Quantification of left ventricular longitudinal strain, strain rate, velocity and displacement in healthy horses by 2-dimensional speckle tracking

Background: The quantification of equine left ventricular (LV) function is generally limited to short-axis M-mode measurements. However, LV deformation is 3-dimensional (3D) and consists of longitudinal shortening, circumferential shortening, and radial thickening. In human medicine, longitudinal motion is the best marker of subtle myocardial dysfunction. Objectives: To evaluate the feasibility and reliability of 2-dimensional speckle tracking (2DST) for quantifying equine LV longitudinal function. Animals: Ten healthy untrained trotter horses; 9.6 +/- 4.4 years; 509 +/- 58 kg. Methods : Prospective study. Repeated echocardiographic examinations were performed by 2 observers from a modified 4-chamber view. Global, segmental, and averaged peak values and timing of longitudinal strain (SL), strain rate (SrL), velocity (VL), and displacement (DL) were measured in 4 LV wall segments. The inter- and intraobserver within- and between-day variability was assessed by calculating the coefficients of variation for repeated measurements. Results: 2DST analysis was feasible in each exam. The variability of peak systolic values and peak timing was low to moderate, whereas peak diastolic values showed a higher variability. Significant segmental differences were demonstrated. DL and VL presented a prominent base-to-midwall gradient. SL and SrL values were similar in all segments except the basal septal segment, which showed a significantly lower peak SL occurring about 60 ms later compared with the other segments. Conclusions and Clinical Importance 2DST is a reliable technique for measuring systolic LV longitudinal motion in healthy horses. This study provides preliminary reference values, which can be used when evaluating the technique in a clinical setting

Myocardial strain in healthy adults across a broad age range as revealed by cardiac magnetic resonance imaging at 1.5 and 3.0T: associations of myocardial strain with myocardial region, age, and sex

Purpose: We assessed myocardial strain using cine displacement encoding with stimulated echoes (DENSE) using 1.5T and 3.0T MRI in healthy adults. Materials and Methods: Healthy adults without any history of cardiovascular disease underwent MRI at 1.5T and 3.0T within 2 days. The MRI protocol included b-SSFP, 2D cine-EPI-DENSE, and late gadolinium enhancement in subjects>45 years. Acquisitions were divided into 6 segments, global and segmental peak longitudinal and circumferential strain were derived and analyzed by field strength, age and gender. Results: 89 volunteers (mean age 44.8 ± 18.0 years, range: 18-87 years) underwent MRI at 1.5T, and 88 of these subjects underwent MRI at 3.0T (1.4±1.4 days between the scans). Compared with 3.0T, the magnitudes of global circumferential (-19.5±2.6% vs. -18.47±2.6%; p=0.001) and longitudinal (-12.47±3.2% vs -10.53±3.1%; p=0.004) strain were greater at 1.5T. At 1.5T, longitudinal strain was greater in females than in males: -10.17±3.4% vs. -13.67±2.4%; p=0.001. Similar observations occurred for circumferential strain at 1.5T (-18.72±2.2% vs. -20.10±2.7%; p=0.014) and at 3.0T (-17.92 ± 1.8% vs -19.1 ± 3.1%; p=0.047). At 1.5T, longitudinal and circumferential strain were not associated with age after accounting for sex (longitudinal strain p= 0.178, circumferential strain p= 0.733). At 3.0T, longitudinal and circumferential strain were associated with age. (p<0.05) Longitudinal strain values were greater in the apico-septal, basal-lateral and mid-lateral segments and circumferential strain in the inferior, infero-lateral and antero-lateral LV segments. Conclusion: Myocardial strain parameters as revealed by cine-DENSE at different MRI field strengths were associated with myocardial region, age and sex

Therapeutic Effect of Targeting Branched-Chain Amino Acid Catabolic Flux in Pressure-Overload Induced Heart Failure.

Background Branched-chain amino acid (BCAA) catabolic defect is an emerging metabolic hallmark in failing hearts in human and animal models. The therapeutic impact of targeting BCAA catabolic flux under pathological conditions remains understudied. Methods and Results BT2 (3,6-dichlorobenzo[b]thiophene-2-carboxylic acid), a small-molecule inhibitor of branched-chain ketoacid dehydrogenase kinase, was used to enhance BCAA catabolism. After 2 weeks of transaortic constriction, mice with significant cardiac dysfunctions were treated with vehicle or BT2. Serial echocardiograms showed continuing pathological deterioration in left ventricle of the vehicle-treated mice, whereas the BT2-treated mice showed significantly preserved cardiac function and structure. Moreover, BT2 treatment improved systolic contractility and diastolic mechanics. These therapeutic benefits appeared to be independent of impacts on left ventricle hypertrophy but associated with increased gene expression involved in fatty acid utilization. The BT2 administration showed no signs of apparent toxicity. Conclusions Our data provide the first proof-of-concept evidence for the therapeutic efficacy of restoring BCAA catabolic flux in hearts with preexisting dysfunctions. The BCAA catabolic pathway represents a novel and potentially efficacious target for treatment of heart failure

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

Fast and accurate classification of echocardiograms using deep learning

Echocardiography is essential to modern cardiology. However, human interpretation limits high throughput analysis, limiting echocardiography from reaching its full clinical and research potential for precision medicine. Deep learning is a cutting-edge machine-learning technique that has been useful in analyzing medical images but has not yet been widely applied to echocardiography, partly due to the complexity of echocardiograms' multi view, multi modality format. The essential first step toward comprehensive computer assisted echocardiographic interpretation is determining whether computers can learn to recognize standard views. To this end, we anonymized 834,267 transthoracic echocardiogram (TTE) images from 267 patients (20 to 96 years, 51 percent female, 26 percent obese) seen between 2000 and 2017 and labeled them according to standard views. Images covered a range of real world clinical variation. We built a multilayer convolutional neural network and used supervised learning to simultaneously classify 15 standard views. Eighty percent of data used was randomly chosen for training and 20 percent reserved for validation and testing on never seen echocardiograms. Using multiple images from each clip, the model classified among 12 video views with 97.8 percent overall test accuracy without overfitting. Even on single low resolution images, test accuracy among 15 views was 91.7 percent versus 70.2 to 83.5 percent for board-certified echocardiographers. Confusional matrices, occlusion experiments, and saliency mapping showed that the model finds recognizable similarities among related views and classifies using clinically relevant image features. In conclusion, deep neural networks can classify essential echocardiographic views simultaneously and with high accuracy. Our results provide a foundation for more complex deep learning assisted echocardiographic interpretation.Comment: 31 pages, 8 figure

Robust Cardiac Motion Estimation using Ultrafast Ultrasound Data: A Low-Rank-Topology-Preserving Approach

Cardiac motion estimation is an important diagnostic tool to detect heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of the complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate the cardiac motion using ultrafast ultrasound data. -- Our solution is based on a variational formulation characterized by the L2-regularized class. The displacement is represented by a lattice of b-splines and we ensure robustness by applying a maximum likelihood type estimator. While this is an important part of our solution, the main highlight of this paper is to combine a low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati Matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. While maintaining the accuracy of the solution, the low-rank preprocessing is shown to speed up the convergence of the variational problem. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that experience motion.Comment: 15 pages, 10 figures, Physics in Medicine and Biology, 201

Assessing the performance of ultrafast vector flow imaging in the neonatal heart via multiphysics modeling and In vitro experiments

Ultrafast vector flow imaging would benefit newborn patients with congenital heart disorders, but still requires thorough validation before translation to clinical practice. This paper investigates 2-D speckle tracking (ST) of intraventricular blood flow in neonates when transmitting diverging waves at ultrafast frame rate. Computational and in vitro studies enabled us to quantify the performance and identify artifacts related to the flow and the imaging sequence. First, synthetic ultrasound images of a neonate's left ventricular flow pattern were obtained with the ultrasound simulator Field II by propagating point scatterers according to 3-D intraventricular flow fields obtained with computational fluid dynamics (CFD). Noncompounded diverging waves (opening angle of 60 degrees) were transmitted at a pulse repetition frequency of 9 kHz. ST of the B-mode data provided 2-D flow estimates at 180 Hz, which were compared with the CFD flow field. We demonstrated that the diastolic inflow jet showed a strong bias in the lateral velocity estimates at the edges of the jet, as confirmed by additional in vitro tests on a jet flow phantom. Furthermore, ST performance was highly dependent on the cardiac phase with low flows (< 5 cm/s), high spatial flow gradients, and out-of-plane flow as deteriorating factors. Despite the observed artifacts, a good overall performance of 2-D ST was obtained with a median magnitude underestimation and angular deviation of, respectively, 28% and 13.5 degrees during systole and 16% and 10.5 degrees during diastole