Doctor of Philosophy

dissertationDiffusion tensor MRI (DT-MRI or DTI) has been proven useful for characterizing biological tissue microstructure, with the majority of DTI studies having been performed previously in the brain. Other studies have shown that changes in DTI parameters are detectable in the presence of cardiac pathology, recovery, and development, and provide insight into the microstructural mechanisms of these processes. However, the technical challenges of implementing cardiac DTI in vivo, including prohibitive scan times inherent to DTI and measuring small-scale diffusion in the beating heart, have limited its widespread usage. This research aims to address these technical challenges by: (1) formulating a model-based reconstruction algorithm to accurately estimate DTI parameters directly from fewer MRI measurements and (2) designing novel diffusion encoding MRI pulse sequences that compensate for the higher-order motion of the beating heart. The model-based reconstruction method was tested on undersampled DTI data and its performance was compared against other state-of-the-art reconstruction algorithms. Model-based reconstruction was shown to produce DTI parameter maps with less blurring and noise and to estimate global DTI parameters more accurately than alternative methods. Through numerical simulations and experimental demonstrations in live rats, higher-order motion compensated diffusion-encoding was shown to successfully eliminate signal loss due to motion, which in turn produced data of sufficient quality to accurately estimate DTI parameters, such as fiber helix angle. Ultimately, the model-based reconstruction and higher-order motion compensation methods were combined to characterize changes in the cardiac microstructure in a rat model with inducible arterial hypertension in order to demonstrate the ability of cardiac DTI to detect pathological changes in living myocardium

A low cost asynchronous eye diagram reconstruction system for high speed links

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 97-98).As link communication data rate increases, there is an increasing need for a more cost eective way to test and monitor signal integrity in link communication systems. Specifically, eye diagrams are valuable visual aids to analyze and quantify digital signal quality. This thesis presents a novel low cost eye diagram reconstruction system using asynchronous undersampling technique, which solves a key problem in performance monitoring in systems where synchronous sampling is not available, such as video switches. Existing works are studied and compared to this work in performance and cost. The proposed system is designed as a system-on-chip (SOC) and contains an undersampling ADC, aliased frequency estimator and a simple reconstruction algorithm. Major building blocks are implemented and simulated in 65nm CMOS process. Extensive system level analysis and simulations demonstrate functionality and performance of the system working at 10Gb/s maximum data rate.by Shijie Zheng.M. Eng

Magnetic Resonance Imaging of Short-T2 Tissues with Applications for Quantifying Cortical Bone Water and Myelin

The human body contains a variety of tissue species with short T2 ranging from a few microseconds to hundreds of microseconds. Detection and quantification of these short-T2 species is of considerable clinical and scientific interest. Cortical bone water and myelin are two of the most important tissue constituents. Quantification of cortical bone water concentration allows for indirect estimation of bone pore volume and noninvasive assessment of bone quality. Myelin is essential for the proper functioning of the central nervous system (CNS). Direct assessment of myelin would reveal CNS abnormalities and enhance our understanding of neurological diseases. However, conventional MRI with echo times of several milliseconds or longer is unable to detect these short-lived MR signals. Recent advances in MRI technology and hardware have enabled development of a number of short-T2 imaging techniques, key among which are ultra-short echo time (UTE) imaging, zero echo time (ZTE) imaging, and sweep imaging with Fourier transform (SWIFT). While these pulse sequences are able to detect short-T2 species, they still suffer from signal interference between different T2 tissue constituents, image artifacts and excessive scan time. These are primary technical hurdles for application to whole-body clinical scanners. In this thesis research, new MRI techniques for improving short-T2 tissue imaging have been developed to address these challenges with a focus on direct detection and quantification of cortical bone water and myelin on a clinical MRI scanner. The first focus of this research was to optimize long-T2 suppression in UTE imaging. Saturation and adiabatic RF pulses were designed to achieve maximum long-T2 suppression while maximizing the signal from short-T2 species. The imaging protocols were optimized by Bloch equation simulations and were validated using phantom and in vivo experiments. The results show excellent short-T2 contrast with these optimized pulse sequences. The problem of blurring artifacts resulting from the inhomogeneous excitation profile of the rectangular pulses in ZTE imaging was addressed. The proposed approach involves quadratic phase-modulated RF excitation and iterative solution of an inverse problem formulated from the signal model of ZTE imaging and is shown to effectively remove the image artifacts. Subsequently image acquisition efficiency was improved in order to attain clinically-feasible scan times. To accelerate the acquisition speed in UTE and ZTE imaging, compressed sensing was applied with a hybrid 3D UTE sequence. Further, the pulse sequence and reconstruction procedure were modified to enable anisotropic field-of-view shape conforming to the geometry of the elongated imaged object. These enhanced acquisition techniques were applied to the detection and quantification of cortical bone water. A new biomarker, the suppression ratio (a ratio image derived from two UTE images, one without and the other with long-T2 suppression), was conceived as a surrogate measure of cortical bone porosity. Experimental data suggest the suppression ratio may be a more direct measure of porosity than previously measured total bone water concentration. Lastly, the feasibility of directly detecting and quantifying spatially-resolved myelin concentration with a clinical imager was explored, both theoretically and experimentally. Bloch equation simulations were conducted to investigate the intrinsic image resolution and the fraction of detectable myelin signal under current scanner hardware constraints. The feasibility of quantitative ZTE imaging of myelin extract and lamb spinal cord at 3T was demonstrated. The technological advances achieved in this dissertation research may facilitate translation of short-T2 MRI methods from the laboratory to the clinic

Advanced methods for mapping the radiofrequency magnetic fields in MRI

As MRI systems have increased in static magnetic field strength, the radiofrequency (RF) fields that are used for magnetisation excitation and signal reception have become significantly less uniform. This can lead to image artifacts and errors when performing quantitative MRI. A further complication arises if the RF fields vary substantially in time. In the first part of this investigation temporal variations caused by respiration were explored on a 3T scanner. It was found that fractional changes in transmit field amplitude between inhalation and expiration ranged from 1% to 14% in the region of the liver in a small group of normal subjects. This observation motivated the development of a pulse sequence and reconstruction method to allow dynamic observation of the transmit field throughout the respiratory cycle. However, the proposed method was unsuccessful due to the inherently time-consuming nature of transmit field mapping sequences. This prompted the development of a novel data reconstruction method to allow the acceleration of transmit field mapping sequences. The proposed technique posed the RF field reconstruction as a nonlinear least-squares optimisation problem, exploiting the fact that the fields vary smoothly. It was shown that this approach was superior to standard reconstruction approaches. The final component of this thesis presents a unified approach to RF field calibration. The proposed method uses all measured data to estimate both transmit and receive sensitivities, whilst simultaneously insisting that they are smooth functions of space. The resulting maps are robust to both noise and imperfections in regions of low signal

Signal Processing in Wireless Communications: Device Fingerprinting and Wide-Band Interference Rejection

The rapid progress of wireless communication technologies that has taken place in recent years has significantly improved the quality of everyday life. However with this expansion of wireless communication systems come significant security threats and significant technological challenges, both of which are due to the fact that the communication medium is shared. The ubiquity of open wireless Internet access networks creates a new avenue for cyber-criminals to impersonate and act in an unauthorized way. The increasing number of deployed wide-band wireless communication systems entails technological challenges for effective utilization of the shared medium, which implies the need for advanced interference rejection methods. Wireless security and interference rejection in wide-band wireless communications are therefore often considered as the two main challenges in wireless network\u27s design and research. Important aspects of these challenges are illuminated and addressed in this dissertation. This dissertation considers signal processing approaches for exploiting or mitigating the effects of non-ideal components in wireless communication systems. In the first part of the dissertation, we introduce and study a novel, model-based approach to wireless device identification that exploits imperfections in the transmitter caused by manufacturing process nonidealities. Previous approaches to device identification based on hardware imperfections vary from transient analysis to machine learning but have not provided verifiable accuracy. Here, we detail a model-based approach, that uses statistical models of RF transmitter components: digital-to-analog converter, power amplifier and RF oscillator, which are amenable for analysis. Our proposed approach examines the key device characteristics that cause anonymity loss, countermeasures that can be applied by the nodes to regain the anonymity, and ways of thwarting such countermeasures. We develop identification algorithms based on statistical signal processing methods and address the challenging scenario when the units that need to be distinguished from one another are of the same model and from the same manufacturer. Using simulations and measurements of components that are commonly used in commercial communications systems, we show that our anonymity breaking techniques are effective. In the second part of the dissertation, we consider innovative approaches for the acquisition of frequency-sparse signals with wide-band receivers when a weak signal of interest is received in the presence of a very strong interference, and the effects of the nonlinearities in the low-noise amplifier at the receiver must be mitigated. All samples with amplitude above a given threshold, dictated by the linear input range of the receiver, are discarded to avoid the distortion caused by saturation of the low noise amplifier. Such a sampling scheme, while avoiding nonlinear distortion that cannot be corrected in the digital domain, poses challenges for signal reconstruction techniques, as the samples are taken non-uniformly, but also non-randomly. The considered approaches fall into the field of compressive sensing (CS); however, what differentiates them from conventional CS is that a structure is forced upon the measurement scheme. Such a structure causes a violation of the core CS assumption of the measurements\u27 randomness. We consider two different types of structured acquisition: signal independent and signal dependent structured acquisition. For the first case, we derive bounds on the number of samples needed for successful CS recovery when samples are drawn at random in predefined groups. For the second case, we consider enhancements of CS recovery methods when only small-amplitude samples of the signal that needs to be recovered are available for the recovery. Finally, we address a problem of spectral leakage due to the limited processing block size of block processing, wide-band receivers and propose an adaptive block size adjustment method, which leads to significant dynamic range improvements

Robust Algorithms for Unattended Monitoring of Cardiovascular Health

Cardiovascular disease is the leading cause of death in the United States. Tracking daily changes in one’s cardiovascular health can be critical in diagnosing and managing cardiovascular disease, such as heart failure and hypertension. A toilet seat is the ideal device for monitoring parameters relating to a subject’s cardiac health in his or her home, because it is used consistently and requires no change in daily habit. The present work demonstrates the ability to accurately capture clinically relevant ECG metrics, pulse transit time based blood pressures, and other parameters across subjects and physiological states using a toilet seat-based cardiovascular monitoring system, enabled through advanced signal processing algorithms and techniques. The algorithms described herein have been designed for use with noisy physiologic signals measured at non-standard locations. A key component of these algorithms is the classification of signal quality, which allows automatic rejection of noisy segments before feature delineation and interval extractions. The present delineation algorithms have been designed to work on poor quality signals while maintaining the highest possible temporal resolution. When validated on standard databases, the custom QRS delineation algorithm has best-in-class sensitivity and precision, while the photoplethysmogram delineation algorithm has best-in-class temporal resolution. Human subject testing on normative and heart failure subjects is used to evaluate the efficacy of the proposed monitoring system and algorithms. Results show that the accuracy of the measured heart rate and blood pressure are well within the limits of AAMI standards. For the first time, a single device is capable of monitoring long-term trends in these parameters while facilitating daily measurements that are taken at rest, prior to the consumption of food and stimulants, and at consistent times each day. This system has the potential to revolutionize in-home cardiovascular monitoring

Steady-state anatomical and quantitative magnetic resonance imaging of the heart using RF-frequencymodulated techniques

Cardiovascular disease (CVD) is the leading cause of death in the United States and Europe and generates healthcare costs of hundreds of billions of dollars annually. Conventional methods of diagnosing CVD are often invasive and carry risks for the patient. For example, the gold standard for diagnosing coronary artery disease, a major class of CVD, is x-ray coronary angiography, which has the disadvantages of being invasive, being expensive, using ionizing radiation, and having a ris k of complications. Conversely, coronary MR angiography (MRA) does not use ionizing radiation, can effectively visualize tissues without the need for exogenous contrast agents, and benefits from an adaptable temporal resolution. However, the acquisition time of cardiac MRI is far longer than the temporal scales of cardiac and respiratory motion, necessitating some method of compensating for this motion. The free-running framework is a novel development in our lab, benefitting from advances over the past three decades, that attempts to address disadvantages of previous cardiac MRI approaches: it provides fully self-gated 5D cardiac MRI with a simplified workflow, improved ease-of-use, reduced operator dependence, and automatic patient-specific motion detection. Free-running imaging increases the amount of information available to the clinician and is flexible enough to be translated to different app lications within cardiac MRI. Moreover, the self-gating of the free-running framework decoupled the acquisition from the motion compensation and thereby opened up cardiac MRI to the wider class of steady-state-based techniques utilizing balanced steady-state free precession (bSSFP) sequences, which have the benefits of practical simplicity and high signal-to-noise ratio. The focus of this thesis was therefore on the application of steady- state techniques to cardiac MRI. The first part addressed the long acquisition time of the current free-running framework and focused on anatomical coronary imaging. The published protocol of the free- running framework used an interrupted bSSFP acquisition where CHESS fat saturation modules were inserted to provide blood-fat contrast, as they suppress the signal of fat tissue surrounding the coronary arteries, and were followed by ramp-up pulses to reduce artefacts arising from the return to steady-state. This interrupted acquisition, however, suffered from an interrupted steady-state, reduced time efficiency, and higher specific absorption rate (SAR). Using novel lipid-insensitive binomial off-resonant RF excitation (LIBRE) pulses developed in our lab, the first project showed that LIBRE pulses incorporated into an uninterrupted free-running bSSFP sequence could be successfully used for 5D cardiac MRI at 1.5T. The free-running LIBRE approach reduced the acquisition time and SAR relative to the previous interrupted approach while maintaining image quality and vessel conspicuity. Furthermore, this had been the first successful use of a fat-suppressing RF excitation pulse in an uninterrupted bSSFP sequence for cardiac imaging, demonstrating that uninterrupted bSSFP can be used for cardiac MRI and addressing the problem of clinical sequence availability. Inspired by the feasibility of uninterrupted bSSFP for cardiac MRI, the second part investigated the potential of PLANET, a novel 3D multiparametric mapping technique, for free-running 5D myocardial mapping. PLANET utilizes a phase-cycled bSSFP acquisition and a direct ellipse-fitting algorithm to calculate T1 and T2 relaxation times, which suggested that it could be readily integrated into the free-running framework without interrupting the steady-state. After initially calibrating the acquisition, the possibility of accelerating the static PLANET acquisition was explored prior to applying it to the moving heart. It was shown that PLANET accuracy and precision could be maintained with two-fold acceleration with a 3D Cartesian spiral trajectory, suggesting that PLANET for myocardial mapping with the free-running 5D radial acquisition is feasible. Further work should investigate optimizing the reconstruction scheme, improving the coil sensitivity estimate, and examining the use of the radial trajectory with a view to implementing free-running 5D myocardial T1 and T2 mapping. This thesis presents two approaches utilizing RF-frequency-modulated steady-state techniques for cardiac MRI. The first approach involved the novel application of an uninterrupted bSSFP acquisition with off-resonant RF excitation for anatomical coronary imaging. The second approach investigated the use of phase-cycled bSSFP for free-running 5D myocardial T1 and T2 mapping. Both methods addressed the challenge of clinical availability of sequences in cardiac MRI, by showing that a common and simple sequence like bSSFP can be used for acquisition while the steps of motion compensation and reconstruction can be handled offline, and thus have the potential to improve adoption of cardiac MRI. -- Les maladies cardiovasculaires (MCV) représentent la principale cause de décès aux États-Unis et en Europe et génèrent des coûts de santé de plusieurs centaines de milliards de dollars par an. Les méthodes conventionnelles de diagnostic des MCV sont souvent invasives et comportent des risques pour le patient. Par exemple, la méthode de référence pour le diagnostic de la maladie coronarienne, une catégorie majeure de MCV, est la coronarographie par rayons X qui a comme inconvénients son caractère invasif, son coût, l’utilisation de rayonnements ionisants et le risque de complications. A l’inverse, l'angiographie coronarienne par résonance magnétique (ARM) n'utilise pas de rayonnements ionisants, permet de visualiser efficacement les tissus sans avoir recours à des agents de contraste exogènes et bénéficie d'une résolution temporelle ajustable. Cependant, le temps d'acquisition en IRM cardiaque est bien plus long que les échelles temporelles des mouvements cardiaques et respiratoires en jeu, ce qui rend la compensation de ces mouvements indispensable. Le cadre dit de « free -running » est un nouveau développement de notre laboratoire qui bénéficie des progrès réalisés au cours des trois dernières décennies et tente de remédier aux inconvénients des approches précédentes pour l'IRM cardiaque : il fournit une IRM cardiaque en cinq dimensions (5D) complètement « self-gated » , c’est-à-dire capable de détecter les mouvements cardiaques et respiratoires, forte d’une implémentation simplifiée, d’une plus grande facilité d'utilisation, d’une dépendance réduite vis-à-vis de l'opérateur et d’une détection automatique des mouvements spécifiques du patient. L'imagerie « free- running » augmente la quantité d'informations à disposition du clinicien et est suffisamment flexible pour être appliquée à différents domaines de l'IRM cardiaque. De plus, le « self-gating » du cadre « free-running » a découplé l'acquisition de la compensation de mouvement et a ainsi ouvert l'IRM cardiaque à la classe plus large des techniques basées sur l'état stationnaire utilisant des séquences de précession libre équilibrée en état stationnaire (bSSFP), qui se distinguent par leur simplicité d’utilisation et leur rapport signal sur bruit élevé. Le thème de cette thèse est donc l'application des techniques basées sur l'état stationnaire à l'IRM cardiaque. La première partie porte sur le long temps d'acquisition de l'actuel cadre « free-running» et se concentre sur l'imagerie anatomique coronaire. Le protocole publié utilise une acquisition bSSFP interrompue où des modules de saturation de graisse (CHESS) sont insérés de façon à fournir un contraste sang-graisse puisqu’ils suppriment le signal du tissu graisseux entourant les artères coronaires, et sont suivis par des impulsions en rampe pour réduire les artefacts résultant du retour à l'état stable. Cette acquisition interrompue souffre cependant d'un état d'équilibre interrompu, d'une efficacité temporelle réduite et d'un débit d'absorption spécifique (DAS) plus élevé. En utilisant les nouvelles impulsions d'excitation radiofréquence (RF) binomiales hors -résonance insensibles aux lipides (LIBRE) développées dans notre laboratoi re, ce premier projet montre que les impulsions LIBRE incorporées dans une séquence bSSFP ininterrompue et « free-running » peuvent être utilisées avec succès pour l'IRM cardiaque 5D à 1,5 T. L'approche « free-running LIBRE » permet de réduire le temps d'acquisition et le DAS par rapport à l'approche interrompue précédente, tout en maintenant la perceptibilité des artères coronariennes. En outre, il s'agit de la première utilisation réussie d'une impulsion d'excitation RF supprimant la graisse dans une séquence bSSFP ininterrompue pour l'imagerie cardiaque, ce qui démontre le potentiel d’utilisation de la séquence bSSFP ininterrompue pour l'IRM cardiaque et résout le problème de la disponibilité de la séquence en clinique. Inspirée par la faisabilité d’utilisation de la séquence bSSFP ininterrompue pour l'IRM cardiaque, la deuxième partie étudie le potentiel de PLANET, une nouvelle technique de cartographie 3D multiparamétrique, pour la cartographie 5D du myocarde via l’imagerie « free-running ». PLANET utilise une acquisition bSSFP à cycle de phase et un algorithme d'ajustement d'ellipse direct pour calculer les temps de relaxation T1 et T2, ce qui suggère que cette méthode pourrait être facilement intégrée au cadre « free - running » sans interruption de l’état d'équilibre. Après calibration de l'acquisition, nous explorons la possibilité d'accélérer l'acquisition statique de PLANET pour l'appliquer au cœur. Nous démontrons que l'exactitude et la précision de PLANET peuvent être maintenues pour une accélération double avec une trajectoire 3D cartésienne en spirale, ce qui suggère que PLANET est réalisable pour la cartographie du myocarde avec une acquisition radiale 5D « free-running ». D'autres travaux devraient porter sur l'optimisation du schéma de reconstruction, l'amélioration de l'estimation de la sensibilité de l’antenne et l'examen de l'utilisation de la trajectoire radiale en vue de la mise en œuvre de la cartographie 5D « free-running » T1 et T2 du myocarde. Cette thèse présente deux approches utilisant des techniques de modulation de fréquence radio en état stationnaire pour l'IRM cardiaque. La première approche implique l'application nouvelle d'une acquisition bSSFP ininterrompue avec une excitation RF hors résonance pour l'imagerie anatomique coronaire. La seconde approche porte sur l'utilisation d’une séquence bSSFP à cycle de phase pour la cartographie 5D T1 et T2 du myocarde. Ces deux méthodes permettent de répondre au défi posé par la disponibilité des séquences en IRM cardiaque en montrant qu'une séquence commune et simple comme la bSSFP peut être utilisée pour l'acquisition, tandis que les étapes de compensation du mouvement et de reconstruction peuvent être traitées hors ligne. Ainsi, ces méthodes ont le potentiel de favoriser l'adoption de l'IRM cardiaque