Advances in computational modelling for personalised medicine after myocardial infarction

Myocardial infarction (MI) is a leading cause of premature morbidity and mortality worldwide. Determining which patients will experience heart failure and sudden cardiac death after an acute MI is notoriously difficult for clinicians. The extent of heart damage after an acute MI is informed by cardiac imaging, typically using echocardiography or sometimes, cardiac magnetic resonance (CMR). These scans provide complex data sets that are only partially exploited by clinicians in daily practice, implying potential for improved risk assessment. Computational modelling of left ventricular (LV) function can bridge the gap towards personalised medicine using cardiac imaging in patients with post-MI. Several novel biomechanical parameters have theoretical prognostic value and may be useful to reflect the biomechanical effects of novel preventive therapy for adverse remodelling post-MI. These parameters include myocardial contractility (regional and global), stiffness and stress. Further, the parameters can be delineated spatially to correspond with infarct pathology and the remote zone. While these parameters hold promise, there are challenges for translating MI modelling into clinical practice, including model uncertainty, validation and verification, as well as time-efficient processing. More research is needed to (1) simplify imaging with CMR in patients with post-MI, while preserving diagnostic accuracy and patient tolerance (2) to assess and validate novel biomechanical parameters against established prognostic biomarkers, such as LV ejection fraction and infarct size. Accessible software packages with minimal user interaction are also needed. Translating benefits to patients will be achieved through a multidisciplinary approach including clinicians, mathematicians, statisticians and industry partners

Three-dimensional echocardiography and 2D-3D speckle tracking imaging in chronic pulmonary hypertension. diagnostic accuracy in detecting hemodynamic signs of RV failure

Background and objective. Our aim was to compare three-dimensional (3D) and 2D and 3D speckle tracking (2D-STE, 3D-STE) echocardiographic parameters with conventional right ventricular (RV) indexes in patients with chronic pulmonary hypertension (PH), and investigate whether these techniques could result in better correlation with hemodynamic variables indicative of heart failure. Methods. Seventy-three adult patients (mean age, 53±13 years; 44% male) with chronic PH of different etiologies were studied by echocardiography and cardiac catheterization (25 precapillary PH from pulmonary arterial hypertension, 23 obstructive pulmonary heart disease, and 23 postcapillary PH from mitral regurgitation). Thirty healthy subjects (mean age, 54±15 years; 43% male) served as controls. Standard 2D measurements (RV-FAC -fractional area change-, TAPSE -tricuspid annular plane systolic excursion-) and mitral and tricuspid tissue Doppler annular velocities were obtained. RV 3D volumes, and global and regional ejection fraction (3D-RVEF) were determined. RV strains were calculated by 2D-STE and 3D-STE. Results. RV 3D global-free-wall longitudinal strain (3DGFW-RVLS), 2D global-free-wall longitudinal strain (GFW-RVLS), apical-free-wall longitudinal strain (AFW-RVLS), basal-free-wall longitudinal strain (BFW-RVLS), and 3D-RVEF were lower in patients with pre-capillary PH (p<0.0001) and post-capillary PH (p<0.01) compared to controls. 3DGFW-RVLS (HR 4.6, 95% CI 2.79-8.38, p=0.004) and 3D-RVEF (HR 5.3, 95% CI 2.85-9.89, p=0.002) were independent predictors of mortality. ROC curves showed that the thresholds offering an adequate compromise between sensitivity and specificity for detecting hemodynamic signs of RV failure were 39% for 3D-RVEF (AUC 0.89), -17% for 3DGFW-RVLS (AUC 0.88), -18% for GFW-RVLS (AUC 0.88), -16% for AFW-RVLS (AUC 0.85), 16mm for TAPSE (AUC 0.67), and 38% for RV-FAC (AUC 0.62). Conclusions. In chronic PH, 3D, 2D-STE and 3D-STE parameters indicate global and regional RV dysfunction that is associated with RV failure hemodynamics better than conventional echo indices

Reproducibility of 4D cardiac computed tomography feature tracking myocardial strain and comparison against speckle-tracking echocardiography in patients with severe aortic stenosis.

BACKGROUND Myocardial strain is an established parameter for the assessment of cardiac function and routinely derived from speckle tracking echocardiography (STE). Novel post-processing tools allow deformation imaging also by 4D cardiac computed tomography angiography (CCT). This retrospective study aims to analyze the reproducibility of CCT strain and compare it to that of STE. METHODS Left (LV) and right ventricular (RV), and left atrial (LA) ejection fraction (EF), dimensions, global longitudinal (GLS), circumferential (GCS) and radial strain (GRS) were determined by STE and CCT feature tracking in consecutive patients with severe aortic stenosis evaluated for transcatheter aortic valve implantation. RESULTS 106 patients (mean age 79.9 ​± ​7.8, 44.3% females) underwent CCT at a median of 3 days (IQR 0-28 days) after STE. In CCT, strain measures showed good to excellent reproducibility (intra- and inter-reader intraclass correlation coefficient ≥0.75) consistently in the LV, RV and LA. In STE, only LV GLS and LA GLS yielded good reproducibility, whereas LV GCS and LV GRS showed moderate, and RV GLS and free wall longitudinal strain (FWLS) poor reproducibility. Agreement between CCT and STE was strong for LV GLS only, while other strain features displayed moderate (LV GCS, LA GLS) or weak (LV GRS, RV GLS and FWLS) inter-modality correlation. CONCLUSION LV, RV and LA CCT strain assessments were highly reproducible. While a strong agreement to STE was found for LV GLS, inter-modality correlation was moderate or weak for LV GCS, LV GRS, and RV and LA longitudinal strain, possibly related to poor reproducibility of STE measurements

Quantitative validation of optical flow based myocardial strain measures using sonomicrometry

Dynamic cardiac metrics, including myocardial strains and displacements, provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, largely 2D strain measures are used despite that cardiac motions are complex 3D volumes over time. Recent advances in 4D ultrasound enable the capability to capture such complex motion in a single image data set. In our previous work, a 4D optical flow based motion tracking algorithm was developed to extract full 4D dynamic cardiac metrics from such 4D ultrasound data. In order to quantitatively evaluate this tracking method, in-vivo coronary artery occlusion experiments at various locations were performed on three canine hearts. Each dog was screened with 4D ultrasound and sonomicrometry data was acquired during each occlusion study. The 4D ultrasound data from these experiments was then analyzed with the tracking method and estimated principal strain measures were directly compared to those recorded by sonomicrometry. Strong agreement was observed independently for the three canine hearts. This is the first validation study of optical flow based strain estimation for 4D ultrasound with a direct comparison with sonomicrometry using in-vivo data

Left atrial trajectory impairment in hypertrophic cardiomyopathy disclosed by geometric morphometrics and parallel transport

The analysis of full Left Atrium (LA) deformation and whole LA deformational trajectory in time has been poorly investigated and, to the best of our knowledge, seldom discussed in patients with Hypertrophic Cardiomyopathy. Therefore, we considered 22 patients with Hypertrophic Cardiomyopathy (HCM) and 46 healthy subjects, investigated them by three-dimensional Speckle Tracking Echocardiography, and studied the derived landmark clouds via Geometric Morphometrics with Parallel Transport. Trajectory shape and trajectory size were different in Controls versus HCM and their classification powers had high AUC (Area Under the Receiving Operator Characteristic Curve) and accuracy. The two trajectories were much different at the transition between LA conduit and booster pump functions. Full shape and deformation analyses with trajectory analysis enabled a straightforward perception of pathophysiological consequences of HCM condition on LA functioning. It might be worthwhile to apply these techniques to look for novel pathophysiological approaches that may better define atrio-ventricular interaction

Left ventricular global longitudinal strain in bicupsid aortic valve patients: head-to-head comparison between computed tomography, 4D flow cardiovascular magnetic resonance and speckle-tracking echocardiography

Left ventricular global longitudinal strain (LVGLS) analysis is a sensitive measurement of myocardial deformation most often done using speckle-tracking transthoracic echocardiography (TTE). We propose a novel approach to measure LVGLS using feature-tracking software on the magnitude dataset of 4D flow cardiovascular magnetic resonance (CMR) and compare it to dynamic computed tomography (CT) and speckle tracking TTE derived measurements. In this prospective cohort study 59 consecutive adult patients with a bicuspid aortic valve (BAV) were included. The study protocol consisted of TTE, CT, and CMR on the same day. Image analysis was done using dedicated feature-tracking (4D flow CMR and CT) and speckle-tracking (TTE) software, on apical 2-, 3-, and 4-chamber long-axis multiplanar reconstructions (4D flow CMR and CT) or standard apical 2-, 3-, and 4-chamber acquisitions (TTE). CMR and CT GLS analysis was feasible in all patients. Good correlations were observed for GLS measured by CMR (− 21 ± 3%) and CT (− 20 ± 3%) versus TTE (− 20 ± 3%, Pearson’s r: 0.67 and 0.65, p 0.61, p < 0.001). Feature-tracking GLS analysis is feasible using the magnitude images acquired with 4D flow CMR. GLS measurement by CMR correlates well with CT and speckle-tracking 2D TTE. GLS analysis on 4D flow CMR allows for an integrative approach, integrating flow and functional data in a single sequence. Not applicable, observational study

Reproducibility of 4D cardiac computed tomography feature tracking myocardial strain and comparison against speckle-tracking echocardiography in patients with severe aortic stenosis

Background: Myocardial strain is an established parameter for the assessment of cardiac function and routinely derived from speckle tracking echocardiography (STE). Novel post-processing tools allow deformation imaging also by 4D cardiac computed tomography angiography (CCT). This retrospective study aims to analyze the reproducibility of CCT strain and compare it to that of STE. Methods: Left (LV) and right ventricular (RV), and left atrial (LA) ejection fraction (EF), dimensions, global longitudinal (GLS), circumferential (GCS) and radial strain (GRS) were determined by STE and CCT feature tracking in consecutive patients with severe aortic stenosis evaluated for transcatheter aortic valve implantation. Results: 106 patients (mean age 79.9 ​± ​7.8, 44.3% females) underwent CCT at a median of 3 days (IQR 0–28 days) after STE. In CCT, strain measures showed good to excellent reproducibility (intra- and inter-reader intraclass correlation coefficient ≥0.75) consistently in the LV, RV and LA. In STE, only LV GLS and LA GLS yielded good reproducibility, whereas LV GCS and LV GRS showed moderate, and RV GLS and free wall longitudinal strain (FWLS) poor reproducibility. Agreement between CCT and STE was strong for LV GLS only, while other strain features displayed moderate (LV GCS, LA GLS) or weak (LV GRS, RV GLS and FWLS) inter-modality correlation. Conclusion: LV, RV and LA CCT strain assessments were highly reproducible. While a strong agreement to STE was found for LV GLS, inter-modality correlation was moderate or weak for LV GCS, LV GRS, and RV and LA longitudinal strain, possibly related to poor reproducibility of STE measurements

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