Analysis of left ventricular mass, volume indices and

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Analysis of left ventricular mass, volume indices and ejection fraction from

SSFP cine imaging: a comparison of semi-automated, simplified manual,

detailed manual and geometric modelling techniques

Christopher A Miller1,2,4*, Peter Jordan1, Alex Borg1, Rachel Argyle1, David Clark3,

Keith Pearce1 and Matthias Schmitt1,4

1. Division of Cardiology and Cardiothoracic Surgery, University Hospital of South

Manchester, Wythenshawe, Manchester M23 9LT, UK

2. Cardiovascular Research Group, The University of Manchester, Oxford Road,

Manchester M13 9PL, UK

3. Alliance Medical, Wythenshawe CMR Unit, Wythenshawe, Manchester M23 9LT,

UK

4. Biomedical Imaging Institute, The University of Manchester, Oxford Road,

Manchester M13 9PL, UK

*Corresponding author

Email addresses:

CAM: [email protected]

PJ: [email protected]

AB: [email protected]

RA: [email protected]

DC: [email protected]

KP: [email protected]

MS: [email protected]

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Abstract

Background: Cardiovascular magnetic resonance (CMR) is considered the gold standard for

assessment of left ventricular (LV) mass, volume indices and ejection fraction (EF) however

variability exists due to LV base positioning, end-‐systolic frame identification and method of

endocardial contouring. The aims of this study were first to compare 3 commonly used

analysis techniques; assessing mass, volume indices and EF obtained with each and their

reproducibility, and second to assess the performance of 6 LV geometric models.

Methods: Steady-‐state free precession images from 50 consecutive patients were analysed

with 3 techniques; 1. Semi-‐automated; including semi-‐automated LV base identification,

end-‐systolic frame selection and endocardial contouring; 2. Simplified manual; including

manual basal LV slice identification, end-‐systolic frame selection and simplified endocardial

contouring (papillary muscles and trabeculae included in volumetric measurements); 3.

Detailed manual; identical to ‘Simplified manual’ except with manual detailed endocardial

contouring (papillary muscles and trabeculae included in mass); and 6 geometric models;

Teicholz, modified Simpson’s, hemi-‐ellipse, monoplane, biplane and triplane. Bland-‐Altman

analysis and Wilcoxon rank testing were used to evaluate the level of agreement between

each method and the significance of mean differences respectively. Interobserver and

intraobserver reproducibility were assessed by re-‐analysis of 25 (50%) scans.

Results: The 3 analysis methods were not interchangeable. Simplified manual analysis

significantly overestimated volumes and underestimated EF (EF underestimated by 6+4%

compared to detailed manual analysis, p<0.0005). Both manual techniques significantly

underestimated mass compared to semi-‐automated analysis (simplified manual analysis

43+20g; detailed manual analysis 34+19g; p<0.0005 for both). Semi-‐automated LV base

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position and end-‐systolic frame selection were significantly different from manual

techniques. Semi-‐automated analysis showed significantly higher reproducibility than both

manual techniques for measurement of EF and mass. Geometric models were not

interchangeable with conventional analysis and their reproducibility was low.

Conclusions: Methods for measuring LV mass, volume and EF are not interchangeable and

normal reference ranges appropriate to analysis technique must be used. A technique that

includes semi-‐automated endocardial contouring, LV base identification and end-‐systolic

frame selection is the most reproducible. Analysis of CMR images with geometric models

should be discouraged.

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Background

Accurate and reproducible assessment of left ventricular (LV) mass, volume indices and

ejection fraction is an important strength of cardiovascular magnetic resonance imaging

(CMR). These parameters remain some of the most evidenced-‐based indictors of prognosis,

and both their absolute measurement and temporal change are used to guide

pharmacological, device and surgical intervention [1-‐5].

Although CMR is the gold standard technique for assessment of LV mass, volume and EF, a

number of factors lead to variability in image analysis. First, many institutions use only short-‐

axis images for analysis despite it often being difficult to determine the basal LV slice, and

how much of it to include, from short-‐axis images alone. Arbitrary criteria are widely used,

such as inclusion of a slice within the LV when at least 50% or 75% of the cavity is

surrounded by myocardium (Figure 1) [6-‐8]. Alternatively if a slice is thought to include both

ventricular and atrial myocardium, others advocate tracing up to the apparent junction of

atrium and ventricle before joining up the contours with a straight or curved line through

the blood pool, creating a semi-‐circle or crescent-‐shaped ‘cavity’ [9]. Second, it is standard

practice in many centres to perform simplified endocardial contouring whereby only the

‘compacted’ endocardial border is traced (Figure 2) [10, 11]. As a result, papillary muscles

and trabeculae are included in cavity volumes rather than within mass. Third, end-‐systolic

frame selection is usually performed manually by visually identifying the frame with the

smallest cavity [6]. However often this is not uniform across short-‐axis slices, particularly in

dyssynchronous ventricles (Figure 3).

This study had two objectives. First, we sought to compare mass, volume indices and EF

obtained using 3 commonly used analysis techniques, and the reproducibility of each

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method, in a prospective cohort reflective of ‘real-‐world’ CMR practice. The 3 techniques

assessed were:

1. Semi-‐automated analysis; including semi-‐automated LV base identification, end-‐systolic

frame selection and endocardial contouring;

2. Simplified manual analysis; including manual basal LV slice identification, end-‐systolic

frame selection and simplified endocardial contouring;

3. Detailed manual analysis; identical to simplified manual analysis except with manual

detailed endocardial contouring (Figures 1-‐3).

We hypothesised that the 3 techniques would yield different LV mass, volume and EF values

and that the techniques would differ in their reproducibility.

Second, we sought to compare volumes and EF obtained with 6 LV geometric modelling

techniques (Figure 4, 5), and the reproducibility of each model, with the most reproducible

of the 3 methods described above.

One of the advantages of CMR is that it can image the LV in its entirety so that no geometric

assumptions need to be made. Nevertheless, a number of LV geometric approximation

models have been validated, are widely used by other imaging modalities, are advocated for

analysing CMR images and are incorporated into state-‐of-‐the-‐art CMR analysis software

packages [8, 12-‐16]. We hypothesised that geometric models would yield different LV

volume and EF values to ‘conventional’ analysis, and would have inferior reproducibility.

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Methods

Patients

The study was conducted according to the Helsinki Declaration. Ethical approval for the

study was given by an ethics committee of the UK National Research Ethics Service

(reference number 08/H1004/153) and written informed consent was obtained from all

participants before entering the study.

Fifty consecutive consenting patients undergoing clinically-‐indicated CMR scanning at a

single institution (University Hospital of South Manchester) were enrolled. Patients were

recruited prospectively, prior to undergoing imaging. The only exclusion criterion was known

complex congenital heart disease. In order to reflect real-‐world clinical practice, patients

were not excluded on the basis of arrhythmia or breath-‐holding ability.

CMR imaging

All patients underwent CMR imaging using a 1.5 Tesla scanner (Avanto; Siemens Medical

Imaging, Erlangen, Germany) with a 32-‐element phased-‐array coil. Steady-‐state free

precession end-‐expiratory breath-‐hold cines were acquired in 3 long-‐axis planes (horizontal

long-‐axis, horizontal short-‐axis and 3-‐chamber long-‐axis). Subsequently, contiguous short-‐

axis cines were acquired from the atrioventricular ring to the apex (SA stack). Typical

parameters included repetition time 2.9ms, echo time 1.2ms, flip angle 80 degrees, matrix

256 x 208, in plane pixel size 1.4 x 1.4mm, slice thickness 8mm (inter-‐slice gap 2mm for the

SA stack), temporal resolution 30-‐50ms, depending on heart rate. Retrospective gating was

used in 48 patients. Prospective gating was used in 2 patients due to arrhythmia.

Image analysis

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LV mass and volumetric analysis was performed on each scan using the 3 methods described

below. Analysis was carried out by a Level 2 accredited operator with over 3-‐years

experience of clinical CMR and of each analysis method.

Semi-‐automated analysis (Auto)

Semi-‐automated analysis was performed using CMRtools (Cardiovascular Imaging Solutions,

London, UK). The epicardial border was manually traced at end-‐diastole in successive short-‐

axis slices. A second contour was placed within the myocardium on the short-‐axis slices at

end-‐diastole and systole allowing the signal intensity between the two contours (i.e. the

signal intensity of myocardium) to be automatically determined. Detailed, semi-‐automated

tracing of the endocardium at end-‐diastole and end-‐systole was then performed using a

signal intensity ‘thresholding’ tool, such that papillary muscles and trabeculae were included

in mass and excluded from volumetric measurements (Figure 2). The mitral and aortic valve

positions at end-‐diastole and systole were manually identified on the 3 long-‐axis images,

allowing the valve planes to be tracked through the cardiac cycle. This was integrated into

the SA stack analysis allowing automated identification of the LV base and outflow tract

(Figure 1). Finally, end-‐systole was automatically determined as being the frame with the

smallest cavity volume, by calculating cavity volume at each frame (Figure 3).

Simplified manual analysis (SimpMan)

Simplified manual analysis was performed using Argus Syngo MR software (Siemens Medical

Imaging, Erlangen, Germany). The epicardial border was manually traced at end-‐diastole in

successive short-‐axis slices. The ‘compacted’ endocardial border was traced on the short-‐

axis slices at end-‐diastole and end-‐systole such that papillary muscles and trabeculae were

included in volumetric and excluded from mass measurements (Figure 2). At the base of the

heart, slices were considered to be within the LV at end-‐diastole and end-‐systole if the cavity

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was surrounded by 50% or more of ventricular myocardium. If the basal slice contained both

ventricular and atrial myocardium, contours were drawn up to the junction and joined by a

curved line through the blood pool (Figure 1). The end-‐systolic frame was manually

identified as the frame in which the LV cavity visually appeared smallest. In cases where

there was a discrepancy between slices, the frame in which the more basal slices had the

smallest cavity was used as it was felt this would more closely represent the smallest cavity

volume.

Detailed manual analysis (DetMan)

Detailed manual analysis was identical to simplified manual analysis except that detailed

manual tracing of the endocardium was performed such that papillary muscles and

trabeculae were included in mass and excluded from volumetric measurements (Figure 2).

The data from each technique was used to calculate end-‐diastolic (EDV) and end-‐systolic

(ESV) volumes, from which stroke volume (SV) and EF were derived. End-‐diastolic myocardial

mass was determined by multiplying myocardial tissue volume at end-‐diastole by 1.05 g/cm3

(specific density of myocardium). Short axis slices were numbered with slice 1 being the

most basal, and the most basal slice included in the analysis at end-‐diastole and end-‐systole

was recorded for each technique, no matter how little of the slice was included. End-‐systolic

frame used and the time taken for analysis was also recorded.

Geometric modelling

LV volumetric analysis was performed on each scan using 6 geometric models (Figure 4, 5).

Appropriate contours were drawn for each model using open-‐source OsiriX Imaging

Software. EDV, ESV and EF were calculated using an OsiriX software plug-‐in, with the

exception of the triplane model where contours were drawn using OsiriX but calculations

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were performed manually as no appropriate plug-‐in was available. Papillary muscles and

trabeculae were included in volumetric measurements. Results obtained from each model

were compared with the method found to be most reproducible of the 3 described above.

LV internal diameter, defined as the distance between the endocardial border of the septum

and the inferolateral wall just distal to the mitral valve leaflet tips in the 3-‐chamber long-‐axis

view, was measured in diastole and systole and compared to EDV and ESV respectively.

Reproducibility

To assess interobserver reproducibility, 25 randomly selected scans (50%) were

independently re-‐analysed by a second experienced observer using the methods described.

To assess intraobserver reproducibility, 25 scans (50%) were re-‐analysed by the first

observer with a 1-‐month temporal separation between analyses.

Statistics

Values are expressed as mean ± standard deviation (SD) unless stated otherwise. Histogram

plots showed the data to be non-‐normally distributed. Agreement between each method

was evaluated using Bland-‐Altman testing by calculating mean difference (bias) and 95%

limits of agreement (i.e. mean difference + 2 SD). The significance of the differences

between each method was assessed using Wilcoxon rank testing. Correlation was assessed

using Spearman’s rank correlation coefficient (whilst it is recognised that assessment of

agreement is more appropriate than correlation, both are displayed in keeping with

convention). Reproducibility of each method was assessed using the repeatability co-‐

efficient (defined as 1.96 x √[sum of the squares of the differences between observer

measurements divided by n]) [17]. The significance of the differences in reproducibility was

assessed using a Wilcoxon rank comparison of the squared differences [18]. P-‐values < 0.05

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were considered significant. Statistical analysis was performed using SPSS Statistics (version

19, IBM).

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Results

Patient characteristics and scan indications were representative of those referred for CMR at

our institution (Table 1). Patients demonstrated a variety of cardiovascular pathology and a

wide range of mass, EDV, ESV and EF (Table 2).

Comparison of semi-‐automated, detailed manual and simplified manual analysis

Volumetric, EF and mass measurement

Compared to the other two techniques, simplified manual analysis significantly

overestimated both EDV and ESV, but ESV to a greater degree (Table 2 and 3, Figure 6). As a

result, this method significantly underestimated SV and EF (mean difference in EF between

semi-‐automated and simplified manual analysis 7+5%, and between detailed manual and

simplified manual analysis 6+4%; p<0.0005 for both). As a consequence, 6 patients (12%)

classified as having a normal EF by the semi-‐automated technique (using a nominal normal

EF cut-‐off of > 55%) were classified as having a reduced EF by the simplified manual

technique. Furthermore, 6 patients (12%) classified as having mild to moderate LV

impairment by the semi-‐automated technique (EF < 55% but > 35%) were classified as

having severe LV impairment (EF < 35%) by the simplified manual technique. There was no

significant difference between semi-‐automated and detailed manual analysis for EDV, ESV,

SV and EF, but the 95% limits of agreement were wide for each parameter suggesting these

methods were not interchangeable (Table 2 and 3).

Whilst the simplified manual technique significantly underestimated mass compared with

the detailed manual technique, both underestimated mass compared with the semi-‐

automated method (mean difference between semi-‐automated and simplified manual

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analysis was 43+20g; between semi-‐automated and detailed manual analysis was 34+19g;

p<0.0005 for both).

Basal slice selection, end-‐systolic frame selection and analysis time

Semi-‐automated analysis determined the base of the LV to be ‘more basal’ than manual

analysis at both end-‐diastole and end-‐systole. The most basal short-‐axis slice included in the

semi-‐automated and manual analyses at end-‐diastole was 1.4+0.5 and 2.0+0.6 respectively

(where short-‐axis slice number 1 is the most basal) and at end-‐systole was 2.1+0.6 and

3.0+0.7 respectively (p<0.0005 for both).

The frame used as end-‐systole was also significantly different between the semi-‐automated

and manual techniques (frame number 10.2+1.5 versus 9.9+1.5 respectively; p=0.003).

However, in the 21 patients where there was a difference in end-‐systolic frame selection,

mean difference in ESV was only 2+1mls.

Time taken for the simplified manual (7.0+1 minutes) and semi-‐automated (7.5+1 minutes)

analyses were both significantly shorter than for detailed manual analysis (11.0+2 minutes;

p<0.0005 for both). There was no significant difference between simplified manual and

semi-‐automated analysis time.

Reproducibility (Figure 7)

Semi-‐automated analysis had higher interobserver and intraobserver reproducibility than

both manual techniques for measurement of EF (interobserver; p<0.0005 compared to

simplified manual technique and p=0.001 compared to detailed manual technique;

intraobserver; p=0.04 compared to both manual techniques) but there was no difference in

reproducibility between the two manual techniques for measurement of EF. Both the semi-‐

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automated and detailed manual techniques were significantly more reproducible than

simplified manual analysis for measurement of EDV and ESV. However there was no

difference in reproducibility between the semi-‐automated and detailed manual techniques

for EDV and ESV measurements. Semi-‐automated analysis had higher interobserver

reproducibility than both manual techniques for measurement of mass (p=0.02 compared to

simplified manual technique and p<0.0005 compared to detailed manual technique)

although intraobserver reproducibility was not significantly different.

Comparison of geometric modelling with semi-‐automated analysis

Geometric models were compared with the semi-‐automated analysis technique. EDV, ESV

and EF varied substantially between geometric models (Table 4). The biplane model was the

most accurate compared with the semi-‐automated technique, with no significant difference

in EDV, ESV and EF, although limits of agreement were wide for each parameter (Table 5).

For the majority of the other models, volume and EF measurements were significantly

different from the semi-‐automated technique, with very wide limits of agreement. There

was a moderate correlation between LV internal diameter in diastole and EDV (RS 0.65) and a

good correlation between LV internal diameter in systole and ESV (RS 0.83).

Interobserver and intraobserver reproducibility for measurement of EF was low for all

models and was significantly lower than that of the semi-‐automated technique (Figure 8).

Reproducibility of EDV and ESV measurements was variable. Interobserver reproducibility

for measurement of EDV using the Teicholz, triplane, modified Simpson’s and biplane

models was not significantly different to that of the semi-‐automated technique. However all

models had significantly lower interobserver reproducibility than the semi-‐automated

technique for measurement of ESV. All models also had statistically lower intraobserver

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reproducibility for measurement of EDV and ESV than the semi-‐automated technique.

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Discussion

This study compared 3 commonly used techniques for measuring LV mass, volume and EF

from CMR SSFP cine images. We found that analysis methods were not interchangeable and

the reproducibility of the methods differed significantly. We also assessed 6 LV geometric

models and found that the majority yielded significantly different volume and EF values

compared to ‘conventional’ analysis and all had statistically inferior reproducibility for

measurement of EF.

Recruitment was prospective and consecutive, without exclusion on grounds of arrhythmia

or breath-‐holding ability and prospective gating was required in 4%. Patients exhibited a

wide range of EF, volumes and mass and a variety of pathology. It is therefore felt that the

study is representative of clinical CMR practice.

Whilst there were no mean differences between the semi-‐automated and detailed manual

techniques for measurement of EDV, ESV and EF, limits of agreement were wide suggesting

they were not interchangeable. As expected, simplified endocardial contouring, where

papillary muscles and trabeculae are included within volumes and excluded from mass, led

to an overestimation of volumes compared to detailed contouring. However in keeping with

other studies, ESV was overestimated to a greater degree (EDV overestimated by 5%, ESV by

19%) [19, 20]. Consequently simplified contouring led to significant underestimation of EF.

The degree of EF underestimation in this study (6% difference between detailed and

simplified manual contouring) is larger than that found by Weinsaft et al [20] (3%) although

the current study includes patients with a wider range of volumes and EF. In a study

assessing the impact of simplified versus detailed tracing of trabeculae alone, Papavassiliu et

al [19] found the simplified technique underestimated EF by 2% (papillary muscles were

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included within mass measurements in all subjects). The greater underestimation of ESV

relative to EDV by the simplified technique may result from it being more difficult to

differentiate the ‘compacted’ endocardial border from papillary muscles and trabeculae at

end-‐systole.

The technique of simplified endocardial contouring is widely practiced [10, 11], despite

detailed contouring (manual or semi-‐automated) having been used to establish normal

reference ranges for SSFP imaging [6, 9, 21] and the greater accuracy of detailed contouring

in ex-‐vivo validatory studies [22, 23]. In this study the use of simplified contouring had

potential clinical implications, with nearly a quarter of patients being assigned to a different

EF ‘category’ compared to detailed contouring (i.e. abnormal EF rather than normal, or

severely impaired EF rather than mild-‐moderately impaired), thus highlighting the

importance of using reference ranges appropriate to the analysis method used.

It appears that the method of endocardial contouring has a greater impact on volumes and

EF than manual versus semi-‐automated LV base positioning and end-‐systolic frame

selection. Detailed manual and semi-‐automated techniques had comparable endocardial

contouring but significant differences in end-‐diastolic and end-‐systolic LV base positioning

and end-‐systolic frame identification. However despite these discrepancies, there were no

differences in volume and EF measurements. Conversely, there was no difference in LV base

positioning and end-‐systolic frame identification between the simplified and detailed

manual endocardial contouring techniques, but volume and EF measurements were

significantly different.

Simplified manual endocardial contouring led to an underestimation of mass compared to

detailed manual contouring, although to a lesser degree than in the study by Weinsaft et al

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[20]. The detailed manual technique also significantly underestimated mass compared with

the semi-‐automated method, with a mean difference of 34g. This large difference appears to

be in accordance with the difference seen between studies by Maceira et al [21] and

Hudsmith at al [6] that defined normal values for LV mass (and volumes and EF) using

different analysis techniques. Using the semi-‐automated method, Maceira et al found mean

myocardial mass to be 156g in healthy males and 128g in healthy females but using the

detailed manual technique, Hudsmith et al found mean mass to be 123g and 96g in healthy

males and females respectively. The reason for this substantial difference between

techniques is not clear, particularly because there were no discernable differences in

epicardial contouring in the current study. It is possible however that the difference in LV

base positioning has a large effect on mass measurements. This finding further highlights the

importance of using normal reference ranges appropriate to analysis method used.

The semi-‐automated technique was the most reproducible for measurement of EF and

mass. With automatically determined end-‐systole, straightforward identification of the

mitral valve plane from long-‐axis images (and hence LV base) and semi-‐automatic

endocardial border tracing, the main observer variability for the semi-‐automated technique

stems from the manual epicardial contouring (which only affects mass) and the level of the

‘thresholding’. In comparison, manual analysis requires much greater manual input

(including manual endocardial and epicardial tracing, manual identification of the LV base

from short axis images alone and manual identification of end-‐systole), explaining the

inferior reproducibility. These significant differences in reproducibility between techniques

are important for patient follow-‐up and for research study sample sizes [24].

Detailed manual endocardial contouring was significantly more reproducible than simplified

manual contouring for measuring EDV and ESV, possibly because the ‘compacted’

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endocardial border was more difficult to identify, however there was no difference in EF

reproducibility. Papavassiliu et al [19] found no significant differences in EDV, ESV or EF

reproducibility although only detailed versus simplified tracing of trabeculae was assessed

(papillary muscles were included within mass measurements in all subjects). Compared with

other parameters, measurement of mass showed greatest variability for all techniques, in

keeping with other studies [24].

Geometric models are frequently used in echocardiography and have been advocated as a

time-‐saving alternate to conventional CMR image analysis [16]. Mean difference and levels

of agreement between each model and ‘conventional’ analysis in this study are similar to

the findings of Thiele et al [12] although somewhat surprisingly, the biplane rather than the

triplane model showed highest EF agreement here. Nevertheless, limits of agreement were

wide for all models suggesting modelling and ‘conventional’ analysis were not

interchangeable. Furthermore, reproducibility of EF for all models was too low for clinical or

research utility, with repeatability co-‐efficients of 13% or greater. It is suggested that

geometric models devalue CMR and their use should be discouraged.

Study limitations

The main limitation of this study is that no comparison is made to an externally validated

gold standard, so accuracy of analysis techniques cannot be assessed. Nevertheless, the

study aimed to compare mass, volume and EF values obtained by each technique and their

reproducibility, which has been possible. In addition, interobserver and intraobserver

reproducibility have been assessed, but not inter-‐study reproducibility. It is likely that inter-‐

study reproducibility would be lower than the reproducibility demonstrated here but we

hypothesis that the semi-‐automated technique would remain the most reproducible.

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Conclusions

Despite advances in all cardiac imaging modalities, the accuracy and reproducibility of CMR

for assessing LV mass, volume indices and EF remains unrivalled. However this status will

only be upheld if image analysis is performed to a high standard and in a consistent manner.

Methods for measuring these parameters are not interchangeable and normal reference

ranges appropriate to analysis technique must be used. A technique that includes semi-‐

automated endocardial contouring, LV base identification and end-‐systolic frame selection

was found to be the most reproducible and these features should be part of all analysis

software. Use of geometric models for analysing CMR images should be discouraged.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

MS and CAM conceived the study. CAM, MS, KP and DC helped plan and design the study.

CAM, PJ, AB, RA, DC, and KP collected the data. CAM analysed the data. CAM wrote the

preliminary draft of the manuscript and all authors supplied comments and corrections. All

authors read and approved the final manuscript. CAM and MS are the guarantors.

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Acknowledgements

Dr Miller was supported by a Doctoral Research Fellowship from the National Institute for

Health Research, UK. Dr Schmitt was supported by Greater Manchester Comprehensive

Local Research Network funding.

21

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Figure legends

Figure 1. Basal short-‐axis slice selection. A and B. The basal LV slice, and how much of it to

include, can be difficult to determine from short axis images alone. At the base of the heart,

slices were considered to be within the LV at end-‐diastole (A) and end-‐systole (B) if the

cavity was surrounded by 50% or more of ventricular myocardium. If the basal slice

contained both ventricular and atrial myocardium, contours were drawn up to the junction

and joined by a curved line through the blood pool. C and D. With the semi-‐automated

analysis, mitral (and aortic) valve positions were identified at end-‐diastole (C) and systole (D)

in all 3 long-‐axis images allowing valve planes to be tracked through the cardiac cycle (only

horizontal long-‐axis image shown for illustration). This was integrated into a LV mesh

created from the short-‐axis image analysis allowing automated three-‐dimensional

identification of the LV base (and outflow tract) at end-‐diastole (E) and end-‐systole (F).

Figure 2. Endocardial contouring. A. Simplified manual contouring; the ‘compacted’

endocardial border is traced resulting in papillary muscles and trabeculae being included in

volumetric and excluded from mass measurements. B. Detailed manual contouring; detailed

tracing of the endocardium is performed manually such that papillary muscles and

trabeculae are included in mass and excluded from volumetric measurements. C. Semi-‐

automated contouring; a signal intensity ‘thresholding’ tool allows detailed, semi-‐automated

tracing of the endocardial border based on the signal intensity of myocardium. Papillary

muscles and trabeculae are included in mass and excluded from volumetric measurements.

Figure 3. End-‐systolic frame selection. Manual end-‐systolic frame selection is performed

manually by visually identifying the frame with the smallest cavity. However often this is not

uniform across short-‐axis slices, as in this example where basally the cavity appears smallest

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in frame 14 but apically it appears smallest in frame 10. The semi-‐automated analysis

technique automatically determines end-‐systole as the frame with the smallest cavity

volume, by calculating cavity volume at each frame, which in this example is frame 11.

Figure 4. Geometric models and formulae for the determination of LV volume (LVV). All

measurements are made at end-‐diastole and end-‐systole to give EDV and ESV. AM = short

axis area at the level of the base, AP = short axis area at the level of the papillary muscles, AH

= long axis area in the horizontal plane, AV= long axis area in the vertical plane, L = length of

the LV, D = short axis diameter of LV measured in the long axis plane

Figure 5. Biplane model. Example of one of the geometric models. For the biplane model

the endocardial border is traced in the horizontal long axis (top left image) and vertical long

axis images at end-‐diastole (pictured) and end-‐systole. These areas are used to calculate

end-‐diastolic and end-‐systolic volumes using the formula given in Figure 4.

Figure 6. Bland Altman comparisons of each analysis technique for measurement of

volume indices, EF and mass. Abbreviations as in Table 2.

Figure 7. Interobserver and intraobserver variability of each analysis technique for

measurement of volume indices, EF and mass. Interobserver and intraobserver variability

(calculated using the repeatability co-‐efficient) is highest for measurement of mass.

Intraobserver variability is less marked than interobserver variability, as would be expected.

Abbreviations as in Table 2.

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Figure 8. Interobserver and intraobserver variability of each geometric model for

measurement of volume indices and EF. Interobserver and intraobserver variability,

calculated using the repeatability co-‐efficient. Abbreviations as in Table 4.

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Table 1. Patient characteristics, scan indications and main findings.

Number (%)

n = 50

Age 61+13 (range 19-‐84)

Male 34 (76%)

Arrhythmia

Frequent univentricular ectopics

Atrial fibrillation

Atrial flutter

5 (10%)

2

2

1

Scan indication

Myocardial perfusion assessment

Viability assessment*

Valvular assessment

Aortic assessment

36 (72%)

10 (20%)

2 (4%)

2 (4%)

Main scan diagnosis

Ischaemic heart disease

Cardiomyopathy

Normal

Valvular heart disease

Pericardial disease

Ascending aortic aneurysm

Intra-‐cardiac mass

20 (40%)

11 (22%)

10 (20%)

4 (8%)

2 (4%)

2 (4%)

1 (2%)

* includes assessment for cardiomyopathy, pericardial disease, intra-‐cardiac masses and

myocardial viability.

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Table 2. Mean + SD (range) volumetric, EF and mass measurements using each analysis technique.

Auto ManDet ManSimp

EDV (mls) 170+54 (61-‐328) 169+52 (69-‐315) 177+53 (77-‐324)

ESV (mls) 76+47 (23-‐240) 78+50 (19-‐245) 92+52 (24-‐258)

SV (mls) 94+28 (13-‐150) 92+30 (19-‐154) 85+26 (21-‐142)

EF (%) 57+16 (21-‐81) 57+17 (20-‐78) 50+15 (19-‐72)

Mass (g) 140+39 (74-‐233) 105+33 (52-‐176) 96+29 (47-‐158)

Auto – semi-‐automated analysis, ManDet – detailed manual analysis, ManSimp – simplified

manual analysis. EDV – end-‐diastolic volume, ESV – end-‐systolic volume, SV – stroke volume,

EF – ejection fraction.

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Table 3. Comparison of volumetric, EF and mass measurements using each analysis technique.

Mean difference (SD), significance of the difference, Bland-‐Altman 95% limits of agreement and correlation coefficient

for the comparison of semi-‐automated, detailed manual and simplified manual analyses. Abbreviations as in Table 2.

Mean difference

+SD

p-‐value 95% limits of

agreement

Correlation

coefficient (rs)

EDV (mls)

Auto – ManDet -‐1+13 0.84 -‐26 to 24 0.94

Auto – ManSimp -‐9+13 <0.0005 -‐35 to 17 0.93

ManDet – ManSimp -‐8+5 <0.0005 1 to 17 0.99

ESV (mls)

Auto – ManDet -‐2+9 0.17 -‐20 to 15 0.96

Auto – ManSimp -‐17+13 <0.0005 -‐42 to 8 0.94

ManDet – ManSimp -‐15+7 <0.0005 -‐1 to 29 0.98

SV (mls)

Auto – ManDet 2+11 0.26 -‐21 to 24 0.88

Auto – ManSimp 8+10 <0.0005 -‐11 to 28 0.89

ManDet – ManSimp 7+6 <0.0005 -‐6 to 19 0.98

EF (%)

Auto – ManDet 1+4 0.12 -‐8 to 10 0.96

Auto – ManSimp 7+5 <0.0005 -‐3 to 17 0.91


Mass (g)

Auto – ManDet 34+19 <0.0005 -‐3 to 72 0.87

Auto – ManSimp 43+20 <0.0005 4 to 83 0.87


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Table 4. Mean + SD volumetric measurements using each geometric model.

Teich ModSimp Hemi Mono Biplane Triplane

EDV (mls) 134+44 165+53 196+63 162+53 173+56 219+68

ESV (mls) 63+44 87+43 103+64 70+47 76+49 105+66

EF (%) 56+20 48+16 50+19 59+17 58+18 55+18

Teich – Teicholz, ModSimp – modified Simpson’s, Hemi – hemi-‐ellipse, Mono – monoplane.

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Table 5. Comparison of volumetric and EF measurements using each geometric model with semi-‐automated analysis.

Mean difference

+SD

p-‐value 95% limits of

agreement

Correlation

coefficient (rs)

EDV (mls)

Auto – Teich 36+42 <0.0005 -‐47 to 119 0.64

Auto – ModSimp 4+22 0.06 -‐39 to 47 0.91

Auto – Hemi -‐27+18 <0.0005 -‐62 to 8 0.95

Auto – Mono 7+22 0.03 -‐36 to 51 0.92

Auto – Biplane -‐4+22 0.39 -‐47 to 39 0.93

Auto – Triplane -‐49+22 <0.0005 -‐7 to 91 0.96

ESV (mls)

Auto – Teich 13+24 <0.0005 -‐35 to 60 0.83

Auto – ModSimp -‐11+14 <0.0005 -‐38 to 17 0.95

Auto – Hemi -‐27+21 <0.0005 -‐69 to 15 0.96

Auto – Mono 6+18 0.01 -‐30 to 41 0.93

Auto – Biplane 0+13 0.64 -‐27 to 26 0.94

Auto – Triplane -‐29+23 <0.0005 -‐74 to 15 0.96

EF (%)

Auto – Teich 2+11 0.36 -‐19 to 23 0.82

Auto – ModSimp 9+9 <0.0005 -‐8 to 26 0.85

Auto – Hemi 7+7 <0.0005 -‐6 to 21 0.89

Auto – Mono -‐1+6 0.06 -‐14 to 11 0.90

Auto – Biplane 0+6 0.87 -‐12 to 11 0.91

Auto – Triplane 3+6 <0.0005 -‐8 to 13 0.92

Mean difference (SD), significance of the difference, Bland-‐Altman 95% limits of agreement and correlation

coefficient for the comparison of each geometric model with semi-‐automated analysis. Abbreviations as in Table 4.

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Analysis of left ventricular mass, volume indices and