Flow Imaging Using MRI: Quantification and Analysis

A complex and challenging problem in flow study is to obtain quantitative flow information in opaque systems, for example, blood flow in biological systems and flow channels in chemical reactors. In this regard, MRI is superior to the conventional optical flow imaging or ultrasonic Doppler imaging. However, for high speed flows, complex flow behaviors and turbulences make it difficult to image and analyze the flows. In MR flow imaging, MR tagging technique has demonstrated its ability to simultaneously visualize motion in a sequence of images. Moreover, a quantification method, namely HARmonic Phase (HARP) analysis, can extract a dense velocity field from tagged MR image sequence with minimal manual intervention. In this work, we developed and validated two new MRI methods for quantification of very rapid flows. First, HARP was integrated with a fast MRI imaging method called SEA (Single Echo Acquisition) to image and analyze high velocity flows. Second, an improved HARP method was developed to deal with tag fading and data noise in the raw MRI data. Specifically, a regularization method that incorporates the law of flow dynamics in the HARP analysis was developed. Finally, the methods were validated using results from the computational fluid dynamics (CFD) and the conventional optimal flow imaging based on particle image velocimetry (PIV). The results demonstrated the improvement from the quantification using solely the conventional HARP method

Flow pattern analysis for magnetic resonance velocity imaging

Blood flow in the heart is highly complex. Although blood flow patterns have been investigated by both computational modelling and invasive/non-invasive imaging techniques, their evolution and intrinsic connection with cardiovascular disease has yet to be explored. Magnetic resonance (MR) velocity imaging provides a comprehensive distribution of multi-directional in vivo flow distribution so that detailed quantitative analysis of flow patterns is now possible. However, direct visualisation or quantification of vector fields is of little clinical use, especially for inter-subject or serial comparison of changes in flow patterns due to the progression of the disease or in response to therapeutic measures. In order to achieve a comprehensive and integrated description of flow in health and disease, it is necessary to characterise and model both normal and abnormal flows and their effects. To accommodate the diversity of flow patterns in relation to morphological and functional changes, we have described in this thesis an approach of detecting salient topological features prior to analytical assessment of dynamical indices of the flow patterns. To improve the accuracy of quantitative analysis of the evolution of topological flow features, it is essential to restore the original flow fields so that critical points associated with salient flow features can be more reliably detected. We propose a novel framework for the restoration, abstraction, extraction and tracking of flow features such that their dynamic indices can be accurately tracked and quantified. The restoration method is formulated as a constrained optimisation problem to remove the effects of noise and to improve the consistency of the MR velocity data. A computational scheme is derived from the First Order Lagrangian Method for solving the optimisation problem. After restoration, flow abstraction is applied to partition the entire flow field into clusters, each of which is represented by a local linear expansion of its velocity components. This process not only greatly reduces the amount of data required to encode the velocity distribution but also permits an analytical representation of the flow field from which critical points associated with salient flow features can be accurately extracted. After the critical points are extracted, phase portrait theory can be applied to separate them into attracting/repelling focuses, attracting/repelling nodes, planar vortex, or saddle. In this thesis, we have focused on vortical flow features formed in diastole. To track the movement of the vortices within a cardiac cycle, a tracking algorithm based on relaxation labelling is employed. The constraints and parameters used in the tracking algorithm are designed using the characteristics of the vortices. The proposed framework is validated with both simulated and in vivo data acquired from patients with sequential MR examination following myocardial infarction. The main contribution of the thesis is in the new vector field restoration and flow feature abstraction method proposed. They allow the accurate tracking and quantification of dynamic indices associated with salient features so that inter- and intra-subject comparisons can be more easily made. This provides further insight into the evolution of blood flow patterns and permits the establishment of links between blood flow patterns and localised genesis and progression of cardiovascular disease.Open acces

Development of Advanced Acquisition and Reconstruction Techniques for Real-Time Perfusion MRI

Diese Doktorarbeit befasst sich mit der methodischen Entwicklung von Akquisition- und Rekonstruktionstechniken zur Anwendung von Echtzeit-Bildgebungstechniken auf das Gebiet der dynamischen kontrastmittelgestützten Magentresonanztomographie. Zur Unterdrückung unerwünschter Bildartefakte wird eine neue Spoiling-Technik vorgeschlagen, die auf randomisierten Phasen der Hochfrequenzanregung basiert. Diese Technik erlaubt eine schnelle, artefaktfreie Aufnahme von T1-gewichteten Rohdaten bei radialer Abtastung. Die Rekonstruktion quantitativer Parameterkarten aus solchen Rohdaten kann als nichtlineares, inverses Problem aufgefasst werden. In dieser Arbeit wird eine modellbasierte Rekonstruktionstechnik zur quantitativen T1-Kartierung entwickelt, die dieses inverse Problem mittels der iterativ regularisierten Gauß-Newton-Methode mit parameterspezifischer Regularisierung löst. In Simulationen sowie in-vitro- und in-vivo-Studien wird Genauigkeit und Präzision dieser neuen Methode geprüft, die ihre direkte Anwendung in in-vitro-Experimenten zur "first-pass"-Perfusion findet. In diesen Experimenten wird ein kommerziell verfügbares Phantom verwendet, dass in-vivo-Perfusion simuliert und gleichzeitig vollständige Kontrolle über die vorherrschenden Austauschraten erlaubt

Doctor of Philosophy

dissertationImage-based biomechanics, particularly numerical modeling using subject-specific data obtained via imaging, has proven useful for elucidating several biomechanical processes, such as prediction of deformation due to external loads, applicable to both normal function and pathophysiology of various organs. As the field evolves towards applications that stretch the limits of imaging hardware and acquisition time, the information traditionally expected as input for numerical routines often becomes incomplete or ambiguous, and requires specific acquisition and processing strategies to ensure physical accuracy and compatibility with predictive mathematical modeling. These strategies, often derivatives or specializations of traditional mechanics, effectively extend the nominal capability of medical imaging hardware providing subject-specific information coupled with the option of using the results for predictive numerical simulations. This research deals with the development of tools for extracting mechanical measurements from a finite set of imaging data and finite element analysis in the context of constructing structural atlases of the heart, understanding the biomechanics of the venous vasculature, and right ventricular failure. The tools include: (1) application of Hyperelastic Warping image registration to displacement-encoded MRI for reconstructing absolute displacement fields, (2) combination of imaging and a material parameter identification approach to measure morphology, deformation, and mechanical properties of vascular tissue, and (3) extrapolation of diffusion tensor MRI acquired at a single time point for the prediction the structural changes across the cardiac cycle with mechanical simulations. Selected tools were then applied to evaluate structural changes in a reversible animal model for right ventricular failure due to pressure overload

A parametric model of the brain vascular system for estimation of the arterial input function (AIF) at the tissue level

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136452/1/nbm3695.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136452/2/nbm3695_am.pd

On motion in dynamic magnetic resonance imaging: Applications in cardiac function and abdominal diffusion

La imagen por resonancia magnética (MRI), hoy en día, representa una potente herramienta para el diagnóstico clínico debido a su flexibilidad y sensibilidad a un amplio rango de propiedades del tejido. Sus principales ventajas son su sobresaliente versatilidad y su capacidad para proporcionar alto contraste entre tejidos blandos. Gracias a esa versatilidad, la MRI se puede emplear para observar diferentes fenómenos físicos dentro del cuerpo humano combinando distintos tipos de pulsos dentro de la secuencia. Esto ha permitido crear distintas modalidades con múltiples aplicaciones tanto biológicas como clínicas. La adquisición de MR es, sin embargo, un proceso lento, lo que conlleva una solución de compromiso entre resolución y tiempo de adquisición (Lima da Cruz, 2016; Royuela-del Val, 2017). Debido a esto, la presencia de movimiento fisiológico durante la adquisición puede conllevar una grave degradación de la calidad de imagen, así como un incremento del tiempo de adquisición, aumentando así tambien la incomodidad del paciente. Esta limitación práctica representa un gran obstáculo para la viabilidad clínica de la MRI. En esta Tesis Doctoral se abordan dos problemas de interés en el campo de la MRI en los que el movimiento fisiológico tiene un papel protagonista. Éstos son, por un lado, la estimación robusta de parámetros de rotación y esfuerzo miocárdico a partir de imágenes de MR-Tagging dinámica para el diagnóstico y clasificación de cardiomiopatías y, por otro, la reconstrucción de mapas del coeficiente de difusión aparente (ADC) a alta resolución y con alta relación señal a ruido (SNR) a partir de adquisiciones de imagen ponderada en difusión (DWI) multiparamétrica en el hígado.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

Characterizing Single Ventricle Patient-Specific Anatomy Using Segmentation of MRI and 3D Reconstruction to Aid Surgical Planning

Single ventricle congenital heart defects occur 2 per every 1000 live births in the USA. In these cases, cyanosis occurs due to the mixing of venous deoxygenated blood and oxygenated blood from the lungs. These defects are surgically treated by the total cavo-pulmonary connection (TCPC), where the superior and inferior vena cavae are connected to the pulmonary arteries routing the systemic venous return directly to the lungs. However, this Fontan repair results in high energy losses and therefore the optimization of this connection prior to the surgery could significantly improve post-operative performance. In this paper, the in-house segmentation and 3D reconstruction scheme is used in the following studies. First, 3D geometrical analysis of the TCPCs is used to determine the advantages and disadvantages of two commonly performed TCPC palliations intra-atrial and extra-cardiac configurations. Then, a surgical planning outline is proposed with segmentation of pre and post surgical Magnetic Resonance Imaging (MRI) data followed by the 3D reconstruction with emphasis on extracting surrounding vessels and structures. A pediatric surgeon performs a virtual surgery on the reconstruction of the patient s pre-Fontan anatomy prior to the actual surgery. A segmentation of the heart, aorta and surrounding vessels superimposed with the Glenn, when used with the SURGEM® tool, simulates the actual Fontan operation. This outline allows the surgeon to envision numerous scenarios of possible surgical options, and accordingly to predict the post operative procedures. The segmentation tool is improved upon to increase the accuracy and efficiency of the process and enhance the quality of the anatomical reconstructions.Committee Member/Second Reader: Kartik S. Sundareswaran; Faculty Mentor: Dr. Ajit P. Yoganatha

On the Quantification of Fluid Mechanical Properties by Means of Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) provides a versatile tool to determine a variety of fluid mechanical properties, but similarly the quantification is biased by the acquisition itself and the technique has limitations among which are limited spatial resolution and low signal-to-noise-ratio. To overcome such issues, phase contrast MRI methods have been investigated at 7 T. At this field strength variations of the transmit field pose a substantial problem. Additionally, so-called displacement artifacts become important, since they scale with spatial resolution. Transmit field variations are addressed in this work by multi-spoke RF pulses, which are not straightforwardly applicable to velocity quantification. They require a detailed investigation of displacement artifacts that arise due to differences in the encoding time points of velocity and space. This work investigates three different encoding schemes, for conventional excitation as well as for multi-spoke excitation, which yield different displacement artifacts. Their impact on derived haemodynamic parameters, such as wall shear stress, which had been unknown so far, are investigated. Moreover, spoke pulses are further fine-tuned by using asymmetric pulse shapes. Besides the correct determination of the velocity at 7 T, the precise quantification of acceleration is another important factor, which is solved in this work by developing an acceleration-encoded sequence free of artifacts. Furthermore, another confounding factor in MRI-based velocitmetry, the intravoxel velocity distributions, affect the velocity encoding process. This effect has been investigated and, based on measured velocity spectra, noise-optimized velocity encoding sensitivity (VENC) values have been proposed. Finally, the potential of precise MR-based velocity measurements is demonstrated for a well-known fluid dynamic test case (flow over periodic hills) with a Reynolds number of 60,000. For this case, the Reynolds stress tensor has been quantified. In conclusion, the presented techniques improve the precision at which fluid mechanical properties can be quantified by means of MRI

Fast upper airway magnetic resonance imaging for assessment of speech production and sleep apnea

The human upper airway is involved in various functions, including speech, swallowing, and respiration. Magnetic resonance imaging (MRI) can visualize the motion of the upper airway and has been used in scientific studies to understand the dynamics of vocal tract shaping during speech and for assessment of upper airway abnormalities related to obstructive sleep apnea and swallowing disorders. Acceleration technologies in MRI are crucial in improving spatiotemporal resolution or spatial coverage. Recent trends in technical aspects of upper airway MRI are to develop state-of-the-art image acquisition methods for improved dynamic imaging of the upper airway and develop automatic image analysis methods for efficient and accurate quantification of upper airway parameters of interest. This review covers the fast upper airway magnetic resonance (MR) acquisition and reconstruction, MR experimental issues, image analysis techniques, and applications, mainly with respect to studies of speech production and sleep apnea