Multi-component MRI transverse-relaxation parameter estimation to detect and monitor neuromuscular disease

We aimed to optimise the estimation of skeletal muscle-water spin-spin relaxation time (T2m), and fat fraction estimated from multi-echo MRI, as potential biomarkers, by accounting for instrumental factors such as B1 errors, non-Gaussian noise and non-ideal echo train evolution. A multi-component slice-profile-compensated extended phase graph (sEPG) model for multi-echo Carr-Purcell-Meiboom-Gill (CPMG) spin-echo sequence signals was implemented, modelling the fat signal as two empirically calibrated sEPG components with fixed parameters, and the remaining unknown parameters (B1 field factor, T2m, fat fraction (ffa), global amplitude and Rician noise SD) determined by maximum likelihood estimation. After validation using a calibrated test object the algorithm was used to analyse clinical muscle study data from patient groups with amyotrophic lateral sclerosis (ALS), Kennedy’s disease (KD) and Duchenne muscular dystrophy (DMD) and matched healthy controls. Parameter maps were generated using quality control steps to reject pixels failing fit quality or physical meaningfulness criteria. Muscle fat-fraction was also determined independently by 3-point Dixon MRI (ffd). In ALS and KD median T2m were significantly elevated compared with healthy controls in varied patterns and time courses, whereas it was decreased in DMD; other T2m distribution histogram metrics such as the skewness and full width at quarter maximum also differed significantly between patients and healthy volunteers. Quantitative comparison of ffa and ffd in the same muscles revealed a monotonic relationship deviating from linearity due to differing deviations from the assumed ideal signal behaviour in each method. Finally, the effects upon estimation accuracy and precision of practically realisable pulse sequence parameter choices were explored in simulations and with real data. Recommendations are presented for optimal choices. Clinically practical conventional CPMG sequences, combined with an appropriate signal model and parameter estimation method can provide robust T2m and ffa measures which change in disease and may sensitively reflect different aspects of neuromuscular pathology

Behind-wall target detection using micro-doppler effects

Abstract: During the last decade technology for seeing through walls and through dense vegetation has interested many researchers. This technology offers excellent opportunities for military and police applications, though applications are not limited to the military and police; they go beyond those applications to where detecting a target behind an obstacle is needed. To be able to disclose the location and velocity of obscured targets, scientists’ resort to electromagnetic wave propagation. Thus, through-the-wall radar (TWR) is technology used to propagate electromagnetic waves towards a target through a wall. Though TWR is a promising technology, it has been reported that TWR imaging (TWRI) poses a range of ambiguities in target characterisation and detection. These ambiguities are related to the thickness and electric properties of walls. It has been reported that the mechanical and electric properties of the wall defocus the target image rendered by the radar. The defocusing problem is the phenomenon of displacing the target away from its true location when the image is rendered. Thus, the operator of the TWR will have a wrong position, not the real position of the target. Defocusing is not the only problem observed while the signal is travelling through the wall. Target classification, wall modelling and others are areas that need investigation...D.Ing. (Electrical and Electronic Engineering

Non-selective Refocusing Pulse Design in Parallel Transmission for Magnetic Resonance Imaging of the Human Brain at Ultra High Field

In Magnetic Resonance Imaging (MRI), the increase of the static magnetic field strength is used to provide in theory a higher signal-to-noise ratio, thereby improving the overall image quality. The purpose of ultra-high-field MRI is to achieve a spatial image resolution sufficiently high to be able to distinguish structures so fine that they are currently impossible to view in a non-invasive manner. However, at such static magnetic fields strengths, the wavelength of the electromagnetic waves sent to flip the water proton spins is of the same order of magnitude than the scanned object. Interference wave phenomena are then observed, which are caused by the radiofrequency (RF) field inhomogeneity within the object. These generate signal and/or contrast artifacts in MR images, making their exploitation difficult, if not impossible, in certain areas of the body. It is therefore crucial to provide solutions to mitigate the non-uniformity of the spins excitation. Failing this, these imaging systems with very high fields will not reach their full potential.For relevant high field clinical diagnosis, it is therefore necessary to create RF pulses homogenizing the excitation of all spins (here of the human brain), and optimized for each individual to be imaged. For this, an 8-channel parallel transmission system (pTX) was installed in our 7 Tesla scanner. While most clinical MRI systems only use a single transmission channel, the pTX extension allows to simultaneously playing various forms of RF pulses on all channels. The resulting sum of the interference must be optimized in order to reduce the non-uniformity typically seen.The objective of this thesis is to synthesize this type of tailored RF pulses, using parallel transmission. These pulses will have as an additional constraint the compliance with the international exposure limits for radiofrequency exposure, which induces a temperature rise in the tissue. In this sense, many electromagnetic and temperature simulations were carried out as an introduction of this thesis, in order to assess the relationship between the recommended RF exposure limits and the temperature rise actually predicted in tissues.This thesis focuses specifically on the design of all RF refocusing pulses used in non-selective MRI sequences based on the spin-echo. Initially, only one RF pulse was generated for a simple application: the reversal of spin dephasing in the transverse plane, as part of a classic spin echo sequence. In a second time, sequences with very long refocusing echo train applied to in vivo imaging are considered. In all cases, the mathematical operator acting on the magnetization, and not its final state as is done conventionally, is optimized. The gain in high field imaging is clearly visible, as the necessary mathematical operations (that is to say, the rotation of the spins) are performed with a much greater fidelity than with the methods of the state of the art. For this, the generation of RF pulses is combining a k-space-based spin excitation method, the kT-points, and an optimization algorithm, called Gradient Ascent Pulse Engineering (GRAPE), using optimal control.This design is relatively fast thanks to analytical calculations rather than finite difference methods. The inclusion of a large number of parameters requires the use of GPUs (Graphics Processing Units) to achieve computation times compatible with clinical examinations. This method of designing RF pulses has been experimentally validated successfully on the NeuroSpin 7 Tesla scanner, with a cohort of healthy volunteers. An imaging protocol was developed to assess the image quality improvement using these RF pulses compared to typically used non-optimized RF pulses. All methodological developments made during this thesis have contributed to improve the performance of ultra-high-field MRI in NeuroSpin, while increasing the number of MRI sequences compatible with parallel transmission.En Imagerie par Résonance Magnétique (IRM), l’augmentation du champ magnétique statique permet en théorie de fournir un rapport signal sur bruit accru, améliorant la qualité des images. L’objectif de l’IRM à ultra haut champ est d’atteindre une résolution spatiale suffisamment haute pour pouvoir distinguer des structures si fines qu’elles sont actuellement impossibles à visualiser de façon non-invasive. Cependant, à de telles valeurs de champs magnétiques, la longueur d’onde du rayonnement électromagnétique envoyé pour basculer les spins des protons de l’eau est du même ordre de grandeur que l’objet dont on souhaite faire l’image. Des phénomènes d’interférences sont observés, ce qui se traduit par l’inhomogénéité de ce champ radiofréquence (RF) au sein de l’objet. Ces interférences engendrent des artefacts de signal et/ou de contraste dans les images IRM, et rendent ainsi leur exploitation délicate. Il est donc crucial de fournir des solutions pour atténuer la non-uniformité de l’excitation des spins, à défaut de quoi de tels systèmes ne pourront atteindre leurs pleins potentiels. Pour obtenir des diagnostics pertinents à très haut champ, il est donc nécessaire de créer des impulsions RF homogénéisant l'excitation de l'ensemble des spins (ici du cerveau humain), optimisées pour chaque individu. Pour cela, un système de transmission parallèle (pTX) à 8 canaux a été installé au sein de notre imageur à 7 Tesla. Alors que la plupart des systèmes IRM cliniques n’utilisent qu’un seul canal d’émission, l’extension pTX permet de jouer différentes formes d’impulsions RF de concert. La somme résultante de ces interférences doit alors être optimisée pour atténuer la non-uniformité observée classiquement. L’objectif de cette thèse est donc de synthétiser ce type d’impulsions, en utilisant la pTX. Ces impulsions auront pour contrainte supplémentaire le respect des limitations internationales concernant l'exposition à des champs radiofréquence, qui induit une hausse de température dans les tissus. En ce sens, de nombreuses simulations électromagnétiques et de températures ont été réalisées en introduction de cette thèse, afin d’évaluer la relation entre les seuils recommandés d’exposition RF et l’élévation de température prédite dans les tissus. Cette thèse porte plus spécifiquement sur la conception de l’ensemble des impulsions RF refocalisantes utilisées dans des séquences IRM non-sélectives, basées sur l’écho de spin. Dans un premier temps, seule une impulsion RF a été générée, pour une application simple : l’inversion du déphasage des spins dans le plan transverse. Dans un deuxième temps, sont considérées les séquences à long train d’échos de refocalisation appliquées à l’in vivo. Ici, l’opérateur mathématique agissant sur la magnétisation, et non pas son état final comme il est fait classiquement, est optimisé. Le gain en imagerie à très haut champ est clairement visible puisque les opérations mathématiques (la rotation des spins) voulues sont réalisées avec plus de fidélité que dans le cadre des méthodes de l’état de l’art. Pour cela, la génération de ces impulsions RF combine une méthode d’excitation des spins avec navigation dans l’espace de Fourier, les kT-points, et un algorithme d’optimisation, appelé Gradient Ascent Pulse Engineering (GRAPE), utilisant le contrôle optimal. Cette conception est rapide grâce à des calculs analytiques plus directs que des méthodes de différences finies. La prise en compte d’un grand nombre de paramètres nécessite l’usage de GPUs (Graphics Processing Units) pour atteindre des temps de calcul compatibles avec un examen clinique. Cette méthode de conception d’impulsions RF a été validée expérimentalement sur l’imageur 7 Tesla de NeuroSpin, sur une cohorte de volontaires sains

Motion robust acquisition and reconstruction of quantitative T2* maps in the developing brain

The goal of the research presented in this thesis was to develop methods for quantitative T2* mapping of the developing brain. Brain maturation in the early period of life involves complex structural and physiological changes caused by synaptogenesis, myelination and growth of cells. Molecular structures and biological processes give rise to varying levels of T2* relaxation time, which is an inherent contrast mechanism in magnetic resonance imaging. The knowledge of T2* relaxation times in the brain can thus help with evaluation of pathology by establishing its normative values in the key areas of the brain. T2* relaxation values are a valuable biomarker for myelin microstructure and iron concentration, as well as an important guide towards achievement of optimal fMRI contrast. However, fetal MR imaging is a significant step up from neonatal or adult MR imaging due to the complexity of the acquisition and reconstruction techniques that are required to provide high quality artifact-free images in the presence of maternal respiration and unpredictable fetal motion. The first contribution of this thesis, described in Chapter 4, presents a novel acquisition method for measurement of fetal brain T2* values. At the time of publication, this was the first study of fetal brain T2* values. Single shot multi-echo gradient echo EPI was proposed as a rapid method for measuring fetal T2* values by effectively freezing intra-slice motion. The study concluded that fetal T2* values are higher than those previously reported for pre-term neonates and decline with a consistent trend across gestational age. The data also suggested that longer than usual echo times or direct T2* measurement should be considered when performing fetal fMRI in order to reach optimal BOLD sensitivity. For the second contribution, described in Chapter 5, measurements were extended to a higher field strength of 3T and reported, for the first time, both for fetal and neonatal subjects at this field strength. The technical contribution of this work is a fully automatic segmentation framework that propagates brain tissue labels onto the acquired T2* maps without the need for manual intervention. The third contribution, described in Chapter 6, proposed a new method for performing 3D fetal brain reconstruction where the available data is sparse and is therefore limited in the use of current state of the art techniques for 3D brain reconstruction in the presence of motion. To enable a high resolution reconstruction, a generative adversarial network was trained to perform image to image translation between T2 weighted and T2* weighted data. Translated images could then be served as a prior for slice alignment and super resolution reconstruction of 3D brain image.Open Acces

Novel computational methods for in vitro and in situ cryo-electron microscopy

Over the past decade, advances in microscope hardware and image data processing algorithms have made cryo-electron microscopy (cryo-EM) a dominant technique for protein structure determination. Near-atomic resolution can now be obtained for many challenging in vitro samples using single-particle analysis (SPA), while sub-tomogram averaging (STA) can obtain sub-nanometer resolution for large protein complexes in a crowded cellular environment. Reaching high resolution requires large amounts of im-age data. Modern transmission electron microscopes (TEMs) automate the acquisition process and can acquire thousands of micrographs or hundreds of tomographic tilt se-ries over several days without intervention. In a first step, the data must be pre-processed: Micrographs acquired as movies are cor-rected for stage and beam-induced motion. For tilt series, additional alignment of all micrographs in 3D is performed using gold- or patch-based fiducials. Parameters of the contrast-transfer function (CTF) are estimated to enable its reversal during SPA refine-ment. Finally, individual protein particles must be located and extracted from the aligned micrographs. Current pre-processing algorithms, especially those for particle picking, are not robust enough to enable fully unsupervised operation. Thus, pre-processing is start-ed after data collection, and takes several days due to the amount of supervision re-quired. Pre-processing the data in parallel to acquisition with more robust algorithms would save time and allow to discover bad samples and microscope settings early on. Warp is a new software for cryo-EM data pre-processing. It implements new algorithms for motion correction, CTF estimation, tomogram reconstruction, as well as deep learn-ing-based approaches to particle picking and image denoising. The algorithms are more accurate and robust, enabling unsupervised operation. Warp integrates all pre-processing steps into a pipeline that is executed on-the-fly during data collection. Inte-grated with SPA tools, the pipeline can produce 2D and 3D classes less than an hour into data collection for favorable samples. Here I describe the implementation of the new algorithms, and evaluate them on various movie and tilt series data sets. I show that un-supervised pre-processing of a tilted influenza hemagglutinin trimer sample with Warp and refinement in cryoSPARC can improve previously published resolution from 3.9 Å to 3.2 Å. Warp’s algorithms operate in a reference-free manner to improve the image resolution at the pre-processing stage when no high-resolution maps are available for the particles yet. Once 3D maps have been refined, they can be used to go back to the raw data and perform reference-based refinement of sample motion and CTF in movies and tilt series. M is a new tool I developed to solve this task in a multi-particle framework. Instead of following the SPA assumption that every particle is single and independent, M models all particles in a field of view as parts of a large, physically connected multi-particle system. This allows M to optimize hyper-parameters of the system, such as sample motion and deformation, or higher-order aberrations in the CTF. Because M models these effects accurately and optimizes all hyper-parameters simultaneously with particle alignments, it can surpass previous reference-based frame and tilt series alignment tools. Here I de-scribe the implementation of M, evaluate it on several data sets, and demonstrate that the new algorithms achieve equally high resolution with movie and tilt series data of the same sample. Most strikingly, the combination of Warp, RELION and M can resolve 70S ribosomes bound to an antibiotic at 3.5 Å inside vitrified Mycoplasma pneumoniae cells, marking a major advance in resolution for in situ imaging

Quantum computing using native interaction in superconducting circuits

Superconducting circuits form one of the most promising hardware platforms for building a quantum computer. As the quantum computing system gets more complex as we increase the size, employing simple circuit designs and control strategies can make the task of building a large scale quantum computer easier. This thesis describes a novel control strategy that utilises spin-echo techniques and native interaction in superconducting circuits, which reduces the cost of calibrating pulsed two-qubit gates. Spin-echo pulses are used to rescale the always-on Hamiltonian, and the timings of spin-echo pulses encode the effective coupling strengths. In collaboration with the NMR group in Oxford, two methods for scaling this technique to large numbers of qubits were explored. In the first approach, pulse sequences for an all-to-all coupled system are obtained numerically using linear programming, and it finds the time-optimal solution for up to twenty qubits and the near time-optimal solution for up to hundreds of qubits. Another approach based on graph colouring finds the near time-optimal pulse sequence analytically, allowing pulse sequences for any number of qubits. An idea based on the Hamiltonian rescaling technique was applied to implementing the variational quantum eigensolver algorithm and error mitigation on two superconducting qubits. In contrast to previous studies, the residual dispersive coupling between qubits was used for computation instead of regarding it as a source of error. Lastly, the detailed dynamics of the residual dispersive coupling in superconducting circuits were investigated to predict the practicality of spin-echo-based quantum computing on superconducting circuits. The Hamiltonian rescaling protocol assumes the always-on coupling to be diagonal, such as Ising Hamiltonian, but deviation from the pure Ising interaction was observed in the strongly coupled superconducting qubits. The origin of the deviation was identified analytically, and the circuit design criteria to suppress the deviation are presented