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\begin{document}

\title{A Multicenter Study of Three-dimensional Echocardiographic Evaluation of
Normal Pediatric Left Ventricular Volumes and Function with Automated
Versus Semi-Automated Quantification}



\author[1]{Pei-Ni Jone}%
\author[1]{Lisa Le}%
\author[2]{Zhaoxing Pan}%
\author[3]{Tim Colen}%
\author[3]{Sachie Shigemitsu}%
\author[3]{Nee Scze Khoo}%
\author[4]{Benjamin Goot}%
\author[5]{Anitha Parthiban}%
\author[6]{David Harrild}%
\author[7]{Alessandra Ferraro}%
\author[6]{Gerald Marx}%
\affil[1]{Children's Hospital Colorado}%
\affil[2]{University of Colorado Denver Children's Hospital Colorado Research Institute}%
\affil[3]{Stollery Children's Hospital}%
\affil[4]{Childrens Wisconsin}%
\affil[5]{Children's Mercy Hospitals and Clinics}%
\affil[6]{Boston Children's Hospital}%
\affil[7]{Boston Children s Hospital}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Background: Three-dimensional echocardiography (3DE) evaluation of left
ventricular (LV) volume and function in pediatrics compares favorably
with cardiac magnetic resonance imaging. A multicenter trial with
automated and semi-automated LV quantification allows for generation of
normative data in large pediatric patients. The aims of this study were
to evaluate the feasibility and reproducibility of measuring
three-dimensional echocardiography (3DE) volumes and function in
pediatric patients in a multicenter trial; to determine if automated
software (without contouring edits) will improve the reproducibility in
volume and function analysis; and thus establish normal z score values
in this unique population. Methods: Six hundred and ninety-eight healthy
children (ages 0 to 18 years) were recruited from 5 centers. Left
ventricular (LV) 3DE was acquired from the 4-chamber view. A vendor
independent software analyzed end-diastolic volume (EDV), end-systolic
volume (ESV), stroke volume (SV), and ejection fraction (EF) using
automated and semi-automated quantification. Feasibility and
reproducibility were assessed. Body surface area (BSA) based z-scores
were generated. Results: Feasibility was 79\% (523/658). Reproducibility
was good between centers using the semi-automated quantification.
Reproducibility was decreased using the automated quantification.
Therefore, Z-scores were generated for ESV, EDV, and SV using the
semi-automated method. Conclusions: 3DE can reliably evaluate LV volumes
and EF in pediatric patients at different centers. We report pediatric
Z-scores for normal LV volumes using the semi-automated method. Further
optimization of technology will be necessary for reliable use of fully
automated quantification by 3DE in children.%
\end{abstract}%



\sloppy


\textbf{A Multicenter Study of Three-dimensional Echocardiographic
Evaluation of Normal Pediatric Left Ventricular Volumes and Function
with Automated Versus Semi-Automated Quantification}

Pei-Ni Jone MD\selectlanguage{ngerman}¹, Lisa Le RDCS¹, Zhaoxing Pan PhD², Tim Colen MBBS³,
Sachie Shigemitsu MD³, Nee Khoo MBBS³, Benjamin H. Goot MD\selectlanguage{english}4, Anitha
Parthiban MD5, \selectlanguage{english}David M. Harrild MD, PhD6, \selectlanguage{english}Alessandra M. Ferraro MD6,
\selectlanguage{english}Gerald Marx MD6

\selectlanguage{ngerman}¹Pediatric Cardiology, Children's Hospital Colorado, University of
Colorado School of Medicine, Aurora, Colorado

²Research Institute, Children's Hospital Colorado, University of
Colorado School of Medicine, Aurora, Colorado

³Stollery Children's Hospital, University of Alberta, Edmonton, Canada

\selectlanguage{english}4Herma Heart Institute, Children's Wisconsin, Medical College of
Wisconsin, Milwaukee, Wisconsin

5\selectlanguage{english}Children's Mercy Hospital, University of Missouri, Kansas City,
Missouri

6\selectlanguage{english}Boston Children's Hospital, Harvard Medical School, Boston,
Massachusetts

\textbf{Disclosures:} The authors report no disclosures.

\textbf{Corresponding Author:}

Pei-Ni Jone MD

Mailing Address:

13123 East 16\textsuperscript{th} Avenue, B100, Aurora, Colorado 80045

Telephone: 720-777-2944

E-mail: pei-ni.jone@childrenscolorado.org

\textbf{Background:} Three-dimensional echocardiography (3DE) evaluation
of left ventricular (LV) volume and function in pediatrics compares
favorably with cardiac magnetic resonance imaging. A multicenter trial
with automated and semi-automated LV quantification allows for
generation of normative data in large pediatric patients. The aims of
this study were to evaluate the feasibility and reproducibility of
measuring three-dimensional echocardiography (3DE) volumes and function
in pediatric patients in a multicenter trial; to determine if automated
software (without contouring edits) will improve the reproducibility in
volume and function analysis; and thus establish normal z score values
in this unique population.

\textbf{Methods:} Six hundred and ninety-eight healthy children (ages 0
to 18 years) were recruited from 5 centers. Left ventricular (LV) 3DE
was acquired from the 4-chamber view. A vendor independent software
analyzed end-diastolic volume (EDV), end-systolic volume (ESV), stroke
volume (SV), and ejection fraction (EF) using automated and
semi-automated quantification. Feasibility and reproducibility were
assessed. Body surface area (BSA) based z-scores were generated.

\textbf{Results:} Feasibility was 79\% (523/658). Reproducibility was
good between centers using the semi-automated quantification.
Reproducibility was decreased using the automated quantification.
Therefore, Z-scores were generated for ESV, EDV, and SV using the
semi-automated method.

\textbf{Conclusions:} 3DE can reliably evaluate LV volumes and EF in
pediatric patients at different centers. We report pediatric Z-scores
for normal LV volumes using the semi-automated method. Further
optimization of technology will be necessary for reliable use of fully
automated quantification by 3DE in children.

\textbf{Key words:} Three dimensional echocardiography, left ventricular
volume, left ventricular function, normal data

\textbf{INTRODUCTION}

Quantification of left ventricular size and function from
echocardiography is important in the diagnosis, prognosis, and
management of pediatric heart disease.\textsuperscript{1} With rapid
improvement in technology, three-dimensional echocardiography (3DE)
evaluation of left ventricular (LV) volume and function in pediatrics
compares favorably with magnetic resonance imaging
(MRI)\textsuperscript{2-5}. However, a multicenter trial, to assess
reproducibility, has not been done in the pediatric population.

Recent technological advances allow fully automated quantification
(without edits to LV contouring borders) of left heart chamber by 3DE,
thus potentially reducing the time and difficulty, and potentially
increasing the reliability of the LV volume quantification. Automated
contouring might enhance the adoption of 3DE quantification of LV that
can be incorporated into routine clinical practice.

A multicenter trial would provide important data concerning the
reproducibility of 3DE to measure LV volumes and function. Such a
large-scale study would also allow for generation of normative data in
pediatric patients. Moreover, such a study could also evaluate the
differences between automated and semi-automated quantification
software. Thus, the aims of this study were to evaluate the feasibility
and reproducibility of measuring 3D volumes and function in young
pediatric patients in a multicenter trial; and to determine if automated
software (without contouring edits) will improve the reproducibility in
volume and function analysis; and thus establish normal z score values
in this unique population.

\textbf{METHODS:}

\emph{Study population}

Three-dimensional LV datasets were obtained from healthy subjects from 5
pediatric centers from 2014-2019. Inclusion criteria were normal
subjects (ages 0 to 18 years) who presented for routine clinical care
for heart murmur, chest pain, or syncope. These subjects had
echocardiographic evidence of structurally and functionally normal
hearts. Exclusion criteria were similar to the Pediatric Heart Network
normal echocardiographic database.\textsuperscript{6} Patients with
cardiac abnormalities (except for patent foramen ovale, trivial branch
pulmonary stenosis, or inaudible patent ductus arteriosus), Kawasaki
disease, cardiomyopathy, exposure to anthracyclines, cardiac
transplantation, chronic systemic disease, and preterm infants
\textless{}37 weeks gestation were excluded. Consents and waiver of
consents were obtained based on the individual institutional ethics
boards and data use agreements were obtained from each center to
Children's Hospital Colorado (Center 1) which served as the core
laboratory for the study. All 3D datasets were anonymized and sent to
the core laboratory for data analysis.

\emph{3D dataset acquisition and analysis}

Real-time 3DE image acquisitions of the LV from the 4-chamber view were
performed using echocardiographic ultrasound platforms (GE Vivid E9/E95;
Vingmed Ultrasound, Horten, Norway, iE33/EPIQ; Philips Medical Systems,
Andover, MA, USA, and/or Siemens SC2000, Siemens Medical Solutions,
Malvern, PA, USA). 3D datasets were excluded by the core lab if any
portion of LV endocardial borders or LV apex were missing from the 3D
dataset. Studies were also excluded if the vendor independent software
(4D LV Analysis, TomTec Imaging Systems version 4.0, Unterschleissheim,
Germany) was not able to automatically track the borders of the LV after
three attempts. At each center (with the exception of center 5), the
fully automated method was first used to generate LV end diastolic and
end systolic volumes (EDV and ESV), stroke volumes (SV), and ejection
fraction (EF) without editing the borders of the LV. Timing from the
start to the end of the analysis was recorded. Then semi-automated
analysis was performed by all centers on the same datasets, manually
editing the contours to define the LV endocardial borders for the same
variables. Timing from the start to the end of the analysis was again
recorded. All LV EDV, ESV, SV, and EF data points from each center were
entered into REDCap located at the core laboratory. Subsequently, all
3DE datasets were transferred to the core laboratory and had the LV
volumes and EF re-measured using the fully automated and semi-automated
methods described above. The core laboratory observer was blinded to the
reported measures in REDCap to determine intercenter reproducibility.
The core laboratory then repeated analysis for intraobserver and
interobserver variability 6 months after initial analysis in 86 randomly
selected studies at the core lab.

\emph{Statistical analysis}

Continuous data were expressed as mean \selectlanguage{ngerman}± standard deviation (SD) or
median and interquartile range (IQR). Reproducibility within core lab
and between centers was compared by Bland-Altman plot and percent
difference was calculated for LV EDV, ESV, and SV as difference of the
two measures divided by the mean of the two measures. Time required to
complete fully automated and semi-automated contouring were compared
between centers using analysis of variance (ANOVA) and as a group using
student t-test. BSA was calculated using Haycock's
method\textsuperscript{7}. To build the z-model of a parameter (i.e.
ESV, DSV and SV), we selected an optimum exponent, \selectlanguage{greek}α, \selectlanguage{english}of the index
parameter (parameter/BSA\selectlanguage{greek}\textsuperscript{α}\selectlanguage{english}) such that: 1.) The index
parameter satisfactorily follows a normal distribution and 2.)The index
parameter does not depend upon BSA. Z-score was then calculated as

\(Z=\frac{[\ \left(\frac{\text{parameter}}{\text{BSA}^{\alpha}}\right)-\left(\text{mean\ value\ of\ indexed\ parameter}\right)]}{\text{SD\ of\ indexed\ parameter}}\).\textsuperscript{6}Normality of an indexed parameter
was evaluated using Shapiro-Wilk and Kolmogorov-Smirnov tests, Q-Q plot,
skewness and kurtosis. Dependence of the indexed parameter on BSA was
evaluated with a test of the slope of the linear regression of the
indexed parameters on BSA. We conducted grid search with a 0.001 step
size to find the optimum exponent, \selectlanguage{greek}α, \selectlanguage{english}and chose the one that maximized
the sum of p-value for Shapiro-Wilk test and the p-value of testing the
slope of index parameter vs. BSA. During the model development,
diagnostic analysis were conducted using leave-one-out method. Few data
points with extreme values that influences the distribution of indexed
parameter were excluded from the final z-model development. After the
optimum has determined, association of indexed parameter with age and
gender were further examined with respectively linear regression and
Student t-test. Gender specific z-scores model hence developed because
there is difference between genders in indexed parameter. A two-sided
p-value \textless{}0.05 was considered statistically significant.
Statistical analysis was performed using SAS version 9.4 (SAS institute,
Cary, NC).

\textbf{RESULTS:}

\emph{Study Subjects}

Six hundred fifty-eight subject studies were sent to the core lab for
analysis. Five hundred twenty-three (79\%) LV 3D datasets could reliably
be traced at the core lab using the automated and semi-automated method.
The median (IQR) patient age was 10 (5 to 14) years. Eighteen percent
(96/523) of the patients were [?] 3 years of age. The mean BSA was 1.2 \selectlanguage{ngerman}±
0.5 m². There were 291 males (56\%) and 232 females (44\%). The age
range and feasibility of study subjects in different age groups are
reported in Table 1.

\emph{Comparison of automated versus semi-automated methods}

Five hundred and thirty-eight datasets were used for automated and
semi-automated methods comparison from all centers. Bland-Altman
analysis showed wide limit of agreement (LOA) between the automated
versus semi-automated contouring of the 3D LV datasets. The bias (LOA)
for EDV, ESV, SV, and EF were -0.56\% (-32.25 to 31.13), 1.01 (-29.94 to
31.96), -1.73 (-18.12 to 14.65), and -1.52 (-17.05 to 14.01)
respectively (Table 2). Sub-analysis of the inter-center reproducibility
for LV volumes and function between the core lab and other centers using
the automated method showed a bigger bias and LOA than the
semi-automated methods (Table 2). The inter-center reproducibility for
LV volumes and EF showed less bias and LOA between the core lab and
other centers using semi-automated contouring (Figure 1 and Table 2).
The percent difference using the automated and semi-automated methods
for LV EDV, ESV, and SV were summarized in Figure 2. The mean percentage
difference in EDV and ESV are higher using the automated method compared
to the semi-automated method. The mean absolute percent difference in 3D
LV EF between all centers was 7.4±5.4\%. Figure 3 shows the Bland-Altman
analysis percent difference of the core lab and other centers using the
semi-automated method in ages 0-4 years, 5-9 years, 10-14 years, and
15-18 years of age respectively.

\emph{Automated versus semi-automated contour timing}

Automated contouring of the LV 3D datasets was faster than
semi-automated contouring. The mean ± SD (minutes) in automated
contouring in in Centers 1-4 were 0.19 ± 0.02, 0.56 ± 0.16, 0.19 ± 0.06,
and 0.32 ± 0.09 minutes respectively (p\textless{}0.001). The mean ± SD
(minutes) in semi-automated contour timing in Center 1-5 were 2.66 ±
0.63, 2.39 ± 0.78, 3.35 ± 1.04, 3.48 ± 1.03, and 2.82 ± 0.66 minutes
respectively (p\textless{}0.001).

\emph{Core Lab Intraobserver Reproducibility of Automated and
Semi-automated Methods}

The intraobserver variability of 86 studies using automated and
semi-automated methods in the core lab was excellent and shown in Table
3. The bias was small in all variables using each of the individual
methods. The LOA of the automated versus semiautomated contouring of the
LV size and function were very wide.

\emph{Z-score generation}

Normative pediatric z-score generation was performed on the 523 LV 3D
datasets using the semi-automated method. The optimum exponents are
shown in Table 4 as well as the mean and SD of indexed parameters.
Figure 4 demonstrates the normative data and z-score for ESV, EDV, and
SV derived from the semi-automated method.

\textbf{DISCUSSION}

This study reports the largest multicenter data collection for
development of 3D echocardiographic z-scores for LV volumes and function
in healthy North American children using the semi-automated
quantification method. The feasibility was 79\% analyzable datasets at
the core laboratory. We demonstrated that the semi-automated software
quantification with LV border adjustment was more reliable between
centers than automated software quantification. Although automated
software quantification took less time, the greater variability in
measurement rendered it less reliable, and therefore the normative
Z-score values were derived from the semi-automated method.

Our study had feasibility of 79\% of obtaining adequate 3D data for
analysis at the core laboratory, similar to another multicenter study in
the pediatric age group \textsuperscript{8}. Krell et al reported having
a feasibility of 74\% in their multicenter study but our study
population was larger with more patients. Kuebler et al reported
normative LV volume and functional values in 238 pediatric subjects of
different age group and body surface area \textsuperscript{9}. Only 14\%
of their subjects were under the age of 5 (34/238) \textsuperscript{9}.
Our study is notable in that 27\% (141/523) of the subjects were under
the age of 5 and 18\% were less than 3 years old. This is the population
that is technically challenging to acquire 3D volumes as young patients
are unable to hold their breath or stay relatively motionless during the
acquisition, obviating ``stitch artifact''. On the other hand, they may
have the best imaging window due to smaller chest walls and ability to
incorporate the entire ventricular volume into the dataset. Cantinotti
et al studied 800 Italian healthy children and reported excellent
feasibility of 91\%; however, the feasibility for smaller children with
smaller BSA less than 0.5 was 68\% to 80\%
respectively\textsuperscript{10}.

We did not find that the automated quantification software improved the
reproducibility in volume and function analysis. There was wide LOA
between automated and semiautomated LV quantification in all centers.
The automated software frequently did not track the LV endocardial
borders. This became apparent in the intraobserver reproducibility in
the core lab when the same LV datasets were re-measured using the
semi-automated contouring method. The intraobserver reproducibility was
excellent when semi-automated method was used and showed small bias and
LOA. However, the intraobserver reproducibility did not have good
agreement when automated versus semi-automated quantification comparison
was used on the same LV datasets. This study highlights the difference
between pediatric and adult studies of using automated versus
semi-automated contouring of LV volumes and function. We postulate that
the current automated contouring does not adequately track LV contours
in pediatric 3D datasets because the fully automated algorithms are
built based on adult 3D datasets. The time for semi-automated contouring
of the LV was not more than a mean of 2-3 minutes in all centers, which
should be acceptable for routine clinical use.

Our study is unique in that we performed extensive analysis of
reproducibility by comparing all 3D datasets from 4 different centers to
the core lab using the semi-automated and automated methods. The
semi-automated methods between centers were reproducible. The percent
difference in the LV EDV was ± 30\% indicating that if an individual
measured the LV EDV at 10ml, the difference could be ± 3ml. This is an
acceptable range of measures between centers. The percent difference for
LV ESV measurement was also about ± 30\% (Figure 3). The LOA of LV
volumes and EF were wider using the automated methods compared to the
semi-automated methods between the core lab to other centers, indicating
that LV volumes and EF were not reproducible using this method. Prior
studies from Kuebler et al and Cantinotti et al have described pediatric
normative LV volumes and function derived from single
centers\textsuperscript{9,10}. Similar to previous studies, LV volumes
indexed to the BSA demonstrated gradual increase from childhood to
adolescent years \textsuperscript{8-12}.

The mean absolute percent difference in 3D LV EF between all centers in
our study was 7\% with the observed difference of 4.2\% if the LV EF was
measured at 60\%. This is better than the reported 2D LV EF absolute
percentage difference of 11.2\% in the Pediatric Heart Network
study\textsuperscript{13}. 3D LV EF has been reported to be more
accurate and reproducible than 2D LV EF in adults and children because
3DE does not rely on geometric assumptions and is less affected by
acquisition technique such as foreshortening \textsuperscript{3,14-18}.
Thus, it is recommended that 3D LV EF should be reported in clinical
echocardiograms in centers with experience in 3DE \textsuperscript{18}.
Our study demonstrated that the reproducibility of 3D LV EF is good to
excellent and can be used in multiple centers.

\textbf{Limitations}

The limitation of the study includes race and ethnicity were not
reported because of the limited data use agreement among centers in
which this information could not be collected. The 1 to 2 year-old
patients were difficult to recruit as they were the most uncooperative
patients and frequently cannot breath hold for image acquisition. We did
not record the amount of time we spent in acquiring the LV 3D datasets
as this can be quite variable depending on the state of the child's
cooperation. However, the post-processing using semi-automated
contouring is feasible once a good dataset is acquired and does not
consume large amount of time making this clinically feasible to use.

\textbf{CONCLUSION}

Generation of normal pediatric z-scores for LV volumes and function from
3DE is feasible, and these values can serve as a reference for pediatric
patients. Semi-automated contouring for the LV in pediatrics is reliable
and reproducible. Agreement between centers was good and supports
between-center comparison of LV volumes and EF. Further optimization of
technology is necessary for reliable use of fully automated
quantification by 3DE in children.

\textbf{Sources of Funding:} None

\textbf{REFERENCES}

1. Lopez L, Colan SD, Frommelt PC, et al. Recommendations for
quantification methods during the performance of a pediatric
echocardiogram: a report from the Pediatric Measurements Writing Group
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2. Shimada YJ, Shiota T. A meta-analysis and investigation for the
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6. Lopez L, Colan S, Stylianou M, et al. Relationship of
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Race, and Ethnicity: The Pediatric Heart Network Normal Echocardiogram
Database. \emph{Circ Cardiovasc Imaging.} 2017;10(11).

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8. Krell K, Laser KT, Dalla-Pozza R, et al. Real-Time Three-Dimensional
Echocardiography of the Left Ventricle-Pediatric Percentiles and
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9. Kuebler JD, Ghelani S, Williams DM, et al. Normal Values and
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10. Cantinotti M, Scalese M, Giordano R, et al. Three-Dimensional
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11. Buccheri S, Costanzo L, Tamburino C, Monte I. Reference Values for
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13. Frommelt PC, Minich LL, Trachtenberg FL, et al. Challenges With Left
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\textbf{Tables}

\textbf{Table 1: Feasibility of study subjects in different age group}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Age (years) & Traceable datasets (N=523) M/F (291/232) & Total in age
group (N=658) & Feasibility in age group (\%)\tabularnewline
\midrule
\endhead
\textless{}1 & 51 & 66 & 77.3\tabularnewline
1 & 6 & 9 & 66.7\tabularnewline
2 & 14 & 19 & 73.7\tabularnewline
3 & 25 & 35 & 71.4\tabularnewline
4 & 15 & 17 & 88.2\tabularnewline
5 & 30 & 38 & 78.9\tabularnewline
6 & 24 & 28 & 85.7\tabularnewline
7 & 21 & 27 & 77.8\tabularnewline
8 & 18 & 21 & 85.7\tabularnewline
9 & 35 & 45 & 77.8\tabularnewline
10 & 28 & 34 & 82.4\tabularnewline
11 & 34 & 39 & 87.2\tabularnewline
12 & 31 & 41 & 75.6\tabularnewline
13 & 37 & 42 & 88.1\tabularnewline
14 & 37 & 49 & 75.5\tabularnewline
15 & 41 & 49 & 83.7\tabularnewline
16 & 30 & 39 & 76.9\tabularnewline
17 & 30 & 40 & 75.0\tabularnewline
18 & 16 & 20 & 80.0\tabularnewline
\bottomrule
\end{longtable}

M = male, F= female

\textbf{Table 2: Bland-Altman analysis of automated and semi-automated
measurements of left ventricular volumes and function in all centers,
and Bland-Altman analysis of automated and semi-automated methods
between core lab and other centers.}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Auto vs Semi} \textbf{All centers}\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Auto Center 1 vs all centers}\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
\textbf{Semi Center 1 vs all centers}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{EDV (ml)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.56 -32.25 to 31.13 0.423\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-3.85 -38.93 to 31.22 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.46 -23.86 to 24.77 0.474\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{ESV (ml)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
1.01 -29.94 to 31.96 0.140\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-4.21 -42.01 to 33.59 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2.56 -10.81 to 15.94 \textless{}0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{SV (ml)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-1.73 -18.12 to 14.65 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.36 -12.20 to 12.92 0.299\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-2.19 -19.55 to 15.17 \textless{}0.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{EF (\%)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-1.52 -17.05 to 14.01 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
4.16 -9.86 to 18.17 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-3.11 -12.67 to 6.44 \textless{}0.001\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

EDV = end-diastolic volume, EF = ejection fraction, ESV = end-systolic
volume, LOA = limit of agreement, SD = standard deviation, SV = stroke
volume.

\textbf{Table 3: Intraobserver variability of semi-automated and
automated measurements of left ventricular volumes and function at core
lab using Bland-Altman analysis.}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
Center 1 (core lab)\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
Semi 1 versus Semi 2 (n=86)\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
Auto 1 versus Auto 2 (n= 86)\strut
\end{minipage} & \begin{minipage}[b]{0.24\columnwidth}\raggedright\strut
Auto 1 versus Semi 1 (n= 86)\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{EDV (ml)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-1.77 -7.73 to 2.12 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.03 -0.64 to 0.58 0.360\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2.22 -19.05 to 23.49 0.061\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{ESV (ml)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.75 -4.71 to 3.21 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.26 -4.92 to 4.40 0.312\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
2.52 -12.31 to 17.35 0.003\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{SV (ml)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-1.02 -5.76 to 3.72 \textless{}0.001\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.23 -3.83 to 4.28 0.313\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.30 -15.58 to 14.98 0.722\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\textbf{EF (\%)}\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
Bias 95\% LOA p\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-0.06 -4.37 to 4.49 0.807\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
0.33 -5.53 to 6.18 0.313\strut
\end{minipage} & \begin{minipage}[t]{0.22\columnwidth}\raggedright\strut
-3.00 -21.13 to 15.13 0.003\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

EDV = end-diastolic volume, EF = ejection fraction, ESV = end-systolic
volume, LOA = limit of agreement, SD = standard deviation, SV = stroke
volume.

\textbf{Table 4: Parameters for calculating z-scores.}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Parameter\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Exponent \selectlanguage{greek}α\selectlanguage{english}\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Gender\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Mean of index parameter\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
SD of index parameters\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
ESV\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.284\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
F and M\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
22.744\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
4.422\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
F\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
21.491\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
3.936\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
M\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
23.768\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
4.538\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
EDV\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.277\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
F and M\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
56.874\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
10.124\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
F\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
53.729\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
8.705\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
M\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
59.416\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
10.485\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
SV\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
1.278\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
F and M\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
34.073\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
6.230\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
F\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
32.237\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
5.497\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
M\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
35.547\strut
\end{minipage} & \begin{minipage}[t]{0.17\columnwidth}\raggedright\strut
6.398\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

Index parameter=Parameter/BSA \selectlanguage{greek}\textsuperscript{α}. \selectlanguage{english}EDV = end-diastolic
volume, ESV = end-systolic volume, F = female, M = male, SV = stroke
volume

\textbf{Figure Legends}

\textbf{Figure 1:} Interobserver variability between the core lab and
other centers using the semi-automated method. Bland-Altman analysis
plots are shown for LV EDV, ESV, SV, and EF. EDV = end-diastolic volume,
EF = ejection fraction, ESV = end-systolic volume, LV = left ventricle,
SV = stroke volume.

\textbf{Figure 2:} Percent difference calculated for LV EDV, ESV, and SV
between core lab versus other centers using the semi-automated and
automated methods. EDV = end-diastolic volume, ESV = end-systolic
volume, LV = left ventricle, SV = stroke volume.

\textbf{Figure 3:} Bland-Altman analysis (percent difference) of left
ventricular parameters in core lab versus other centers in all ages, and
break down of 0-4 years of age, 5-9 years of age, 10-14 years of age,
and 15-18 years of age.

\textbf{Figure 4:} Normative Z-score values for left ventricular
volumes. BSA = body surface area, EDV = end-diastolic volume, ESV =
end-systolic volume, SV = stroke volume.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1/Figure-1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-3/Figure-3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-4/Figure-4}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

