Myocardial strain analysis with high temporal resolution MRI tagging: extended 3D motion tracking in normal and LBBB hearts

Tese de doutoramento em Biofísica, apresentada à Universidade de Lisboa através da Faculdade de Ciências, 200

Feature based estimation of myocardial motion from tagged MR images

In the past few years we witnessed an increase in mortality due to cancer relative to mortality due to cardiovascular diseases. In 2008, the Netherlands Statistics Agency reports that 33.900 people died of cancer against 33.100 deaths due to cardiovascular diseases, making cancer the number one cause of death in the Netherlands [33]. Even if the rate of people affected by heart diseases is continually rising, they "simply don’t die of it", according to the research director Prof. Mat Daemen of research institute CARIM of the University of Maastricht [50]. The reason for this is the early diagnosis, and the treatment of people with identified risk factors for diseases like ischemic heart disease, hypertrophic cardiomyopathy, thoracic aortic disease, pericardial (sac around the heart) disease, cardiac tumors, pulmonary artery disease, valvular disease, and congenital heart disease before and after surgical repair. Cardiac imaging plays a crucial role in the early diagnosis, since it allows the accurate investigation of a large amount of imaging data in a small amount of time. Moreover, cardiac imaging reduces costs of inpatient care, as has been shown in recent studies [77]. With this in mind, in this work we have provided several tools with the aim to help the investigation of the cardiac motion. In chapters 2 and 3 we have explored a novel variational optic flow methodology based on multi-scale feature points to extract cardiac motion from tagged MR images. Compared to constant brightness methods, this new approach exhibits several advantages. Although the intensity of critical points is also influenced by fading, critical points do retain their characteristic even in the presence of intensity changes, such as in MR imaging. In an experiment in section 5.4 we have applied this optic flow approach directly on tagged MR images. A visual inspection confirmed that the extracted motion fields realistically depicted the cardiac wall motion. The method exploits also the advantages from the multiscale framework. Because sparse velocity formulas 2.9, 3.7, 6.21, and 7.5 provide a number of equations equal to the number of unknowns, the method does not suffer from the aperture problem in retrieving velocities associated to the critical points. In chapters 2 and 3 we have moreover introduced a smoothness component of the optic flow equation described by means of covariant derivatives. This is a novelty in the optic flow literature. Many variational optic flow methods present a smoothness component that penalizes for changes from global assumptions such as isotropic or anisotropic smoothness. In the smoothness term proposed deviations from a predefined motion model are penalized. Moreover, the proposed optic flow equation has been decomposed in rotation-free and divergence-free components. This decomposition allows independent tuning of the two components during the vector field reconstruction. The experiments and the Table of errors provided in 3.8 showed that the combination of the smoothness term, influenced by a predefined motion model, and the Helmholtz decomposition in the optic flow equation reduces the average angular error substantially (20%-25%) with respect to a similar technique that employs only standard derivatives in the smoothness term. In section 5.3 we extracted the motion field of a phantom of which we know the ground truth of and compared the performance of this optic flow method with the performance of other optic flow methods well known in the literature, such as the Horn and Schunck [76] approach, the Lucas and Kanade [111] technique and the tuple image multi-scale optic flow constraint equation of Van Assen et al. [163]. Tests showed that the proposed optic flow methodology provides the smallest average angular error (AAE = 3.84 degrees) and L2 norm = 0.1. In this work we employed the Helmholtz decomposition also to study the cardiac behavior, since the vector field decomposition allows to investigate cardiac contraction and cardiac rotation independently. In chapter 4 we carried out an analysis of cardiac motion of ten volunteers and one patient where we estimated the kinetic energy for the different components. This decomposition is useful since it allows to visualize and quantify the contributions of each single vector field component to the heart beat. Local measurements of the kinetic energy have also been used to detect areas of the cardiac walls with little movement. Experiments on a patient and a comparison between a late enhancement cardiac image and an illustration of the cardiac kinetic energy on a bull’s eye plot illustrated that a correspondence between an infarcted area and an area with very small kinetic energy exists. With the aim to extend in the future the proposed optic flow equation to a 3D approach, in chapter 6 we investigated the 3D winding number approach as a tool to locate critical points in volume images. We simplified the mathematics involved with respect to a previous work [150] and we provided several examples and applications such as cardiac motion estimation from 3-dimensional tagged images, follicle and neuronal cell counting. Finally in chapter 7 we continued our investigation on volume tagged MR images, by retrieving the cardiac motion field using a 3-dimensional and simple version of the proposed optic flow equation based on standard derivatives. We showed that the retrieved motion fields display the contracting and rotating behavior of the cardiac muscle. We moreover extracted the through-plane component, which provides a realistic illustration of the vector field and is missed by 2-dimensional approaches

Towards automating cine DENSE MRI image analysis : segmentation, tissue tracking and strain computation

Includes bibliographical references (p. 192-206).Over the past two decades, magnetic resonance imaging (MRI) has developed into a powerful imaging tool for the heart. Imaging cardiac morphology is now commonplace in clinical practice, and a plethora of quantitative techniques have also arisen on the research front. Myocardial tagging is an established quantitative cardiac MRI method that involves magnetically tagging the heart with a set of saturated bands, and monitoring the deformation of these bands as the heart contracts

Neuronal activity mediated regulation of glutamate transporter GLT-1 surface diffusion in rat astrocytes in dissociated and slice cultures.

The astrocytic GLT-1 (or EAAT2) is the major glutamate transporter for clearing synaptic glutamate. While the diffusion dynamics of neurotransmitter receptors at the neuronal surface are well understood, far less is known regarding the surface trafficking of transporters in subcellular domains of the astrocyte membrane. Here, we have used live-cell imaging to study the mechanisms regulating GLT-1 surface diffusion in astrocytes in dissociated and brain slice cultures. Using GFP-time lapse imaging, we show that GLT-1 forms stable clusters that are dispersed rapidly and reversibly upon glutamate treatment in a transporter activity-dependent manner. Fluorescence recovery after photobleaching and single particle tracking using quantum dots revealed that clustered GLT-1 is more stable than diffuse GLT-1 and that glutamate increases GLT-1 surface diffusion in the astrocyte membrane. Interestingly, the two main GLT-1 isoforms expressed in the brain, GLT-1a and GLT-1b, are both found to be stabilized opposed to synapses under basal conditions, with GLT-1b more so. GLT-1 surface mobility is increased in proximity to activated synapses and alterations of neuronal activity can bidirectionally modulate the dynamics of both GLT-1 isoforms. Altogether, these data reveal that astrocytic GLT-1 surface mobility, via its transport activity, is modulated during neuronal firing, which may be a key process for shaping glutamate clearance and glutamatergic synaptic transmission

Analysis of myocardial contractility with magnetic resonance

Heart failure has considerable morbidity and poor prognosis. An understanding of the underlying mechanics governing myocardial contraction is a prerequisite for interpreting and predicting changes induced by heart disease. Gross changes in contractile behaviour of the myocardium are readily detected with existing techniques. For more subtle changes during early stages of cardiac dysfunction, however, it requires a sensitive method for measuring, as well as a precise criterion for quantifying, normal and impaired myocardial function. Cardiovascular Magnetic Resonance (CMR) imaging is emerging as an important clinical tool because of its safety, versatility, and the high quality images it produces that allow accurate and reproducible quantification of cardiac structure and function. Traditional CMR approaches for measuring contractility rely on tagging of the myocardium with fiducial markers and require a lengthy and often subjective dependant post-processing procedure. The aim of this research is to develop a new technique, which uses velocity as a marker for the visualisation and assessment of myocardial contractility. Two parallel approaches have been investigated for the assessment of myocardial velocity. The first of these is haimonic phase (HARP) imaging. HARP imaging allows direct derivation of myocardial velocity and strain without the need of further user interaction. We investigated the effect of respiration on the accuracy of the derived contractility, and assessed the clinical applicability and potential pitfalls of the technique by analysing results from a group of patients with hypertrophic cardiomyopathy. The second technique we have investigated is the direct measurement of myocardial velocity with phase contrast myocardial velocity mapping. The imaging sequence used employs effective blood saturation for reducing flow induced phase errors within the myocardium. View sharing was used to improve the temporal resolution, which permitted acquisition of 3D velocity information throughout the cardiac cycle in a single breath-hold, enabling a comprehensive assessment of strain rate of the left ventricle. One key factor that affects the derivation of myocardial contractility based on myocardial velocity is the practical inconsistency of the velocity data. A novel iterative optimisation scheme by incorporating the incompressibility constraint was developed for the restoration of myocardial velocity data. The method allowed accurate assessment of both in-plane and through-plan strain rates, as demonstrated with both synthetic and in vivo data acquired from normal subjects and ischaemic patients. To further enhance the clinical potential of the technique and facilitate the visual assessment of contractile abnormality with myocardial velocity mapping, a complementary analysis framework, named Virtual Tagging, has been developed. The method used velocity data in all directions combined with a finite element mesh incorporating geometrical and physical constraints. The Virtual Tagging framewoik allowed velocity measurements to be used for calculating strain distribution within the 3D volume. It also permitted easy visualisation of the displacement of the tissue, akin to traditional CMR tagging. Detailed validation of the technique is provided, which involves both numerical simulation and in vitro phantom experiments. The main contribution of this thesis is in the improvement of the effectiveness and quality of quantitative myocardial contractility analysis from both sequence design and medical image computing perspectives. It is aimed at providing a sensitive means of detecting subtle as well as gross changes in contractile behaviour of the myocardium. The study is expected to provide a clinically viable platform for functional correlation with other functional measures such as myocardial perfusion and diffusion, and to serve as an aid for further understanding of the links between intrinsicOpen acces

Quaternary structure of a G-protein coupled receptor heterotetramer in complex with Gi and Gs

Background: G-protein-coupled receptors (GPCRs), in the form of monomers or homodimers that bind heterotrimeric G proteins, are fundamental in the transfer of extracellular stimuli to intracellular signaling pathways. Different GPCRs may also interact to form heteromers that are novel signaling units. Despite the exponential growth in the number of solved GPCR crystal structures, the structural properties of heteromers remain unknown. Results: We used single-particle tracking experiments in cells expressing functional adenosine A1-A2A receptors fused to fluorescent proteins to show the loss of Brownian movement of the A1 receptor in the presence of the A2A receptor, and a preponderance of cell surface 2:2 receptor heteromers (dimer of dimers). Using computer modeling, aided by bioluminescence resonance energy transfer assays to monitor receptor homomerization and heteromerization and G-protein coupling, we predict the interacting interfaces and propose a quaternary structure of the GPCR tetramer in complex with two G proteins. Conclusions: The combination of results points to a molecular architecture formed by a rhombus-shaped heterotetramer, which is bound to two different interacting heterotrimeric G proteins (Gi and Gs). These novel results constitute an important advance in understanding the molecular intricacies involved in GPCR function

Cardiac motion estimation using covariant derivatives and Helmholtz decomposition

The investigation and quantification of cardiac movement is important for assessment of cardiac abnormalities and treatment effectiveness. Therefore we consider new aperture problem-free methods to track cardiac motion from 2-dimensional MR tagged images and corresponding sine-phase images. Tracking is achieved by following the movement of scale-space maxima, yielding a sparse set of linear features of the unknown optic flow vector field. Interpolation/reconstruction of the velocity field is then carried out by minimizing an energy functional which is a Sobolev-norm expressed in covariant derivatives (rather than standard derivatives). These covariant derivatives are used to express prior knowledge about the velocity field in the variational framework employed. They are defined on a fiber bundle where sections coincide with vector fields. Furthermore, the optic flow vector field is decomposed in a divergence free and a rotation free part, using our multi-scale Helmholtz decomposition algorithm that combines diffusion and Helmholtz decomposition in a single non-singular analytic kernel operator. Finally, we combine this multi-scale Helmholtz decomposition with vector field reconstruction (based on covariant derivatives) in a single algorithm and present some experiments of cardiac motion estimation. Further experiments on phantom data with ground truth show that both the inclusion of covariant derivatives and the inclusion of the multi-scale Helmholtz decomposition improves the optic flow reconstruction

Test of multiple sensor set-up for head motion characterization during MRI acquisition

L'Imaging a Risonanza Magnetica (MRI) è una tecnica di imaging ampiamente utilizzata in ambito medico. La ricerca in questo campo si sta focalizzando sullo sviluppo di scanner a campi molto intensi, come lo scanner a 7 T utilizzato in questa tesi. La risoluzione delle immagini e l'entità degli artefatti creati dai movimenti involontari del paziente sono proporzionali all'intensità di campo magnetico e diventano rilevanti ad intensità molto elevate. Le tecniche di Motion Correction, nota la cinetica dei movimenti, permettono di correggere queste distorsioni. La tesi è inserita in un progetto che ha come scopo la misura indiretta dei movimenti della testa durante la scansione MRI. In particolare, mi sono concentrata sui miglioramenti da apportare al set-up e sulla caratterizzazione dei tre strumenti usati per la misura: la telecamera di campo magnetico (Clip on Camera Head, CCH) formata da 16 sonde fissate in una struttura cilindrica posizionata attorno alla testa del paziente; la telecamera ottica (Moiré Phase Tracking System, MPT) che misura i movimenti tramite l'immagine di un marker olografico supportato da un bite tenuto nella bocca del volontario; il dispositivo (Physlog) dello scanner che fornisce i parametri fisiologici (respirazione e battito cardiaco). La comunicazione hardware degli strumenti avviene grazie a un segnale di trigger, di cui ho ottimizzato la sincronizzazione. Inoltre, abbiamo acquisito dataset completi di tre volontari, a diverse condizioni. I dati sono stati sincronizzati e analizzati, tramite analisi multivariate, per caratterizzare la risposta e la stabilità del sistema e la variabilità individuale dei pazienti. L'analisi ha permesso di capire meglio le proprietà dello strumento e ha consentito di associare le misure del campo magnetico al di fuori del cranio ai valori fisiologici dei volontari

Characterization of Maga Expression and Iron Uptake in P19 Cells: Implications for Use as a Gene-Based Contrast Agent

Magnetic resonance imaging (MRI) is one of the non-invasive imaging modalities used in longitudinal cell tracking. Previous studies suggest that MagA, a putative iron transport protein from magnetotactic bacteria, is a useful gene-based magnetic resonance contrast agent. Hemagglutinin (HA)-tagged MagA was stably expressed in undifferentiated embryonic mouse teratocarcinoma, multipotent P19 stem cells to provide a suitable model for tracking these cells during differentiation. Western blot and immunocytochemistry confirmed the expression and membrane localization of MagA-HA in P19 cells. Elemental iron analysis using inductively-coupled plasma mass spectrometry revealed significant iron uptake in both parental and MagA-HA-expressing P19 cells, cultured in the presence of iron-supplemented medium. Withdrawal of this extracellular iron supplement revealed unexpected iron export activity in P19 cells, which MagA-HA expression attenuated. The influence of iron supplementation on parental and MagA-HA-expressing cells was not reflected by longitudinal relaxation rates. Measurement of transverse relaxation rates (R2* and R2) reflected changes in total cellular iron content. In particular, the reversible component R2′ (R2* ‒ R2) provided a moderately strong correlation to amount of cellular iron, normalized to amount of protein

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