The Impact of Function Flow Interaction on Left Ventricular Efficiency in Patients With

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The Impact of Function – Flow – Interaction on Left Ventricular Efficiency in Patients with Conduction Abnormalities: A Particle Image Velocimetry and Tissue Doppler Study

Emre Gürel, MD1); Christian Prinz, MD, PhD2); Lieve Van Casteren, MD3); Hang Gao, PhD; RikWillems, MD, PhD; Jens-Uwe Voigt, MD, PhD

Dept. of Cardiovascular Sciences, Catholic University Leuven and
Dept. of Cardiovascular Diseases, University Hospital Gasthuisberg,
Catholic University Leuven, Belgium

Word count: 4375

Address for correspondence:

Prof. Dr. Jens-Uwe Voigt

Dept. of Cardiovascular Diseases

University Hospital Gasthuisberg

Herestraat 49, 3000 Leuven, Belgium

Tel:+32 16 349016

Fax:+32 16 344240

Email:

1) EG is currently affiliated with the Department of Cardiology, Pendik State Hospital, Istanbul, Turkey
2) CP is currently working in private practice in Sögel, Germany.
3) LVC is currently affiliated with the Department of Rhythmology, University Hospital Liege, Belgium.

Abstract

Background: We aimed to assess the influence of left bundle branch block (LBBB)-like conduction abnormalities on left ventricular (LV) blood flow patterns and to characterize their potential impact on LV efficiency by measuring the changes in vortex formation and energy dissipation in the LV using echocardiographic Particle Image Velocimetry (Echo-PIV).

Methods: We prospectively studied 36 subjects, including 20 pacemaker patients (PMP), 6 patients with LBBB and 10 healthy controls (NORM), all of whom had normal ejection fraction (EF>50%). In PMP, data were acquired, both in DDD and AAI mode. Standard grey scale, tissue Doppler myocardial imaging (DMI) and contrast enhanced Echo-PIV data were acquired and LV flow patterns were analyzed using dedicated software. Dyssynchrony was quantified by measuring apical transverse motion (ATM).

Results: ATM was significantly higher in LBBB compared to NORM (4.9±1.9mm vs. 1.0±0.7mm, p<0.001). Quantitative measures of vortex energy dissipation (Relative Strength, Vortex Relative Strength and Vortex Pulsation Correlation) were significantly higher in LBBB (2.05±0.54, 0.53±0.13, 0.87±0.47) compared to NORM (1.48±0.28, 0.33±0.05, 0.24±0.51, all p<0.02). Vortex duration time in relation to the entire cardiac cycle was shorter in LBBB than in NORM (28% vs. 44%). All findings in LBBB and NORM were comparable to DDD and AAI.

Conclusion: LV flow pattern analysis by Echo-PIV reveals that conduction delay by LBBB or due to pacemaker stimulation in the RV (DDD) disturbs the transfer of kinetic energy during the cardiac cycle and causes less efficient LV function. Our data contribute to a better understanding of hemodynamic consequences of conduction delays and may help optimizing therapeutic approaches.

Key words:

Particle Imaging Velocimetry, LV blood flow, LBBB, Apical Rocking, Ventricular efficiency

Abbreviations

ATM: Apical transverse motion, a parameter to quantify apical rocking

DMI: Tissue Doppler myocardial imaging

Echo-PIV: Echocardiographic particle image velocimetry

EF: Ejection fraction

IVC, IVR:Isovolumic contraction, isovolumic relaxation

LBBB:Left bundle branch block

LV: Left ventricle

LVCA:Left ventricular cavity area

ROI:Regions of interest

RS: Relative pulsatilevorticity strength

RVAP: Right ventricular apical pacing

VAmax:Maximal vortex area

VD, VL: Vortex depth, vortex length

VDT: Vortex duration time

VPC:Vortex pulsation correlation

VRS: Vortex relative pulsatilevorticity strength

VTI: Velocity time integral

2D: Two dimensional

Introduction:

Vortices are complex flow structures which contain kinetic energy due to rotating fluid.1,2 In two dimensions, vortical flow can be quantified by the parameter vorticity (ω) which describes the difference of the gradient of the y-component of the flow velocity in x-direction () and the gradient of the x-component of the flow velocity in the y-direction () according to the following formula:

Accordingly, a counterclockwise vortex has positive vorticity and clockwise vortex has negative vorticity while laminar flow has zero vorticity.3

Vortices occur when laminar flow detaches from a sharp edge. In the human left ventricle (LV), diastolic filling triggers vortex formation at the tips of the mitral valve leaflets.4,5 As the moving blood of a vortex stores kinetic energy, it thereby facilitates its transmission from diastolic inflow to systolic outflow and reduces the need for re-acceleration of the blood before ejection, which increases LV efficiency. Any pathology which disturbs the normal interplay of chamber mechanics and hemodynamics by preventing vortex formation might therefore impair ventricular efficiency.6,7

While a singular, large vortex is a relatively steady structure, turbulence is characterized by many fast changing vortices which cause a rapid dissipation of kinetic energy. The amount of regional change in vortex structures has been referred to as “pulsatility” and can be described for the entire LV as relative pulsatilevorticity strength (RS) or - for the vortex only - vortex relative pulsatilevorticity strength (VRS) and the correlation between steady and pulsatilevorticity (VPC). All three parameters have been proposed as indicators of energy dissipation in the human LV.3

Particle image velocimetry (PIV) is an image analysis method which allows to determine flow patterns by tracking particles which move together with the fluid. Recently, this method has been successfully applied to contrast enhanced echocardiographic images (Echo-PIV). Initial studies showed, that contrast tracking delivers sufficiently accurate information for the detection of vortex structures and the calculation of vorticity and other derived parameters.8,9

Electrical conduction abnormalities such as left bundle branch block (LBBB) patterns are common in heart failure patients. Similarly, therapeutic right ventricular apical pacing (RVAP) can induce conduction abnormalities comparable to LBBB and lead to systolic dyssynchrony.10 In both cases, the sequentially activated LV myocardial regions pre-stretch each other which results in inefficient ventricular work. Consequently, hearts with LBBB like conduction delays generate less stroke volume, have prolonged isovolumetric time intervals and a disturbed filling.11,12 It is widely unknown, however, to which extent the abnormal sequence of LV wall contraction interacts with vortex formation and the transfer of kinetic energy from diastole to systole.

The aim of this study was therefore to investigate the influence of LBBB-like conduction abnormalities on LV blood flow patterns and to characterize their potential impact on LV efficiency by measuring the changes in vortex formation and energy dissipation in the LV by means of Echo-PIV.

Methods:

Study population

A total of 54 persons were prospectively screened for this study, including 23 pacemaker patients, 21 patients with left bundle branch block (LBBB) and 10 volunteers. Bad echogenicity, reduced LV ejection fraction (EF<50%), regional dysfunction, more than mild valvular disease, pulmonary hypertension, previous myocardial infarction, percutaneous coronary intervention, cardiac surgery, atrial/ventricular arrhythmia or any unstable cardiovascular condition were exclusion criteria:

Pacemaker group: This group was recruited from the pacemaker clinic of our department (UZ Gasthuisberg, Leuven). All patients underwent a pacemaker test and a screening echocardiographic examination before inclusion. We selected patients with a dual chamber pacemaker capable of working in AAI and DDD mode with the ventricular lead placed at the RV apex. Care was taken, that all atrioventricular or ventricular conduction delays were intermittent and not present at the time of the investigation. Patients with permanent AV block, any intrinsic bundle branch block or inadequate echo image quality were excluded. From 23 screened patients, three were excluded due to bad echo image quality.

LBBB group: Patients were recruited by screening ECGs from the ECG service of our department. As in pacemaker patients, all LBBB patients had a screening echo prior to inclusion to rule out structural heart disease and to check for adequate echocardiographic image quality. Six patients with idiopathic LBBB and normal global LV function could be included. All were in sinus rhythm without any atrial or ventricular arrhythmia. The absence of coronary artery disease was confirmed by coronary angiography in all patients. From 21 screened patients 15 had to be excluded due to LV dysfunction (3), coronary artery disease (3), atrial fibrillation (5) or bad image quality (4).

NORM: Finally, 10 healthy volunteers without any history of cardiovascular disease and with normal findings on ECG, physical examination and echocardiography were recruited to participate in this study. All screened volunteers could be included.

All participants gave written informed consent prior to inclusion. The study was approved by the local ethics committee.

Pacing Protocol

Pacemakers were programmed to a heart rate slightly higher than the intrinsic sinus activity in order to allow constant atrial pacing. All echocardiographic data were acquired twice, both in AAI and in DDD pacing mode. Five minutes of hemodynamic adaptation were allowed after mode change. Order of modes was at random. For DDD pacing, the AV delay was adjusted in a way that full ventricular capture was achieved, but no A-wave truncation occurred.

Echocardiographic Image Acquisition

A commercially available Vivid 7 ultrasound scanner was used (GE Vingmed, Horton, Norway) to acquire a complete standard transthoracic echocardiogram. In order to characterize regional myocardial function, color tissue Doppler myocardial imaging (DMI) data were acquired from a parasternal (parasternal long axis) and apical windows (four-, three- and two-chamber view) with optimized sector and depth settings to achieve high frame rates.

For Echo-PIV, dedicated 2D grey scale images with the highest possible frame rate (95-110 fps) were acquired from three apical planes using a Siemens-Acuson Sequoia ultrasound system (Siemens Medical Solutions, Mountain view, CA). We used Sonovue (Bracco, Milan, Italy) as contrast agent which contains microbubbles in a concentration of 1 to 5 x 108 per milliliters.13 This suspension was injected intravenously as a bolus (0.1-0.2 ml) followed by 10 ml of saline flush. Since a high contrast bubble concentration causes shadowing in the deeper parts of the image, we carefully waited for a sufficient decay of the bubble concentration in the LV cavity, so that single bubbles could be clearly distinguished from each other in the entire chamber.14 Only then, contrast bubbles were imaged with a mechanical index (MI) of 0.4-0.5 in order to minimize further bubble destruction. From each acquisition, three consecutive heart cycles were stored for later post-processing. All participants underwent the same scanning protocol, pacemaker patients twice, in both AAI and DDD mode.

Post-processing and measurements

Standard Imaging: An Echopac workstation (BT 09, GE Vingmed, Horton, Norway) was used to measure cardiac diameters, volumes, ejection fraction (by bi-plane Simpson’s method), conventional Doppler parameters and valve timing data. From the latter, phases of the cardiac cycle were defined. Diastole was divided into early diastole, diastasis and late diastole. Diastasis was defined as the period between end of E and onset of A wave in the mitral inflow signal (Figure 1). Ejection fraction estimates were averaged from independent readings of two experienced observers.

Echo-PIV: Two dimensional grey scale contrast images of three apical planes were analyzed offline using the dedicated software (Q Flow Version 2.4.6., Siemens). After the definition of QRS onset, endocardial borders were delineated manually and LV cavity was automatically tracked by the software. Afterwards, the intracavitary region was processed obtaining detailed intraventricular flow tracking data. Quantitative parameters of vorticity (), the average main vortex position and size (vortex depth [VD], vortex length [VL]) as well as energy dissipation (relative strength [RS], vortex relative strength [VRS] and vortex pulsation correlation [VPC]) were automatically derived by the software, displayed in color coded images (Figure 2). Red color indicated a counterclockwise vortex, which is the main vortex as visualized in an apical four chamber view, while blue color indicated clockwise vortex flow, which is normally observed in the apical long axis and the apical two chamber views. Since the behavior of quantitative vortex parameters was comparable in all scan planes, only results of the four chamber view are reported. Lower VD values indicate a more basal position of the average main vortex relative to the LV longitudinal axis. The area of the main vortex (VA) in relation to LV cavity area (LVCA) was assessed throughout the cardiac cycle as VArel (Figure 2). The vortex duration time (VDT) was defined as the time between the onset of vortex formation and its disappearance and expressed in relation to the length of the entire cardiac cycle and of the different time intervals.

Wall motion analysis by tissue Doppler: Myocardial velocity and strain rate traces were extracted from the Tissue Doppler Data by placing regions of interest (ROI) at the basal, medial and apical segments of each myocardial wall (septal, lateral, anteroseptal, posterior, anterior, inferior). An additional, far apical velocity trace was extracted from each wall for the later calculation of apical transverse motion (ATM) as quantitative description of apical rocking (Figure 3). All ROI positions were manually tracked during the cardiac cycle in order to follow myocardial motion. Traces were stored numerically for further processing.

A dedicated MATLAB (The Math Works Inc., Natick, Massachusetts, USA) based analysis software (TVA version 14.7, JU Voigt, Leuven, Belgium) was used for the processing and analysis of the tissue Doppler derived velocity and strain rate traces. In strain curves, we measured the segmental amplitude of shortening during ejection time (εet) and during the entire cardiac cycle (εtot). The ratio εet / εtot, averaged over all 18 myocardial segments, describes the fraction of myocardial contraction which contributes to ejection and was therefore used as indicator for LV contraction efficiency. Furthermore, the difference in average shortening during ejection time in the septal and lateral wall (εdiff_4CV = εet(lat) – εet(sep)) was calculated.15,16 Typical strain patterns are shown in Figure 4.

Apical Transverse Motion:In a heart with LBBB-like motion, the typical excursion pattern of the apex is commonly referred to as “apical rocking” and considered a sign of mechanical dyssynchrony.15Apical Transverse Motion (ATM) quantifies apical rocking by measuring the apical excursion perpendicular to the LV long axis. It was calculated from the far apical color tissue Doppler velocity traces as previously described.15,16 In short, the integral of the velocity curves (i.e. the longitudinal motion curves) of the far apical ROIs are averaged while inverting the right-sided curve of the image. Assuming that the apex is a homogeneous ‘cap’, the result can be interpreted as reflecting ATM. Values were expressed in millimeters.

Statistical analysis

All continuous variables were expressed as mean ± standard deviation. For multiple group comparison, analysis of variance (ANOVA) was used with Bonferroni’s correction for post-hoc pair-wise comparisons. Pearson’s coefficient (r) was used to assess correlations. In order to evaluate the ability of ATM4CV to distinguish between normal and LBBB-like conduction, a Receiver-Operating-Characteristics (ROC) curve was constructed and area under the curve (AUC) was calculated. 10 randomly selected data sets were re-analyzed to determine the reproducibility of strain, ATM measurements and post-processed vortex parameters by means of a Bland-Altman-analysis. We further calculated the intra-class correlation (with 95% confidence interval [lower limit, upper limit]) and coefficient of variation between two readings. All statistical calculations were performed using SPSS (version 16.0, SPSS Inc., Chicago, USA). P-values below 0.05 were considered significant.

Results:

Study population, hemodynamic and echocardiographic characteristics

Table 1 presents the characteristics of the study population. Heart rate was not significantly different between groups and identical between AAI and DDD. QRS was significantly wider in DDD and LBBB than in AAI and NORM (both p<0.001). ANOVA showed no significant differences in volumes, diameters and mitral inflow velocities of the ventricles in the different groups, while it revealed a minor, but significant decrease of EF in the pacemaker patients when paced in DDD mode instead of AAI (p<0.02).

Feasibility and reproducibility

918 possible velocity and 918 segmental deformation traces were extracted. Due to the strict pre-selection for image quality, only 5 of the velocity traces and 19 of the deformation traces could not be analyzed (99 and 97% feasibility, resp.). It was possible to calculate ATM in all patients (100% feasibility). Analysis of contrast data was not possible in 2 patients due to insufficent image quality (95% feasibility).

Intra-observer coefficients of variance of εetand εtot were 12% and 11%, respectively, while the intra-class correlation coefficients were 0.84 [0.80-0.87] and 0.86 [0.83-0.89]. Repeated readings of ATMet and ATMtot in the 4 chamber view showed a coefficient of variance of 10% and 9%, respectively. Intra-observer coefficients of variance of VD, VL, RS, VRS, VPC and VArel were 17%, 14%, 16%, 12%, 10% and 17%, respectively, with an intra-class correlation coefficient of 0.94 [0.90-0.98], 0.78 [0.75-0.81], 0.90 [0.86-0.94], 0.83 [0.80-0.86], 0.92 [0.88-0.94] and 0.84 [0.80-0.88], respectively.

Regional Myocardial Deformation

Results are summarized in Figure 4 and Figure 5. The average strain during the entire cardiac cycle (εtot) was similar in the NORM, AAI, DDD and LBBB group (-17.8±2.7%, -17.8±2.6%, -18.1±2.6%, -18.2±2.7%, resp., p=0.3). However, the average strain during ejection time (εet) was significantly lower in DDD and LBBB (-12.4 ± 2.4% and -9.9 ± 0.6%, resp.) compared to NORM and AAI (-14.3 ± 1.6% and -14.4 ± 2.0%, both p<0.001). During ejection time, both NORM and AAI showed slightly higher strain amplitudes in the septum compared to the lateral wall (-15.8 ± 2.8% vs. -11.9 ±1.5%, p<0.001 and -15.9 ± 4.2% vs. -12.9 ± 2.8%, p<0.02, resp.) while DDD and LBBB groups showed markedly lower strain amplitudes in the septum compared to the lateral wall (-11.2 ± 3.6% vs. -14.0 ± 2.0%, p<0.005 and -7.5 ± 2.3% vs. -14.9 ± 1.0%, p<0.003, resp).

In all deformation parameters, the behaviour of AAI was comparable to NORM while DDD behaved comparable to LBBB (Figure 4).

Apical Transverse Motion

Results are displayed in Figure 6. In AAI, ATM4CV was small and not significantly different to NORM (1.2±0.5mm vs. 1.0±0.7mm, p=0.9). Both DDD and LBBB showed a marked motion of the apex which was significantly higher than in AAI and NORM (3.4 ± 1.0 and 4.9 ± 1.9mm, resp., both p<0.001). In all patients of the DDD and LBBB groups, apical motion was directed towards the lateral wall during ejection (typical “apical rocking”). ATM4CV was significantly correlated with the deformation difference (εdiff_4CV) between septum and lateral wall(r=-0.62, p<0.001). When tested in an ROC-analysis, ATM4CV distinguished the NORM and AAI group from LBBB and DDD with an excellent AUC of 0.98 (CI 0.88-1.0). As in regional deformation analysis, ATM of AAI and NORM groups behaved comparable as did DDD and LBBB groups.