Mihaela Silvia Amzulescu

Three-dimensional echocardiographic quantification of the left-heart chambers using an automated adaptive analytics algorithm: multicentre validation study.

Aims Although recommended by current guidelines, adoption of three-dimensional echocardiographic (3DE) chamber quantification in clinical practice has lagged because of time-consuming analysis. We recently validated an automated algorithm that measures left atrial (LA) and left ventricular (LV) volumes and ejection fraction (EF). This study aimed to determine the accuracy and reproducibility of these measurements in a multicentre setting. Methods and results 180 patients underwent 3DE imaging (Philips) at six sites. Images were analysed using automated HeartModel (HM) software with endocardial border correction when necessary and by manual tracing. Measurements were performed by each site and by the Core Laboratory (CL) as the reference. Inter-technique comparisons included HM measurements by the sites against manual tracing by CL, and showed strong correlations (r-values: LVEDV: 0.97, LVESV: 0.97, LVEF: 0.88, LAV: 0.96), with the automated technique slightly underestimating LV volumes (biases: LVEDV: -14 ± 20 ml, LVESV: -6 ± 20 ml), LVEF (-2 ± 7%) and LAV (-9 ± 10 ml). Intra-technique comparisons included HM measurements by the sites against CL, with and without corrections. Corrections were unnecessary or minimal in most patients, and improved the measurements only modestly. Comparisons without corrections showed perfect agreement for all parameters. With corrections, correlations were better (r-values: LVEDV: 0.99, LVESV: 0.99, LVEF: 0.94, LAV: 0.99) and biases (LVEDV: -8 ± 12 ml, LVESV: -6 ± 12 ml, LVEF: 1 ± 5%, LAV: -10 ± 6 ml) smaller than in inter-technique comparison. All automated measurements with corrections were more reproducible than manual measurements. Conclusion Automated 3DE analysis of left-heart chambers is an accurate alternative to conventional manual methodology, which yields almost the same values across laboratories and is more reproducible. This technique may contribute towards full integration of 3DE quantification into clinical routine.

Head-to-Head Comparison of Global and Regional Two-Dimensional Speckle Tracking Strain Versus Cardiac Magnetic Resonance Tagging in a Multicenter Validation StudyCLINICAL PERSPECTIVE

Background— Despite widespread use to characterize and refine prognosis, validation data of two-dimensional (2D) speckle tracking (2DST) echocardiography myocardial strain measurement remain scarce. Methods and Results— Global and regional subendocardial peak-systolic Lagrangian longitudinal (LS) and circumferential strain (CS) by 2DST and 2D-tagged (2DTagg) cardiac magnetic resonance imaging were compared against sonomicrometry in a dynamic heart phantom and among each other in 136 patients included prospectively at 2 centers. The ability of regional LS and CS 2DST and 2DTagg to identify late gadolinium enhancement was compared using receiver operating characteristics curves. In vitro, both LS-2DST and 2DTagg highly agreed with sonomicrometry (intraclass correlation coefficient [ICC], 0.89 and ICC, 0.90, both P<0.001 with −3±2.8% and 0.34±4.35% bias, respectively). In patients, both global LS and global CS 2DST agreed well with 2DTagg (ICC, 0.89 and ICC, 0.80; P<0.001); however, they provided systematically greater values (relative bias of −37±27% and −25±37% for global LS and global CS, respectively). On regional basis, however, ICC (from 0.17 to 0.81) and relative bias (from −9 to −98%) between 2DST and 2DTagg varied strongly among segments. Ability to discriminate infarcted versus noninfarcted segments by late gadolinium enhancement was similarly good for regional LS 2DTagg and 2DST (area under the curve, 0.66 versus 0.59; P=0.08), while it was lower for CS 2DST than 2DTagg (area under the curve, 0.61 versus 0.75; P<0.001). Conclusions— The high accuracy against sonomicrometry and good agreement of global LS and global CS by 2DST and 2DTagg confirm the overall validity of 2DST strain measurement. Yet, higher intertechnique segmental variability and lower ability for detecting infarct suggest that 2DST strain estimates may be less performant on regional than on global basis.

Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion

A cardiac motion atlas provides a space of reference in which the cardiac motion fields of a cohort of subjects can be directly compared. From such atlases, descriptors can be learned for subsequent diagnosis and characterization of disease. Traditionally, such atlases have been formed from imaging data acquired using a single modality. In this work we propose a framework for building a multimodal cardiac motion atlas from MR and ultrasound data and incorporate a multiview classifier to exploit the complementary information provided by the two modalities. We demonstrate that our novel framework is able to detect non ischemic dilated cardiomyopathy patients from ultrasound data alone, whilst still exploiting the MR based information from the multimodal atlas. We evaluate two different approaches based on multiview learning to implement the classifier and achieve an improvement in classification performance from 77.5% to 83.50% compared to the use of US data without the multimodal atlas.

PROGNOSTIC VALUE OF RIGHT VENTRICULAR SYSTOLIC DYSFUNCTION IN HEART FAILURE WITH REDUCED EJECTION FRACTION

Recent studies showed that right ventricular systolic dysfunction (RVSD) predicts worse prognosis in patients with heart failure (HF). We thus sought to evaluate the prognostic value of RVSD assessed by cardiac magnetic resonance (CMR) in HF patients with low ejection fraction due to idiopathic (DCM

Improvements of Myocardial Deformation Assessment by Three-Dimensional Speckle-Tracking versus Two-Dimensional Speckle-Tracking Revealed by Cardiac Magnetic Resonance Tagging

Background: In prior work, the authors demonstrated that two‐dimensional speckle‐tracking (2DST) correlated well but systematically overestimated global longitudinal strain (LS) and circumferential strain (CS) compared with two‐dimensional cardiac magnetic resonance tagging (2DTagg) and had poor agreement on a segmental basis. Because three‐dimensional speckle‐tracking (3DST) has recently emerged as a new, more comprehensive evaluation of myocardial deformation, this study was undertaken to evaluate whether it would compare more favorably with 2DTagg than 2DST. Methods: In a prospective two‐center trial, 119 subjects (29 healthy volunteers, 63 patients with left ventricular dysfunction, and 27 patients with left ventricular hypertrophy) underwent 2DST, 3DST, and 2DTagg. Global, regional (basal, mid, and apical), and segmental (18 and 16 segments per patient) LS and CS by 2DST and 3DST were compared with 2DTagg using intraclass correlation coefficients (ICCs) and Bland‐Altman analysis. Test‐retest reproducibility of 3DST and 2DST was compared in 48 other patients. Results: Both global LS and CS by 3DST agreed better with 2DTagg (ICC = 0.89 and ICC = 0.83, P < .001 for both; bias = 0.5 ± 2.3% and 0.2 ± 3%) than 2DST (ICC = 0.65 and ICC = 0.55, P < .001 for both; bias = −5.5 ± 2.5% and −7 ± 5.3%). Unlike 2DST, 3DST did not overestimate deformation at the regional and particularly the apical levels and at the segmental level had lower bias (LS, 0.8 ± 2.8% vs −5.3 ± 2.4%; CS, −0.01 ± 2.8% vs −7 ± 2.8%, respectively) but similar agreement with 2DST (LS: ICC = 0.58 ± 0.16 vs 0.56 ± 0.12; CS: ICC = 0.58 ± 0.12 vs 0.51 ± 0.1) with 2DTagg. Finally, 3DST had similar global LS, but better global CS test‐retest variability than 2DST. Conclusions: Using 2DTagg as reference, 3DST had better agreement and less bias for global and regional LS and CS. At the segmental level, 3DST demonstrated comparable agreement but lower bias versus 2DTagg compared with 2DST. Also, test‐retest variability for global CS by 3DST was better than by 2DST. This suggests that 3DST is superior to 2DST for analysis of global and regional myocardial deformation, but further refinement is needed for both 3DST and 2DST at the segmental level. HIGHLIGHTS3DST GLS and GCS agreed better with 2DTagg than 2DST.Unlike 2DST, 3DST did not overestimate GCS vs 2DTagg.Segmental strains by both 3DSTand 2DST agreed suboptimally with 2DTagg.3DST and 2DST test‐retest reproducibility were similar for GLS. 3DST had better GCS test‐retest reproducibility than 2DST.

Cardiac myxoma: a contemporary multimodality imaging review

Cardiac myxoma (CM) is by far the most common primary benign cardiac tumor, typically arising in the left atrium with an attachment point in the fossa ovalis region. Although the etiology of CM remains unclear, we know that this endocardial-based mass originates from undifferentiated mesenchymal cells. Continuous technical improvements in the field of echocardiography since the 1960s has profoundly changed the diagnostic approach by allowing a good tumor detection as well as the preoperative planning by providing crucial information concerning the attachment point location. However, echocardiography has its limitations among which lack of tissue characterization and restricted field of view can arise diagnosis difficulties in atypical presentations. With the widespread and routine use of echocardiography and chest computed tomography (CT), incidental detection of CM is not infrequent. As a consequence, it has become mandatory for cardiologists and radiologists evolving in a multimodality imaging world to be familiar with the wide range of presentations of this tumor. The authors present here a review of the common and less common aspects of CM using the main imaging modalities available: echocardiography, cardiovascular magnetic resonance imaging, CT, positron emission tomography and coronary angiography.

Handcrafted features vs ConvNets in 2D echocardiographic images

In this paper, we address the problem of automated pose classification and segmentation of the left ventricle (LV) in 2D echocardiographic images. For this purpose, we compare two complementary approaches. The first one is based on engineering ad-hoc features according to the traditional machine learning paradigm. Namely, we extract phase features to build an unsupervised LV pose estimator, as well as a global image descriptor for view type classification. We also apply the Supervised Descent Method (SDM) to iteratively refine the LV contour. The second approach follows the deep learning framework, where a Convolutional Network (ConvNet) learns the visual features automatically. Our experiments on a large database of apical sequences show that the two approaches yield comparable results on view classification, but SDM outperforms ConvNet on LV segmentation at a significantly lower training computational cost.

Evaluation of myocardial fibrosis with cardiac magnetic resonance contrast-enhanced t1 mapping in adults patients with aortic stenosis

Background Development of diffuse myocardial fibrosis in aortic stenosis (AS) has been associated with an adverse prognosis. Measurement of extracellular volume (ECV) from T1 mapping contrast magnetic resonance (CMR), has been recently validated as a non-invasive method for assessment of such diffuse myocardial fibrosis.Our objective was to evaluate the functional consequences of diffuse myocardial fibrosis, measured by T1-ECV in patients with AS, on systolic and diastolic left ventricular function by transthoracic echocardiography (TEE) and CMR. Methods

0294: Extravascular volume by cardiac MR T1 mapping accurately predicts histologically measured fibrosis in valve disease

Background Valvular heart disease is associated with left ventricular hypertrophy, remodeling and development of diffuse interstitial fibrosis. So far, histopathology remains the gold standard for evaluating diffuse myocardial fibrosis. Gadolinium enhanced Cardiac Magnetic Resonance (CMR) T1 mapping is new method which allows to quantify the myocardial extracellular volume (ECV). Hence, it was suggested that this ECV measurements allows to non-invasive estimate diffuse fibrosis. However validations studies are scars. Therefore the aim of this study was to validate measurements of ECV by T1-Modified Lock-locker (MOLLI) CMR against histological measurement. Methods and results Between June 2012 and September 2013, 15 patients (age=57±15 years, 73% men) with either severe aortic valve disease (stenosis or regurgitation) or severe mitral regurgitation, but without coronary artery disease preoperatively underwent ECV measurement by CMR MOLLI T1 mapping. LV biopsies were performed at the time of surgery 7±8 days later and stained with Sirius red. The amount of fibrosis quantified by biopsy was 6.6±4.8% [2.1;15.9]. ECV by T1 mapping was 28.3±4.7% [23.3;38.6] (values are presented as mean±SD [min;max]). There was a good correlation between histologically measured fibrosis and T1 mapping ECV (r=0.77, p Conclusion ECV determined by CMR T1 mapping closely correlates with histologically determined diffuse interstitial fibrosis and could thus be used to non-invasively quantify interstitial fibrosis in patients with heart diseases.