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A new automated method for analysis of gated-SPECTimages based on a 3-dimensional heart shaped model

Milan Lomsky1, Jens Richter2, Lena Johansson1, Henrik El-Ali3, Karl Åström4, Michael

Ljungberg3, Lars Edenbrandt1, 2

1Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden2Department of Clinical Physiology, Malmö University Hospital, Malmö, Sweden3Department of Radiation Physics, Lund University, Lund, Sweden4Department of Mathematics, Lund Institute of Technology, Lund, Sweden

Corresponding author:

Lars Edenbrandt

Department of Clinical Physiology

Malmö University Hospital

SE-205 02 Malmö

Sweden

E-mail: lars.edenbrandt@klinfys.mas.lu.se

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Abstract

A new automated method for quantification of left ventricular function from gated-SPECT

images has been developed. The method denoted CAFU is based on a heart shaped model and

the active shape algorithm. The model contains statistical information of the variability of left

ventricular shape. CAFU was adjusted based on the results from the analysis of five simulated

gated-SPECT studies with well defined volumes of the left ventricle. The digital phantom NCAT

and the Monte-Carlo method SIMIND were used to simulate the studies. Finally CAFU was

validated on ten rest studies from patients referred for routine stress/rest myocardial perfusion

scintigraphy and compared to QGS, a commercially available program for quantification of

gated-SPECT images. The maximal differences between the CAFU estimations and the true left

ventricular volumes of the digital phantom were 11 ml for the end-diastolic volume (EDV), 3 ml

for the end-systolic volume (ESV) and 3% for the ejection fraction (EF). The largest differences

were seen in the smallest heart. In the patient group the EDV calculated using QGS and CAFU

showed good agreement for large hearts and higher CAFU values compared to QGS for the

smaller hearts. In the larger hearts, ESV was much larger for QGS than for CAFU both in the

phantom and patient studies. In the smallest hearts there was good agreement between QGS and

CAFU. The findings of this study indicate that our new automated method for quantification of

gated-SPECT images can accurately measure left ventricular volumes and EF.

Key words: Computer-Assisted Image processing; Radionuclide imaging; Cardiac function

tests

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Introduction

Left ventricular (LV) ejection fraction (EF) and volumes are valuable indices in clinical

decision making and powerful independent prognostic variables (Travin et al., Go et al.) ECG-

gating of myocardial perfusion single photon emission computed tomography (SPECT) images

allows a simultaneous evaluation of LV function (EF, volumes, wall thickening and wall motion)

and perfusion. There are presently several commercially available software packages for the

quantification of gated-SPECT (Germano et al., Faber et al.). They have all – to variable degree –

been validated using other nuclear medicine techniques (Everaert et al.) and other imaging

modalities (Nichols et al. 2000, Vallejo et al.). There have been mostly a good correlation

between the gated-SPECT methods and the reference methods, but some methods showed a

consistent underestimation of EF (ref) and the variability between the results from different

software packages could be substantial (Nakajima et al., Nichols et al. 2002). A recent meta

analysis of data from studies comparing LV end-diastolic volume (EDV), end-systolic volume

(ESV) and EF measured with gated-SPECT to the corresponding measurements from cardiac

magnetic resonance imaging showed high correlations between the methods but considerable

discrepancies for individual subjects (Ioannidis et al.). For example, as many as 11% of patients

would be misclassified with gated-SPECT when identifying subjects with EF of 40% or less.

Therefore, new approaches to quantify gated-SPECT images could be of value.

The aim of this study was to develop a new automated method for quantification of LV

function based on gated-SPECT images. We decided to use a detection algorithm, which is

based on a heart shaped model and adjusted using a digital heart phantom.

Material and Methods

CAFU

The new method for quantification of CArdiac FUnction – denoted CAFU – is based on the

active shape algorithm. The search and delineation of the left ventricle in the gated-SPECT

images is based on a heart model, which was developed using 50 selected patient studies. The

model contains statistical information of the variability of LV shape in this group of patients.

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Step 1 – LV search in frame 1

The short axis slices are used as input to CAFU. The total count values of each of the slice

images are calculated. Seven adjacent slice images with high total count values are assumed to be

in the middle of the left ventricle. Each of these images is binarised by setting 15% of the pixels

with highest count values to 1 and the rest to 0. The seven images are thereafter summed and the

sum image is binarised by setting pixels greater than 50% to 1 and the rest to 0. This new image

is searched for LV lumen candidates, i.e. regions with “0-pixels” surrounded by “1-pixels”.

The cluster of candidates with positions closest to the upper right corner is defined as the LV

lumen position.

Thereafter, a search for the first estimate of the LV base is performed. In each slice image

starting from the most basal slice, a search from the LV lumen position in 16 directions was

performed. Maximum count values greater than 40% of maximum was considered to be LV wall

candidates. At least seven such candidates were required to define the first estimate of the LV

base. Thereafter, the first estimate of the LV apex was calculated in a similar way.

Step 2 – Delineation of mid-myocardial surface

In an iterative process, the heart shaped LV model is adjusted to optimize the fit with the

image data of frame 1. The model is positioned and scaled in order to fit with the first estimate of

LV base and apex from step 1. The model contains 272 landmarks distributed in 17 layers from

apex to base with 16 landmarks in each layer. In each landmark, a count profile normal to the

surface of the model is extracted. The position of the maximal count value in each profile is

noted provided that this value is at least 30% of the maximal myocardial count. The LV model is

then adjusted to minimize the distances between the landmarks and the corresponding positions

of the maximal count values. After this adjustment of the model a new iteration with search for

maximal count values and model adjustment is performed. This procedure is continued until the

changes of the LV model are very small or the maximum number of iterations (fifteen) has been

performed.

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Step 3 – Epi- and endocardial delineation

In the 10% landmarks with the highest count values, count profiles normal to the surface of

the model are extracted. An average profile is calculated and the positions corresponding to 75 %

of the maximum count values in this profile are defined as the epi- and endocardial positions.

The distance between these positions is used as an estimation of the average thickness of the

myocardium in the region corresponding to the 10% landmarks used in this calculation. The

corresponding average count values for these landmarks is also calculated. The thickness in each

landmark point of the myocardium is then calculated as the product between this average

thickness and the ratio between the count value for the specific landmark and the calculated

average count value. Thickness values less than 8 mm are set to this value. Finally the epi- and

endocardial surfaces are used to calculate the myocardial volume.

Step 4 – Analysis of the following frames

The final position of the LV model in frame 1 is the first estimation of the position of the

model in the rest of the frames. The same iterative procedure is applied in the other frames in

order to find the midmyocardial surface. Thereafter the area of this midmyocardial surface is

calculated. The average thickness of the myocardium in the frame is determined based on the

assumption of constant myocardial volume of the left ventricle throughout the cardiac cycle. The

area of the midmyocardial surface from the specific frame and the volume estimation from frame

1 is used in this calculation. The thickness in each landmark point is adjusted with a factor

correlated to the relation between average count value of the myocardium in the frame and the

count value for the landmark.

Step 5 – Calculation of volumes

The LV volume is calculated using the endocardial surface and the LV valve plane. This

calculation is performed in all frames and the largest volume is defined as the EDV and the

smallest is defined as the ESV. The LV EF is calculated as the (EDV-ESV)/EDV. Frames with a

total count value for the myocardium less than 80% of that of frame 1 (tail drop) are not

considered in these calculations.

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Step 6 – Wall motion and thickening

The wall motion measure for each landmark is calculated as the distance normal to the

surface of the myocardium between the position of each landmark in the ESV and EDV frames.

The thickening measure for each landmark is calculated as the ratio between the count value in

the ESV frame and the count value in the EDV frame.

Digital Phantom

The dynamic anthropomorphic computer phantom NCAT v1.12 (Segars et al.) was used.

This phantom includes possibilities of several alterations of the shape of the phantom and the

cardiac structure. For this simulation study, five different heart sizes were used in a male

geometry. We have used a standard 9 9Tcm -Sestamibi gated-SPECT study as a model for our

simulations where the heart cycle is divided into eight timeframes. The phantom also allows for

respiratory movements but this was not used in this work. The NCAT phantom gives an activity

map and a corresponding attenuation map for each time frame.

We used the Monte-Carlo program SIMIND (Ljungberg et al.) to simulate gated-SPECT

studies based on these activity and attenuation maps. The Monte-Carlo program was setup to

simulate a SPECT scintillation camera system with a low energy high resolution collimator with

energy resolution of 9.8% full width half maximum at 140 keV and an intrinsic resolution of 4

mm. The simulations mimic a common clinical procedure including acquisition of 48 projections

over 180 degree rotation mode starting at angle 315. The radius of rotation was kept to 26 cm

and the energy window was 20%.

Five perfusion studies with different heart sizes were obtained with the NCAT phantom and

SIMIND program. The EDV ranged between 57 and 186 ml and the ESV between 22 and 72

ml. The studies all had a motion pattern corresponding to a LV EF of 61%. The NCAT software

also provides the true chamber volume for each segment. These values were compared to the

values reported by the two analysis programs.

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QGS

The Cedar-Sinai quantitative gated-SPECT (QGS) program (Germano et al.), which is the

most widely used program for quantification of LV function in gated-SPECT images, was used

for comparison to CAFU. Shortly, the QGS program operates in the three-dimensional space

and uses gated short axis slices as input. The automatic algorithm identifies the epi- and

endocardial contours for each of the sets of short axis slices in the cardiac cycle to calculate

volume changes. The largest and the smallest LV volumes correspond to the EDV and ESV,

respectively.

Patients

A total of 50 rest studies from patients referred for routine stress/rest myocardial perfusion

scintigraphy at Sahlgrenska University Hospital in Gothenburg, Sweden were used in the

construction of the heart model. The patients were selected to represent a variety of different

heart shapes. Ten other rest studies were used in the evaluation phase of CAFU. The patients

were selected to give a distribution of hearts sizes (EDV from approximately 50 ml to 200 ml).

Patients with large perfusion defects were not included. An experienced physician did the

selection of the studies.

Image acquisition

The rest and stress studies were performed using a two-day 99m Tc-sestamibi protocol.

Rest acquisition began at least 60 minutes after the injection of 600 MBq 99m Tc-sestamibi.

Images were acquired with a rotating dual-head SPECT camera equipped with low energy, high

resolution collimators. Acquisition was done with two different cameras, both using circular

acquisition and 64x64 matrix; in seven patients with camera A using 64 projections over 180

degrees for 40 s per projection and in three patients with camera B using 68 projections over 204

degrees for 40 s per projection. The patients were positioned supine on the SPECT table and

monitored with a three-lead ECG. The acceptance window was opened to 20% of the predefined

R-R interval. Other beats were rejected. Each R-R interval was divided into eight equal time

intervals. Gated-SPECT acquisition was performed at the same time as routine SPECT

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acquisition. Projection images were reconstructed into transaxial images using filtered

backprojection. No attenuation or scatter correction was used.

Results

CAFU was first applied to the five phantom studies and after adjustment of parameters in

the algorithms the measurements calculated by CAFU were close to the true values. The true

volume of the myocardium for the five phantoms ranged between 89 and 301 ml and the

volumes calculated using CAFU were 1-8% lower. The LV EF and ESV for all five phantom

studies and the EDV for the two largest phantom studies were almost correctly calculated (Table

1). The EDV for the three smallest phantom studies were underestimated by CAFU by

approximately 10 ml. The epi- and endocardial boundaries calculated by CAFU for the smallest

and largest of the phantom studies are presented in Figure 1.

QGS calculated EDV (r = 0.99) and ESV (r = 0.99) values that correlated well with the true

volumes for the phantom studies (Figure 2). The absolute differences between the true volumes

and the volumes calculated using QGS were, however, substantial for the larger hearts, especially

for the ESV (Table 1). This relation resulted in a QGS measured EF as low as 39% compared to

the true EF of 61% for the largest phantom study. The overestimation of EDV by QGS for the

large phantom was caused by a false delineation of the basal part of the LV (Figure 1).

In the patient group the EDV calculated using QGS and CAFU showed good agreement for

large hearts and higher CAFU values compared to QGS for the smaller hearts (Figure 3). The

relation that QGS calculated much larger ESV than CAFU for large hearts, which was found in

the phantom studies, was also found in the patient studies (Figure 4). For the smallest hearts

there was good agreement between QGS and CAFU. The epi- and endocardial boundaries

calculated by CAFU and QGS for a small and a large heart of the patient studies are shown in

Figure 4.

Discussion

We have developed a new automated method for quantification of LV function based on

gated-SPECT images. The innovative approach with our method compared to previously

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presented methods is the use of the active shape algorithm. With this technique a heart shaped

model is used instead of geometrical models such as an ellipsoid model or a hybrid cylindric-

spheric model in which the basal two thirds of the myocardium are modeled as cylindrical and

the apex is modeled as hemispheric. A heart shaped model is more likely to fit to myocardial

surfaces from patients with different shapes than a geometrical model.

During the initial development of a new method visual inspection of the epi- and endocardial

boundaries produced by the algorithm can be used. Serious mistakes by the algorithm are

possible to find from presentations such as those of Figure 4. This type of analysis is, however,

not accurate enough for a more precise adjustment of the algorithm. Independent examinations

such as gated blood-pool imaging, first pass studies, echocardiography or magnetic resonance

imaging are also difficult to use as reference methods for this purpose. The last of these methods

is probably the most accurate reference method, but this method has the disadvantage that the

examinations are not performed simultaneously. Differences in physiological states between the

two examinations may cause differences in LV volumes and EF. Therefore we used the digital

phantom NCAT and the Monte-Carlo method SIMIND to simulate gated-SPECT studies for the

development and adjustment of CAFU. This approach has the advantage that the true volumes

are known.

A limitation of the study is that CAFU was developed and validated on a limited number of

normal ventricles from different phantoms and patients. In the next step, the accuracy of the

method will need to be further evaluated in larger patient groups with independent methods to

assess, for example the LV EF. A large validation set that includes, for example, left ventricles

with large perfusion defects and cases with extra-cardiac activity will be of value in the evaluation

process. These type of cases have previously shown to cause problems for the quantitative

analysis.

The findings of this study indicate that our new automated method for quantification of

gated-SPECT images can accurately measure left ventricular volumes and EF. Further studies

are needed to evaluate the clinical value of CAFU.

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Acknowledgments

This study was supported by grants from the Swedish Medical Research Council.

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Table 1 CAFU and QGS results in the phantom study

Phantom EDV ESV EF

True CAFU QGS True CAFU QGS True CAFU QGS

1 57 46 45 22 21 21 61 58 54

2 80 71 70 31 28 37 61 61 47

3 109 101 104 43 43 57 61 58 45

4 144 142 145 56 59 83 61 59 43

5 186 185 201 72 71 122 61 62 39EDV – end-diastolic volume; ESV – end-systolic volume; EF – ejection fraction

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Figure Legends

Figure 1 Largest and smallest phantom quantified by CAFU and QGS.

Figure 2 Relation between true phantom volume and EDV (H) and ESV (Δ)measurements by

CAFU (filled) and QGS (open).

Figure 3 Relation between EDV ( ) and ESV (Δ)measurements by QGS and CAFU for 5

phantoms (open) and ten patients (filled).

Figure 4 Two patient studies quantified by CAFU and QGS.