Implicit Modeling with Uncertainty Estimation for Intravoxel Incoherent Motion Imaging

Intravoxel incoherent motion (IVIM) imaging allows contrast-agent free in vivo perfusion quantification with magnetic resonance imaging (MRI). However, its use is limited by typically low accuracy due to low signal-to-noise ratio (SNR) at large gradient encoding magnitudes as well as dephasing artefacts caused by subject motion, which is particularly challenging in fetal MRI. To mitigate this problem, we propose an implicit IVIM signal acquisition model with which we learn full posterior distribution of perfusion parameters using artificial neural networks. This posterior then encapsulates the uncertainty of the inferred parameter estimates, which we validate herein via numerical experiments with rejection-based Bayesian sampling. Compared to state-of-the-art IVIM estimation method of segmented least-squares fitting, our proposed approach improves parameter estimation accuracy by 65% on synthetic anisotropic perfusion data. On paired rescans of in vivo fetal MRI, our method increases repeatability of parameter estimation in placenta by 46%

Advanced Medical Image Registration Methods for Quantitative Imaging and Multi-Channel Images

This thesis proposes advanced medical image registration methods for applications that can be grouped in two broad themes. The first theme focuses on registration techniques increasing the reliability of _quantitative measurements_ extracted from sets of medical images. The second theme that is considered in this thesis is the registration of _multi-channel_ images

Anatomical Modeling of Cerebral Microvascular Structures: Application to Identify Biomarkers of Microstrokes

Les réseaux microvasculaires corticaux sont responsables du transport de l’oxygène et des substrats énergétiques vers les neurones. Ces réseaux réagissent dynamiquement aux demandes énergétiques lors d’une activation neuronale par le biais du couplage neurovasculaire. Afin d’élucider le rôle de la composante microvasculaire dans ce processus de couplage, l’utilisation de la modélisation in-formatique pourrait se révéler un élément clé. Cependant, la manque de méthodologies de calcul appropriées et entièrement automatisées pour modéliser et caractériser les réseaux microvasculaires reste l’un des principaux obstacles. Le développement d’une solution entièrement automatisée est donc important pour des explorations plus avancées, notamment pour quantifier l’impact des mal-formations vasculaires associées à de nombreuses maladies cérébrovasculaires. Une observation courante dans l’ensemble des troubles neurovasculaires est la formation de micro-blocages vascu-laires cérébraux (mAVC) dans les artérioles pénétrantes de la surface piale. De récents travaux ont démontré l’impact de ces événements microscopiques sur la fonction cérébrale. Par conséquent, il est d’une importance vitale de développer une approche non invasive et comparative pour identifier leur présence dans un cadre clinique. Dans cette thèse,un pipeline de traitement entièrement automatisé est proposé pour aborder le prob-lème de la modélisation anatomique microvasculaire. La méthode de modélisation consiste en un réseau de neurones entièrement convolutif pour segmenter les capillaires sanguins, un générateur de modèle de surface 3D et un algorithme de contraction de la géométrie pour produire des mod-èles graphiques vasculaires ne comportant pas de connections multiples. Une amélioration de ce pipeline est développée plus tard pour alléger l’exigence de maillage lors de la phase de représen-tation graphique. Un nouveau schéma permettant de générer un modèle de graphe est développé avec des exigences d’entrée assouplies et permettant de retenir les informations sur les rayons des vaisseaux. Il est inspiré de graphes géométriques déformants construits en respectant les morpholo-gies vasculaires au lieu de maillages de surface. Un mécanisme pour supprimer la structure initiale du graphe à chaque exécution est implémenté avec un critère de convergence pour arrêter le pro-cessus. Une phase de raffinement est introduite pour obtenir des modèles vasculaires finaux. La modélisation informatique développée est ensuite appliquée pour simuler les signatures IRM po-tentielles de mAVC, combinant le marquage de spin artériel (ASL) et l’imagerie multidirectionnelle pondérée en diffusion (DWI). L’hypothèse est basée sur des observations récentes démontrant une réorientation radiale de la microvascularisation dans la périphérie du mAVC lors de la récupéra-tion chez la souris. Des lits capillaires synthétiques, orientés aléatoirement et radialement, et des angiogrammes de tomographie par cohérence optique (OCT), acquis dans le cortex de souris (n = 5) avant et après l’induction d’une photothrombose ciblée, sont analysés. Les graphes vasculaires informatiques sont exploités dans un simulateur 3D Monte-Carlo pour caractériser la réponse par résonance magnétique (MR), tout en considérant les effets des perturbations du champ magnétique causées par la désoxyhémoglobine, et l’advection et la diffusion des spins nucléaires. Le pipeline graphique proposé est validé sur des angiographies synthétiques et réelles acquises avec différentes modalités d’imagerie. Comparé à d’autres méthodes effectuées dans le milieu de la recherche, les expériences indiquent que le schéma proposé produit des taux d’erreur géométriques et topologiques amoindris sur divers angiogrammes. L’évaluation confirme également l’efficacité de la méthode proposée en fournissant des modèles représentatifs qui capturent tous les aspects anatomiques des structures vasculaires. Ensuite, afin de trouver des signatures de mAVC basées sur le signal IRM, la modélisation vasculaire proposée est exploitée pour quantifier le rapport de perte de signal intravoxel minimal lors de l’application de plusieurs directions de gradient, à des paramètres de séquence variables avec et sans ASL. Avec l’ASL, les résultats démontrent une dif-férence significative (p <0,05) entre le signal calculé avant et 3 semaines après la photothrombose. La puissance statistique a encore augmenté (p <0,005) en utilisant des angiogrammes capturés à la semaine suivante. Sans ASL, aucun changement de signal significatif n’est trouvé. Des rapports plus élevés sont obtenus à des intensités de champ magnétique plus faibles (par exemple, B0 = 3) et une lecture TE plus courte (<16 ms). Cette étude suggère que les mAVC pourraient être carac-térisés par des séquences ASL-DWI, et fournirait les informations nécessaires pour les validations expérimentales postérieures et les futurs essais comparatifs.----------ABSTRACT Cortical microvascular networks are responsible for carrying the necessary oxygen and energy substrates to our neurons. These networks react to the dynamic energy demands during neuronal activation through the process of neurovascular coupling. A key element in elucidating the role of the microvascular component in the brain is through computational modeling. However, the lack of fully-automated computational frameworks to model and characterize these microvascular net-works remains one of the main obstacles. Developing a fully-automated solution is thus substantial for further explorations, especially to quantify the impact of cerebrovascular malformations associ-ated with many cerebrovascular diseases. A common pathogenic outcome in a set of neurovascular disorders is the formation of microstrokes, i.e., micro occlusions in penetrating arterioles descend-ing from the pial surface. Recent experiments have demonstrated the impact of these microscopic events on brain function. Hence, it is of vital importance to develop a non-invasive and translatable approach to identify their presence in a clinical setting. In this thesis, a fully automatic processing pipeline to address the problem of microvascular anatom-ical modeling is proposed. The modeling scheme consists of a fully-convolutional neural network to segment microvessels, a 3D surface model generator and a geometry contraction algorithm to produce vascular graphical models with a single connected component. An improvement on this pipeline is developed later to alleviate the requirement of water-tight surface meshes as inputs to the graphing phase. The novel graphing scheme works with relaxed input requirements and intrin-sically captures vessel radii information, based on deforming geometric graphs constructed within vascular boundaries instead of surface meshes. A mechanism to decimate the initial graph struc-ture at each run is formulated with a convergence criterion to stop the process. A refinement phase is introduced to obtain final vascular models. The developed computational modeling is then ap-plied to simulate potential MRI signatures of microstrokes, combining arterial spin labeling (ASL) and multi-directional diffusion-weighted imaging (DWI). The hypothesis is driven based on recent observations demonstrating a radial reorientation of microvasculature around the micro-infarction locus during recovery in mice. Synthetic capillary beds, randomly- and radially oriented, and op-tical coherence tomography (OCT) angiograms, acquired in the barrel cortex of mice (n=5) before and after inducing targeted photothrombosis, are analyzed. The computational vascular graphs are exploited within a 3D Monte-Carlo simulator to characterize the magnetic resonance (MR) re-sponse, encompassing the effects of magnetic field perturbations caused by deoxyhemoglobin, and the advection and diffusion of the nuclear spins. The proposed graphing pipeline is validated on both synthetic and real angiograms acquired with different imaging modalities. Compared to other efficient and state-of-the-art graphing schemes, the experiments indicate that the proposed scheme produces the lowest geometric and topological error rates on various angiograms. The evaluation also confirms the efficiency of the proposed scheme in providing representative models that capture all anatomical aspects of vascular struc-tures. Next, searching for MRI-based signatures of microstokes, the proposed vascular modeling is exploited to quantify the minimal intravoxel signal loss ratio when applying multiple gradient di-rections, at varying sequence parameters with and without ASL. With ASL, the results demonstrate a significant difference (p<0.05) between the signal-ratios computed at baseline and 3 weeks after photothrombosis. The statistical power further increased (p<0.005) using angiograms captured at week 4. Without ASL, no reliable signal change is found. Higher ratios with improved significance are achieved at low magnetic field strengths (e.g., at 3 Tesla) and shorter readout TE (<16 ms). This study suggests that microstrokes might be characterized through ASL-DWI sequences, and provides necessary insights for posterior experimental validations, and ultimately, future transla-tional trials

Magnetic resonance imaging of muscle structure and function

Ziel dieser Arbeit ist die Implementierung und kombinierte Anwendung verschiedener MRT Techniken zur Untersuchung der Struktur und Funktion der humanen Skelettmuskulatur. Insbesondere steht deren Applikation an der Rückenmuskulatur im Vordergrund, um auf Basis dieser Untersuchungen einen Beitrag zur Ursachenforschung des unspezifischen - meist chronifizierten - Rückenschmerzes zu leisten. Vor diesem Hintergrund wurden in der vorliegenden Dissertation dezidierte MR-Pulssequenzen und Bildrekonstruktionsverfahren entwickelt, welche unter Verwendung der diffusionsgewichteten MR-Bildgebung (diffusion-weighted imaging, DWI) die 3D-Rekonstruktion der Muskelfaserarchitektur sowie die Quantifizierung der muskulären Vaskularität ermöglichen. Die Erfassung der Faserarchitektur basiert auf der Diffusionstensorbildgebung (diffusion tensor imaging, DTI) - einer Weiterentwicklung der DWI - und wurde am Tiermodell anhand sequentiell durchgeführter in vivo und post mortem Messungen validiert. Anschließend wurde diese Methode in einer Pilotstudie genutzt, um degenerative Veränderungen bei Patienten nach Wirbelsäulenoperation zu erfassen. Im zweiten Schritt dieser Arbeit, wurde ein Messprotokoll zur funktionellen MR-Untersuchung implementiert, welches Messungen vor, während und nach willkürlicher Muskelkontraktion beinhaltet. Dieses Protokoll sieht weiterhin die Applikation einer neuartigen perfusionsensitiven DWI-Sequenz sowie optimierten Sequenzen zur quantitativen T2-gewichteten MR-Bildgebung und ortaufgelösten 31P-MR-Spektroskopie vor, wobei die beiden letztgenannten Techniken es erlauben, komplexe funktionelle Vorgänge, wie beispielsweise die des Energiemetabolismus, unter Einfluss einer Belastungssituation zu untersuchen. Diese funktionellen MR-Messprinzipien werden in der Regel unter dem Begriff muscle functional MRI (mfMRI) subsumiert und ermöglichen die multi-parametrische Erfassung unterschiedlicher funktioneller und struktureller Eigenschaften der Muskelphysiologie. Dies wird in der vorliegenden Arbeit anhand einer gerontologischen Studie demonstriert, wobei die hierbei gewonnenen Ergebnisse Einblick in zahlreiche altersassoziierte Aspekte der Rückenphysiologie geben. Zusammenfassend werden in dieser Dissertation verschiedene Ansätze der MR-Bildgebung und MR-Spektroskopie vorgestellt, die einerseits für grundlagenwissenschaftliche Fragestellungen zum unspezifischen Rückenschmerz, andererseits aber auch in der klinischen Routine zur Untersuchung degenerativer Veränderungen der Skelettmuskulatur herangezogen werden können.The aim of this work is the implementation and combined application of different MRI-based methods, which facilitate the comprehensive assessment of the skeletal muscle structure and function. Especially, the application of these MRI techniques to human back muscles has been put into focus, which may provide deeper insights into the origin of non-specific - and in most cases chronic - back pain. To this end, dedicated MRI sequences and quantitative image reconstruction approaches were developed in this work, which are based on diffusion-weighted imaging (DWI) and enable the 3D reconstruction of the muscle fiber architecture as well as the assessment of a surrogate measure of the vascular capacity. The MRI-based reconstruction of the fiber architecture relies on diffusion tensor imaging (DTI) - an extension of DWI - and was validated by successive in vivo and post mortem measurements. Afterwards, this method was employed in a pre-clinical pilot study in order to assess surgeryrelated degenerative changes of the back muscles in patients after spinal surgery. In the second step of this work, functional measurements of the human skeletal muscles, which means quantitative measurements prior to, during and after muscular loading, were performed by using a novel perfusion-sensitive DWI sequence as well as optimized sequence protocols of quantitative T2-weighted MRI and spatially resolved 31P-MR spectroscopy. The latter two methods allow the quantification of complex physiological processes, such as of the high-energy metabolism, during the exercise of skeletal muscles, and are often subsumed under the term muscle functional MRI (mfMRI). Combined application of these mfMRI techniques provides multi-parametric evaluation of several structural and functional determinants and, thus, allows comprehensive characterization of the muscle physiology. In order to demonstrate the capabilities of the proposed multi-parametric mfMRI approach, a gerontological study is performed in this work, while the obtained results indicate several age-related aspects of the human back muscle physiology. Overall, this thesis introduces MR imaging and MR spectroscopy techniques, which may, on the one hand, contribute to research of low back pain and, on the other hand, serve as basis of clinical investigations in order to investigate degenerative processes of skeletal muscles

Preclinical MRI of the Kidney

This Open Access volume provides readers with an open access protocol collection and wide-ranging recommendations for preclinical renal MRI used in translational research. The chapters in this book are interdisciplinary in nature and bridge the gaps between physics, physiology, and medicine. They are designed to enhance training in renal MRI sciences and improve the reproducibility of renal imaging research. Chapters provide guidance for exploring, using and developing small animal renal MRI in your laboratory as a unique tool for advanced in vivo phenotyping, diagnostic imaging, and research into potential new therapies. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Preclinical MRI of the Kidney: Methods and Protocols is a valuable resource and will be of importance to anyone interested in the preclinical aspect of renal and cardiorenal diseases in the fields of physiology, nephrology, radiology, and cardiology. This publication is based upon work from COST Action PARENCHIMA, supported by European Cooperation in Science and Technology (COST). COST (www.cost.eu) is a funding agency for research and innovation networks. COST Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. PARENCHIMA (renalmri.org) is a community-driven Action in the COST program of the European Union, which unites more than 200 experts in renal MRI from 30 countries with the aim to improve the reproducibility and standardization of renal MRI biomarkers

Multi-parametric quantification of white matter microstructure in the human brain

To date the majority of MRI studies of white matter (WM) microstructure have used diffusion tensor MRI (DT-MRI), comparing groups on a voxel-by-voxel basis. There are limitations to this approach. Firstly, the analysis approach treats each voxel independently, ignoring the fact that adjacent voxels may come from the same tract (or may come from completely separate tracts). Secondly, DT-MRI is sensitive to both interesting properties of WM (e.g., myelination, axon density), and less interesting properties (e.g., intra-voxel orientational dispersion). In contrast, other imaging approaches, based on different contrast mechanisms, can provide increased specificity and therefore sensitivity to differences in one particular attribute of tissue microstructure (e.g., myelin content or axonal density). Both quantitative magnetization transfer (qMT) imaging and multicomponent relaxometry provide proxy estimates of myelin content while the combined hindered and restricted model of diffusion (CHARMED) provides a proxy estimate of axon density. We present a novel imaging method called tractometry, which permits simultaneous quantitative assessment of these different microstructural attributes along specific pathways.Crucially, the metrics were only weakly correlated, suggesting that tractometry provides complementary WM microstructural information to DT-MRI. In developing the tractometry pipeline, we also performed a detailed examination of the qMT pipeline, identifying and reducing sources of variance to provide optimized results. We also identify a number of issues with the current state-of-the art, including the stability of tract based spatial statistics (TBSS). We show that conducting a structure-function correlation TBSS study may lead to vastly different conclusions, based simply on the participants recruited into the study. We also address microstructural asymmetry, including the degree of partial-volume effects (PVEs) from free water, which impact on WM metrics. The observed spatial heterogeneity of PVEs can potentially confound interpretation in studies where contralateral hemispheres are used as internal controls, and could either exacerbate or possibly negate tissue difference

Preclinical MRI of the kidney : methods and protocols

This Open Access volume provides readers with an open access protocol collection and wide-ranging recommendations for preclinical renal MRI used in translational research. The chapters in this book are interdisciplinary in nature and bridge the gaps between physics, physiology, and medicine. They are designed to enhance training in renal MRI sciences and improve the reproducibility of renal imaging research. Chapters provide guidance for exploring, using and developing small animal renal MRI in your laboratory as a unique tool for advanced in vivo phenotyping, diagnostic imaging, and research into potential new therapies. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Preclinical MRI of the Kidney: Methods and Protocols is a valuable resource and will be of importance to anyone interested in the preclinical aspect of renal and cardiorenal diseases in the fields of physiology, nephrology, radiology, and cardiology. This publication is based upon work from COST Action PARENCHIMA, supported by European Cooperation in Science and Technology (COST). COST (www.cost.eu) is a funding agency for research and innovation networks. COST Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. PARENCHIMA (renalmri.org) is a community-driven Action in the COST program of the European Union, which unites more than 200 experts in renal MRI from 30 countries with the aim to improve the reproducibility and standardization of renal MRI biomarkers

Intelligent Imaging of Perfusion Using Arterial Spin Labelling

Arterial spin labelling (ASL) is a powerful magnetic resonance imaging technique, which can be used to noninvasively measure perfusion in the brain and other organs of the body. Promising research results show how ASL might be used in stroke, tumours, dementia and paediatric medicine, in addition to many other areas. However, significant obstacles remain to prevent widespread use: ASL images have an inherently low signal to noise ratio, and are susceptible to corrupting artifacts from motion and other sources. The objective of the work in this thesis is to move towards an "intelligent imaging" paradigm: one in which the image acquisition, reconstruction and processing are mutually coupled, and tailored to the individual patient. This thesis explores how ASL images may be improved at several stages of the imaging pipeline. We review the relevant ASL literature, exploring details of ASL acquisitions, parameter inference and artifact post-processing. We subsequently present original work: we use the framework of Bayesian experimental design to generate optimised ASL acquisitions, we present original methods to improve parameter inference through anatomically-driven modelling of spatial correlation, and we describe a novel deep learning approach for simultaneous denoising and artifact filtering. Using a mixture of theoretical derivation, simulation results and imaging experiments, the work in this thesis presents several new approaches for ASL, and hopefully will shape future research and future ASL usage