3D Deformation Parameters Research Articles

The Value of Strain Echocardiography in Predicting Electrical Progression in Patients With Arrhythmogenic Right Ventricular Cardiomyopathy.

Arrhythmogenic right ventricular (RV) cardiomyopathy is a progressive disease characterized by the replacement of the normal myocardium with fibrofatty tissue. This study aimed to determine the value of echocardiographic RV deformation parameters in predicting electrical progression as assessed by serial changes in RV lead sensing and threshold in patients with arrhythmogenic RV cardiomyopathy. The present study recruited 40 patients with a definitive diagnosis of arrhythmogenic RV cardiomyopathy at a mean (SD) age of 38.6 (14.2) years between 2018 and 2020. All patients had received an implantable cardioverter-defibrillator for the primary or secondary prevention of sudden cardiac death. The patients underwent 2-dimensional (2D) and 3-dimensional (3D) transthoracic echocardiographic examinations and RV 2D and 3D strain analyses, comprising free-wall longitudinal strain, global longitudinal strain, and strain rate. They were then followed up for electrical progression. During a mean (SD) follow-up period of 20 (6) months, the RV lead amplitude decreased from 7.95 (IQR, 4.53-10.25) mV to 5.25 (IQR, 2.88-8.55) mV (P < .001), and the lead threshold increased from 0.75 (IQR, 0.50-0.79) V to 0.75 (IQR, 0.75-1.00) V (P < .001). Right ventricular 2D free-wall (ρ = 0.56, P = .01), RV 2D global (ρ = 0.58, P = .007), and RV 3D free-wall (ρ = 0.65; P = .003) longitudinal strain correlated with electrical progression. Right ventricular 2D and 3D deformation parameters were found to be significant predictors of electrical progression during follow-up of patients with arrhythmogenic RV cardiomyopathy. These findings suggest that echocardiography has a pivotal role in predicting patients at high risk for electrical progression.

3D speckle tracking echocardiographic strain pattern in Hypertrophic Cardiomyopathy and its relation with Sudden Cardiac Death risk markers

ContextSudden cardiac death (SCD) predictability for assessing the need for primary insertion of Implantable Cardioverter Defibrillator (ICD) in patients with Hypertrophic cardiomyopathy (HCM) is difficult though there are several conventional risk markers. The role of deformation indices in predicting SCD in HCM is less addressed. ObjectivesTo analyse the 3D speckle tracking echocardiographic strain parameters of HCM patients and its relation with SCD risk markers. Design and study methodologyIt was a cross-sectional observation study done over a period of one year with a follow up period of one year. Fifty HCM patients were included after screening eighty-two patients. Their global LV strain parameters, Global Longitudinal Strain (GLS), Global Circumferential Strain (GCS), Global Radial Strain (GRS) and Global area strain (GAS) were analysed with respect to their age and gender-matched controls. The various strain parameters were correlated with the conventional SCD risk markers and the ESC SCD risk score among these HCM patients. ResultsAll the global strain parameters were significantly low in HCM patients compared to their controls {GLS -7.30 ± 3.424 vs −18.78 ± 2.342, p < 001; GCS -11.26 ± 2.754 vs −25.08 ± 3.542, p < 001; GRS 20.56 ± 8.929 vs 39.70 ± 7.546, p < 001}. On subgroup analysis of HCM patients with LV thickness >30 mm, abnormal exercise test, family history of SCD, LVOT gradients >30mmHgand more than one SCD risk marker had significantly low values for all global deformation parameters, when compared with their control HCM cohort. The ESC risk score also had significant inverse correlation with all deformation parameters (GLS 0.496, p < 0.001; GCS 0.491, p < 0.001; GRS -0.529, p < 0.001; GAS 0.519, p < 0.001). On follow up, only one event was recorded in this cohort. ConclusionThere exists a possible linear correlation between conventional SCD risk markers and 3D deformation parameters, which may be utilized for risk stratification and SCD predictability in HCM patients after confirmation with further large prospective studies.

Speckle tracking deformation imaging to detect regional fibrosis in hypertrophic cardiomyopathy: a comparison between 2D and 3D echo modalities.

We aimed at directly comparing three-dimensional (3D) and two-dimensional (2D) deformation parameters in hypertrophic hearts and depict which may best reflect underlying fibrosis in hypertrophic cardiomyopathy (HCM), defined by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR). We included 40 HCM [54.1 ± 14.3 years, 82.5% male, maximum wall thickness (MWT) 19.3 ± 4.8 mm] and 15 hypertensive (HTN) patients showing myocardial hypertrophy (58.1 ± 15.6 years, 80% male, MWT 12.8 ± 1.4 mm) who have consecutively undergone 2D-, 3D-speckle tracking echocardiography and LGE CMR. Deformation parameters (2D and 3D) presented overall poor to moderate correlations, with 3D_longitudinal strain (LS) and 3D_circumferential strain (CS) values being constantly higher compared to 2D derivatives. By regression analysis, hypertrophy substrate (HCM vs. hypertension) and hypertrophy magnitude were the parameters to influence 2D-3D LS and CS strain correlations (R2 = 0.66, P < 0.001 and R2 = 0.5, P = 0.001 accordingly). Among segmental deformation indices, 2D_LS showed the best area under the curve [AUC = 0.78, 95% confidence intervals (CI) (0.75-0.81), P < 0.0005] to detect fibrosis, with 3D deformation parameters showing similar AUC (0.65) and 3D_LS presenting the highest specificity [93.1%, 95% CI (90.6-95.1)]. In hypertrophic hearts, 2D and 3D deformation parameters are not interchangeable, showing modest correlations. Thickness, substrate, and tracking algorithm calculating assumptions seem to induce this variability. Nevertheless, among HCM patients 2D_peak segmental longitudinal strain remains the best strain parameter for tissue characterization and fibrosis detection.

P984 A head-to-head comparison between 2D and 3D segmental strain parameters in hypertrophic cardiomyopathy

Abstract Funding Acknowledgements Supported with a scholarship by the Greek State Scholarship Foundation (IKY). Background Previous studies have suggested that in normal and ischemic hearts three- (3D) and two-dimensional (2D) strain values present a moderate agreement which is prone to technical considerations. However, the level of agreement between 2D and 3D-strain imaging has never been adequately addressed in hypertrophic hearts, nor has it been validated against a "ground truth". Especially in hypertrophic cardiomyopathy (HCM), the magnitude and eccentricity of hypertrophy set additional challenges in standardization and measurement of regional 3D deformation parameters. Purpose Aims of this study were i) to investigate the consistency between 3D and 2D regional deformation parameters in HCM and ii) to test their accuracy in identifying regional fibrosis as this is defined by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR). Methods We included 40 HCM patients (54.1 ± 14.3 years, 82.5% male, maximum wall thickness 19.3 ± 4.8mm) who have consecutively undergone 2D-,3D-speckle tracking echocardiography and CMR. Segmental circumferential (SCS) and longitudinal (SLS) strain have been calculated from 2D acquisitions and 3D full volume data, where additionally radial (SRS) and area (SAS) strain have been extracted using an 18 segment left ventricle model. Accordingly, segmental fibrosis was defined by LGE in corresponding CMR slices. Results Out of 720 segments evaluated, 134 (19.7%) were enhanced and 95(13.2%) thickened (thickness &amp;gt; 12 mm). Two dimensional LS and CS analysis was feasible in 719 (99.9%) and 678 (94.2%) segments respectively, while 686 segments (95.3%) were appropriate for 3D tracking. 3D_SLS values were -7.9 ± 6.8% less negative compared to 2D_SLS values [level of agreement (LOA)(-21.1-5.4%)], while the bias for SCS values was even higher -8.5 ± 8.6 [LOA(-25.4-8.4%)]. Absolute agreement between 2D and 3D deformation imaging modalities was poor to moderate [Intra-class Correlation Coefficient (ICC)= 0.46, 95%CI (0.15-0.68), p &amp;lt; 0.0005 for SLS and ICC = 0.19, 95%CI(0.07-0.38), p &amp;lt; 0.0005 for SCS] (Panel A). Following regression analysis, regional thickness was the only segmental factor to influence the correlation between 3D and 2D_SLS [R2 = 0.504, B = 0.33, 95%CI(0.22-0.44), p &amp;lt; 0.0005)], without, however, being a significant regressor for the other 2D vs 3D correlations. Among deformation indices, 2D_SLS showed the best area under the curve [(AUC)=0.78, 95%CI(0.75-0.81), p &amp;lt; 0.0005] to detect segmental fibrosis identified by CMR LGE, with 3D_SLS, 3D_SAS and 3D_SRS showing similar AUC (0.65) and 3D_SLS presenting the highest specificity [93.1%, 95%CI(90.6-95.1)] (Panel B). Conclusions In HCM, 2D and 3D deformation parameters are not interchangeable, showing modest agreement. Thickness and tracking algorithm calculating assumptions seem to induce this inconsistency. Among HCM patients, 2D_SLS remains the most accurate strain parameter to detect regional fibrosis. Abstract P984 Figure.

Abstract 14645: Three Dimensional Ejection Fraction is More Strongly Determined by Strain Than by Torsion in a Cohort of Breast Cancer Patients Undergoing Anthracycline-Based Chemotherapy

Introduction: Anthracycline cardiotoxicity affects approximately 10-20% of treated individuals, representing a significant health burden. Three dimensional (3D) echocardiographic measures of myocardial mechanics have the potential to improve our understanding of the functional changes that occur with anthracyclines, and may play an important role in cardiotoxicity risk prediction. Our objective was to define the relationships between 3D myocardial deformation parameters and left ventricular ejection fraction (LVEF) in a longitudinal, prospective cohort of patients with breast cancer. Methods: We performed 3D echocardiograms at standardized intervals in a longitudinal cohort of women with breast cancer undergoing doxorubicin therapy with or without trastuzumab. We acquired all 3D images at a minimum of 22 frames per second and excluded from analysis all images that had poor tracking of greater than 3 myocardial segments, dropout of the apex, or stitch artifact. Two readers used a vendor-independent analysis platform (TomTec Cardiac Performance Analyses, Unterschleissheim, Germany) to measure 3D LVEF and the following 3D deformation parameters: principal strain, global longitudinal strain (GLS), global circumferential strain (GCS), and left ventricular torsion. Spearman correlation analyses were performed to understand the relationships amongst these parameters. Results: We analyzed 270 total echocardiograms from 87 women (mean age 49). Conventional 3D strain parameters were highly correlated with 3D LVEF (principal strain, r=-0.95, p&lt;0.001; GLS, r=-0.85, p&lt;0.001; GCS r=-0.97, p&lt;0.001). In contrast, left ventricular torsion was only modestly correlated with 3D LVEF (r=0.51, p&lt;0.001). Conclusions: Three dimensional principal strain, GLS, and GCS were all strongly correlated with 3D LVEF. However, left ventricular torsion was only weakly correlated to LVEF, suggesting that LVEF is determined less by torsion than by 3D strain. With further study, 3D strain may play an important role in chemotherapy cardiotoxicity risk prediction.

Local metric learning in 2D/3D deformable registration with application in the abdomen.

In image-guided radiotherapy (IGRT) of disease sites subject to respiratory motion, soft tissue deformations can affect localization accuracy. We describe the application of a method of 2D/3D deformable registration to soft tissue localization in abdomen. The method, called registration efficiency and accuracy through learning a metric on shape (REALMS), is designed to support real-time IGRT. In a previously developed version of REALMS, the method interpolated 3D deformation parameters for any credible deformation in a deformation space using a single globally-trained Riemannian metric for each parameter. We propose a refinement of the method in which the metric is trained over a particular region of the deformation space, such that interpolation accuracy within that region is improved. We report on the application of the proposed algorithm to IGRT in abdominal disease sites, which is more challenging than in lung because of low intensity contrast and nonrespiratory deformation. We introduce a rigid translation vector to compensate for nonrespiratory deformation, and design a special region-of-interest around fiducial markers implanted near the tumor to produce a more reliable registration. Both synthetic data and actual data tests on abdominal datasets show that the localized approach achieves more accurate 2D/3D deformable registration than the global approach.

Predictive value of 3D left ventricular myocardial deformation parameters after Acute Coronary Syndrome (ACS) in the development of heart failure

Background: It is usually difficult to predict whether a patient with an ACS will develop heart failure (HF) over follow up. In addition to LVEF, many parameters have been evaluated to provide information about this. However, the utility of 3D LV deformation and mechanical parameters has not been rigorously evaluated yet in this sense. Aims: To demonstrate the relationship between the degree of alteration of different myocardial deformation parameters (3D global, radial, longitudinal and circumferential strain) after an acute coronary syndrome and the subsequent development of HF Methods: 30 patients who were admitted with ACS (elevation of biomarkers of myocardial injury) were included. All patients underwent invasive angiography and intervention of the culprit artery). A transthoracic echocardiogram was performed in all cases with 3D volume acquisition for semiautomatic calculation of 3D LV deformation parameters. 6 month follow up was performed and HF events recorded. Results: 30 patients were included. Male 76.6%. Mean age 63.5 years. Mean LV ejection fraction was 53,01±11,2. 22 patients (73,3%) were classified as ST elevation ACS and 8 patients (22,7%) with non ST elevation ACS. Significant correlation was found between different 3D deformation parameters and HF (see table). By means of the ROC curve, the optimal cutting point of 3D global strain value for the prediction of HF was estimated as < 32, 7. View this table: Conclusions: The degree of initial alteration of 3D global, longitudinal and radial strain values obtained immediately after an ACS represents a reliable predictor of heart failure development in the follow up, regardless of left ventricular ejection fraction in ACS. Besides this, in a subgroup of patients with LVEF>50% the alteration of these parameters still shows a significant relationship with the development of HF over follow up. These parameters may be usefull for medical optimization treatment in these patients.

Young Investigator Award session - Clinical * Clinical applications

Young Investigator Award session - Clinical * Clinical applications

MO-F-BRA-05: Real-Time 3D Tumor Localization for Lung IGRT Using a Single X-Ray Projection.

To study the feasibility of a novel 2D/3D image registration method, called Projection Metric Learning for Shape Kernel Regression (PML-SKR), in supporting on-board x-ray imaging systems to perform real-time image-guided radiation therapy in the lung. PML-SKR works in two stages: planning and treatment. At planning stage, firstly it parameterizes the patient's respiratory deformation from the patient's treatment-planning Respiratory-Correlated CTs (RCCTs) by doing PCA analysis on the inter-phase respiratory deformations. Secondly, it simulates a set of training projection images from a set of deformed CTs where their associated deformation parameters are sampled within 3 standard deviations of the parameter's values observed in the RCCTs. Finally, it learns a Riemannian distance metric on projection intensity for each deformation parameter. The learned distance metric forms a Gaussian kernel of a kernel regression that minimizes the leave-one-out regression residual of the corresponding deformation parameter. At treatment stage, PML-SKR interpolates the patient's 3D deformation parameters from the parameter's values in the training cases using the kernel regression with the learned distance metrics. We tested PML-SKR on the NST (Nanotube Stationary Tomosynthesis) x-ray imaging system. In each test case, a DRR (dimension: 64×64) of an x-ray source in the NST was simulated from a target CT for registration. The target CTs were deformed by normally distributed random samples of the first three deformation parameters. We generated 300 synthetic test cases from 3 lung datasets and measured the registration quality by the mTRE (mean Target Registration Error) over all cases and all voxels at tumor sites. With PML-SKR's registrations, the average mTRE and its standard deviation are down from 10.89±4.44 to 0.67±0.46 mm using 125 training projection images. The computation time for each registration is 12.71±0.70 ms. The synthetic results have shown PML-SKR's promise in supporting real-time, accurate, and low-dose lung IGRT. This work was partially supported by Siemens Medical Solutions.

3D modelling of elastic articulated objects and its parameter determination from image points

This paper presents a new model of elastic articulated objects based on revolving conic surface. The model includes 3D object skeleton and deformable surfaces that can represent the deformation of human body surfaces. In each limb, surface deformation is represented by adjusting only one deformation parameter. Then, the 3D deformation parameters are determined by corresponding 2D image points from a sequence of stereo images. The 3D motion parameters are estimated based on the skeleton points. The algorithm presented in this paper includes skeleton-based parameter estimation of motion and parameter determination of deformable surfaces.

Motion estimation of elastic articulated objects from points and contours with volume invariable constraint

This paper presents a model of elastic articulated objects based on revolving conic surface and a method of model-based motion estimation. The model includes 3D object skeleton and deformable surfaces that can represent the deformation of human body surfaces. In each limb, surface deformation is represented by adjusting one or two deformation parameters. Then, the 3D deformation parameters are determined by corresponding 2D image points and contours with volume invariable constraint from a sequence of stereo images. The 3D motion parameters are estimated based on the 3D model. The algorithm presented in this paper includes model-based parameter estimation of motion and parameter determination of deformable surfaces.