scholarly journals Left Ventricular Deformation and Vortex Analysis in Heart Failure: From Ultrasound Technique to Current Clinical Application

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 892
Author(s):  
Simona Sperlongano ◽  
Antonello D’Andrea ◽  
Donato Mele ◽  
Vincenzo Russo ◽  
Valeria Pergola ◽  
...  
Keyword(s):  
Heart Failure ◽  
Color Doppler ◽  
Left Ventricular ◽  
Response To Therapy ◽  
Cardiac Resynchronization ◽  
Flow Mapping ◽  
Ultrasound Technique ◽  
Left Ventricular Deformation ◽  
Cardiovascular Morbidity And Mortality ◽  
Therapeutic Decision Making

Heart failure (HF) is a leading cause of cardiovascular morbidity and mortality. However, its symptoms and signs are not specific or can be absent. In this context, transthoracic echocardiography plays a key role in diagnosing the various forms of HF, guiding therapeutic decision making and monitoring response to therapy. Over the last few decades, new ultrasound modalities have been introduced in the field of echocardiography, aiming at better understanding the morpho-functional abnormalities occurring in cardiovascular diseases. However, they are still struggling to enter daily and routine use. In our review article, we turn the spotlight on some of the newest ultrasound technologies; in particular, analysis of myocardial deformation by speckle tracking echocardiography, and intracardiac flow dynamics by color Doppler flow mapping, highlighting their promising applications to HF diagnosis and management. We also focus on the importance of these imaging modalities in the selection of responses to cardiac resynchronization therapy.

P2477Assessment of intraventricular flow dynamics in acute heart failure studied by Vector Flow Mapping

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
K Masuda ◽  
S Minami ◽  
M Stugaard ◽  
A Kozuma ◽  
S Takeda ◽  
...  
Keyword(s):  
Heart Failure ◽  
Diastolic Pressure ◽  
Color Doppler ◽  
Propagation Distance ◽  
Left Ventricular ◽  
Flow Dynamics ◽  
Significant Part ◽  
Flow Mapping ◽  
Vector Flow Mapping ◽  
Ejection Rate

Abstract Background Although left ventricular (LV) flow dynamics should be closely related to LV morphology and function, little is known about how heart failure (HF) changes it. Pathline Analysis (PA), a recently developed software based on Vector Flow Mapping (VFM, Hitachi), enables us to trace the virtual blood particles entering to the LV in diastole and being ejected in systole. We investigated the change of flow dynamics in HF induced in dogs using PA. Methods In 15 open-chest dogs, HF was induced by intracoronary injection of microspheres. Color Doppler images of apical long-axis view were acquired using Prosound F75 (Hitachi) before and after HF and were analyzed by PA. We calculated the ratio of the numbers of entering particles in diastole and ejected particles in systole (ejection rate) and the distance reached by the particles in diastole corrected by the LV long-axis diameter (propagation distance). Apical and basal short axis images were acquired using GE Vivid E9 and were analyzed for peak rotation and peak twist. Results After inducing HF, LV end-diastolic pressure increased from 6±2 to 15±5 mmHg (p<0.001) and ejection fraction (EF), apical peak rotation and peak twist decreased significantly (EF; 58±5 to 36±8%, apical peak rotation; 14±5 to 3±2 degree, peak twist; 19±5 to 6±3 degree, p<0.05, respectively). PA showed most of the entering particles to the LV were ejected in the following systole at the control stage, but in HF, a significant part of the entering particles were not ejected and remained in the LV (Figure). Ejection rate decreased from 50±11 to 26±11% (p<0.001) and the propagation distance decreased from 85±9 to 66±13% (p<0.001) after inducing HF. There were significant relationships between indices obtained by PA and EF and peak twist (Table). Conclusion A significant part of inflow is not ejected directly to the outflow in the next systole and remains in the LV in HF, suggesting inefficient flow dynamics.

scholarly journals Loss of apical suction assessed by noninvasive pressure differences and twist in acute heart failure: a novel method using vector flow mapping

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
S Ido ◽  
K Masuda ◽  
S Yoshimura ◽  
H Tanaka ◽  
M Stugaard
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Diastolic Pressure ◽  
Color Doppler ◽  
Left Ventricular ◽  
Frame Rate ◽  
Flow Mapping ◽  
Vector Flow Mapping ◽  
Funding Sources ◽  
Novel Method

Abstract Background Early diastolic intraventricular pressure difference (IVPD) reflects left ventricular (LV) apical suction, and IVPD is closely related to cardiac function, especially LV twist. Vector Flow Mapping (VFM) allows visualization of regional pressure distribution and noninvasive quantification of IVPD. The purpose of the present study was to investigate if and how IVPDs are related to LV twist in a model of acute heart failure (HF). Methods In 15 open-chest dogs, HF was induced by intracoronary injection of microspheres. The HF model was classified into two groups based on the LV end-diastolic pressure (LVEDP) (group1: LVEDP&lt;18 mmHg (n=10), group2: LVEDP≥18 mmHg (n=8)). Color Doppler images from apical long-axis views were acquired at baseline and during HF. From these images, pressure differences (ΔP) were calculated along the LV inflow tract throughout the cardiac cycle. For the purpose of this study, the differences between apex and base during isovolumic relaxation time (ΔPIRT) and rapid early inflow period (ΔPE) were used for analyses. Furthermore, apical and basal short axis high frame rate 2D images were acquired, and peak rotation and peak twist were analyzed. Results LVEDP was 7±9, 14±2, 21±3 mmHg for baseline, group1 HF, and group2 HF, respectively. Pressure differences (both ΔPIRT and ΔPE) were visibly changed by the increase of LVEDP (Figure), and the magnitude of ΔPIRT, ΔPE and peak twist decreased significantly with the severity of heart failure. There were significant relationships between pressure differences (ΔPIRT and ΔPE) and dP/dtmin, tau, EF and peak twist (Table). In multivariate analyses, tau and peak twist were independent predictors for ΔPIRT and peak twist was independent predictor for ΔPE. Conclusion VFM analysis is feasible to noninvasively assess the IVPDs in acute heart failure. The IVPDs are closely related to the twisting motion of the LV, and reflect loss of apical suction during severe HF. FUNDunding Acknowledgement Type of funding sources: None. VFM images of pressure differences Correlations of pressure differences

Time interval from left ventricular stimulation to QRS onset is a predictor of mortality in patients with cardiac resynchronization therapy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Yagishita ◽  
Y Yagishita ◽  
S Kataoka ◽  
K Yazaki ◽  
M Kanai ◽  
...  
Keyword(s):  
Heart Failure ◽  
Independent Predictor ◽  
Total Mortality ◽  
Left Ventricular ◽  
Cardiac Resynchronization ◽  
Time Interval ◽  
Heart Failure Hospitalization ◽  
Conduction Disturbance ◽  
Secondary Endpoints ◽  
Fibrotic Lesion

Abstract Introduction In our previous report, the time interval from left ventricular (LV) pacing to the earliest onset of QRS (S-QRS interval) has been found to be an independent predictor of mechanical response to cardiac resynchronization therapy (CRT). The S-QRS interval may indicate the conduction disturbance relevant to the localized tissue property such as scar or fibrotic lesion. Therefore, S-QRS interval longer than 37ms was associated with poor response to CRT, and proposed as suboptimal LV lead position. Then, we hypothesized that the longer S-QRS interval at the LV pacing site could be related to long term mortality and heart failure events in patients with CRT. Methods This retrospective study included 82 consecutive heart failure patients with sinus rhythm, reduced LV ejection fraction (≤35%), and a wide QRS complex (≥120ms), who undergone CRT implantation between 2012 January and 2017 December. Patients were divided into Short S-QRS group (&lt;37ms, SS-QRS) and Long S-QRS group (≥37ms, LS-QRS) according to the previously reported optimal cut off value. A responder was defined as one with ≥15% reduction in LV end-systolic volume assessed by echocardiography at 6 months after CRT. The primary endpoint was total mortality, which included LV assist device implantation or heart transplantation. The secondary endpoints included the composite endpoint of total mortality or heart failure hospitalization. Results The study patients were divided into SS-QRS (N=43, age 65.9±13.2 years, 77% male) and LS-QRS (N=39, age 63.0±13.4, 85% male). In the electrocardiographic measurements, there were no significant differences in baseline QRS duration (162.4±30.3ms in SS-QRS vs. 154.5±31.6ms in LS-QRS, P=0.19) and LV local activation time assessed as Q-LV interval (118.3±34.3ms in SS-QRS vs. 115.3±32.0ms in LS-QRS, P=0.71). S-QRS interval was 25.9±5.3ms in SS-QRS and 51.5±13.7ms in LS-QRS (P&lt;0.01), and the responder rate was significantly higher in SS-QRS compared with LS-QRS (79% vs. 29%, P&lt;0.01). During mean follow up of 47.7±22.4 months, 24 patients (29%) reached to the primary endpoint, while the secondary endpoints were observed in 47 patients (57%). LS-QRS patients had significantly worse event-free survival for both primary and secondary endpoints (Figure). After the multivariate Cox regression analysis, LS-QRS (≥37ms) was an independent predictor of total mortality (HR=2.6, 95% CI: 1.11 to 6.12, P=0.03) and the secondary composite events (HR=2.4, 95% CI: 1.31 to 4.33, P&lt;0.01). Conclusion The S-QRS interval longer than 37ms, which may reflect the conduction disturbance relevant to the scar or fibrotic lesion at the LV pacing site, was a significant predictor of the total mortality and heart failure hospitalization. These findings have implications for the optimal LV lead placement in patients with CRT device. Clinical outcomes according to S-QRS Funding Acknowledgement Type of funding source: None

scholarly journals Importance of systematic right ventricular assessment in cardiac resynchronization therapy candidates: a machine-learning approach

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
E Galli ◽  
V Le Rolle ◽  
OA Smiseth ◽  
J Duchenne ◽  
JM Aalen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Failure ◽  
Cardiac Resynchronization Therapy ◽  
Right Ventricular ◽  
Systolic Heart Failure ◽  
Left Ventricular ◽  
Supervised Machine Learning ◽  
Cardiac Resynchronization ◽  
Resynchronization Therapy ◽  
Crt Response

Abstract Funding Acknowledgements Type of funding sources: None. Background Despite having all a systolic heart failure and broad QRS, patients proposed for cardiac resynchronization therapy (CRT) are highly heterogeneous and it remains extremely complicated to predict the impact of the device on left ventricular (LV) function and outcomes. Objectives We sought to evaluate the relative impact of clinical, electrocardiographic, and echocardiographic data on the left ventricular (LV) remodeling and prognosis of CRT-candidates by the application of machine learning (ML) approaches. Methods 193 patients with systolic heart failure undergoing CRT according to current recommendations were prospectively included in this multicentre study. We used a combination of the Boruta algorithm and random forest methods to identify features predicting both CRT volumetric response and prognosis (Figure 1). The model performance was tested by the area under the receiver operating curve (AUC). We also applied the K-medoid method to identify clusters of phenotypically-similar patients. Results From 28 clinical, electrocardiographic, and echocardiographic-derived variables, 16 features were predictive of CRT-response; 11 features were predictive of prognosis. Among the predictors of CRT-response, 7 variables (44%) pertained to right ventricular (RV) size or function. Tricuspid annular plane systolic excursion was the main feature associated with prognosis. The selected features were associated with a very good prediction of both CRT response (AUC 0.81, 95% CI: 0.74-0.87) and outcomes (AUC 0.84, 95% CI: 0.75-0.93) (Figure 1, Supervised Machine Learning Panel). An unsupervised ML approach allowed the identifications of two phenogroups of patients who differed significantly in clinical and parameters, biventricular size and RV function. The two phenogroups had significant different prognosis (HR 4.70, 95% CI: 2.1-10.0, p &lt; 0.0001; log –rank p &lt; 0.0001; Figure 1, Unsupervised Machine Learning Panel). Conclusions Machine learning can reliably identify clinical and echocardiographic features associated with CRT-response and prognosis. The evaluation of both RV-size and function parameters has pivotal importance for the risk stratification of CRT-candidates and should be systematically assessed in patients undergoing CRT. Abstract Figure 1

INTRA-LEFT VENTRICULAR FLOW DISTRIBUTIONS IN DIASTOLIC AND SYSTOLIC PHASES, BASED ON ECHO VELOCITY FLOW MAPPING OF NORMAL SUBJECTS AND HEART FAILURE PATIENTS, TO CHARACTERIZE LEFT VENTRICULAR PERFORMANCE OUTCOMES OF HEART FAILURE

2012 ◽  
Vol 12 (05) ◽  
pp. 1240029 ◽  
Author(s):  
THU-THAO LE ◽  
RU-SAN TAN ◽  
FEIQIONG HUANG ◽  
LIANG ZHONG ◽  
SRIDHAR IDAPALAPATI ◽  
...  
Keyword(s):  
Heart Failure ◽  
Velocity Vector ◽  
Normal Subjects ◽  
Performance Outcomes ◽  
Left Ventricular ◽  
Inflow Rate ◽  
Flow Mapping ◽  
Velocity Flow ◽  
Outflow Rate ◽  
Blood Flow Patterns

Heart failure (HF), one of the most common diseases in the world, causes left ventricular dysfunction (LV) and high mortality. HF patients are stratified into two groups based on their LV ejection fraction (EF) — HF with normal EF (HFNEF) and with reduced EF (HFREF). EF is a commonly used measure of LV contractile performance. Despite preserved EF, a complex mixture of systolic and diastolic dysfunction and variable degrees of LV remodelling underlying HFNEF poses challenges to diagnose and provide pharmacological treatment for HFNEF. In recent years, the velocity flow mapping (VFM) technique has been developed to generate flow velocity vector fields by post-processing color Doppler echocardiographic (echo) images. We aim to obtain the intra-LV blood flow patterns for patients with HFNEF, HFREF, and normal subjects, in order to characterize the LV performance outcomes of normal subjects and HF patients. Two subjects from each group of HFNEF, HFREF, and normal underwent echo scans. Velocity vector distributions throughout the cardiac cycle were then analysed using the VFM technique. In each subject, the outflow rate during systole, inflow rate during diastole, as well as wall stress-based pressure-normalized contractility index, dσ*/dt max , were computed and compared among the groups. This study demonstrated the use of VFM to visualize LV blood flow patterns in HF patients and normal subjects. Different patterns of flow distributions were observed in these subjects. In HFREF patients, dσ*/dt max , the peak outflow rate and peak inflow rate during early filling were markedly reduced. In HFNEF patients, peak outflow rates were increased compared to those of normal subjects.

Abstract 16574: Heart Failure Biomarkers (NT-proBNP, Gal-3, sST2) Correlate With Right Ventricular Systolic Pressure and Provide Insight to Poor CRT Response: A BIOCRT Substudy

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Roderick C Deaño ◽  
Jackie Szymonifka ◽  
Qing Zhou ◽  
Jigar H Contractor ◽  
Zachary Lavender ◽  
...  
Keyword(s):  
Heart Failure ◽  
Right Ventricular ◽  
Systolic Pressure ◽  
Fold Increase ◽  
Left Ventricular ◽  
Cardiac Resynchronization ◽  
Cardiac Transplant ◽  
Right Ventricular Systolic Pressure ◽  
Ventricular Systolic Pressure ◽  
Crt Response

Objective: Patients with heart failure (HF) and pulmonary hypertension (PH) have worse outcomes after cardiac resynchronization therapy (CRT). The relationship of circulating HF biomarkers and right ventricular systolic pressure (RVSP) may provide insight to the mechanism between PH and poor CRT response. Methods: In 90 patients (age 65 ± 13, 78% male, EF 26 ± 8%, RVSP 44 ± 12 mmHg) undergoing CRT, we measured baseline RVSP by echocardiography and obtained peripheral blood samples drawn at the time of device implantation. We measured levels of established and emerging HF biomarkers (Table 1). CRT non-response was defined as no improvement of adjudicated HF Clinical Composite Score at 6 months. Major adverse cardiac event (MACE) was defined as composite endpoint of death, cardiac transplant, left ventricular assist device, and HF hospitalization within 2 years. Results: There were 34% CRT non-responders and 27% had MACE. Per 1 unit increase in log-transformed RVSP, there was an 11-fold increase risk of having CRT non-response (odd ratio [OR] 11.0, p=0.01) and over 5-fold increase of developing 2-year MACE (hazard ratio [HR] 5.8, p=0.02). When comparing patients with severe PH (RVSP>60 mmHg) to those without PH (RVSP < 35 mmHg), there was an 8-fold increase in CRT nonresponse (OR 8.4, p=0.03) but no difference in MACE (p=NS). RVSP was correlated with increased biomarker levels of myocardial stretch and fibrosis, but not myocardial necrosis (Table 1). Conclusions: Higher RVSP is associated with greater rates of CRT non-response and adverse clinical outcomes. The mechanistic association between severe PH and CRT nonresponse may be explained by the biomarker profile reflective of myocardial wall stretch and fibrosis.

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