a multi-center phantom study comparing image resolution from three state-of-the-art spect-ct systems

ORIGINAL ARTICLE

A multi-center phantom study comparing imageresolution from three state-of-the-art SPECT-CTsystems

Tyler Hughes, BSc,a,c Sergey Shcherbinin, PhD,a,b and Anna Celler, PhDa,b

Background. Ongoing advancements in SPECT-CT technology raise important questionsregarding the differences in performance between various cameras and their respective image-processing algorithms. Our study seeks the answer to this question via measurement ofphantom myocardial wall thickness (MWT) on images obtained from three state-of-the-artcameras.

Methods. A thorax phantom with an insert modeling a healthy heart was scanned usingcardiac acquisition protocols with Philips’ Precedence (PP), GE’s Infinia Hawkeye (IH), andSiemens’ Symbia-T6 (SS). Processing was performed using advanced reconstruction techniquesavailable on the cameras and our own independent software. The MWT measurement was usedas a figure of merit in performance evaluation.

Results. When using 50% threshold, MWTs measured for the data acquired using PP, IH,and SS and reconstructed with independent standardized software were 8.5 ± 1.2 mm,7.7 ± 1.2 mm, and 9.3 ± 0.9 mm, respectively; and 9.3 ± 0.5 mm, 19.2 ± 0.8 mm and18.4 ± 1.1 mm when using the manufacturers’ own reconstructions, respectively. Thresholdsoptimized for each image (ranging from 32% to 68%) produced much more uniform results.

Conclusions. No significant differences were observed between image resolutions whendata acquired from different cameras were reconstructed with an independent algorithm.However, different manufacturers’ reconstruction algorithms produced MWTs that differed byup to about 110% when using a set threshold of 50%. (J Nucl Cardiol 2009;16:914–26.)

Key Words: Myocardial perfusion imaging Æ SPECT Æ attenuation and scatter correction Æimage processing

INTRODUCTION

The recent advent of hybrid single photon emission

computed tomography combined with x-ray computed

tomography systems (SPECT-CT) has created an ideal

avenue for improving the quality of clinical SPECT

images through accurate attenuation correction (AC)

based on CT attenuation maps.1,2 In parallel, several

resolution recovery (RR) methods3-7 have been devel-

oped, which enable algorithms to correct for collimator

blurring, thus improving the resolution of patient ima-

ges. Currently, most clinical iterative reconstruction

methods offer RR in addition to some form of scatter

correction (SC). However, two of the SC techniques that

are implemented in clinical systems are based on rather

simple approaches, such as the dual energy window

(DEW) technique which is utilized by Siemens and GE,8

while the effective scatter source estimation (ESSE)9 has

been employed by Philips. More sophisticated approa-

ches, which include Monte Carlo based methods10 and

analytical photon distribution (APD) techniques,11,12

offer improved quantitative accuracy but continue to

require extensive calculation times, making them cur-

rently impractical for clinical use.

The combined application of attenuation, scatter

and collimator blurring corrections should not only

improve image quality but could also lead to the long-

awaited quantitation of activity distributions within a

patient. However, the lack of detailed information

regarding these technological advancements and their

operation creates a complex ‘‘black box’’ environment

From the Department of Physics and Astronomy,a Department of

Radiology,b University of British Columbia, Vancouver, BC,

Canada; and Vancouver General Hospital,c Vancouver, BC, Canada.

Received for publication Feb 2, 2009; final revision accepted Jul 16,

2009.

Reprint requests: Tyler Hughes, BSc, Vancouver General Hospital,

Research Pavilion, Room 366, 828 West 10th Avenue, Vancouver,

BC V5Z 1L8, Canada; [email protected].

1071-3581/$34.00

Copyright � 2009 by the American Society of Nuclear Cardiology.

doi:10.1007/s12350-009-9132-7

914

for the user, who is ultimately forced to trust the results

without being able to check their accuracy and precision.

Due to the rapid development of SPECT-CT technolo-

gies and increased sophistication of image-processing

software, there has been minimal time to address a very

important question regarding the relative performance of

these innovative systems in standard clinical applica-

tions, such as SPECT-CT myocardial perfusion imaging

(MPI). This issue may be particularly important when

comparing the results of multiple studies of the same

patient performed using different cameras, especially

those produced by different manufacturers who make

use of dissimilar reconstruction algorithms.

In 2002, O’Connor et al13 performed a multi-center

study using a standardized phantom to investigate the

performance of eight AC techniques and ultimately

discovered considerable variability in performance

between them. With little work being done since that

study regarding inter-vendor camera performances, the

problem of objective evaluation of the equipment

remains unsolved as these technologies continue to

evolve.

Our study aims to address this issue through a

comprehensive analysis pertaining to the relative per-

formance of three leading state-of-the-art SPECT-CT

systems: Philips’ Precedence (PP), General Electric’s

Infinia Hawkeye (IH), and Siemens’ Symbia-T6 (SS).

These systems were located in three different centers,

namely the Royal Inland Hospital (Kamloops, Canada),

Vancouver General Hospital (Vancouver, Canada), and

St. Paul’s Hospital (Vancouver, Canada), for PP, IH, and

SS, respectively. Moreover, the image-processing soft-

ware packages available on the aforementioned systems

were also tested, specifically AstonishTM (AST)3 from

Philips, EvolutionTM for Cardiac (EfC)4,6 from GE, and

Flash-3DTM (FL3)5 from Siemens. Additionally, all

acquired datasets were reconstructed using the software

developed in-house by our Medical Imaging Research

Group (MIRG).14 Our investigation specifically focuses

on the tomographic resolution of the reconstructed

images by measuring the myocardial wall thickness

(MWT) of a phantom heart placed in the Data Spectrum

Thorax phantom, which was scanned and reconstructed

using the aforesaid hardware and software, respectively.

Recently, a similar comparative study was repor-

ted15 for line sources in air, water, and background with

activity. When using AST, Evolution, and FL3, with AC

and RR, the resolution of all systems was found to be

about 30% improved over their respective standard

reconstruction methods [maximum likelihood expecta-

tion maximization (MLEM) and ordered subsets

expectation maximization (OSEM) without corrections],

but no conclusions were made regarding the relative

performance of these systems.

MATERIALS AND METHODS

Experiments with Capillary Tubes in Air

Camera tomographic resolution is often analyzed using

acquisitions with small line sources (capillary tubes) placed in

air, thus we included such capillary tube experiments in our

study. Source configuration and acquisition parameters in these

experiments followed the NEMA recommendations16 for

tomographic resolution tests. Four capillary tubes (7.5 cm

long and 1 mm diameter) were filled with Tc-99m activity

(15-18 MBq per tube). The activity extended over 3-4 cm

within each tube, effectively creating line sources. They were

positioned on a Styrofoam support placed on the camera

scanning bed. Three tubes were parallel to the axis of rotation

of the camera, where one was on the axis of rotation and two

were at distance of 10 cm off axis. The fourth tube was ori-

ented perpendicular to the axis of rotation.

For each investigated system, namely PP, IH and SS, a

standard tomographic acquisition was performed with a clini-

cally relevant radius of rotation set at 23 cm (circular) and an

acquisition time equal to 5 seconds per projection. The matrix

was 128 9 128, with 120 or 128 views acquired over a 360�camera rotation. The cameras were equipped with their

respective high-resolution collimators, VXGP for PP, and

LEHR for both IH and SS. The acquired datasets were

reconstructed using the software available on each of the

systems, namely, AST, EfC, and FL3 for PP, IH, and SS,

respectively.

Thorax Phantom Data Acquisition Protocols

The conditions of capillary tube experiments do not

realistically represent those of patient studies; therefore, in

order to better model patient scans with photon attenuation and

scatter in a non-uniform medium, while still maintaining

control over the true activity distribution, we performed a

series of experiments using the Thorax phantom (Data Spec-

trum Corp.). The phantom, with a total volume of 7000 mL,

contained two lung inserts filled with Styrofoam beads (with-

out activity) and a spine insert made of bone-equivalent

attenuating material. The phantom also contained a 120 mL

heart insert modeling a healthy myocardium (i.e. no perfusion

defect were modeled) and three 33 mL cylindrical bottles were

used to create non-uniform activity in the body (such as gall

bladder or tumors). This configuration modeled a non-uniform

activity distribution with additional sources of scattered pho-

tons, thus creating a reconstruction problem resembling a

clinical situation. A hot liver was not modeled as photons

scattering from the liver would produce a well-known artifact,

which could potentially alter the results of our investigations.

The physical setup of the phantom and its components is

illustrated in Figure 1.

The heart insert, three bottles and the body of the phantom

were filled with water containing Tc-99m activity. For all

experiments, we used a 6 to 1 (heart and bottles to background)

ratio of activity concentration, which is similar to the ratios

typically encountered in clinical Sestamibi MPI studies. The

Journal of Nuclear Cardiology Hughes et al 915

Volume 16, Number 6;914–26 A multi-center phantom study comparing image resolution

total activities and activity concentrations at the time of each

acquisition in each of the compartments in the phantom, as

well as their respective volumes, can be found in Table 1.

The phantom was scanned in three separate studies using

the three aforesaid systems. Two different cardiac acquisition

protocols were followed for each camera (Table 2). In all

cases, the detectors were positioned at 90� relative to each

other and completed a rotation of 180� around the phantom.

The first set of acquisitions (Protocol A) followed the protocols

recommended by the manufacturers for SPECT MPI. The

second set of acquisitions (Protocol B) was aimed toward

achieving the best resolution, thus the data were collected

using a 128 9 128 matrix. In all cases, the nuclear medicine

acquisitions were followed by CT scans which used the man-

ufacturers’ recommended protocols. The resulting CT images

were converted into attenuation maps, again using the

respective software on each camera, for the purposes of

attenuation (and scatter) corrections.

Phantom Data Processing

All datasets acquired on each of the three SPECT-CT

cameras were reconstructed using the proprietary software

available on the systems. The parameters used in these

reconstructions (number of iterations, subsets, and filters) fol-

lowed or were close to those recommended by the

manufacturers of each system and acquisition type. A sum-

mary of the parameters used in our reconstructions is presented

in Table 3.

The PP reconstructions were performed on Philips’

JetStreamTM workstation using the AST reconstruction

software which employs an iterative 3D OSEM algorithm

with built-in corrections for AC, RR and the ESSE based

SC, in addition to Philips’ matched filtering technique.17 In

all AST reconstructions, 6 iterations with 8 subsets were

used as compared to 4 and 8 currently recommended by

Philips, respectively.

The reconstructions of the datasets acquired on the IH

system were performed on GE’s XelerisTM workstation. For

both protocols, the datasets were reconstructed using GE’s

OSEM-based EfC software, with RR and AC. The number of

iterations and subsets followed GE recommendations.

The reconstructions for the SS camera used Siemens’

SyngoTM workstation with the FL3 software, which is also an

OSEM-based algorithm with AC, RR and DEW-based SC. The

FL3 reconstructions used 10 iterations and 8 subsets as com-

pared to the 12 iterations and 8 subsets recommended by

Siemens.

Finally, in order to compare the quality of the data

acquired on these different systems, all datasets were processed

Bottle 1

Bottle 2 Bottle 3

A

C

B

Heart

Figure 1. A schematic representation of the structures used inthe phantom experiments. The heart and the three bottles (darkgrey structures), which contained activity, are labeled explic-itly on the image. Objects A and B, which did not containactivity, are the right and left lungs, respectively. Object Crepresents the cold spine, positioned in the posterior aspect(into the page) of the phantom.

Table 1. Total Tc-99m activities (Act.) in MBq and concentrations (Con.) in MBq/mL used in thephantom experiments

Protocol Camera

Heart(120 mL)

Background(7000 mL)

Bottle 1(33 mL)

Bottle 2(33 mL)

Bottle 3(33 mL)

Act.(MBq)

Con.(MBq/mL)

Act.(MBq)

Con.(MBq/mL)

Act.(MBq)

Con.(MBq/mL)

Act.(MBq)

Con.(MBq/mL)

Act.(MBq)

Con.(MBq/mL)

A PP 13.3 0.11 118.1 0.02 6.2 0.19 6.1 0.18 5.8 0.18

IH 21.3 0.18 175.2 0.03 4.5 0.14 4.5 0.14 4.6 0.14

SS 17.3 0.14 175.1 0.03 7.7 0.23 7.9 0.24 7.6 0.23B PP 15.6 0.13 128.5 0.02 7.0 0.21 6.9 0.21 6.7 0.20

IH 22.5 0.19 184.1 0.03 4.7 0.14 4.8 0.15 4.8 0.15

SS 17.3 0.14 175.1 0.03 7.7 0.23 7.9 0.24 7.6 0.23

The values are adjusted to match those at the time of each acquisition.

916 Hughes et al Journal of Nuclear Cardiology

A multi-center phantom study comparing image resolution November/December 2009

again, this time with our MIRG quantitative reconstruction

software (referred to as MIRG herein). This OSEM-based

software combines our 3D depth-dependent RR7 with patient-

specific correction for attenuation and scatter. Our SC uses an

analytical APD method (based on the Klein-Nishina formula),

which calculates the distributions of scattered photons and

incorporates them into the forward projection step of OSEM.12

As the MIRG software is very flexible, allowing us to use any

combination of these corrections for a given reconstruction, we

tested the resulting MWT measurements for a series of different

reconstructions: OSEM ? AC, OSEM ? RR, OSEM ?

AC ? RR, OSEM ? AC ? RR ? SC. Each dataset was

reconstructed with our MIRG software using 10 iterations and 8

subsets without any post-reconstruction filtering.

Pixel Size Correction

Due to the intrinsic differences in hardware and the lim-

itations in acquisition zoom options available on the

investigated cameras, it was not possible to match the pixel

sizes between the three acquisitions (pixel sizes for PP, IH, and

SS were 3.2 mm, 4.4 mm, and 4.8 mm, respectively). So, in

order to eliminate potential bias in our resolution measure-

ments resulting from the differences in pixel sizes, an

interpolation-based correction was performed. Specifically, the

following procedures were used:

• The pixel sizes for all reconstructed datasets corresponding

to the experiment with capillary tubes were rescaled to

2.0 mm, conforming to the NEMA regulations, which states

that the pixel size should be less than or equal to 2.5 mm.16

In order to rescale the pixel sizes, a bicubic interpolation

algorithm (MATLAB R2008b, The MathWorks, Inc) was

employed to resize the matrices based on a factor

determined by the ratio of the original pixel size to the

desired pixel size (i.e. 2.0 mm). The tomographic resolution

for each reconstruction was measured by first calculating

the full width at half maximum (FWHM) of a Gaussian

curve fitted to a profile drawn through the center of each

Table 2. Details of the acquisition protocols used in the Thorax phantom experiments

Protocol CameraMatrixsize

No. ofProjections

Angularextent

(�)Collimator

type

Projectiontime

(seconds)Zoomfactor

Pixelsize(mm)

A PP 64 9 64 64 180 VXGP 25 1.46 6.39

IH 64 9 64 60 180 LEHR 25 1.30 6.80

SS 128 9 128 64 180 LEHR 25 1.00 4.80

B PP 128 9 128 64 180 VXGP 25 1.46 3.20

IH 128 9 128 60 180 LEHR 30 1.00 4.42

SS 128 9 128 64 180 LEHR 25 1.00 4.80

Table 3. Details of the reconstructions used in the Thorax phantom experiments

Protocol Camera Reconstruction

Corrections

Filtering Iterations SubsetsAC RR SC

A PP AST 4 4 4 M 6 8

MIRG 4 4 4 10 8

IH EfC 4 4 B (0.52, 5) 12 10

MIRG 4 4 4 10 10

SS FL3 4 4 4 G (11 mm SD) 10 8

MIRG 4 4 4 10 8

B PP AST 4 4 4 M 6 8

MIRG 4 4 4 10 8

IH EfC 4 4 B (0.52, 5) 12 10

MIRG 4 4 4 10 10

SS FL3 4 4 4 G (11 mm SD) 10 8

MIRG 4 4 4 10 8

Gaussian, Matched, and Butterworth filters are represented as G, M, and B, respectively. SD refers to the standard deviation ofthe Gaussian filter and the Butterworth filter parameters are indicated in parentheses as (cut-off, order).



capillary tube in the experiment.18 The final resolution for

each reconstruction was then represented as the average of

all four capillary tube FWHM measurements, and the

corresponding errors were expressed as 95% confidence

intervals.

• In order to eliminate any bias resulting from the differences

in pixel sizes between the Protocol B acquisitions (see

Table 2) and to produce a fully standardized protocol, a

pixel size correction was performed on all Protocol B

reconstructions using the same algorithm described above.

However, in this case, the pixel sizes for the IH (4.42 mm)

and SS (4.80 mm) reconstructed datasets were matched to

the pixel size of the PP reconstructions (3.20 mm). Herein,

this new pixel size corrected (PSC) version of Protocol B

will be referred to as Protocol B-PSC.

MWT Measurements

The MWT measurements were made with our semiauto-

matic iQuant software.19 This software runs on the MATLAB

platform and employs a threshold based technique as means to

segment the left ventricle (LV) in a SPECT MPI dataset. The

threshold is defined as a percentage of a maximum count value,

which is determined as the average of the 30 highest counts

found within the LV for a given dataset. An additional feature

of the iQuant software includes the functional ability for

manual intervention by the user to add or remove extraneous

pixels to or from the segmented LV, respectively.

Two particular thresholds were analyzed in this study,

namely, a 50% threshold and an optimized threshold (Opt%).

The 50% threshold was selected as a standardized threshold to

enable a direct comparison between all reconstructed datasets.

The motivation behind using a 50% threshold was that it has

been employed by one of the most commonly used clinical

cardiac analysis software packages as a means to extract the

LV from SPECT MPI datasets.20

Our Opt%, on the other hand, is a data-dependent tech-

nique which is defined as the highest threshold that can be

applied to a particular dataset without the creation of unex-

pected (false) defects in the segmented healthy LV of the

phantom (or patient). The optimized threshold was determined

for each case separately via visual analysis of the segmented

images when increasing the values of the threshold by 1%

increments (starting from 0%). Thus, the first threshold that

creates unexpected (false) defects in the healthy LV is con-

sidered to be too high and the threshold 1% below this value is

considered to be optimal.

Subsequent to the LV segmentation, the MWT measure-

ment was made for each reconstruction. The LV was first

reoriented into the short axis (SA) display. From here, three SA

slices were selected (about 1 cm apart) in the mid-ventricular

region and on each of these slices, wall thickness measure-

ments were made at four pre-defined positions around each of

the slices: septal, lateral, anterior and inferior. The final MWT

value was defined as the average these 12 measurements

(4 positions 9 3 slices), to yield a global value for the given

image. Volume measurements were performed by summing

the number of voxels within the segmented LV volume and

then converting this volume to milliliters.

Statistical Analysis

In order to accurately represent the globally averaged

MWTs for each dataset, 95% confidence intervals were cal-

culated and are shown as the error bars in each of the

subsequent figures.

The mean values of the MWTs from reconstructions

which used different acquisitions were compared using inde-

pendent-sample t-tests, with a significant difference between

the two groups being presumed for values of P \ .05. Paired-

sample t-test was used to compare the MWTs obtained from

different reconstructions of the same acquisition, with no sig-

nificant difference between groups for values of P [ .05.

RESULTS

The results of the tomographic resolution mea-

surements made from the NEMA-type experiments

using capillary tubes are presented in Table 4.

For the phantom experiments, we first compared the

quality of data acquired from the three investigated

systems by reconstructing them with our independent

MIRG software using identical parameters for each case.

The resulting MWTs obtained using the 50% threshold

and Opt% for four different MIRG reconstructions with

different combinations of corrections (AC, RR, AC ?

RR, AC ? RR ? SC) for each of the acquired datasets

are presented in Figures 2 and 3, respectively. The

datasets used in this analysis were for Protocol B-PSC.

Subsequently, the same acquired datasets were

reconstructed using the manufacturers’ own algorithms.

The MWTs measured using 50% and Opt% for manu-

facturers’ and MIRG reconstructions (with AC ?

RR ? SC) for each of the three cameras are shown in

Figures 4, 5, and 6 for Protocols A, B, and B-PSC,

respectively. Table 5 provides numerical values of LV

myocardial volumes corresponding to each of the dis-

cussed cases.

Table 4. Results of the tomographic resolutionmeasurements made for the PP, IH, and SSsystems and respective reconstructionsacquired from the NEMA-type experiments

Camera—reconstruction

Tomographicresolution (mm)

PP—AST 8.1 ± 0.2

IH—EfC 8.0 ± 0.1

SS—FL3 8.3 ± 0.2

The uncertainties are represented as 95% confidenceintervals.



0.00

5.00

10.00

15.00

20.00

25.00

OSEM+AC (8ss, 10it) + OSEM+AC+RR (8ss, 10it)

OSEM+RR (8ss, 10it)Butterworth Filter

(0.5,5)

OSEM+AC+RR+SC(8ss,10it)

MW

T (

mm

)

PP Data IH Data SS Data

Figure 2. MWTs measured using 50% thresholds for various MIRG reconstructions used on PP,IH, and SS datasets. In each case the number of subsets (ss) and iterations (it) used in eachreconstruction are listed in parentheses. All reconstructions used data from Protocol B-PSC. Errorbars represent 95% confidence intervals.

46%

42%40% 32%69%

43% 50%43%

62%

45%53% 48%

0.00

5.00

10.00

15.00

20.00

25.00

OSEM+AC (8ss, 10it) +Butter worth Filter

(0.5,5)

OSEM+RR (8ss, 10it) OSEM+AC+RR (8ss,10it)

OSEM+AC+RR+SC(8ss,10it)

MW

T (

mm

)

PP Data IH Data SS Data

Figure 3. MWTs measured using Opt% (indicated above each dataset) for various MIRGreconstructions used on PP, IH, and SS datasets. In each case the number of subsets (ss) anditerations (it) used in each reconstruction are listed in parentheses. All reconstructions used datafrom Protocol B-PSC. Error bars represent 95% confidence intervals.



In parallel to the numerical analysis of MWTs, a

visual comparison of the images obtained using different

reconstruction algorithms was performed. For instance,

Figures 7, 8, and 9 display short axis slices in the mid-

ventricular region for each of the images obtained from

MIRG and the respective vendor reconstructions for

41%

Optimal Thresholds

51% 39% 67%50% Threshold 54% 64%0.00

5.00

10.00

15.00

20.00

25.00

MW

T (

mm

)

MIRG (PP Data) AST (PP Data) MIRG (IH Data) EfC (IH Data) MIRG (SS Data) FL3 (SS Data)

Figure 4. MWTs measured using 50% and Opt% thresholds (indicated below each case) for AST,EfC, FL3, and MIRG reconstructions using PP, IH, and SS datasets acquired using Protocol A.Error bars represent 95% confidence intervals.

32%

Optimal Thresholds

42% 38% 67%50% Threshold

54% 64%0.00

5.00

10.00

15.00

20.00

25.00

MW

T (

mm

)


Figure 5. MWTs measured using 50% and Opt% thresholds (indicated below each case) for AST,EfC, FL3, and MIRG reconstructions using PP, IH, and PP datasets acquired using Protocol B.Error bars represent 95% confidence intervals.



Protocols A, B, and B-PSC, respectively. In order to

facilitate the comparison, the images in these figures

were normalized and are displayed using the same color

scale.

A comparison of profiles drawn through the mid-

ventricular region of the phantom heart in the MIRG and

manufacturer images reconstructed using datasets

acquired from PP, IH, and SS is illustrated in Figure 10

(using Protocol B-PSC data). In order to assist in the

comparison of all investigated reconstructions, Fig-

ure 11 combines all of the profiles drawn through the

septal wall in the mid-ventricular region for each study

into one display (using Protocol B-PSC data). Each of

the profiles in Figures 10 and 11 was normalized to the

maximum value of each analyzed slice.

DISCUSSION

As expected, there were no significant differences

found between the resolutions of the three investigated

SPECT-CT systems for small sources (capillary tubes)

without the presence of background activity or attenuating

material [8.1 ± 0.2 mm (PP-AST) vs 8.0 ± 0.2 mm

(IH-EfC) vs 8.3 ± 0.2 mm (SS-FL3); P [ .05]. Although

32% 42% 43% 68% 48%50% Threshold 65%0.00

5.00

10.00

15.00

20.00

25.00

MW

T (

mm

)


Figure 6. MWTs measured using 50% and Opt% thresholds (indicated below each case) for AST,EfC, FL3, and MIRG reconstructions using PP, IH, and PP datasets using Protocol B-PSC. Errorbars represent 95% confidence intervals.

Table 5. Volumes of the LV extracted from each reconstructed dataset using a set 50% threshold andtheir respective optimal thresholds

Camera Reconstruction

Protocol A Protocol B Protocol B-PSC

Opt% 50% Opt% 50% Opt% 50%Volume(mL)

Volume(mL)

Volume(mL)

Volume(mL)

Volume(mL)

Volume(mL)

PP MIRG 123.9 97.8 140.1 70.6 143.4 87.4

AST 121.3 125.2 130.7 100.2 128.4 110.5

IH MIRG 132.7 91.8 136.3 94.1 124.2 85.3

EfC 144.8 200.0 127.6 186.3 124.2 191.8

SS MIRG 96.9 110.6 96.9 110.6 96.9 110.6

FL3 124.6 185.8 124.6 185.8 124.6 185.8

Protocols A, B, and B-PSC are displayed. The true volume of the phantom heart is equal to 120 mL.



it is a standard procedure to assess the tomographic res-

olution of SPECT systems using point source

measurements (e.g. NEMA recommendation), such

studies do not realistically model clinical situations. Thus,

the results of these studies cannot be extrapolated into the

clinical domain since the problem solved by the recon-

struction algorithm is oversimplified.

From the analysis regarding the effects associated

with different levels of corrections included in the

algorithm for reconstructions performed with our inde-

pendent MIRG software (Figure 2), it is evident that

reconstructions with AC only produced the largest

MWT measurements (ranging from 14 mm to 21 mm

for different cameras) under a set threshold of 50%, as

where the integration of RR into the algorithm consid-

erably reduced the MWT values (the range of values

became 5-10 mm) in all cases. Although these results

suggest that the addition of RR improves the MWT

measurements by producing values closer to the truth

(10 mm), it is necessary to consider the qualitative

aspects of these images and the resulting segmentations.

In this respect, we observed that false defects were

created in all cases with RR-only reconstructions when a

50% threshold was used to segment the LV. Therefore,

these results cannot be considered representative of the

true MWT measurement. Specifically, a majority of

these false defects were located in the inferior region of

the LV myocardium, which was the region deepest in

the phantom and consequently most effected by photon

attenuation.

The addition of AC corrects for this phenomenon

and effectively thickens the inferior wall, thus increasing

the MWT measurements. Therefore, albeit RR tends to

reduce the MWTs to values closer to the truth (using a

50% threshold), the inclusion of AC with RR into the

algorithm is necessary to more accurately represent the

true shape of the LV. The further inclusion of SC in

the reconstruction algorithm with AC and RR did not

significantly influence the results for the MWT mea-

surements in our study; however, this was likely due to

the fact that there were no substantial sources of scatter

adjacent to the phantom heart. In order to better

understand the effects of SC on tomographic resolution

for this type of phantom study, it would be necessary to

place a source near the location of the heart.

We found that a 50% threshold is too rigid for this

analysis as it created false defects in the LV for several of

the investigated cases, suggesting that either the count

distribution within the reconstructed LV had severe non-

uniformities (artifacts) or that the threshold was too high.

Indeed, the former was true for the cases with extensive

inferior wall attenuation artifacts (when reconstructed

without AC), as where the latter was true for the

best reconstructions, such as OSEM ? AC ? RR and

Figure 7. Examples of SA slices in the mid-ventricular region of the reconstructed phantom heartimages. Columns A, B, and C represent reconstructions with data acquired from PP, IH, and SS,respectively. Row (i) represents MIRG reconstructions and row (ii) represents the manufacturers’reconstructions (i.e. AST, EfC, and FL3). All reconstructions were performed with the correctionsindicated in Table 3, using Protocol A acquisitions. Each image is normalized to its maximumcount value.



Figure 8. Examples of SA slices in the mid-ventricular region of the reconstructed phantom heartimages. Columns A, B, and C represent reconstructions with data acquired from PP, IH, and SS,respectively. Row (i) represents MIRG reconstructions and row (ii) represents the manufacturers’reconstructions (i.e. AST, EfC, and FL3). All reconstructions were performed with the correctionsindicated in Table 3, using Protocol B acquisitions. Each image is normalized to its maximumcount value.

Figure 9. Examples of SA slices in the mid-ventricular region of the reconstructed phantom heartimages. Columns A, B, and C represent reconstructions with data acquired from PP, IH, and SS,respectively. Row (i) represents MIRG reconstructions and row (ii) represents the manufacturers’reconstructions (i.e. AST, EfC, and FL3). All reconstructions were performed with the correctionsindicated in Table 3, using Protocol B-PSC data. Each image is normalized to its maximumcount value.



OSEM ? AC ? RR ? SC. Nevertheless, it has been

demonstrated in either situation that using a 50%

threshold to define the boundaries of the true myocar-

dium is unreliable which, in clinical studies, could

potentially lead to false-positive diagnoses.

Although a 50% threshold used in SPECT MPI has

been widely accepted for the use of LV segmentation, it

should be noted that this threshold was developed for

filtered back projection reconstructions and not iterative

techniques. Moreover, there have been multiple reports

suggesting different thresholds that should be used to

segment the LV in SPECT MPI,21,22 but each of these

thresholds have been established using different iterative

algorithms with different levels of correction.

The combination of our observations and the vari-

ous conclusions from previous reports prompted us to

suggest that a reconstruction-specific (optimized)

threshold should be considered. By definition, this Opt%

does not allow for the creation of false perfusion defects,

which assures that the resulting MWT measurements

better represent the true values as they are not artificially

reduced by physical effects (e.g. photon attenuation).

Not surprisingly then, we observed reduced MWT (and

volume, see Table 3) variability between the studies

analyzed using the Opt% method relative to the 50%

threshold. Additionally, all MWTs measured with Opt%

were greater than or equal to the truth, which would be

expected taking into account the SPECT acquisition and

reconstruction process.

For the reconstructions using data acquired from

different cameras and processed with a standardized

algorithm, namely our MIRG algorithm (OSEM ?

AC ? RR ? SC), there were no significant differences

found between MWT measurements using the universal

threshold of 50% (see Figures 4, 5, and 6) for all proto-

cols. While for the Opt% we found significant differences

between the aforementioned cases for acquisitions fol-

lowing Protocol A [e.g. 9.9 ± 1.4 mm (SS) vs 14.2 ±

1.1 mm (IH); P \ .05], no significant differences were

discovered when better resolution acquisitions (Protocol

B) were used [9.9 ± 1.4 mm (SS) vs 11.8 ± 1.2 mm (IH)

vs 11.4 ± 0.9 (PP); P [ .05]. Moreover, Protocol B-PSC,

which had the best resolution and standardized pixel size,

also did not produce significant differences in MWT for

Figure 10. Profiles drawn through SA slices in the mid-ventricular region of the reconstructedphantom heart images. The profiles in A, B, and C correspond to the data acquired using PP, IH,and SS, respectively. In all cases, the thick solid line represents our MIRG reconstruction. In A, B,and C, the dashed lines represent profiles from the AST, EfC, and FL3 reconstructions,respectively. All corrections included in the reconstructions are indicated in Table 3, using ProtocolB-PSC data. The counts for each dataset were normalized to the maximum value of each analyzedslice.

Figure 11. A comparison of profiles drawn through the septalwall for a SA slice chosen in the mid-ventricular region of thephantom heart. The images were reconstructed with PP (thinsolid black), EfC (solid grey), FL3 (thin dashed black), andMIRG (thick black) with the corrections indicated in Table 3using Protocol B-PSC. Counts are normalized to maximumvalue found within each dataset. The horizontal solid blackline aims guide the eye and illustrate the variable thicknessesbetween reconstructions at a set threshold of 60%.



the MIRG reconstructions using the Opt% [10.4 ±

0.8 mm (SS) vs 10.4 ± 0.8 mm (IH) vs 11.4 ± 0.9 (PP);

P [ .05]. The difference found in the case with Protocol A

was likely due to the large differences in matrix size using

this protocol (PP and IH uses 6.4 mm and 6.8 mm,

respectively, whereas SS uses 4.8 mm). The results from

this aspect of the investigation suggest that there were no

differences in the quality of the datasets that were

acquired on each of the SPECT-CT systems; thus, the

acquisition performances of the systems seem to be on par

with each other.

However, when using the reconstruction algorithms

native to each of the SPECT-CT systems, we found

significant differences (P \ .05) between MWT mea-

surements for all investigated protocols when using both

thresholding techniques (Figures 4, 5, and 6). Strikingly,

the relative differences between the highest and lowest

MWTs measured for each protocol using a set 50%

threshold were as high as 66%, 110%, and 106% for

Protocols A, B, and B-PSC, respectively. The fact that

there were no differences observed when these acquired

datasets were reconstructed with a standardized algo-

rithm (MIRG) and that there were differences observed

when the different vendor algorithms were applied

suggests that these commercial reconstructions would

produce different images if reconstructing the same

dataset. The significance of these observations renders

itself in clinical situations where two (or more) SPECT

MPI studies are performed on the same patient using

different SPECT-CT systems. Therefore, it is very

important that physicians interpreting these studies are

aware of these differences.

CONCLUSIONS

When considering the testing process of the tomo-

graphic resolution of a SPECT-CT system, which would

be relevant for clinical applications, our results suggest

that traditional point-source experiments, performed

without the presence of background activity or attenu-

ating material, may not reveal the system’s true

performance. Although this is certainly an appropriate

starting point when performing acceptance tests of a

new camera as it would be sensitive to hardware or

software malfunctions, our study suggests that a stan-

dardized phantom model, such as the one used in this

study, should be implemented to provide a more com-

prehensive analysis of camera performance.

Although there were no significant differences

found between acquired phantom data from the three

systems when reconstructed with a standardized algo-

rithm (our own MIRG software), the fact that there

were substantial differences in tomographic resolution

found between the investigated clinically employed

reconstructions algorithms images is unsettling and

requires further investigation. This observed inter-man-

ufacturer variability in SPECT-CT performance can

potentially translate into differences in perfusion defect

sensitivities leading to diagnostic inconsistencies.

Future studies may include an investigation

regarding the accuracy of the scatter correction meth-

odologies which are integrated into some of the

commercial reconstruction algorithms, as there is a wide

range of possible correction approaches and no reliable

guidelines. These studies should be performed using

phantom experiments with additional hot source(s) in

the proximity of the heart (modeling a hot liver) which

would enable a more comprehensive analysis of the

algorithms.

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a multi-center phantom study comparing image resolution from three state-of-the-art spect-ct systems

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