Daniel Giese

High resolution three‐dimensional cardiac perfusion imaging using compartment‐based k‐t principal component analysis

Three‐dimensional myocardial perfusion imaging requires significant acceleration of data acquisition to achieve whole‐heart coverage with adequate spatial and temporal resolution. The present article introduces a compartment‐based k‐t principal component analysis reconstruction approach, which permits three‐dimensional perfusion imaging at 10‐fold nominal acceleration. Using numerical simulations, it is shown that the compartment‐based method results in accurate representations of dynamic signal intensity changes with significant improvements of temporal fidelity in comparison to conventional k‐t principal component analysis reconstructions. Comparison of the two methods based on rest and stress three‐dimensional perfusion data acquired with 2.3 × 2.3 × 10 mm3 during a 225 msec acquisition window in patients confirms the findings and demonstrates the potential of compartment‐based k‐t principal component analysis for highly accelerated three‐dimensional perfusion imaging. Magn Reson Med, 2011.

Analysis and correction of background velocity offsets in phase-contrast flow measurements using magnetic field monitoring.

The value of phase‐contrast magnetic resonance imaging for quantifying tissue motion and blood flow has been long recognized. However, the sensitivity of the method to system imperfections can lead to inaccuracies limiting its clinical acceptance. A key source of error relates to eddy current‐induced phase fluctuations, which can offset the measured object velocity significantly. A higher‐order dynamic field camera was used to study the spatiotemporal evolution of background phases in cine phase‐contrast measurements. It is demonstrated that eddy current‐induced offsets in phase‐difference data are present up to the second spatial order. Oscillatory temporal behaviors of offsets in the kHz range suggest mechanical resonances of the MR system to be non‐negligible in phase‐contrast imaging. By careful selection of the echo time, their impact can be significantly reduced. When applying field monitoring data for correcting eddy current and mechanically induced velocity offsets, errors decrease to less than 0.5% of the maximum velocity for various sequence settings proving the robustness of the correction approach. In vivo feasibility is demonstrated for aortic and pulmonary flow measurements in five healthy subjects. Using field monitoring data, mean error in stroke volume was reduced from 10% to below 3%. Magn Reson Med, 2012.

Improved UTE-based attenuation correction for cranial PET-MR using dynamic magnetic field monitoring

PURPOSE Ultrashort echo time (UTE) MRI has been proposed as a way to produce segmented attenuation maps for PET, as it provides contrast between bone, air, and soft tissue. However, UTE sequences require samples to be acquired during rapidly changing gradient fields, which makes the resulting images prone to eddy current artifacts. In this work it is demonstrated that this can lead to misclassification of tissues in segmented attenuation maps (AC maps) and that these effects can be corrected for by measuring the true k-space trajectories using a magnetic field camera. METHODS The k-space trajectories during a dual echo UTE sequence were measured using a dynamic magnetic field camera. UTE images were reconstructed using nominal trajectories and again using the measured trajectories. A numerical phantom was used to demonstrate the effect of reconstructing with incorrect trajectories. Images of an ovine leg phantom were reconstructed and segmented and the resulting attenuation maps were compared to a segmented map derived from a CT scan of the same phantom, using the Dice similarity measure. The feasibility of the proposed method was demonstrated in in vivo cranial imaging in five healthy volunteers. Simulated PET data were generated for one volunteer to show the impact of misclassifications on the PET reconstruction. RESULTS Images of the numerical phantom exhibited blurring and edge artifacts on the bone-tissue and air-tissue interfaces when nominal k-space trajectories were used, leading to misclassification of soft tissue as bone and misclassification of bone as air. Images of the tissue phantom and the in vivo cranial images exhibited the same artifacts. The artifacts were greatly reduced when the measured trajectories were used. For the tissue phantom, the Dice coefficient for bone in MR relative to CT was 0.616 using the nominal trajectories and 0.814 using the measured trajectories. The Dice coefficients for soft tissue were 0.933 and 0.934 for the nominal and measured cases, respectively. For air the corresponding figures were 0.991 and 0.993. Compared to an unattenuated reference image, the mean error in simulated PET uptake in the brain was 9.16% when AC maps derived from nominal trajectories was used, with errors in the SUV max for simulated lesions in the range of 7.17%-12.19%. Corresponding figures when AC maps derived from measured trajectories were used were 0.34% (mean error) and -0.21% to +1.81% (lesions). CONCLUSIONS Eddy current artifacts in UTE imaging can be corrected for by measuring the true k-space trajectories during a calibration scan and using them in subsequent image reconstructions. This improves the accuracy of segmented PET attenuation maps derived from UTE sequences and subsequent PET reconstruction.

Highly undersampled phase-contrast flow measurements using compartment-based k–t principal component analysis

The applicability of cine blood flow measurements in a clinical setting is often compromised by the long scan times associated with phase‐contrast imaging. In this work, we propose an extension to the k–t principal component analysis method and demonstrate that by definition of spatial compartment‐dependent temporal basis functions, significant improvements in reconstruction accuracy can be achieved relative to the original k–t principal component analysis and k–t SENSE formulations. Using this method, it is shown that prospective nominal undersampling of up to 16 corresponding to a net acceleration factor of 8 including training data acquisition can be realized while keeping the error in stroke volume below 5%. As a practical application, the acquisition of cine flow data in the aorta is demonstrated permitting assessment of two‐dimensional velocity images and pulse wave velocities at 100 frames per second in a single breathhold per slice. Magn Reson Med, 2013.

Reconstruction of divergence-free velocity fields from cine 3D phase-contrast flow measurements.

Three‐dimensional phase‐contrast velocity vector field mapping shows great potential for clinical applications; however measurement inaccuracies may limit the utility and robustness of the technique. While parts of the error in the measured velocity fields can be minimized by background phase estimation in static tissue and magnetic field monitoring, considerable inaccuracies remain. The present work introduces divergence‐reduction processing of 3D phase‐contrast flow data based on a synergistic combination of normalized convolution and divergence‐free radial basis functions. It is demonstrated that this approach effectively addresses erroneous flow for image reconstructions from both fully sampled and undersampled data. Using computer simulations and in vivo data acquired in the aorta of healthy subjects and a stenotic valve patient it is shown that divergence arising from measurement imperfections can be reduced by up to 87% resulting in improved vector field representations. Based on the results obtained it is concluded that integration of the divergence‐free condition into postprocessing of vector fields presents an efficient approach to addressing flow field inaccuracies. Magn Reson Med, 2013.

A sensitivity analysis on 3D velocity reconstruction from multiple registered echo Doppler views

We present a new method for reconstructing a 3D+t velocity field from multiple 3D+t colour Doppler images. Our technique reconstructs 3D velocity vectors from registered multiple standard 3D colour Doppler views, each of which contains a 1D projection of the blood velocity. Reconstruction is based on a scalable patch-wise Least Mean Squares approach, and a continuous velocity field is achieved by using a B-spline grid. We carry out a sensitivity analysis of clinically relevant parameters which affect the accuracy of the reconstruction, including the impact of noise, view angles and registration errors, using simulated data. A realistic simulation framework is achieved by a novel noise model to represent variations in colour Doppler images based on multiscale additive Gaussian noise. Simulations show that, if the Target Registration Error <2.5mm, view angles are >20° and the standard deviation of noise in the input data is <10 cm/s, the reconstructed velocity field presents visually plausible flow patterns and mean error in flow rate is approximately 10% compared to 2D+t Flow MRI. These results are verified by reconstructing 3D velocity on three healthy volunteers. The technique is applied to reconstruct 3D flow on three paediatric patients showing promising results for clinical application.

Quantitative Analysis of Vortical Blood Flow in the Thoracic Aorta Using 4D Phase Contrast MRI.

Introduction Phase contrast MRI allows for the examination of complex hemodynamics in the heart and adjacent great vessels. Vortex flow patterns seem to play an important role in certain vascular pathologies. We propose two- and three-dimensional metrics for the objective quantification of aortic vortex blood flow in 4D phase contrast MRI. Materials and Methods For two-dimensional vorticity assessment, a standardized set of 6 regions-of-interest (ROIs) was defined throughout the course of the aorta. For each ROI, a heatmap of time-resolved vorticity values ω→=∇v→ was computed. Evolution of minimum, maximum, and average values as well as opposing rotational flow components were analyzed. For three-dimensional analysis, vortex core detection was implemented combining the predictor-corrector method with λ2 correction. Strength, elongation, and radial expansion of the detected vortex core were recorded over time. All methods were applied to 4D flow MRI datasets of 9 healthy subjects, 2 patients with mildly dilated aorta, and 1 patient with aortic aneurysm. Results Vorticity quantification in the 6 standardized ROIs enabled the description of physiological vortex flow in the healthy aorta. Helical flow developed early in the ascending aorta (absolute vorticity = 166.4±86.4 s-1 at 12% of cardiac cycle) followed by maximum values in mid-systole in the aortic arch (240.1±45.2 s-1 at 16%). Strength, elongation, and radial expansion of 3D vortex cores escalated in early systole, reaching a peak in mid systole (strength = 241.2±30.7 s-1 at 17%, elongation = 65.1±34.6 mm at 18%, expansion = 80.1±48.8 mm2 at 20%), before all three parameters similarly decreased to overall low values in diastole. Flow patterns were considerably altered in patient data: Vortex flow developed late in mid/end-systole close to the aortic bulb and no physiological helix was found in the aortic arch. Conclusions We have introduced objective measures for quantification of vortical flow in 4D phase contrast MRI. Vortex blood flow in the thoracic aorta could be consistently described in all healthy volunteers. In patient data, pathologically altered vortex flow was observed.

Image-based background phase error correction in 4D flow MRI revisited.

To correct background phase errors in phase‐contrast magnetic resonance imaging (MRI), image‐based correction by referencing through stationary tissue is widely used. The aim of the present study was a detailed assessment of background phase errors in 4D Flow MRI and limitations of image‐based correction.

3D Intraventricular Flow Mapping from Colour Doppler Images and Wall Motion

We propose a new method to recover 3D time-resolved velocity vectors within the left ventricle (LV) using a combination of multiple registered 3D colour Doppler images and LV wall motion. Incorporation of wall motion, calculated from 3D B-Mode images, and the use of a multi-scale reconstruction framework allow recovery of 3D velocity over the entire ventricle, even in regions where there is little or no Doppler data. Our method is tested on the LV of a paediatric patient and is compared to 2D and 3D flow Magnetic Resonance Imaging (MRI). Use of wall motion information increased stroke volume accuracy by 14%, and enabled full 3D velocity mapping within the ventricle. Velocity distribution showed good agreement with respect to MRI, and vortex formation during diastole was successfully reconstructed.

Accuracy of 4D Flow Measurement of Cerebrospinal Fluid Dynamics in the Cervical Spine: An In Vitro Verification Against Numerical Simulation

Abnormal alterations in cerebrospinal fluid (CSF) flow are thought to play an important role in pathophysiology of various craniospinal disorders such as hydrocephalus and Chiari malformation. Three directional phase contrast MRI (4D Flow) has been proposed as one method for quantification of the CSF dynamics in healthy and disease states, but prior to further implementation of this technique, its accuracy in measuring CSF velocity magnitude and distribution must be evaluated. In this study, an MR-compatible experimental platform was developed based on an anatomically detailed 3D printed model of the cervical subarachnoid space and subject specific flow boundary conditions. Accuracy of 4D Flow measurements was assessed by comparison of CSF velocities obtained within the in vitro model with the numerically predicted velocities calculated from a spatially averaged computational fluid dynamics (CFD) model based on the same geometry and flow boundary conditions. Good agreement was observed between CFD and 4D Flow in terms of spatial distribution and peak magnitude of through-plane velocities with an average difference of 7.5 and 10.6% for peak systolic and diastolic velocities, respectively. Regression analysis showed lower accuracy of 4D Flow measurement at the timeframes corresponding to low CSF flow rate and poor correlation between CFD and 4D Flow in-plane velocities.