Quantification in cardiac MRI: advances in image acquisition and processing

Cardiac magnetic resonance (CMR) imaging enables accurate and reproducible quantification of measurements of global and regional ventricular function, blood flow, perfusion at rest and stress as well as myocardial injury. Recent advances in MR hardware and software have resulted in significant improvements in image quality and a reduction in imaging time. Methods for automated and robust assessment of the parameters of cardiac function, blood flow and morphology are being developed. This article reviews the recent advances in image acquisition and quantitative image analysis in CMR

Myocardial strain estimated from standard cine MRI closely represents strain estimated from dedicated strain-encoded MRI

A method of non-rigid image registration was developed and evaluated for the purpose of quantifying myocardial displacement and strain from cine MRI using DENSE MRI as the reference standard. The objective of this paper was to study the potential use of cine MRI with image registration, as a means of measuring strain. The local displacement of the left ventricle was modelled by free-form deformations using b-splines. Cardiac MRI images were obtained from four healthy volunteers at 1.5T and analysed by the implementation of image registration algorithms in cine data and with DENSE view in DENSE data. The results indicated there was less than 3% difference between the strain values obtained from cine and DENSE scans averaging across the regions of the left ventricle in healthy subjects (n=4). There lies great potential in the implementation of cine MRI as a means of strain estimation. As such the measurement of strain from standard cine MRI poses an appealing and potentially clinically useful new option for assessing patients with myocardial dysfunction

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

Principles of cardiovascular magnetic resonance feature tracking and echocardiographic speckle tracking for informed clinical use

Tissue tracking technology of routinely acquired cardiovascular magnetic resonance (CMR) cine acquisitions has increased the apparent ease and availability of non-invasive assessments of myocardial deformation in clinical research and practice. Its widespread availability thanks to the fact that this technology can in principle be applied on images that are part of every CMR or echocardiographic protocol. However, the two modalities are based on very different methods of image acquisition and reconstruction, each with their respective strengths and limitations. The image tracking methods applied are not necessarily directly comparable between the modalities, or with those based on dedicated CMR acquisitions for strain measurement such as tagging or displacement encoding. Here we describe the principles underlying the image tracking methods for CMR and echocardiography, and the translation of the resulting tracking estimates into parameters suited to describe myocardial mechanics. Technical limitations are presented with the objective of suggesting potential solutions that may allow informed and appropriate use in clinical applications

Circumferential strain predicts major adverse cardiovascular events following an acute ST-segment-elevation myocardial infarction

Purpose: To investigate the prognostic value of circumferential left ventricular (LV) strain measured by using cardiac MRI for prediction of major adverse cardiac events (MACE) following an acute ST-segment–elevation myocardial infarction (STEMI). Materials and Methods: Participants with acute STEMI were prospectively enrolled from May 11, 2011, to November 22, 2012. Cardiac MRI was performed at 1.5 T during the index hospitalization. Displacement encoding with stimulated echoes (DENSE) and feature tracking of cine cardiac MRI was used to assess circumferential LV strain. MACE that occurred after discharge were independently assessed by cardiologists blinded to the baseline observations. Results: A total of 259 participants (mean age, 58 years ± 11 [standard deviation]; 198 men [mean age, 58 years ± 11] and 61 women [mean age, 58 years ± 12]) underwent cardiac MRI 2.2 days ± 1.9 after STEMI. Average infarct size was 18% ± 13 of LV mass and circumferential strain was −13% ± 3 (DENSE method) and −24% ± 7 (feature- tracking method). Fifty-one percent (131 of 259 participants) had presence of microvascular obstruction. During a median follow-up period of 4 years, 8% (21 of 259) experienced MACE. Area under the curve (AUC) for DENSE was different from that of feature tracking (AUC, 0.76 vs 0.62; P = .03). AUC for DENSE was similar to that of initial infarct size (P = .06) and extent of microvascular obstruction (P = .08). DENSE-derived strain provided incremental prognostic benefit over infarct size for prediction of MACE (hazard ratio, 1.3; P < .01). Conclusion: Circumferential strain has independent prognostic importance in study participants with acute ST-segment–elevation myocardial infarction

Dynamic finite-strain modelling of the human left ventricle in health and disease using an immersed boundary-finite element method

Detailed models of the biomechanics of the heart are important both for developing improved interventions for patients with heart disease and also for patient risk stratification and treatment planning. For instance, stress distributions in the heart affect cardiac remodelling, but such distributions are not presently accessible in patients. Biomechanical models of the heart offer detailed three-dimensional deformation, stress and strain fields that can supplement conventional clinical data. In this work, we introduce dynamic computational models of the human left ventricle (LV) that are derived from clinical imaging data obtained from a healthy subject and from a patient with a myocardial infarction (MI). Both models incorporate a detailed invariant-based orthotropic description of the passive elasticity of the ventricular myocardium along with a detailed biophysical model of active tension generation in the ventricular muscle. These constitutive models are employed within a dynamic simulation framework that accounts for the inertia of the ventricular muscle and the blood that is based on an immersed boundary (IB) method with a finite element description of the structural mechanics. The geometry of the models is based on data obtained non-invasively by cardiac magnetic resonance (CMR). CMR imaging data are also used to estimate the parameters of the passive and active constitutive models, which are determined so that the simulated end-diastolic and end-systolic volumes agree with the corresponding volumes determined from the CMR imaging studies. Using these models, we simulate LV dynamics from end-diastole to end-systole. The results of our simulations are shown to be in good agreement with subject-specific CMR-derived strain measurements and also with earlier clinical studies on human LV strain distributions

Cardiovascular Magnetic Resonance Imaging in Experimental Models

Cardiovascular magnetic resonance (CMR) imaging is the modality of choice for clinical studies of the heart and vasculature, offering detailed images of both structure and function with high temporal resolution

Image based approach for early assessment of heart failure.

In diagnosing heart diseases, the estimation of cardiac performance indices requires accurate segmentation of the left ventricle (LV) wall from cine cardiac magnetic resonance (CMR) images. MR imaging is noninvasive and generates clear images; however, it is impractical to manually process the huge number of images generated to calculate the performance indices. In this dissertation, we introduce a novel, fast, robust, bi-directional coupled parametric deformable models that are capable of segmenting the LV wall borders using first- and second-order visual appearance features. These features are embedded in a new stochastic external force that preserves the topology of the LV wall to track the evolution of the parametric deformable models control points. We tested the proposed segmentation approach on 15 data sets in 6 infarction patients using the Dice similarity coefficient (DSC) and the average distance (AD) between the ground truth and automated segmentation contours. Our approach achieves a mean DSC value of 0.926±0.022 and mean AD value of 2.16±0.60 mm compared to two other level set methods that achieve mean DSC values of 0.904±0.033 and 0.885±0.02; and mean AD values of 2.86±1.35 mm and 5.72±4.70 mm, respectively. Also, a novel framework for assessing both 3D functional strain and wall thickening from 4D cine cardiac magnetic resonance imaging (CCMR) is introduced. The introduced approach is primarily based on using geometrical features to track the LV wall during the cardiac cycle. The 4D tracking approach consists of the following two main steps: (i) Initially, the surface points on the LV wall are tracked by solving a 3D Laplace equation between two subsequent LV surfaces; and (ii) Secondly, the locations of the tracked LV surface points are iteratively adjusted through an energy minimization cost function using a generalized Gauss-Markov random field (GGMRF) image model in order to remove inconsistencies and preserve the anatomy of the heart wall during the tracking process. Then the circumferential strains are straight forward calculated from the location of the tracked LV surface points. In addition, myocardial wall thickening is estimated by co-allocation of the corresponding points, or matches between the endocardium and epicardium surfaces of the LV wall using the solution of the 3D laplace equation. Experimental results on in vivo data confirm the accuracy and robustness of our method. Moreover, the comparison results demonstrate that our approach outperforms 2D wall thickening estimation approaches

Unravelling the role of the left and right ventricles in pulmonary arterial hypertension: patient and small animal cardiac MRI studies

The definite hemodynamic diagnosis of pulmonary hypertension (PH) requires direct measurement of the pulmonary artery pressure by right heart catheterisation. As right heart catheterisation is an invasive test with a small risk of associated morbidity and mortality, diagnostic algorithms have been devised that combines clinical history and examination, cardio- respiratory assessment by non-imaging techniques and subsequently imaging techniques in patients suspected of having PH. The aim of these initial investigations is to establish a tentative diagnosis of PH, help identify the underlying aetiology and to provide information regarding disease severity and determine response to treatment. Although PH is a disease of the pulmonary vasculature, it is the subsequent right ventricular (RV) failure that is the main cause of morbidity and mortality in PH patient. Thus, RV is the most widely studied of the chambers in PH, however focus has started to move to the left ventricle (LV). Although a disease of the pulmonary circulation and the RV, there is now evidence demonstrating LV abnormalities in PH. Further to this, the atrial chambers offer valuable information when measuring cardiac function as well as in identifying the aetiology of PH. Small animal (rodent) models are increasingly used to identify pathophysiology as well as therapies for PH with the intention of translating the findings to humans. Accurate monitoring of disease in rodents with emphasis on ventricular function and the ability to monitor the disease state without killing the animal is needed

4D FLOW CMR in congenital heart disease

This thesis showed that the use of a cloud-based reconstruction applicationwith advanced eddy currents correction, integrated with interactiveimaging evaluation tools allowed for remote visualization and interpretationof 4D flow data and that was sufficient for gross visualizationof aortic valve regurgitation. Further, this thesis demonstrated that bulkflow and pulmonary regurgitation can be accurately quantified using 4Dflow imaging analyzed. Peak systolic velocity over the pulmonary valvemay be underestimated. However, the measurement of peak systolicvelocity can be optimized if measured at the level of highest velocity inthe pulmonary artery. Also correlated against invasive measurements (inan animal model), this thesis shows that aorta flow and pulmonary flowcan be accurately and simultaneously measured by 4D flow MRI.When applied in clinical practice, 4D flow has extra advantages, of beingable to visualize flow pattern, vorticity and to predict aortic growth. InASD patients it can measure shunt volume directly following the septumframe by frame. In Fontan patients in can visualize better than standardMRI the Fontan circuit and it can measure flow at multiple points alongthe Fontan circuit. We observed in our Fontan population that shunt lesionswere very common, most of the time via veno-venous collaterals.Further using advanced computations, we showed that WSS angle wasthe only independent predictor of aortic growth in BAV patients. We alsoshowed the feasibility of GLS analysis on 4D flow MRI and presented anintegrative approach in which flow and functional data are acquired inone sequence.From the technical point of view, 4D flow MRI has proved to complementthe traditional components of the standard cardiac MR exams, enablingin-depth insights into hemodynamics. At this moment it proved its addedvalue, but in most of the cases it is not able yet to replace the standardexam. This is still due to long scanning times and relatively longpost-processing times.<br/