Determination of Lateral Modulation Apodization Functions Using a Regularized, Weighted Least Squares Estimation

Recently, work in this group has focused on the lateral cosine modulation method (LCM) which can be used for next-generation ultrasound (US) echo imaging and tissue displacement vector/strain tensor measurements (blood, soft tissues, etc.). For instance, in US echo imaging, a high lateral spatial resolution as well as a high axial spatial resolution can be obtained, and in tissue displacement vector measurements, accurate measurements of lateral tissue displacements as well as of axial tissue displacements can be realized. For an optimal determination of an apodization function for the LCM method, the regularized, weighted minimum-norm least squares (WMNLSs) estimation method is presented in this study. For designed Gaussian-type point spread functions (PSFs) with lateral modulation as an example, the regularized WMNLS estimation in simulations yields better approximations of the designed PSFs having wider lateral bandwidths than a Fraunhofer approximation and a singular-value decomposition (SVD). The usefulness of the regularized WMNLS estimation for the determination of apodization functions is demonstrated

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book

Acquisition strategies for fat/water separated MRI

This thesis focuses on new ways to more efficiently acquire the signal for fat/water separated MRI, also known as Dixon methods. In paper I, the concept of dual bandwidths was introduced to improve SNR efficiency by removing dead times in a spin echo PROPELLER sequence. By correcting for the displacement of fat, we were able to improve the motion correction. This required additional considerations during reconstruction in order to avoid noise amplification, which was solved with a noise-whitening Tikhonov regularization. Paper II explores the combination of fat/water separation in k-space with partially acquired data, i.e. partial Fourier sampling. With reduced sampling coverage comes the ability of increased spatial resolution, which is often limited in fat/water imaging, particularly in gradient echo sequences. A modified POCS routine was also developed with real-valued estimates, exploiting Hermitian symmetry to improve the inverse problem conditioning in the fully sampled region. A single-TR dual-bandwidth RARE (fast/turbo spin echo) sequence without dead times was developed in Paper III, which uses partial Fourier sampling with late and early echoes to improve the chemical shift encoding. The proposed sequence can acquire images with 0.5 mm in-plane resolution without dead times, with image quality exceeding current state-of-the-art techniques. An automated selection of gradient waveforms based on Cramér-Rao bounds was implemented on the scanner. In Paper IV, the dual-bandwidth concept was generalized to continuous bandwidths. Instead of the conventional shift of a trapezoidal readout gradient, we describe a new method of encoding chemical shift by using asymmetric readout waveforms. Asymmetric readouts were implemented in a RARE sequence to completely remove dead times from multi-TR acquisitions, with typical scan time reductions of 25 %. The developed methods enable fat/water imaging with reduced scan times and increased spatial resolution, which has previously limited their use

IMPROVED IMAGE QUALITY IN CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED INTERVENTIONS

In the past few decades, cone-beam computed tomography (CBCT) emerged as a rapidly developing imaging modality that provides single rotation 3D volumetric reconstruction with sub-millimeter spatial resolution. Compared to the conventional multi-detector CT (MDCT), CBCT exhibited a number of characteristics that are well suited to applications in image-guided interventions, including improved mechanical simplicity, higher portability, and lower cost. Although the current generation of CBCT has shown strong promise for high-resolution and high-contrast imaging (e.g., visualization of bone structures and surgical instrumentation), it is often believed that CBCT yields inferior contrast resolution compared to MDCT and is not suitable for soft-tissue imaging. Aiming at expanding the utility of CBCT in image-guided interventions, this dissertation concerns the development of advanced imaging systems and algorithms to tackle the challenges of soft-tissue contrast resolution. The presented material includes work encompassing: (i) a comprehensive simulation platform to generate realistic CBCT projections (e.g., as training data for deep learning approaches); (ii) a new projection domain statistical noise model to improve the noise-resolution tradeoff in model-based iterative reconstruction (MBIR); (iii) a novel method to avoid CBCT metal artifacts by optimization of the source-detector orbit; (iv) an integrated software pipeline to correct various forms of CBCT artifacts (i.e., lag, glare, scatter, beam hardening, patient motion, and truncation); (v) a new 3D reconstruction method that only reconstructs the difference image from the image prior for use in CBCT neuro-angiography; and (vi) a novel method for 3D image reconstruction (DL-Recon) that combines deep learning (DL)-based image synthesis network with physics-based models based on Bayesian estimation of the statical uncertainty of the neural network. Specific clinical challenges were investigated in monitoring patients in the neurological critical care unit (NCCU) and advancing intraoperative soft-tissue imaging capability in image-guided spinal and intracranial neurosurgery. The results show that the methods proposed in this work substantially improved soft-tissue contrast in CBCT. The thesis demonstrates that advanced imaging approaches based on accurate system models, novel artifact reduction methods, and emerging 3D image reconstruction algorithms can effectively tackle current challenges in soft-tissue contrast resolution and expand the application of CBCT in image-guided interventions

Distinguishing non-resonant four-wave-mixing noise in coherent stokes and anti-stokes Raman scattering

A method of examining a sample comprises exposing the sample to a pump pulse of electromagnetic radiation for a first period of time, exposing the sample to a stimulant pulse of electromagnetic radiation for a second period of time which overlaps in time with at least a portion of the first exposing, to produce a signal pulse of electromagnetic radiation for a third period of time, and interfering the signal pulse with a reference pulse of electromagnetic radiation, to determine which portions of the signal pulse were produced during the exposing of the sample to the stimulant pulse. The first and third periods of time are each greater than the second period of time

Spectroscopie RMN du 1H et 31P pour l'étude du métabolisme cérébral à très haut champ magnétique du rongeur à l'homme

1H and 31P nuclear magnetic resonance spectroscopy allows to detect and to measure in vivo and non-invasively the concentrations of biologically relevant compounds associated to metabolic processes such as neurotransmission (glutamate, GABA), neuronal and glial density (N-acetyl-aspartate, myo-inositol) and energetic metabolism (phosphocreatine, ATP) among others. Knowledge of the biochemical profile provides a mean to evaluate the metabolic state of the brain in pathological cases or in evolving physiological conditions, such as aging. Yet, the neural basis of age-related cognitive dysfunction in normal brain aging remains to be elucidated and it has been shown to develop at different rates depending on the structural region.At ultra-high magnetic fields, magnetic resonance spectroscopy (MRS) benefits from an increased signal-to-noise ratio and a higher chemical shift dispersion, resulting in an increased sensitivity and spectral resolution. To exploit these advantages, 1H and 31P longitudinal studies were carried out in vivo at 17.2 Tesla in the aging rat brain to evaluate the progressive metabolic changes within the same individuals from the ages of 1 to up to 22 months of age using two rat cohorts with 1 and 8 months of age at the beginning of the study. For the 1H MRS studies, T1 and T2 metabolite relaxation times were measured at each exam in order to control age-related variations and to calculate absolute metabolite concentrations. 1H neurochemical profiles from four volumes of interest (VOI) in the brain were studied, revealing a progressive increase in myo-inositol and macromolecule content throughout the brain. In our main VOI composed mostly of cortex but also of corpus callosum and hippocampus, increased levels of choline-containing compounds (tCho) and glutamine were also observed, suggesting a mild neuroinflammation. No changes in NAA were observed in our main VOI, the thalamus or the caudate putamen (striatum). T2 decreases were observed with age for total NAA, tCho and macromolecules. Notably, unexpected effects correlated with the number of NMR exams were observed, the most prominent effect being an increase of the T1 relaxation times of the majority of metabolites.The second axis of the work done during this thesis was to set up an experimental framework for MR spectroscopic imaging (MRSI) studies at 7 Tesla in the human brain. 2D MRSI pulse sequences were developed for the acquisition of 31P and 1H metabolite maps using either slab selection or STEAM localization, respectively. A WET water suppression scheme was numerically optimized for its application at 7 T. Static B1-shimming configurations were implemented to reduce the inhomogeneity of the excitation field in the volume of interest and to generate outer-volume suppression (OVS) “ring” modes to saturate the signal in the periphery of the head. This approach allows to reduce the energy deposition in comparison to conventional OVS bands. Experiments were done in vitro showing their feasibility. The performance of standard OVS bands was also compared to a B1-insensitive train to obliterate signal (BISTRO) scheme in vivo using a double-tuned 1H/31P phased-array coil in a single-channel configuration for transmission. The demonstrated suppression efficacy of BISTRO opens the way for its use as a frequency-selective pre-saturation module for future 31P magnetization transfer experiments for the study of brain energy metabolism at very high magnetic field.La Spectroscopie RMN (SRMN) du 1H et du 31P permet de détecter et de mesurer in vivo de façon non-invasive la concentration de composés biologiques qui sont pertinents à l’étude des aspects variés du métabolisme cérébral comme la neurotransmission (glutamate, GABA), la densité neuronale (N-acetyl-aspartate) et gliale (myo-inositol) ou le métabolisme énergétique (phosphocreatine, ATP), entre autres. Ainsi, l’analyse des profils biochimiques permet d’étudier longitudinalement l’évolution de la physiologie cérébrale en conditions pathologiques ou normales. Par ailleurs, à ultra-haut champ magnétique la SRMN bénéficie d’une sensibilité et d’une résolution spectrale accrues, maximisant l’information métabolique exploitable. Au cours de cette thèse, nous nous sommes surtout intéressés à l’étude du vieillissement cérébral normal. Une étude longitudinale en 1H et 31P a été menée in vivo à 17.2 Tesla afin de suivre les altérations métaboliques pendant 14 mois chez deux cohortes de rats Dark Agouti âgés d’un mois et 8 mois au départ de l’étude. Les concentrations ainsi que les temps de relaxation T1 et T2 de plus de 20 métabolites ont été mesurés jusqu’à l’âge de 22 mois. Nous avons notamment observé une augmentation des concentrations de myo-inositol et des macromolécules dans les 4 volumes d’intérêt (VOI) étudiés. Dans le VOI Main, comprenant principalement du cortex mais aussi du corps calleux et de l’hippocampe, ces changements métaboliques ont été accompagnés par une augmentation des niveaux de glutamine et de composés contenant de la choline (tCho). Ces observations sont cohérentes avec une possible neuro-inflammation modéré au cours du vieillissement. Aucun changement du NAA a été observé sur le Main VOI, thalamus et putamen caudé (striatum). Additionnement, une réduction des temps T2 pour le NAA total, la tCho et les macromolécules a été observée, en accord avec une altération du milieu cellulaire et une accumulation de fer dans les tissus avec l’âge. Etonnamment, nous avons observé un effet corrélé avec le nombre d’examens RMN, qui a été fortement manifesté par une augmentation significative des temps T1 de nombreux métabolites.Un deuxième axe de travail pendant cette thèse a été la mise en place des outils méthodologiques nécessaires à la réalisation des études par SRMN du 1H et du 31P à 7 Tesla chez l’homme. Des séquences d’imagerie spectroscopique 2D ont été développées pour obtenir des cartes de concentration des métabolites 31P et 1H respectivement par la sélection d’une coupe ou bien d’un voxel par écho-stimulé. Un schéma de suppression d’eau WET a été optimisé pour son application à 7 T. Des modes d’excitation et de saturation du signal extérieur (OVS) en « anneau » ont été implémentés avec la méthode de transmission parallèle pour son application en imagerie spectroscopique 1H par l’optimisation des configurations statiques d’excitation ou « shimming-B1 ». Cette approche a permis d’appliquer des champs d’excitation plus homogènes et de réduire le dépôt d’énergie chez le sujet par rapport à l’utilisation des bandes OVS classiques. Des expériences in vitro ont été menées pour démontrer leur faisabilité. Enfin, un module de saturation BISTRO a été implémenté pour l’acquisition in vivo de cartes métaboliques en 31P. L’efficacité du module BISTRO a été démontrée et ce module peut être adapté pour des expériences 31P de transfert d’aimantation, ouvrant la voie de l’étude du métabolisme énergétique cérébral chez l’homme à très haut champ magnétique

Model-Based Iterative Reconstruction in Cone-Beam Computed Tomography: Advanced Models of Imaging Physics and Prior Information

Cone-beam computed tomography (CBCT) represents a rapidly developing imaging modality that provides three-dimensional (3D) volumetric images with sub-millimeter spatial resolution and soft-tissue visibility from a single gantry rotation. CBCT tends to have small footprint, mechanical simplicity, open geometry, and low cost compared to conventional diagnostic CT. Because of these features, CBCT has been used in a variety of specialty diagnostic applications, image-guided radiation therapy (on-board CBCT), and surgical guidance (e.g., C-arm based CBCT). However, the current generation of CBCT systems face major challenges in low-contrast, soft-tissue image quality – for example, in the detection of acute intracranial hemorrhage (ICH), which requires a fairly high level of image uniformity, spatial resolution, and contrast resolution. Moreover, conventional approaches in both diagnostic and image-guided interventions that involve a series of imaging studies fail to leverage the wealth of patient-specific anatomical information available from previous scans. Leveraging the knowledge gained from prior images holds the potential for major gains in image quality and dose reduction. Model-based iterative reconstruction (MBIR) attempts to make more efficient use of the measurement data by incorporating a forward model of physical detection processes. Moreover, MBIR allows incorporation of various forms of prior information into image reconstruction, ranging from image smoothness and sharpness to patient-specific anatomical information. By leveraging such advantages, MBIR has demonstrated improved tradeoffs between image quality and radiation dose in multi-detector CT in the past decade and has recently shown similar promise in CBCT. However, the full potential of MBIR in CBCT is yet to be realized. This dissertation explores the capabilities of MBIR in improving image quality (especially low-contrast, soft-tissue image quality) and reducing radiation dose in CBCT. The presented work encompasses new MBIR methods that: i) modify the noise model in MBIR to compensate for noise amplification from artifact correction; ii) design regularization by explicitly incorporating task-based imaging performance as the objective; iii) mitigate truncation effects in a computationally efficient manner; iv) leverage a wealth of patient-specific anatomical information from a previously acquired image; and v) prospectively estimate the optimal amount of prior image information for accurate admission of specific anatomical changes. Specific clinical challenges are investigated in the detection of acute ICH and surveillance of lung nodules. The results show that MBIR can substantially improve low-contrast, soft-tissue image quality in CBCT and enable dose reduction techniques in sequential imaging studies. The thesis demonstrates that novel MBIR methods hold strong potential to overcome conventional barriers to CBCT image quality and open new clinical applications that would benefit from high-quality 3D imaging