optimizing the reconstruction. CONCLUSIONS Local point spread functions enable the evaluation of the local spatial and temporal resolution of images reconstructed with the nonlinear and nonstationary iterative soft thresholding algorithm. By determining the influence of thresholding parameter and sampling pattern chosen on this model-based reconstruction, the method allows selecting appropriate acquisition parameters and thus improving the results.PURPOSE Magnetic resonance imaging systems usually feature linear and shift-invariant (stationary) transform characteristics. The point spread function or equivalently the modulation transfer function may thus be used for an objective quality assessment of imaging modalities. The recently introduced theory of compressed sensing, however, incorporates nonlinear and nonstationary reconstruction algorithms into the magnetic resonance imaging process which prohibits the usage of the classical point spread function and therefore the according evaluation. METHODS In this work, a local point spread function concept was applied to assess the quality of magnetic resonance images which were reconstructed by an iterative soft thresholding algorithm for compressed sensing. The width of the main lobe of the local point spread function was used to perform studies on the spatial and temporal resolution properties of both numerical phantom and in vivo images. The impact of k-space sampling patterns as well as additional sparsifying transforms on the local spatial image resolution was investigated. In addition, the local temporal resolution of image series, which were reconstructed by exploiting spatiotemporal sparsity, was determined. Finally, the dependency of the local resolution on the thresholding parameter of the algorithm was examined. RESULTS The sampling patterns as well as the additional sparsifying transform showed a distinct impact on the local image resolution of the phantom image. The reconstructions, which were using x-f-space as a sparse transform domain showed slight temporal blurring for dynamic parts of the imaged object. The local image resolution had a dependence on the thresholding parameter, which allowed for optimizing the reconstruction. CONCLUSIONS Local point spread functions enable the evaluation of the local spatial and temporal resolution of images reconstructed with the nonlinear and nonstationary iterative soft thresholding algorithm. By determining the influence of thresholding parameter and sampling pattern chosen on this model-based reconstruction, the method allows selecting appropriate acquisition parameters and thus improving the results.

Model-based acceleration of look-locker T1 mapping.

Mapping the longitudinal relaxation time T 1 has widespread applications in clinical MRI as it promises a quantitative comparison of tissue properties across subjects and scanners. Due to the long scan times of conventional methods, however, the use of quantitative MRI in clinical routine is still very limited. In this work, an acceleration of Inversion-Recovery Look-Locker (IR-LL) T 1 mapping is presented. A model-based algorithm is used to iteratively enforce an exponential relaxation model to a highly undersampled radially acquired IR-LL dataset obtained after the application of a single global inversion pulse. Using the proposed technique, a T 1 map of a single slice with 1.6mm in-plane resolution and 4mm slice thickness can be reconstructed from data acquired in only 6s. A time-consuming segmented IR experiment was used as gold standard for T 1 mapping in this work. In the subsequent validation study, the model-based reconstruction of a single-inversion IR-LL dataset exhibited a T 1 difference of less than 2.6% compared to the segmented IR-LL reference in a phantom consisting of vials with T 1 values between 200ms and 3000ms. In vivo, the T 1 difference was smaller than 5.5% in WM and GM of seven healthy volunteers. Additionally, the T 1 values are comparable to standard literature values. Despite the high acceleration, all model-based reconstructions were of a visual quality comparable to fully sampled references. Finally, the reproducibility of the T 1 mapping method was demonstrated in repeated acquisitions. In conclusion, the presented approach represents a promising way for fast and accurate T 1 mapping using radial IR-LL acquisitions without the need of any segmentation.

Whole-Heart Cine MRI in a Single Breath-Hold – A Compressed Sensing Accelerated 3D Acquisition Technique for Assessment of Cardiac Function

PURPOSE The aim of this study was to perform functional MR imaging of the whole heart in a single breath-hold using an undersampled 3 D trajectory for data acquisition in combination with compressed sensing for image reconstruction. MATERIALS AND METHODS Measurements were performed using an SSFP sequence on a 3 T whole-body system equipped with a 32-channel body array coil. A 3 D radial stack-of-stars sampling scheme was utilized enabling efficient undersampling of the k-space and thereby accelerating data acquisition. Compressed sensing was applied for the reconstruction of the missing data. A validation study was performed based on a fully sampled dataset acquired by standard Cartesian cine imaging of 2 D slices on a healthy volunteer. The results were investigated with regard to systematic errors and resolution losses possibly introduced by the developed reconstruction. Subsequently, the proposed technique was applied for in-vivo functional cardiac imaging of the whole heart in a single breath-hold of 27  s. The developed technique was tested on three healthy volunteers to examine its reproducibility. RESULTS By means of the results of the simulation (temporal resolution: 47  ms, spatial resolution: 1.4 × 1.4 × 8  mm, 3 D image matrix: 208 × 208 × 10), an overall acceleration factor of 10 has been found where the compressed sensing reconstructed image series shows only very low systematic errors and a slight in-plane resolution loss of 15 %. The results of the in-vivo study (temporal resolution: 40.5  ms, spatial resolution: 2.1 × 2.1 × 8  mm, 3 D image matrix: 224 × 224 × 12) performed with an acceleration factor of 10.7 confirm the overall good image quality of the presented technique for undersampled acquisitions. CONCLUSION The combination of 3 D radial data acquisition and model-based compressed sensing reconstruction allows high acceleration factors enabling cardiac functional imaging of the whole heart within only one breath-hold. The image quality in the simulated dataset and the in-vivo measurement highlights the great potential of the presented technique for an efficient assessment of cardiac functional parameters.

Using self‐consistency for an iterative trajectory adjustment (SCITA)

To iteratively correct for deviations in radial trajectories with no need of additionally performed calibration scans.

Consideration of slice profiles in inversion recovery Look-Locker relaxation parameter mapping☆

PURPOSE To include the flip angle distribution caused by the slice profile into the model used for describing the relaxation curves observed in inversion recovery Look-Locker FLASH T1 mapping for a more accurate determination of the relaxation parameters. MATERIALS AND METHODS For each inversion time, the flip angle dependent signal of the mono-exponential relaxation model is integrated across the slice profile. The resulting Consideration of Slice Profiles (CSP) relaxation curves are compared to the mono-exponential signal model in numerical simulations as well as in phantom and in-vivo experiments. RESULTS All measured relaxation curves showed systematic deviations from a mono-exponential curve increasing with flip angle and T1 but decreasing with repetition time. Additionally, the accuracy of T1 was found to be largely dependent on the temporal coverage of the relaxation curve. All these systematic errors were largely reduced by the CSP model. CONCLUSION The proposed CSP model represents a useful extension of the conventionally used mono-exponential relaxation model. Despite inherent model inaccuracies, the mono-exponential model was found to be sufficient for many T1 mapping situations. However, if only a poor temporal coverage of the relaxation process is achievable or a very precise modeling of the relaxation course is needed as in model-based techniques, the mono-exponential model leads to systematic errors and the CSP model should be used instead.

High-resolution functional cardiac MR imaging using density-weighted real-time acquisition and a combination of compressed sensing and parallel imaging for image reconstruction

PURPOSE The aim of this study was to perform high-resolution functional MR imaging using accelerated density-weighted real-time acquisition (DE) and a combination of compressed sensing (CO) and parallel imaging for image reconstruction. MATERIALS AND METHODS Measurements were performed on a 3 T whole-body system equipped with a dedicated 32-channel body array coil. A one-dimensional density-weighted spin warp technique was used, i. e. non-equidistant phase encoding steps were acquired. The two acceleration techniques, compressed sensing and parallel imaging, were performed subsequently. From a complete Cartesian k-space, a four-fold uniformly undersampled k-space was created. In addition, each undersampled time frame was further undersampled by an additional acceleration factor of 2.1 using an individual density-weighted undersampling pattern for each time frame. Simulations were performed using data of a conventional human in-vivo cine examination and in-vivo measurements of the human heart were carried out employing an adapted real-time sequence. RESULTS High-quality DECO real-time images using parallel acquisition of the function of the human heart could be acquired. An acceleration factor of 8.4 could be achieved making it possible to maintain the high spatial and temporal resolution without significant noise enhancement. CONCLUSION DECO parallel imaging facilitates high acceleration factors, which allows real-time MR acquisition of the heart dynamics and function with an image quality comparable to that conventionally achieved with clinically established triggered cine imaging.

An intravoxel oriented flow model for diffusion-weighted imaging of the kidney.

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow‐related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOFf) is applied to diffusion‐weighted imaging of human kidneys.