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Time-to-peak measurements and single-parameter observations are cumbersome and often confusing for quantifying local changes in myocardial function. Recent spatiotemporal normalization techniques can provide a global picture of myocardial motion and strain patterns and overcome some of these limitations. Despite these advances, the quantification of pattern changes remains descriptive, which limits their relevance for longitudinal studies. Our paper provides a new perspective to the longitudinal analysis of myocardial motion. Non-rigid registration (diffeomorphic registration via currents) is used to match pairs of patterns, and pattern changes are inferred from the registration output. Scalability is added to the different components of the input patterns in order to tune up the contributions of the spatial, temporal and magnitude dimensions to data changes, which are of interest for our application. The technique is illustrated on 2D echocardiographic sequences from 15 patients with hypertrophic obstructive cardiomyopathy. These patients underwent biventricular pacing, which aims at provoking mechanical dyssynchrony to reduce left ventricular outflow tract (LVOT) obstruction. We demonstrate that our method can automatically quantify timing and magnitude changes in myocardial motion between baseline (non-paced) and 1 year follow-up (pacing on), resulting in a more robust analysis of complex patterns and subtle changes. Our method helps confirming that the reduction of LVOT pressure gradient actually comes from the induction of the type of dyssynchrony that was expected., (Copyright © 2014 Elsevier B.V. All rights reserved.)

In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the abnormality in the motion of a given subject against a reference population, at every location in time and space. The critical computational cost inherent to the construction of an atlas is highly reduced by the definition of myocardial velocities under a small displacements hypothesis. The indexes we propose are of notable interest for the assessment of anomalies in cardiac mobility and synchronicity when applied, for instance, to candidate selection for cardiac resynchronization therapy (CRT). We built an atlas of normality using 2D ultrasound cardiac sequences from 21 healthy volunteers, to which we compared 14 CRT candidates with left ventricular dyssynchrony (LVDYS). We illustrate the potential of our approach in characterizing septal flash, a specific motion pattern related to LVDYS and recently introduced as a very good predictor of response to CRT., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Objective: To investigate the presence of any regional myocardial deformation abnormalities in Marfan syndrome (MFS) and determine the benefits of using advanced echocardiography compared to conventional techniques., Background: Myocardial dysfunction in MFS may be caused by extracellular matrix remodeling thus, resulting in uniform reduced functionality. However, increased aortic stiffness may cause segmental ventricular abnormalities. Strain rate imaging (SRI) constitutes a validated technique to assess regional deformation in various clinical conditions. With this in mind, we aimed to investigate biventricular function in MFS using SRI., Methods: Forty-four MFS patients (mean age 30 ± 12 years, 26 men) and 49 controls without valvular disease were examined using SRI. Ejection fraction (EF) was calculated by the Simpson's biplane method. Biventricular deformation was assessed by measuring strain/strain rate. Strain values were divided by left ventricular (LV) end-diastolic volume to adjust LV deformation for geometry changes providing a strain index (SI). Aortic stiffness was evaluated using the β-stiffness index., Results: EF (%) was reduced in MFS patients (59 ± 5 vs 72 ± 4, P < 0.001), whereas β-stiffness was increased (P < 0.001). LV radial and LV and right ventricular (RV) long-axis strain values (%) were reduced in the patient group (70 ± 17 vs 93 ± 10; 19 ± 2 vs 25 ± 2; 30 ± 9 vs 36 ± 8, respectively, P < 0.001). Strain rate measurements were also reduced (P < 0.001). In a multiple regression analysis, MFS diagnosis was negatively associated with LV SI (-0.262 [-0.306, -0.219], P < 0.001). β-Stiffness was negatively associated with SI obtained from the septum, inferior and anterior walls. ROC analyses demonstrated that SRI, when compared with conventional echocardiography, had higher sensitivity and specificity in predicting biventricular dysfunction in MFS., Conclusions: Our study showed a uniform reduction in biventricular deformation in MFS. These findings suggest that assessment of myocardial function using advanced echocardiographic techniques could be more accurate in MFS patient evaluation than conventional echocardiography alone., (© 2011, Wiley Periodicals, Inc.)

Aims: Previous studies provided evidence about left ventricular systolic and diastolic dysfunction in adults with Marfan syndrome (MFS). However, in the literature, data on right ventricular and bi-atrial diastolic function are limited. We aimed to investigate whether, in the absence of significant valvular disease, diastolic dysfunction is present not only in both ventricles but also in the atrial cavities., Methods and Results: Seventy-two adult unoperated MFS patients and 73 controls without significant differences in age, sex, and body surface area from the patient group were studied using two-dimensional, pulsed, and colour-Doppler and tissue-Doppler imaging (TDI). Biventricular early filling measurements were significantly decreased in MFS patients when compared with controls (P < 0.001). Pulsed TDI early filling measurements obtained from five mitral annular regions and over the lateral tricuspid valve corner were significantly reduced in the patient group (P < 0.001). Indices reflecting atrial function at the reservoir, conduit and contractile phases were also significantly decreased in MFS patients (P < 0.001)., Conclusion: This study demonstrated significant biventricular diastolic and biatrial systolic and diastolic dysfunction in MFS patients. Our findings suggest that MFS affects diastolic function independently. Diastolic abnormalities could be attributed to fibrillin-1 deficiency and dysregulation of transforming growth factor-beta activity in the cardiac extracellular matrix.

In this paper, we propose a complete framework for the automatic detection and quantification of abnormal heart motion patterns using Statistical Atlases of Motion built from healthy populations. The method is illustrated on CRT patients with identified cardiac dyssynchrony and abnormal septal motion on 2D ultrasound (US) sequences. The use of the 2D US modality guarantees that the temporal resolution of the image sequences is high enough to work under a small displacements hypothesis. Under this assumption, the computed displacement fields can be directly considered as cardiac velocities. Comparison of subjects acquired with different spatiotemporal resolutions implies the reorientation and temporal normalization of velocity fields in a common space of coordinates. Statistics are then performed on the reoriented vector fields. Results show the ability of the method to correctly detect abnormal motion patterns and quantify their distance to normality. The use of local p-values for quantifying abnormal motion patterns is believed to be a promising strategy for computing new markers of cardiac dyssynchrony for better characterizing CRT candidates.

Spectral estimation is a major component in studies aiming at characterizing biological tissues through the analysis of backscattered radio frequency (RF) ultrasonic signals and images. However, conventional spectral estimation techniques yield a well-known trade-off between spatial resolution and variance. The backscattered signals are stochastic by nature, so short-term local analysis results in a high variance of the estimates, which cannot efficiently be reduced through conventional spatial averaging. We address this issue by describing a spectral estimation technique that reduces the variance of the estimates (by smoothing the local estimates in spectrally homogeneous regions) while preserving spectral discontinuities (i.e., the smoothing is not performed across regions with different spectral contents). The proposed approach is set in a Bayesian framework and is based on local autoregressive (AR) estimation, constrained by smoothness priors. These smoothness priors are introduced through a Markov random field in which the associated potential functions are nonquadratic, allowing thereby to preserve discontinuity. The method is validated on simulated RF images and tested on echocardiographic images acquired in vivo. The results are compared to the estimates provided by the conventional Burg technique. These results clearly demonstrate the ability of the proposed approach to improve spectral estimation in terms of variance reduction and discontinuity detection.

BACKGROUND: Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left ventricular function at rest and exercise objectively captures differences between HFpEF and healthy subjects. METHODS AND RESULTS: One hundred fifty-six subjects aged >60 years (72 HFpEF+33 healthy for the initial analyses; 24 hypertensive+27 breathless for independent evaluation) underwent stress echocardiography, in the MEDIA study (Metabolic Road to Diastolic Heart Failure). Left ventricular long-axis myocardial velocity patterns were analyzed using an unsupervised ML algorithm that orders subjects according to their similarity, allowing exploration of the main trends in velocity patterns. ML identified a continuum from health to disease, including a transition zone associated to an uncertain diagnosis. Clinical validation was performed (1) to characterize the main trends in the patterns for each zone, which corresponded to known characteristics and new features of HFpEF; the ML-diagnostic zones differed for age, body mass index, 6-minute walk distance, B-type natriuretic peptide, and left ventricular mass index (P<0.05) and (2) to evaluate the consistency of the proposed groupings against diagnosis by current clinical criteria; correlation with diagnosis was good (κ, 72.6%; 95% confidence interval, 58.1-87.0); ML identified 6% of healthy controls as HFpEF. Blinded reinterpretation of imaging from subjects with discordant clinical and ML diagnoses revealed abnormalities not included in diagnostic criteria. The algorithm was applied independently to another 51 subjects, classifying 33% of hypertensive and 67% of breathless controls as mild-HFpEF. CONCLUSIONS: The analysis of left ventricular long-axis function on exercise by interpretable ML may improve the diagnosis and understanding of HFpEF. [ABSTRACT FROM AUTHOR]

Background: Extracellular matrix remodeling in the aortic wall results in increased aortic stiffness (AoS) in Marfan syndrome (MFS). Pulsed-wave velocity (PWV) constitutes the best indirect AoS measurement. We aimed to assess PWV in MFS patients using two-dimensional (2D) and Doppler echocardiography. Methods: Thirty-one MFS patients, (mean age 31 ± 14 years, 16 men) and 31 controls were examined. Blood flow was recorded in the aorta near the aortic valve and immediately after in the descending aorta with simultaneous electrocardiography. PWV was calculated by dividing the distance between the two sample volume positions (D) by the time difference (TD) between the intervals from the QRS start to the ascending and descending aortic flow onsets. B-stiffness was also measured. Results: TD (described in 'Methods' section) and, aortic arch length were significantly increased in MFS patients, P < 0.001. Thus, PWV values were significantly higher in patients when compared with controls, 7.20 m/s (5.12, 9.43) versus 4.64 m/s (3.37, 6.24), P < 0.001. B-stiffness was also significantly increased in MFS patients; 5.15 (3.69, 7.65) versus 2.44 (1.82, 3.66), P < 0.001. Multiple regression analysis showed a positive association with MFS diagnosis and age, (P = 0.002 and 0.009, respectively). Reproducibility of PWV measurements was <5%. Conclusions: AoS was significantly higher in MFS patients as expected. Our data demonstrated that PWV measurements can be performed, in the absence of serious musculoskeletal abnormalities in MFS adults, as part of a cardiac ultrasound scan. This technique can be helpful in diagnosis and management in MFS. (Echocardiography 2011;28:29-37) [ABSTRACT FROM AUTHOR]

We investigated left ventricular (LV) remodeling, mechanics, systolic and diastolic function, combined with clinical characteristics and heart-failure treatment in association to death or heart-transplant (DoT) in pediatric idiopathic, genetic or familial dilated cardiomyopathy (DCM), using interpretable machine-learning. Echocardiographic and clinical data from pediatric DCM and healthy controls were retrospectively analyzed. Machine-learning included whole cardiac-cycle regional longitudinal strain, aortic, mitral and pulmonary vein Doppler velocity traces, age and body surface area. We used unsupervised multiple kernel learning for data dimensionality reduction, positioning patients based on complex conglomerate information similarity. Subsequently, k-means identified groups with similar phenotypes. The proportion experiencing DoT was evaluated. Pheno-grouping identified 5 clinically distinct groups that were associated with differing proportions of DoT. All healthy controls clustered in groups 1 to 2, while all, but one, DCM subjects, clustered in groups 3 to 5; internally validating the algorithm. Cluster-5 comprised the oldest, most medicated patients, with combined systolic and diastolic heart-failure and highest proportion of DoT. Cluster-4 included the youngest patients characterized by severe LV remodeling and systolic dysfunction, but mild diastolic dysfunction and the second-highest proportion of DoT. Cluster-3 comprised young patients with moderate remodeling and systolic dysfunction, preserved apical strain, pronounced diastolic dysfunction and lowest proportion of DoT. Interpretable machine-learning, using full cardiac-cycle systolic and diastolic data, mechanics and clinical parameters, can potentially identify pediatric DCM patients at high-risk for DoT, and delineate mechanisms associated with risk. This may facilitate more precise prognostication and treatment of pediatric DCM. [ABSTRACT FROM AUTHOR]

We propose an independent objective method to characterize different patterns of functional responses to stress in the heart failure with preserved ejection fraction (HFPEF) syndrome by combining multiple temporally-aligned myocardial velocity traces at rest and during exercise, together with temporal information on the occurrence of cardiac events (valves openings/closures and atrial activation). The method builds upon multiple kernel learning, a machine learning technique that allows the combination of data of different nature and the reduction of their dimensionality towards a meaningful representation (output space). The learning process is kept unsupervised, to study the variability of the input traces without being conditioned by data labels. To enhance the physiological interpretation of the output space, the variability that it encodes is analyzed in the space of input signals after reconstructing the velocity traces via multiscale kernel regression. The methodology was applied to 2D sequences from a stress echocardiography protocol from 55 subjects (22 healthy, 19 HFPEF and 14 breathless subjects). The results confirm that characterization of the myocardial functional response to stress in the HFPEF syndrome may be improved by the joint analysis of multiple relevant features. [ABSTRACT FROM AUTHOR]

Echocardiography has a leading role in the routine assessment and diagnosis of hypertrophic ventricles. However, the use of M-mode echocardiography and measurement of global left ventricular function may be misleading. Traditionally, systolic function was thought to be preserved in patients with hypertrophic myopathies until the late stages of the disease, and hypertrophic myopathies were thought to affect the myocardium more diffusely than ischemic heart disease. Ultrasound deformation imaging, either by Doppler myocardial imaging or speckle tracking, provides more-sensitive detection of regional myocardial motion and deformation than standard echocardiography. Basic and clinical studies that apply these techniques have revealed early, often subclinical impairment in systolic function. This information allows the detection and treatment of myocardial dysfunction at an early stage, which is of high clinical importance. Physiological hypertrophic remodeling seen in athletes differs from pathological myocardial hypertrophy, which can be caused by compensatory reactive hypertrophy owing to pressure overload in patients with aortic stenosis or hypertension, as well as amyloidosis, Fabry disease or Friedreich ataxia. Each of the etiologies associated with hypertrophy demonstrate distinct regional changes in myocardial deformation, which allows identification of the underlying processes, and will improve the assessment and follow-up of patients with hypertrophic myopathies. [ABSTRACT FROM AUTHOR]