POCS-based reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE): A general algorithm for reducing motion-related artifacts.

PURPOSE: A projection onto convex sets reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE) is developed to reduce motion-related artifacts, including respiration artifacts in abdominal imaging and aliasing artifacts in interleaved diffusion-weighted imaging. THEORY: Images with reduced artifacts are reconstructed with an iterative projection onto convex sets (POCS) procedure that uses the coil sensitivity profile as a constraint. This method can be applied to data obtained with different pulse sequences and k-space trajectories. In addition, various constraints can be incorporated to stabilize the reconstruction of ill-conditioned matrices. METHODS: The POCSMUSE technique was applied to abdominal fast spin-echo imaging data, and its effectiveness in respiratory-triggered scans was evaluated. The POCSMUSE method was also applied to reduce aliasing artifacts due to shot-to-shot phase variations in interleaved diffusion-weighted imaging data corresponding to different k-space trajectories and matrix condition numbers. RESULTS: Experimental results show that the POCSMUSE technique can effectively reduce motion-related artifacts in data obtained with different pulse sequences, k-space trajectories and contrasts. CONCLUSION: POCSMUSE is a general post-processing algorithm for reduction of motion-related artifacts. It is compatible with different pulse sequences, and can also be used to further reduce residual artifacts in data produced by existing motion artifact reduction methods

Comparison of TGSE-BLADE DWI, RESOLVE DWI, and SS-EPI DWI in healthy volunteers and patients after cerebral aneurysm clipping

Diffusion-weighted magnetic resonance imaging is prone to have susceptibility artifacts in an inhomogeneous magnetic field. We compared distortion and artifacts among three diffusion acquisition techniques (single-shot echo-planar imaging [SS-EPI DWI], readout-segmented EPI [RESOLVE DWI], and 2D turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory [TGSE-BLADE DWI]) in healthy volunteers and in patients with a cerebral aneurysm clip. Seventeen healthy volunteers and 20 patients who had undergone surgical cerebral aneurysm clipping were prospectively enrolled. SS-EPI DWI, RESOLVE DWI, and TGSE-BLADE DWI of the brain were performed using 3 T scanners. Distortion was the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI near air–bone interfaces in healthy volunteers (P < 0.001). Length of clip-induced artifact and distortion near the metal clip were the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI (P < 0.01). Image quality scores for geometric distortion, susceptibility artifacts, and overall image quality in both healthy volunteers and patients were the best in TGSE-BLADE DWI, and better in RESOLVE DWI than SS-EPI DWI (P < 0.001). Among the three DWI sequences, image quality was the best in TGSE-BLADE DWI in terms of distortion and artifacts, in both healthy volunteers and patients with an aneurysm clip

Regularized joint water-fat separation with B-0 map estimation in image space for 2D-navigated interleaved EPI based diffusion MRI

Purpose To develop a new water-fat separation and B-0 estimation algorithm to effectively suppress the multiple resonances of fat signal in EPI. This is especially relevant for DWI where fat is often a confounding factor. Methods Water-fat separation based on chemical-shift encoding enables robust fat suppression in routine MRI. However, for EPI the different chemical-shift displacements of the multiple fat resonances along the phase-encoding direction can be problematic for conventional separation algorithms. This work proposes a suitable model approximation for EPI under B-0 and fat off-resonance effects, providing a feasible multi-peak water-fat separation algorithm. Simulations were performed to validate the algorithm. In vivo validation was performed in 6 volunteers, acquiring spin-echo EPI images in the leg (B-0 homogeneous) and head-neck (B-0 inhomogeneous) regions, using a TE-shifted interleaved EPI sequence with/without diffusion sensitization. The results are numerically and statistically compared with voxel-independent water-fat separation and fat saturation techniques to demonstrate the performance of the proposed algorithm. Results The reference separation algorithm without the proposed spatial shift correction caused water-fat ambiguities in simulations and in vivo experiments. Some spectrally selective fat saturation approaches also failed to suppress fat in regions with severe B-0 inhomogeneities. The proposed algorithm was able to achieve improved fat suppression for DWI data and ADC maps in the head-neck and leg regions. Conclusion The proposed algorithm shows improved suppression of the multi-peak fat components in multi-shot interleaved EPI applications compared to the conventional fat saturation approaches and separation algorithms.Neuro Imaging ResearchRadiolog

Hyper-fast NMR imaging

The work presented in this thesis was carried out in the Physics Department at the University of Nottingham between October 1988 and October 1991. It is the original work of the author except where indicated by reference. This thesis describes the continuation of the development of Echo Volumar Imaging (EVI) to facilitate snapshot imaging of a volume within the human body. Variants of the technique which have also been investigated include a spin echo version, SE-EVI, and a zoomed version ZEVI. All formats acquired data in a modulus fashion in times ranging from 64 ms to 120 ms. Hardware limitations have restricted the image matrix size to 64 x 32 x 8 voxels and prompted the employment of more efficient gradient driver circuitry. A multi-mode resonant gradient circuit is described for use in both Echo Planar Imaging (EPI) and EVI. The circuit behaves in an overall resonant manner but at a fixed number of discrete frequencies. By choosing the number of resonant modes, the circuit can be used to generate approximations to a square wave or trapezoidal waveform. Because of the energy conserving nature of the circuit design much faster current rise times can be achieved with a given amplifier and gradient coil. The multi-mode gradient driver circuit was utilized both for planar imaging and to investigate the effect of rapidly modulated magnetic fields on the human body. A simple neural stimulation model is used to evaluate the stimulation threshold current density for a variety of magnetically induced waveforms and for sinusoidal stimulation as a function of frequency. Experimental results correlate well with the model showing that for short times, contrary to the widely held view, neural stimulation is independent of the magnetic field switching rate dB / dt, but depends on the final magnetic field value

Analysis of first pass myocardial perfusion imaging with magnetic resonance

Early diagnosis and localisation of myocardial perfusion defects is an important step in the treatment of coronary artery disease. Thus far, coronary angiography is the conventional standard investigation for patients with known or suspected coronary artery disease and it provides information about the presence and location of coronary stenoses. In recent years, the development of myocardial perfusion CMR has extended the role of MR in the evaluation of ischaemic heart disease beyond the situations where there have already been gross myocardial changes such as acute infarction or scarring. The ability to non-invasively evaluate cardiac perfusion abnormalities before pathologic effects occur, or as follow-up to therapy, is important to the management of patients with coronary artery disease. Whilst limited multi-slice 2D CMR perfusion studies are gaining increased clinical usage for quantifying gross ischaemic burden, research is now directed towards complete 3D coverage of the myocardium for accurate localisation of the extent of possible defects. In 3D myocardial perfusion imaging, a complete volumetric data set has to be acquired for each cardiac cycle in order to study the first pass of the contrast bolus. This normally requires a relatively large acquisition window within each cardiac cycle to ensure a comprehensive coverage of the myocardium and reasonably high resolution of the images. With multi-slice imaging, long axis cardiac motion during this large acquisition window can cause the myocardium imaged in different cross- sections to be mis-registered, i.e., some part of the myocardium may be imaged more than twice whereas other parts may be missed out completely. This type of mis-registration is difficult to correct for by using post-processing techniques. The purpose of this thesis is to investigate techniques for tracking through plane motion during 3D myocardial perfusion imaging, and a novel technique for extracting intrinsic relationships between 3D cardiac deformation due to respiration and multiple ID real-time measurable surface intensity traces is developed. Despite the fact that these surface intensity traces can be strongly coupled with each other but poorly correlated with respiratory induced cardiac deformation, we demonstrate how they can be used to accurately predict cardiac motion through the extraction of latent variables of both the input and output of the model. The proposed method allows cross-modality reconstruction of patient specific models for dense motion field prediction, which after initial modelling can be use in real-time prospective motion tracking or correction. In CMR, new imaging sequences have significantly reduced the acquisition window whilst maintaining the desired spatial resolution. Further improvements in perfusion imaging will require the application of parallel imaging techniques or making full use of the information content of the ¿-space data. With this thesis, we have proposed RR-UNFOLD and RR-RIGR for significantly reducing the amount of data that is required to reconstruct the perfusion image series. The methods use prospective diaphragmatic navigator echoes to ensure UNFOLD and RIGR are carried out on a series of images that are spatially registered. An adaptive real-time re-binning algorithm is developed for the creation of static image sub-series related to different levels of respiratory motion. Issues concerning temporal smoothing of tracer kinetic signals and residual motion artefact are discussed, and we have provided a critical comparison of the relative merit and potential pitfalls of the two techniques. In addition to the technical and theoretical descriptions of the new methods developed, we have also provided in this thesis a detailed literature review of the current state-of-the-art in myocardial perfusion imaging and some of the key technical challenges involved. Issues concerning the basic background of myocardial ischaemia and its functional significance are discussed. Practical solutions to motion tracking during imaging, predictive motion modelling, tracer kinetic modelling, RR-UNFOLD and RR-RIGR are discussed, all with validation using patient and normal subject data to demonstrate both the strength and potential clinical value of the proposed techniques.Open acces

Blind Retrospective Motion Correction of MR Images

Die Bewegung des Patienten während einer MRI Untersuchung kann die Bildqualität stark verringern. Eine Verschiebung des abzubildenden Objektes von nur ein Paar Millimetern ist genug um Bewegungsartefakte zu erzeugen und der Scan unbrauchbar für die medizinische Diagnostik zu machen. Obwohl in den letzten 20 Jahren mehrere Verfahren entwickelt wurden, ist die Bewegungskorrektur immer noch ein ungelöstes Problem. Wir schlagen einen neuen retrospektiven Bewegungskorrekturalgorithmus vor, mit dem man die Qualität von 3D MR Bildern verbessern kann. Mit diesem Verfahren ist es möglich sowohl starre als auch nicht starre Körperbewegungen zu korrigieren. Der wichtigste Aspekt unserer Algorithmen ist, dass keine Informationen über die Bewegungstrajektorie, z. B. von Kameras, nötig sind um die Bewegungskorrektur durchzuführen. Unsere Verfahren verwenden die RAW-Dateien von normalen MRT-Sequenzen und brauchen keinerlei Anderungen im Scanablauf. Wir benutzen Grafikprozessoren um die Bewegungskorrektur zu beschleunigen – im Fall von starren Körperbewegungen sind nur wenige Sekunden erforderlich, bei nicht starrer Körperbewegung nur einige Minuten Unser Bewegungskorrekturalgorithmus für starre Körper basiert auf der Minimierung einer Kostenfunktion, die die objektive Qualit ̈at des korrigierten Bildes abschätzt. Die Hauptidee ist, durch Optimierung eine Bewegungstrajektorie zu finden, die den kleinsten Betrag der Kostenfunktion liefert. Wir verwenden die Entropie der Bildgradienten als Bildqualitätsfunktion. Um nicht starre Körperbewegungen zu korrigieren, erweitern wir unser mathematisches Modell von Bewegungseffekten. Wir approximieren nicht starre Körperbewegungen als mehrere lokale starre Körperbewegungen. Um solche Bewegungen zu korrigieren, entwickeln wir ein neues annealing-basiert Optimierungsverfahren. Während der Optimierung wechseln wir zwei Schritte ab - die Kostenfunktionsminimierung durch Bild- und Bewegungsparameter. Wir haben mehrere Simulationen sowie in vivo Versuche am Menschen durchgeführt – beide lieferten wesentliche Bildqualitätsverbesserungen