Background
The use of resynchronization therapy for the treatment of left ventricular (LV) systolic dysfunction in children has been expanding. Because QRS duration is not a reliable indicator of the presence or severity of dyssynchrony in every case, additional methods of quantitation of dyssynchrony are needed. The purpose of this study was threefold: (1) to define normal values for LV real-time quantitative three-dimensional echocardiographic (3DE) dyssynchrony indices (DIs), (2) to analyze the feasibility and observer variability of 3DE DIs in a wide range of children, and (3) to determine the effects of age, heart rate, body surface area, and LV end-diastolic volume on these parameters.
Methods
The two specific parameters studied were the standard deviation of the time to minimum systolic volume for the number of segments analyzed and the time difference between the earliest and latest contracting segments. Both parameters were expressed as a percentage of the cardiac cycle length.
Results
In 125 normal children aged 1 day to 19 years, adequate dyssynchrony studies were obtained in 102 (81.8%). The mean LV 3DE DIs expressed as the standard deviation of the time to minimum systolic volume for the number of segments analyzed were 1.16 ± 0.58 for 16 segments, 1.01 ± 0.60 for 12 segments, and 0.93 ± 0.68 for 6 segments. The mean LV 3DE DIs expressed as the time difference between the earliest and latest contracting segments were 3.80 ± 1.57 for 16 segments, 2.99 ± 1.42 for 12 segments, and 2.27 ± 1.35 for 6 segments. There were no effects of age, heart rate, body surface area, or LV end-diastolic volume on 3DE DIs. Intraobserver variability was 5.1%, and interobserver variability was 7.6%.
Conclusion
Three-dimensional echocardiographic DI analysis is reproducible and feasible in most children. Three-dimensional echocardiographic DIs are not affected by growth-related parameters in children but are lower than previously reported adult values.
The use of resynchronization therapy for the treatment of left ventricular (LV) dyssynchronous systolic dysfunction in children has been expanding and includes temporary perioperative multisite pacing as well as chronic treatment of the failing ventricle in cardiomyopathy and in those with congenital heart disease. Because QRS duration is not a reliable indicator of the presence or severity of dyssynchrony in every case, particularly in children, additional methods of quantitation of dyssynchrony are needed. Reports of normal values for three-dimensional echocardiographically derived dyssynchrony indices (DIs) in children are limited by small sample size and lack of data in patients aged < 12 years. The purpose of this study was threefold (1) to define normal values for LV real-time quantitative three-dimensional echocardiographic (3DE) DIs, (2) to analyze the feasibility and observer variability of 3DE DIs in a wide range of children, and (3) to determine the effects of age, heart rate (HR), body surface area (BSA), and LV end-diastolic volume (LVEDV) on these parameters.
Methods
Study Population
The study population consisted of 125 normal children aged 1 day to 19 years. Appropriate subjects were defined as healthy children who were referred for evaluation of heart murmur, chest pain, or sports clearance. All had no histories of cardiovascular disease, no cardiac symptoms, normal blood pressure, normal electrocardiographic results with normal QRS durations, and normal results on complete standard two-dimensional, pulsed-wave Doppler, and color Doppler echocardiography. All had official interpretations of normal echocardiographic results for age, including small patent foramen ovales with trivial left-to-right shunt in younger patients, as read by the clinical echocardiography attending physicians, who were blinded to the 3DE findings.
Real-Time Three-Dimensional Echocardiography
Real-time three-dimensional echocardiography was performed using the iE33 ultrasound machine (Philips Medical Systems, Andover, MA) with either the X3-1 or the X7-2 transducer. Images were optimized to obtain the entire left ventricle in the full-volume data set in the apical four-chamber view. Data sets were acquired using a four-heartbeat or seven-heartbeat acquisition setting during a period of stable HR, defined as the HR not changing during the acquisition time and varying by <3 beats/min for the 30 seconds before acquisition. End-expiratory breath holding was performed when feasible. A minimum of four data sets were acquired in each subject, and the three highest quality data sets were selected for analysis. Data sets that excluded a portion of the left ventricle, had indistinct endocardial borders, or had stitch artifacts were excluded.
Data Analysis
This study was prospectively planned and conducted. After three-dimensional images were obtained as a real-time pyramidal volumetric data sets in full-volume acquisition mode, offline analysis was performed on a QLAB workstation (3DQ-Advanced; Philips Medical System). In each data set, the frame immediately before full closure of the mitral valve was selected as end-diastole, and the frame immediately before full closure of the aortic valve was selected as end-systole. Five anatomic landmarks were identified from apical two-chamber and four-chamber orthogonal views, which were extracted from the pyramidal data set in multiplanar reconstruction mode: two points to specify each edge of the mitral valve annulus in two-chamber and four-chamber views and one point to identify the LV apex. A cast of the LV cavity was then created using an automatic edge detection algorithm and divided into 16 segments, excluding the cardiac apex. Endocardial tracking was inspected on a frame-by-frame basis and manually edited as needed. A time-volume data curve for each of the segments over the cardiac cycle was generated and displayed automatically along with end-diastolic volume, end-systolic volume, stroke volume, and ejection fraction. The time taken to reach minimum systolic volume for each of the 16 standard myocardial segments was calculated automatically. The systolic DI was defined as the standard deviation of these timings, expressed as a percentage of the RR interval (SD%). In addition, the maximum time difference of the time taken to reach minimum systolic volume between the earliest and latest contracting segments was calculated and expressed as a percentage of the RR interval (difference%). The same measurements were performed for 12 segments (six basal and six mid segments) and 6 segments (six basal segments only).
Reproducibility Analysis
Interobserver variability was measured by evaluating 26 randomly selected data sets by two of the investigators. Intraobserver variability was measured by evaluating 26 randomly selected data sets twice by one investigator with a 2-month interval between the two analyses.
Statistical Analysis
Continuous data are reported as mean ± SD. DIs were analyzed by descriptive statistics, including lowest and highest values, mean, median, and percentile distribution. Skew and kurtosis analysis were used to evaluate the degree of symmetry and data distribution and the degree of peakness or flatness of the data distribution. Generalized linear model was performed to determine the effects of age, HR, BSA, and LVEDV on DIs. Bland-Altman analysis was used to examine intraobserver and interobserver variability. Statistical significance was declared when computed P values from two-sided tests were <.05. Analyses were performed using SPSS version 18.0 for Windows (SPSS, Inc., Chicago, IL).
Ethics
This study complied with all institutional requirements for patient confidentiality and safety, including institutional review board approval. There were no financial or other relationships present that may have biased the results or their interpretation.
Results
Feasibility of 3DE Acquisition, Demographic Characteristics, and 3DE LV Volumes
In 23 of the 125 subjects (18.4%), it was not possible to derive 3DE DIs or 3DE volumetric analyses, because of inadequate visualization of LV segments due to body habitus, lack of patient cooperation, extensive respiratory motion, or stitch artifacts. Acquisition of real-time 3DE data sets was feasible in 102 subjects (81.8%). Therefore, the final quantitative study population encompassed 102 healthy children (54 male, 48 female; age range, 1 day to 19 years; mean age, 9.5 ± 5.9 years). The age groups of these 102 children included 22 aged < 1 year, 18 aged 1 to 5 years, 37 aged 5 to 12 years, and 35 aged > 12 years. All 102 subjects were in sinus rhythm. HRs ranged from 47 to 167 beats/minute (mean, 91 ± 28 beats/min). Respiratory rates varied from 0 breaths/min with breath holding to 32 breaths/min in a neonate. No child aged < 5 years performed effective breath holding. In those unable to hold their breath, respiratory rates varied from 14 to 32 breaths/min. BSAs ranged from 0.12 to 2.20 m 2 (mean, 1.18 ± 0.61 m 2 ). By real-time 3DE imaging, LVEDVs ranged from 2.6 to 122.2 mL (mean, 58.7 ± 35.4 mL), LV end-systolic volumes ranged from 0.8 to 53.5 mL (mean, 19.5 ± 13.8 mL), LV stroke volumes ranged from 1.8 to 85.5 mL (mean, 39.2 ± 23.2 mL), and LV ejection fractions ranged from 51.6% to 82.0% (mean, 68.3 ± 7.1%) ( Table 1 , Figure 1 ). Frame rates varied from 16 to 62 frames/sec (from 16 to 39 frames/sec for four-beat acquisition mode and from 23 to 62 frames/sec for seven-beat acquisition mode). Frame rates in patients aged < 1 year ranged from 39 to 62 frames/sec, in those aged 1 to 12 years from 27 to 48 frames/sec, and in those aged > 12 years from 18 to 30 frames/sec.
| Variable | Range | Mean ± SD |
|---|---|---|
| Age | 1 day to 19 years | 9.5 ± 5.9 years |
| HR (beats/min) | 47–167 | 91 ± 28 |
| BSA (m 2 ) | 0.12–2.20 | 1.18 ± 0.61 |
| EDV (mL) | 2.6–122.2 | 58.7 ± 35.4 |
| ESV (mL) | 0.8–53.5 | 19.5 ± 13.8 |
| SV (mL) | 1.8–85.5 | 39.2 ± 23.2 |
| EF (%) | 51.6–82.0 | 68.3 ± 7.1 |
Normal Values and Distribution of DIs
LV 3DE DIs expressed as SD% were 1.16 ± 0.58 for 16 segments, 1.01 ± 0.60 for 12 segments, and 0.93 ± 0.68 for 6 segments. LV 3DE DIs expressed as difference% were 3.80 ± 1.57 for 16 segments, 2.99 ± 1.42 for 12 segments, and 2.27 ± 1.35 for 6 segments. Results along with statistical descriptive analyses are summarized in Table 2 . Figure 2 shows histograms representing the frequency distribution of SD% and difference% for 16, 12, and 6 segments.
| SD% | Difference% | |||||
|---|---|---|---|---|---|---|
| Variable | 16 Segments | 12 Segments | 6 Segments | 16 Segments | 12 Segments | 6 Segments |
| Range | 0.27–3.17 | 0.20–3.33 | 0.09–4.15 | 1.02–8.73 | 0.74–8.73 | 0.26–6.77 |
| Mean ± SD | 1.16 ± 0.58 | 1.01 ± 0.60 | 0.93 ± 0.68 | 3.80 ± 1.57 | 2.99 ± 1.42 | 2.27 ± 1.35 |
| Median | 1.01 | 0.85 | 0.79 | 3.59 | 2.64 | 1.99 |
| Skewness | 1.201 | 1.624 | 2.337 | 0.744 | 1.114 | 1.094 |
| SE of skewness | 0.239 | 0.239 | 0.239 | 0.239 | 0.239 | 0.239 |
| Kurtosis | 1.415 | 3.236 | 7.280 | 0.460 | 2.073 | 0.976 |
| SE of kurtosis | 0.474 | 0.474 | 0.474 | 0.474 | 0.474 | 0.474 |
| Percentiles | ||||||
| 2.5 | 0.3103 | 0.2200 | 0.1473 | 1.3305 | 0.7700 | 0.3678 |
| 25 | 0.7175 | 0.6500 | 0.5225 | 2.5875 | 2.0250 | 1.3250 |
| 50 | 1.0100 | 0.8450 | 0.7850 | 3.5900 | 2.6400 | 1.9900 |
| 75 | 1.4700 | 1.2750 | 1.0300 | 4.7450 | 3.8400 | 2.8800 |
| 97.5 | 2.7925 | 3.0268 | 3.4572 | 7.5617 | 6.5515 | 5.6662 |
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