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Quantification and data optimisation of heart and brain studies in conventional nuclearmedicineDobbeleir, André Alfons

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13

2. Determination of left ventricular ejection fraction by first pass

and gated SPECT studies.

2.1.Performance of a single crystal digital gamma camera for first pass cardiac

studies.

A. Dobbeleir

1, P.R. Franken

1, H.R. Ham

2, C. Brihaye

3, M. Guillaume

3, F.F. Knapp

4 and

J. Vandevivere1

1Division of Nuclear Medicine, Middelheim General Hospital Antwerpen, 2020 Belgium,

2Division

of Nuclear Medicine, St Peter’s Hospital, 1000 Bruxelles, Belgium, 3Cyclotron Research Center,

University of Liège, Belgium, 4Nuclear Medicine Group, Health and Safety Research Division, Oak

Ridge National Laboratory (ORNL), Oak Ridge, TN 37831-0622, USA

Nuclear Medicine Communications 1991; 12: 27-34.

Summary

First pass radionuclide angiocardiography (FPRNA) has gained increasing interest because of the

development of new 99Tc

m-labelled perfusion agents and of new

191Os/

191Irm generator systems. The

aim of the study was to evaluate the performance capacities of a small field of view crystal digital

gamma camera for 99Tc

m and

191Irm at high count rates. The camera dead time for

99Tc

m (window

30%) was well corrected up to 300 kcps in fast acquisition mode using the relative decrease of a

small shielded reference source. Using the decaying activity method for 191

Irm the non-linearity

response of the gamma camera was corrected by an 191

Os reference source up to 210 kcps at 70

keV, 75 kcps at 129 keV and 320 kcps including both peaks. Saturation count rates were

respectively 270 kcps, 150 kcps and 420 kcps and high count rate resolution (FWHM) 9.0, 7.3 and

10.3 mm. Since the accuracy of the first pass measurements is more sensitive to count rate than to

spatial resolution the 50-150 keV window was chosen for clinical studies. In data obtained from 32

ECG gated FPRNA patient studies, the whole field of view count rate during the left ventricular

phase ranged from 100 to 250 kcps with 80 to 120 mCi (2960-4400 MBq) of 191

Irm and 100 to 180

kcps with 20 to 25 mCi (750-925 MBq) of 99Tc

m red blood cells permitting for both tracers accurate

non-linearity correction.

Introduction

First pass radionuclide angiocardiography (FPRNA) has recently gained increasing interest for

measuring left ventricular function. Firstly, because of the availability of new 99Tc

m-labelled

myocardial perfusion agents allowing simultaneous assessment of myocardial perfusion and

function [1, 2]. Secondly, because of the development of new high performance 191

Os/191

Irm

generator systems [3-5] offering the opportunity to conduct rapid, repeat, multiple first pass studies

of the cardiovascular system with the ultrashort half-lived 191

Irm [6-8]. The aim of this study was to

evaluate the performance capacities and the limitations of a single crystal digital gamma camera

(SCDGC) with respect to the high count rates needed for accurate measurements of ventricular

function with the FPRNA method.

14

Materials and methods

191

Irm

191Irm is the daughter of

191Os (

191Os:β-

emission ; T1/2 = 15,4 days) and decays with a half-life of

4,96 s to stable iridium emitting a gamma-ray at 129 keV and three X-rays at 63 keV, 16%; 65 keV,

28%; and 74 keV, 12%. The X-rays cannot be resolved with the Na crystal and appear thus as one

single peak at about 69 keV (Fig 1.). In this study, 191

Irm was produced by elution of a carbon-based

191Os/

191Irm generator system with pH 2, 0,9% NaCl solution containing potassium iodide and

subsequently neutralized with a TRIS buffer. Details concerning the preparation and use of this

generator system have been published elsewhere [3, 8, 9].

Data acquisition

Data were acquired in the ‘normal’ acquisition mode or in the ‘fast’ acquisition mode with a small

field of view (20 cm) SCDGC (APEX 215M, Elscint) equipped with a very high sensitivity, low-

energy, parallel hole collimator. In the ‘fast’ mode, a higher number of counts can be acquired using

a different electronic circuit integrating only the first 400 ns of the scintilation.

Fig. 1. Spectrum of

191Ir

m measured with a gamma camera.

Camera resolution

The resolution of the camera for different energies was tested with 99Tc

m, 201

Tl and 191Os point

sources in the ‘normal’ and in the ‘fast’ acquisition modes [10]. 191

Os decays to 191

Irm by β-

emission without emitting photons. The FWHM, FW20M and FW10M were calculated in a 30%

window centered over the 140 keV 99Tc

m photopeak, in a 40% window centered over the 70 keV

201Tl photopeak and in the 50-100, 100-150 and 50-150 keV windows of the

191Irm spectrum.

Count-rate linearity

The linearity of the gamma camera for 99Tc

m was measured by placing an increasing number of

small vials (1 cm diameter) on the collimator. The activities were measured using a dose calibrator

15

and no scattering material was used. Data were acquired in the ‘fast’ mode with the energy of the

pulse height analyser set at 140 keV with a 30% window. Increasing 99Tc

m activities were measured

together with a 10 kcps activity shielded reference source of 99Tc

m placed in the field of view of the

camera. The measured activity was corrected for the dead time of the camera by a software

correction program based on the detected counts before the pulse height analyser (provided by the

manufacturer) and by the relative decrease of activity of a reference source [11, 12]. The linearity of

the gamma camera for 191

Irm was tested using the decaying source method. For that purpose a bolus

of 100 mCi (3700 MBq) of 191

Irm was extracted from the generator system using 15 ml of normal

saline solution, collected in an extension tube and directly divided through a three-way stopcock

into two 100 ml beakers placed on the collimator. The beakers contained a small quantity of water

in order to obtain a distributed source. A 10 kcps activity shielded 191

Os source was placed on the

camera as reference. Data were acquired in dynamic mode (25 frames per second) for 30 s. This

procedure was repeated three times in the 50-100, 100-150 and 50-150 keV windows. Time-activity

curves were then generated from regions of interest (ROI) drawn over the reference source, over the

two beakers and over a region between the two beakers ROIs, the latter being used to estimate the

relative amount of misplaced pile-up events [13, 14]. The activity curves of the two beakers were

added together and corrected for camera dead time by the relative decrease of the reference source

activity. The linearity response of the gamma camera was then established by comparing the dead

time corrected activity curve to the theoretical decaying curve of 191

Irm. For this purpose, a linear fit

with a slope = -0.140 corresponding to the decay constant of 191

Irm was applied on the low values of

the corrected activity curve expressed in the natural log (Fig. 2). Accepting a 1% deviation as

criteria, the limits of the linearity response of the system was determined for the above-mentioned

windows of the 191

Irm spectrum.

Fig. 2. Linear fit with a slope of –0.140 is applied to the dead time corrected decay curve of

191Ir

m in order to

determine the limits of linearity response of the system.

Patient studies

First pass radionuclide angiocardiographic studies were obtained at rest in 32 patients with 80-120

mCi (2960-4400 MBq) of 191

Irm and a few minutes later with 20-25 mCi (750-925 MBq) of

99Tc

m

red blood cells. Pulse height analyser windows were set over the 50-150 keV windows for 191

Irm

16

studies and over the 119-161 keV windows for the 99Tc

m studies. Data were collected in the ‘fast’

mode in a 32 x 32 x 8 matrix (25 frames per second) for 30 s.

Results

Camera resolution

The FWHM, FW20M and FW10M with 99Tc

m, 201Tl and

191Os point sources are given in table 1.

Table 1. Spatial resolution on point sources of

99Tc

m, 201Tl and

191Ir

m (50-100, 100-150 and 50-150 keV

windows) in the ‘normal’ (N) and ‘fast’ (F) acquisition modes.

191Ir

m

99

Tcm

201Tl 50-100 keV 100-150 keV 50-150 keV

N F N F N F N F N F

FWHM 6.0 7.3 6.5 8.6 6.9 9.0 6.4 7.3 7.7 10.3

FW20M 9.8 11.2 10.3 12.9 10.3 14.2 9.9 12.0 11.2 15.0

FW10M 12.4 14.2 13.3 16.3 12.5 16.3 12.0 14.2 13.3 18.1

As expected, the spatial resolution of the system was better for 99Tc

m than for

201Tl in the ‘normal’

as well as in the ‘fast’ acquisition modes. In the latter, a small but consistent degradation of the

resolution was observed with both isotopes. The resolution of the system for 191

Irm depends

obviously on the window selection. The resolution was similar to that of 201Tl for the 50-100 keV

window (FW20M 10.3 mm versus 10.3 mm) and similar to that of 99Tc

m for the 100-150 keV

window (FW20M 9.9 mm versus 9.8 mm) while the largest window (50-150 keV) gave the largest

FW20M (11.2 mm). Again the ‘fast’ acquisition mode induced a degradation of the spatial

resolution for all energy windows. This influence of window selection on the spatial resolution of

the gamma camera was further observed in clinical studies comparing 191

Irm FPRNA to

99Tc

m. The

left ventricular ROI area averaged 164 ± 29 pixels in 99Tcm studies and 192 ± 28 pixels in the 191Irm studies (P<0.0001).

Camera linearity

Using the relative decrease of the shielded point source activity as a reference, the camera dead time

for 99Tc

m (with a 30% window) was corrected up to 80 kcps in the ‘normal’ acquisition mode and

up to 300 kcps in the ‘fast’ acquisition mode, corresponding to true count rates of about 160 and

650 kcps, respectively. The software correction resulted in systematic undercorrection of the

linearity response of the camera. The saturation count rate for 191

Irm was 270 kcps in the 50-100

keV window, 150 kcps in the 100-150 keV window and 420 kcps in the 50-150 keV window. Using

the decaying source method, the camera dead time was corrected with an error of less than 1% up to

210 kcps in the 50-100 keV window, 320 kcps in the 50-150 keV window, but only up to 75 kcps in

the 100-150 keV window. The number of pile-up events was estimated from the ROI drawn

between the two beakers. At bolus arrival up to 9% of the total measured activity in the camera field

of view was related to misplaced events in the 100-150 keV window compared to 2.5% in the 50-

100 keV window and 5.5% in the 50-150 keV window (Fig. 3). A 1% or less misplaced events were

observed in the 50-100 keV window at the maximal count rate capacity of the camera (270 kcps), in

the 50-150 keV window at 70% (300 kcps) of the maximal capacity, but in the 100-150 keV at only

40% (60 kcps) of the maximal capacity of the camera system.

Patient studies

The highest count rates in the WFOV and in the right and left ventricular ROIs during the first

transit of 191

Irm (50-150 keV window) observed in 3 of the 32 patients are given in table 2. In

Patient 1, although left ventricular count rate was rather low the WFOV count rate during the right

17

phase of the transit was just below the maximal limit of accurate dead time correction of the system.

In Patient 2, and certainly in Patient 3, the count rates during the right transit phase were out of the

limits of dead time correction: the maximum WFOV count rate was reached at 0.3 and 2.6 s,

respectively, after the passage of the bolus in the right ventricle, indicating saturation of the gamma

camera and precluding simultaneous assessment of right and left ventricular function studies during

a single injection of 191

Irm.

Table 2. Maximal count rates during

191Ir

m (50-150 keV window) FPRNA studies in three patients.

FPRNA RV phase LV phase

WFOV RV WFOV LV WFOV

Patient (kcps) (kcps) (kcps) (kcps) (kcps)

Delay

max FPRNA-

max RV phase ( s)

1 306 201 306 51 132 0.0

2 400 278 398 99 212 0.3

3 441 187 380 195 331 2.6

The maximal count rate in the 20 cm field of view of the camera observed in most patients during

the left ventricular transit of the 191

Irm bolus ranged between 100 and 250 kcps. The maximal count

rate observed in those patients during the left ventricular transit of the 99Tc

m bolus ranged between

100 and 180 kcps. Left ventricular counts in the 40 ms end-diastolic image of the ECG-gated left

ventricular representative cycle averaged 14.8 kcounts (range 5.3-30.3) with 191

Irm and 10.2 kcounts

(range 3.6-22.1) with 99Tc

m.

Discussion

The count rates observed during left ventricular FPRNA studies using 99Tc

m and

191Irm were within

the limits of accurate dead time correction for this gamma camera system. Left ventricular counts

were sufficiently high to measure left ventricular function accurately [15].

Window selection on the 191

Irm spectrum with the pulse height analyser is of major importance for

both camera resolution and linearity when performing studies with this tracer. Although the 100-

150 keV window is associated with the best camera resolution, this selection is the worst with

respect to count rate capacities and dead time correction because the relative low contribution of

those photons to the total number of photons reaching the crystal and because of the pile-up events.

Accurate dead time corrections with the reference activity source were obtained, in the 50-100 keV

as well as in the 50-150 keV window, for count rates higher than those observed in patients during

left ventricular first pass studies. Although the spatial resolution of the 50-100 keV was somewhat

better than the 50-150 keV window, this latter was chosen for clinical studies because the accuracy

of first pass measurements is known to be more sensitive to count rate than to spatial reslution [15].

Using this window, the number of counts in the left ventricular cavity with 191

Irm were at least equal

to those obtained with 99Tc

m in all patients.

During the right ventricular transit phase of the bolus, the total count rate was obviously over the

count rate capacities of the camera in most patients precluding simultaneous studies of the right en

left ventricles during a single injection of 191

Irm.

In our patient population, the mean total activity in the 20 cm field of view of the camera was about

1.15 times higher during diastole than during systole, introducing a relative dead time correction of

1.03 to 1.04. On the other hand, for 191

Irm, the relative decay correction between diastolic and

systolic frames ranged between 1.04 and 1.06. As the linearity correction factor and the decay

correction factor work in the opposite direction, an error of maximum 3% would be made on the

ejection fraction not applying any correction. For large field of view gamma cameras one can

expect a smaller relative dead time correction between diastolic and systolic frames due to a less

varying total activity in the large field of view.

18

Fig. 3. Time-activity curves of a decaying

191Ir

m source (initial activity 100 mCi) in the 50-100, 100-150 and

50-150 keV windows, respectively. For display purposes, the activity of the 191Os reference source and of the

misplaced events recorded simultaneously, were multiplied by a factor of 5.

References

1. Sporn V, Perez Balino N, Holman BL et al. Simultaneous measurement of ventricular

function and myocardial perfusion using the technetium-99m isonitriles. Clin Nucl Med

1988; 13: 77-81.

2. Baillet GY, Mena IG, Kuperus JH et al. Simultaneous technetium-99m MIBI angiography

and myocardial perfusion imaging. J Nucl Med 1989;30: 38-44.

3. Brihaye C, Butler TA, Knapp FF Jr et al. A new osmium-191/iridium-191m radionuclide

generator system using activated carbon. J Nucl Med 1986; 27: 380-7.

19

4. Packard AB, Treves ST, O’Brien GM, Lim KS. An osmium-191/iridium-191m radionuclide

generator using an oxalato osmate parent complex. J Nucl Med 1987; 28: 1571-6.

5. Issachar D, Abrashkins S, Weinigerr J et al. Osmium-191/iridium-191m generator based on

silica gel imregnated with tridodecylmethylammonium chloride. J Nucl Med 1989; 30: 538-

41.

6. Heller GV, Treves ST, Parker JA et al. Comparison of ultrashort-lived iridium-191m with

technetium-99m for first pass radionuclide angiocardiographic evaluation of right and left

ventricular function in adults. J Am Coll Cardiol 1986; 7: 1295-302.

7. Hellman C, Zafrir N, Shimoni A et al. Evaluation of ventricular function with first pass

iridium-191m radionuclide angiography. J Nucl Med 1989; 30: 450-7.

8. Franken PR, Dobbeleir A, Ham HR et al. Clinical usefulness of ultrashort-lived iridium-

191m from carbon-based generator system for the evaluation of the left ventricular function.

J Nucl Med 1989; 30: 1025-31.

9. Brihaye C, Dewez S, Guillaume M et al. Reactor production and purification of osmium-

191 for use in a new OS-191/Ir-191m radionuclide generator system. Appl Radiat Isot 1989;

40: 183-9.

10. Performance standards of scintillation cameras, Standards Publication/No. NU 1-1986.

National Electrical Manufacturers Association.

11. Ullman V, Husak V, Dubroka L. Deadtime correction in dynamic radionuclides studies by

computer. Eur J Nucl Med 1978; 3: 197-202.

12. Johnston AS, Arnold JE, Pinsky SM. Anger camera deadtime: marker source correction and

two parameter model. J Nucl Med 1975; 16: 539.

13. Lange D, Hermann HJ, Wetzel E, Schenck P. Critical parameters to estimate the use of a

scintillation camera in high dose dynamic studies. Medical Radionuclide Imaging (Proc.

Symp. Los Angeles) 1. Vienna: IAEA 1977; 85-100.

14. Johnston AS, Gergans GA, Kim I et al. Deadtime of computers coupled with anger cameras:

counting losses and false counts. Single photon emission computed tomography and other

selected computer topics (Proc. Symp. Miami 1980). Sorenson, ed. New York: Society of

Nuclear Medicine.

15. Dymond DS, Elliot A, Stone D et al. Factors that affect the reproducibility of measurements

of left ventricular function from first pass radionculide ventriculograms. Circulation 1982;

65: 311-22.

20

2.2 Variability of left ventricular ejection fraction and volumes by quantitative gated

SPET : influence of algorithm, pixel size and reconstruction parameters in normal

and small-sized hearts.

Anne-Sophie Hambye1, Ann Vervaet

2, André Dobbeleir

2,3

1Nuclear Medicine, CHU-Tivoli, La Louvière, Belgium

2Nuclear Medicine, Middelheim Hospital, Antwerp, Belgium

3Nuclear Medicine, University Hospital Ghent, Ghent, Belgium

Eur J Nucl Med Mol Imaging 2004; 31: 1606-1613.

Abstract

Several software are commercially available for quantification of left ventricle ejection fraction and

volumes from myocardial gated SPET, all with a high reproducibility. However, their accuracy has

been questioned in patients with a small-sized heart. This study aimed at evaluating the

performances of different software and the influence of modifications in acquisition or

reconstruction parameters on ejection fraction and volumes measurements, depending on the heart

size. Methods: Sixty-four2 and 1282 matrix size acquisitions were consecutively obtained in 31

patients referred for gated SPET. After reconstruction by filtered backprojection (Butterworth, 0.4,

0.5 or 0.6 cyc/cm cutoff, order 6), LVEF and volumes were computed with different software (3

versions of Quantitative Gated SPECT (QGS), Emory Cardiac Toolbox (ECT) and the Stanford

University (SU) Medical School algorithm), and processing workstations. Depending upon their

end-systolic volume (ESV), patients were classified into 2 groups: Group I (ESV>30ml, n=14) and

Group II (ESV <30ml, n=17). Agreement between the different software, and the influence of

matrix size and sharpness of the filter on LVEF and volumes were evaluated in both groups.

Results: In Group I, the correlation coefficients between the different methods ranged from 0.82 to

0.94 except for SU (r=0.77), and were slightly lower for volumes than ejection fraction. Mean

differences between the methods were not significant, except for ECT which LVEF values were

systematically higher by more than 10%. Changes in matrix size had no significant influence on

LVEF or volumes. On the other hand, a sharper filter was associated with significantly larger

volume values though this did usually not result in significant LVEF changes. In Group II, many

patients had a LVEF at the higher range. The correlations coefficients between the different

methods ranged between 0.80 and 0.96 except for SU (r=0.49), and were slightly worse for volumes

than LVEF values. Contrary to Group I, a majority of mean differences between LVEF

measurements was significant. LVEF was systematically the highest by ECT and the lowest by SU.

With QGS, changes in matrix size from 642 to 1282 were associated with significantly larger

volumes as well as lower LVEF values. Increasing the filter cutoff frequency had the same effect.

With SU-Segami, a larger matrix was associated with larger end-diastolic and smaller end-systolic

volumes, resulting in a highly significant increase in LVEF. Increasing the filter sharpness on the

other hand had no influence on LVEF though the measured volumes were significantly larger.

Conclusion: In patients with a normal-sized heart, LVEF and volume estimates computed from

different commercially available software for quantitative gated SPET are well correlated. LVEF

and volumes are little sensitive to changes in matrix size. Smoothing on the other hand was

associated with significant changes in volumes but usually not in LVEF values. However, owing to

21

the specific characteristics of each algorithm, software should not be interchanged for follow-up in

an individual patient.

In small-sized hearts on the other hand, both the used software and the matrix size or smoothing

significantly influence the results of quantitative gated SPET. LVEF at the higher range are

frequently observed with all the studied software except for SU-Segami. A larger matrix or a

sharper filter could be suggested to enhance the accuracy of most commercial software, more

particularly in patients with a small heart.

Keywords: quantitative gated SPET – LVEF – small heart – inter-software comparison

Introduction

Gated myocardial SPET has become the state-of-the-art for myocardial perfusion imaging, offering

the simultaneous evaluation of left ventricular perfusion and function with a single test. Different

methods to quantify left ventricular ejection fraction (LVEF) and volumes have been described [1-

6], all with a high reproducibility and a good agreement with various non nuclear or nuclear

techniques [6-10].

However, owing to the specific characteristics of each algorithm, software interchangeability for

repeated examinations in an individual patient should not be recommended [9,11] despite the good

correlations reported between different software computing the same gated SPET data [8,9,11].

Moreover, experimental data have revealed the sensitivity of gated SPET measured LVEF to

particular acquisition conditions such as time of imaging, background activity or injected dose [12],

filtering and zooming [13-15], and larger discrepancies between the methods have been described

for LV volumes [8], particularly at both ends of the scope of volume values.

Another problem in using quantitative gated SPET for LVEF calculation is encountered in patients

with a small heart such as children or some small women. Indeed, due to the limited spatial

resolution of the gamma cameras, the opposite endocardial edges of the left ventricle overlap, so

that the ventricular cavity may become almost virtual especially at end-systole. This results in an

underestimation of volumes, hence overestimation of LVEF [13-17], particularly using algorithms

based upon edge detection.

The purpose of our study was to compare LVEF and volumes computed from the same gated SPET

data by different versions of the QGS-package [1], the Emory Cardiac Toolbox [4,5] and the

Standford-University algorithm [6], and to evaluate the influence of filter and matrix size on the

measurements.

Material and methods

Patients and acquisition

During a 3-month period, QGS-analysis [1] was systematically performed in all patients undergoing

a stress test as a part of a two-day stress-rest gated myocardial SPET. Depending upon their end-

systolic volume (ESV) calculated on a GE-Elscint Expert system, the patients were classified into a

group with a normal or large-sized heart (ESV >30 ml, Group I) and a group with a small-sized

heart (ESV <30 ml, Group II). This value of 30ml-ESV was chosen based upon data from Ford et

al, reporting that the difference between measured and true LVEF in a cardiac phantom becomes

pronounced when the end-diastolic volume is <70 ml and the true LVEF is >40% [14]. Clinical

characteristics of the both patients groups are reported in Table 1.

Among those who required a comparative rest test, 31 underwent two consecutive gated SPET at

rest: 14 of Group I and 17 of Group II. Decision to perform this double rest study was based solely

upon the availability of free time-slots on the gamma-camera. The first acquisition in matrix 642,

zoom 1.28 (6.9 mm-pixel size) started about 1 hour after injection of 740-1000 MBq 99mTc-

sestamibi and was immediately followed by a second acquisition in a 1282 matrix, zoom 1.28 (3.45

mm-pixel size). Both SPET acquisitions lasted 25-30 minutes and were performed with a GE-

22

Elscint VariCam dual-head gamma camera equipped with VPC-35 collimators (system resolution of

9.0 mm FWHM at 10 cm distance; 290 cpm/µCi), using an eight-bin gated protocol (90 projections

(45/head) of 35 second/each; 360°-rotation; automatic body-contouring).

Gated SPET Analysis

Acquisition data sets were transferred from the GE-Elscint Expert system to a Sun Ultra10 Link

Medical system (Link Medical, Hamshire, UK), a PC-Windows NT GE system (GE Medical

Systems, Milwaukee, USA) and a PC-Windows NT Segami system (Segami, Columbia, USA)

using DicomP10, and to a Nuclear Diagnostic Hermes system (Nuclear Diagnostic, Stockholm,

Sweden) using modified interfile. The rough 642 and 1282 matrix gated SPET acquisitions were

reconstructed with Butterworth filters of 0.4, 0.5 or 0.6 cyc/cm cutoff (order 6) on different

workstations. LVEF and volumes were automatically quantified from the gated coronal slices using

commercially available software routinely used by the nuclear medicine community (three versions

of Quantitative Gated SPECT (QGS), Cedars-Sinai Medical Center, Los Angeles, CA; Emory

Cardiac Toolbox (ECT), Emory University, Atlanta, GA; Stanford University (SU) Medical School

algorithm). These six different processings will be further referred to as QGS-Link, QGS-GE, QGS-

Hermes, QGS-eNTEGRA, ECT-eNTEGRA and SU-Segami respectively. All have been described

in detail elsewehere [1,3-5] and widely validated.

Table 1. Clinical characteristics of the patient population (p=NS if >0.05).

Group I: ESV > 30ml; Group II: ESV <30 ml; CRF: cardiovascular risk factors; MI: myocardial infarction;

bicycle: upright bicycle stress test, 25W increment/2 min up to maximum heart rate; adenosine:

140µg/kg.min during 6 minutes; dobutamine: 10 to 40µg/kg.min with 3-min increments, + atropine if

required.

Group I (n=14) Group II (n=17) P value

Age (years); mean±SD 55.3±14.6 65.1±12.1 0.048

Gender (M/F) 7 / 7 2 / 15 0.044

CRF 7 10 NS

Prior MI 5 1 NS

Prior revascularization 5 4 NS

Referral reason

Chest pain

Abnormal stress EKG

Other

9

2

3

16

1

0

NS

NS

NS

Kind of stress test

(bicycle/adenosine/dobutamine)

9 / 4 / 1

8 / 9 / 0

NS

Evidence of stress ischemia on SPECT 5 6 NS

23

Statistical analysis

Results are expressed in absolute EF units for LVEF and in ml for the volumes.

All statistical analyses were performed using the SPSS statistical program package (SPSS Inc,

Chicago, USA). Inter-method variability was expressed as mean difference +/- SD. The significance

of the difference between two groups of data was assessed by the paired or unpaired Student’s t-test

and chi squared test or Fisher’s exact test, when appropriate. Paired data among three or more

groups were compared using repeated measurements ANOVA. A p value of 0.05 or less was

considered significant.

To identify the differences for multiple testing, a Bonferroni correction was applied for comparing

each pair of methods. With this correction, a p value of less than 0.0033 was considered significant.

Pearson correlation coefficients were calculated, and Bland-Altman plots [18] were generated to

search for trends by plotting the differences versus averages of paired values. For this part of the

analysis, QGS-Link was arbitrarily chosen as a reference against which the other methods were

plotted, as it constituted the last version of the most widely spread quantification method.

Fig 1. Bland-Altman plots showing the agreement for ejection fraction between the reference method (QGS-

Link) and the other packages. (ESV>30ml in open circles; ESV<30ml in solid circles).

LVEF: left ventricular ejection fraction; ESV: end-systolic volume.

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

0,0 20,0 40,0 60,0 80,0 100,0

mean

QGS GE - QGS Link

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

0,0 20,0 40,0 60,0 80,0 100,0

mean

QGS Hermes-QGS Link

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

0,0 20,0 40,0 60,0 80,0 100,0

mean

QGS eNTEGRA-QGS Link

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

0,0 20,0 40,0 60,0 80,0 100,0

mean

SU Segami-QGS Link

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

35

0,0 20,0 40,0 60,0 80,0 100,0

mean

ECT eNTEGRA-QGS Link

24

Results

Using repeated measures analysis of variance between the six processings and the two groups of

patients, a highly significant interaction was found, indicating that the impact of the software

differed for the two patients groups. In addition, a significant overall difference was found between

the six methods and also between the two patients groups (both p<0.001).

Influence of the processing algorithm on ejection fraction and volume values.

Group I (ESV> 30 ml).

The different methods were fairly correlated with QGS-Link, with r values ranging between 0.82

and 0.94, except for SU-Segami (r=0.77).

Mean LVEF and volume values were quite similar for the different methods, except for ECT-

eNTEGRA which resulted in higher LVEF (Table 2). By Bland-Altman analysis, no significant

trend toward higher or lower LVEF was found across the whole range of values for any method but

ECT-eNTEGRA compared to QGS-Link (Figure 1, open circles). By paired Student’s t-test, highly

significant differences (0.0001<p<0.0033) were noted between ECT-eNTEGRA and the other

methods for LVEF and end-systolic but not for end-diastolic volume values (Table 3). Significant

differences were also found for volume values between the QGS versions.

Group II (ESV<30 ml)

In keeping with Group I, all methods except SU-Segami correlated well with QGS-Link (r values

between 0.80 and 0.96; r=0.49 for SU-Segami).

Mean LVEF values were above 70% for all programs except for SU-Segami (mean LVEF: 60.4%,

Table 2), and was highest by ECT-eNTEGRA. Opposite to Group I however, inter-method

variability was quite large and most mean LVEF differences were significant (Table 3). Significant

disparities in volume estimates were more frequent for end-systolic than end-diastolic volumes, and

were particularly large for SU-Segami (between 10ml and 20ml, all p values <0.0001, Table 3).

Compared to QGS-Link, LVEF was systematically higher by ECT-eNTEGRA (8.1±5.46%) and

lower by SU-Segami (-13.7±8.01%) as shown on the Bland-Altman plots (Figure 1, solid circles).

More surprisingly, a small but systematic difference in LVEF was also found by Bland-Altman

analysis between the three versions of the QGS software, reaching the level of statistical

significance for QGS-Hermes (Table 3).

Table 2. Mean±SD ejection fraction and volumes for the different software

(Group I: ESV > 30ml; Group II: ESV <30 ml; LVEF: left ventricular ejection fraction;

EDV: end-diastolic volume; ESV: end-systolic volume).

QGS Link QGS GE QGS Hermes QGS

eNTEGRA

ECT

eNTEGRA

SU Segami

LVEF (%) 45.1±12.98 47.4±12.43 49.4±12.48 47.5±13.53 62.0±14.13 50.1±12.67

EDV (ml) 119.5±66.24 122.4±63.85 112.6±63.85 119.3±65.76 108.2±51.22 119.3±49.19

Group I

ESV (ml) 72.3±59.96 69.9±58.32 62.7±52.47 69.9±57.89 46.1±41.14 64.3±45.45

LVEF (%) 74.5±9.06 70.1±7.35 78.1±8.49 73.1±7.80 82.4±8.24 60.4±5.43

EDV (ml) 53.6±17.23 57.8±15.68 51.6±18.21 55.6±17.31 54.9±17.25 70.9±15.25

Group

II

ESV (ml) 14.8±9.02 17.1±6.86 12.8±8.38 15.9±8.41 10.1±5.76 28.5±7.65

25

Influence of filtering on left ventricular ejection fraction and volume values.

For this part of the study, 642 matrix size images were used. Due to technical limitations of some

programs at our disposal at the time of the study, only QGS-GE, QGS-Hermes and SU-Segami

were compared.

Group I (ESV> 30 ml).

Increasing the cutoff frequency of the Butterworth filter from 0.4 to 0.6 cyc/cm (order 6) resulted in

significantly larger volumes for both QGS versions, and smaller volumes

for SU-Segami. However, the subsequent changes in LVEF were significant only by QGS-GE

(Table 4). The effect of filtering was more striking for the end-systolic volumes in relative values,

although the absolute changes were usually higher for the end-diastolic (Table 4).

Group II (ESV<30 ml)

Sharper filtering resulted in significantly larger volumes for QGS, and particularly the end-diastolic,

and in smaller volumes for SU-Segami. The ensuing LVEF change was however significant only

for the QGS-versions, the SU-Segami LVEF remaining remarkably stable (Table 4).

Table 3. Mean±SD difference in ejection fraction and volumes value according to the processing method

used.

(Group I: ESV > 30ml; Group II: ESV <30 ml; LVEF: left ventricular ejection fraction (%); EDV: end-

diastolic volume (ml); ESV: end-systolic volume (ml)).

P values are calculated using the Student’s paired t-test after Bonferroni correction. *: 0.0001<p<0.0033; **:

p<0.0001. All p values >0.0033 are considered as not significant.

Group I Group II

LVEF EDV ESV LVEF EDV ESV

QGS Link-QGS GE -2.2+/-7.61 -2.9+/-12.26 2.4+/-11.52 3.3+/-4.39 -3.8+/-6.81 -1.6+/-3.07

QGS Link-QGS Hermes -4.3+/-4.60 6.9+/-9.33 9.6+/-8.36 * -2.9+/-2.50 * 2.2+/-8.27 1.7+/-2.95

QGS Link-QGS eNTEG -2.3+/-7.57 1.8+/-14.59 3.8+/-13.58 1.1+/-2.47 -0.9+/-2.76 -0.7+/-1.88

QGS Link-ECT eNTEG -16.9+/-8.16 ** 11.3+/-21.95 26.1+/-22.52 * -8.1+/-5.46 ** 0.6+/-8.79 5.1+/-4.50 *

QGS Link-SU Segami -4.9+/-8.69 0.2+/-23.9 8.0+/-19.48 13.7+/-8.01 ** -17.5+/-6.09 ** -13.5+/-4.29 **

QGS GE-QGS Hermes -2.1+/-5.94 9.8+/-8.46 * 7.1+/-10.60 -6.2+/-3.42 ** 5.6+/-11.9 3.1+/-3.29

QGS GE-QGS eNTEG -1.0+/-3.74 5.4+/-10.53 2.5+/-8.56 -2.4+/-3.05 2.8+/-6.88 1.1+/-2.82

QGS GE-ECT eNTEG -14.6+/-4.8 ** 14.2+/-17.68 23.7+/-18.94 * -11.8+/-6.35 ** 3.5+/-11.91 6.9+/-2.53 **

QGS GE-SU Segami -2.7+/-4.91 3.1+/-18.03 5.6+/-15.16 9.7+/-7.28 ** -13.2+/-7.61 ** -11.4+/-4.65 **

QGS eNT-QGS Herm -2.0+/-5.87 5.0+/-12.35 5.9+/-11.71 -4.1+/-2.25 ** 2.9+/-7.65 2.4+/-1.91 *

QGS eNT-ECT eNTEG -14.4+/-4.87 ** 10.9+/-16.8 23.0+/-16.84 * -9.4+/-5.32 ** 0.7+/-8.20 5.8+/-3.87 **

QGS eNTEG-SU Seg -2.2+/-7.06 -0.7+/-18.5 4.5+/-15.42 12.3+/-7.45 ** -16.4+/-4.92 ** -12.8+/-3.69 **

QGS Herm-ECT eNT -12.6+/-7.25 ** 4.4+/-15.69 16.6+/-15.66 * -5.2+/-5.54 -1.4+/-8.01 3.5+/-4.16

QGS Herm-SU Segami -0.6+/-6.77 -6.6+/-16.29 -1.6+/-11.98 17.1+/-8.43 ** -19.1+/-6.76 ** -15.1+/-3.92 **

SU Sega-ECT eNTEG -11.9+/-6.63 ** 11.1+/-12.45 18.1+/-9.4 ** -21.7+/-9.02 ** 17.1+/-8.27 ** 18.6+/-4.27 **

26

Table 4: Influence of the filter cutoff frequency (order 6) on mean values for ejection fraction, end-diastolic

and end-systolic volumes. The p values are calculated by overall repeated measurements ANOVA (p=NS if

>0.05)

(Group I: ESV > 30ml; Group II: ESV <30 ml; BW: Butterworth filter; LVEF: left ventricular ejection

fraction; EDV: end-diastolic volume; ESV: end-systolic volume).

Group I

Group II

BW 0.4 BW 0.5 BW 0.6 P value BW 0.4 BW 0.5 BW 0.6 P value

EF (%) 48.1 47.4 45.1 0.008 72.6 70.1 69.8 0.003

EDV (ml) 111.1 122.4 122.3 <0.001 50.7 57.8 57.5 <0.0001

QGS GE

ESV (ml) 62.0 69.9 72.7 <0.0001 13.7 17.1 17.1 <0.0001

EF (%) 49.6 49.5 48.7 NS 82.5 78.1 77.1 0.007

EDV (ml) 100.9 112.6 118.9 <0.0001 47.8 51.6 56.3 <0.0001

QGS

Hermes

ESV (ml) 55.7 62.7 67.7 0.002 10.0 12.8 13.9 0.004

EF (%) 49.5 50.1 49.0 NS 60.3 60.4 60.5 NS

EDV (ml) 128.6 119.3 112.9 <0.0001 74.3 70.9 67.9 0.002

SU

Segami

ESV (ml) 69.8 64.3 62.1 <0.001 29.8 28.5 26.9 0.003

Influence of matrix size on left ventricular ejection fraction and volume values.

For this part of the study, the 0.5 cyc/cm Butterworth filter images (order 6) were processed by

QGS-GE, QGS-Hermes and SU-Segami.

Group I (ESV> 30 ml).

In this group, modifying the matrix size did not significantly influence mean LVEF and volume

values except for the end-diastolic volumes by SU-Segami (Table 5). Mean± SD differences (matrix

642 – 128

2) for LVEF, EDV and ESV were respectively 0.7±5.88%, 3.6±13.3 ml and 1.9±12.05 ml

for QGS-GE, 0.6±6.15%, –1.7±8.97 ml and -1.3±8.96 ml for QGS-Hermes, and -3.9±7.18%, -

9.1±10.51 ml and -1.1±9.36 ml for SU-Segami.

Group II (ESV<30 ml)

Decreasing the pixel size from 6.9 to 3.45 mm significantly modified the LVEF and volume values

regardless of the used processing (Table 5).

Using QGS, a smaller pixel size was associated with lower LVEF and larger volumes. Mean± SD

differences (matrix 642 – 128

2) for LVEF, EDV and ESV were respectively 2.8±4.36% (p=0.021), -

6.8±8.28 ml (p=0.004) and -4.1±4.24 ml (p=0.001) for QGS-GE, and 5.1±4.66% (p=0.001), –

6.7±7.02 ml (p=0.003) and -3.8±3.07 ml (p<0.0001) for QGS-Hermes. The effect of a smaller pixel

size seemed particularly marked for end-diastolic volumes of 60ml and below.

Using SU-Segami, results were divergent for end-diastolic and end-systolic volumes, the former

increasing from a mean value of 70.9 ml to 76.1ml for the 1282 matrix (p=0.014), and the latter

decreasing from 28.5 ml to 20.5 ml (p<0.001). As a consequence, LVEF increased by 12.9±5.74%

on average (p<0.0001).

27

Table 5: Influence of the acquisition matrix (642 or 128

2) on mean values for ejection fraction, end-diastolic

and end-systolic volumes. The p values are calculated by paired Student’s t-test (p=NS if >0.05).

(Group I: ESV > 30ml; Group II: ESV <30 ml; LVEF: left ventricular ejection fraction; EDV: end-diastolic

volume; ESV: end-systolic volume).

Group I

Group II

Matrix size 642 128

2 P value 64

2 128

2 P value

LVEF (%) 47.4 46.6 NS 70.1 67.4 0.021

EDV (ml) 122.4 118.9 NS 57.8 64.6 0.004

QGS GE

ESV(ml) 69.9 68.0 NS 17.1 21.2 <0.001

LVEF (%) 49.4 48.9 NS 78.1 71.5 0.001

EDV (ml) 112.6 114.4 NS 51.6 58.5 0.003

QGS

Hermes

ESV(ml) 62.7 64.0 NS 12.8 17.4 <0.0001

LVEF (%) 50.1 53.9 NS 60.5 73.4 <0.0001

EDV(ml) 119.3 128.4 0.006 70.9 76.1 0.014

SU

Segami

ESV(ml) 64.3 65.4 NS 28.5 20.5 <0.0001

Discussion

Using gated myocardial SPET, several algorithms have been developed for the calculation of LVEF

and volumes, each owing its specific assumptions for left ventricle modeling. Among the various

commercial programs, Cedars-Sinai Quantitative Gated SPECT (QGS, 1) is currently the most

widely used in the clinical setting. Its reliability and reproducibility are excellent and have been

validated against a whole range of methods. Nevertheless, with increased routine use, some

limitations have appeared, such as a falsely elevated LVEF in patients with a small-sized heart like

children or some women [14,16].

In patients with a normal- or large-sized heart, our study confirms the good agreement for LVEF

between different processing methods [7-9] and the absence of significant bias through the whole

range of LVEF values. Indeed, except for ECT-eNTEGRA that systematically overestimated LVEF

by more than 10%, no significant method-related mean differences in LVEF were noted. This

overestimation of LVEF by ECT has also been reported by others, including the authors of the

program themselves [9,19], and might be due to specificities in time sampling or shape used for LV

modeling [19]. Despite this good agreement, interchanging algorithms, or even consecutive

versions of the same algorithm for follow-up studies in an individual patient should not be

recommended because of the rather large standard deviation of the differences between the

methods. For the volume values, and more particularly the end-systolic, we found a larger

variability than for LVEF, with significant differences not only between ECT-eNTEGRA and the

other programs, but also between the three versions of QGS, maybe due to (minor) modifications of

its algorithm. In this patient population, increasing the matrix size had no significant influence on

volume or LVEF values. Increasing the filter cutoff frequency on the other hand significantly

modified the volume measurements, though this resulted in significant changes in LVEF only with

QGS-GE.

In patients with a small-sized heart, most mean differences in LVEF were significant despite a good

agreement between the different methods except for SU-Segami. Moreover, a systematic bias was

noted not only for ECT-eNTEGRA but also for SU-Segami which volumes were systematically

28

markedly larger, probably due to differences in the location of the ventricular wall which

corresponds to the average position for the latter and to the endocardial surface for the former [7].

Also changes in matrix of filter cutoff significantly influenced volume and LVEF values in small

hearts. This influence of the pixel size has already been reported by Nakajima et al in a cardiac

phantom study [13]. They found a decrease from 49% to 3% in the overestimation of a 37-ml

chamber volume by increasing the zoom from none to 2x during the acquisition, and confirmed

their findings in a pediatric population, but only in children younger than 7 years [13]. However, the

1.28x-zooming applied in the present study is the maximum magnifying factor that can be used for

a 60cm-field of view gamma camera without mechanical device keeping the heart in the center of

rotation, so that we were compelled to increase the matrix from 642 to 128

2 to reduce the pixel size

from 6.9 to 3.45 mm and so improve the delineation of the left ventricle endocardial border. Using

QGS, this modification resulted in significantly larger volumes and lower LVEF, particularly for

end-diastolic volumes of 60ml and below. By SU-Segami on the other hand, the combination of

larger end-diastolic and smaller end-systolic volumes for a 1282 matrix resulted in a highly

significant increase in LVEF, probably because of an insufficient count density and thus enhanced

statistical fluctuations.

By increasing the cutoff frequency of the Butterworth filter from a smooth 0.4 to a sharper 0.6

cyc/cm, larger volumes and a significant decrease in LVEF was obtained by QGS. By SU-Segami

on the contrary, LVEF remained stable despite significantly smaller volumes with a sharper filter,

probably because of parallel changes in end-diastolic and end-systolic volumes. The influence of

smoothing on LVEF and volumes could be due to the fact that, because of the limited spatial

resolution of a gamma-camera, the proportion of LV volume contained in an individual pixel is

larger in small than in large-sized hearts. In this way, changes in count density of the (especially

endocardial) pixels related to the cardiac motion are probably more abrupt for higher cutoff

frequency filtering. With a smooth filter, the systolo-diastolic transition in count density might be

softer, hence volume estimates smaller and LVEF higher. The lesser filter-dependence observed

with SU-Segami could be explained by the fact that its algorithm relies on the average ventricular

wall position instead of the endocardial surface.

This study compared different processing methods for quantitative estimates of LVEF and volumes

using gated myocardial perfusion SPET. Despite good correlations with regard to the calculated

values, clear differences were found between the algorithms, and more particularly between SU-

Segami and the other methods, especially in patients with a small heart. No single external standard

was available in our patients to determine the “true” values, so that the most recent version of the

most widely used program was arbitrarily chosen as a reference. Therefore, the calculated results

might be only a rough estimation of the patients’ real LVEF and volumes. However, since we

aimed at correlating different processing methods computing the same gated SPET data, the use of

an external standard does not seem an absolute prerequisite to validate the results. Another

limitation consists in the use of low-energy general-purpose collimators (system resolution: 9.0 mm

FWHM at 10 cm distance) for the gated SPET acquisition. Indeed, a high-resolution collimator

should be preferred from a theoretical point of view since resolution recovery is expected to affect

small volumes more than large. With a high resolution collimator, a 1.5 mm gain in resolution could

be anticipated, but at the expense of a 40 %-count reduction which would require a smoother filter,

hence loss of resolution, for acceptable image quality. The choice of general-purpose collimators

constitutes thus a compromise between resolution and noise, especially using an automatic body-

contouring to reduce the patient-collimator distance. A last limitation concerns the small number of

patients included. Despite this small sampling, highly significant results could be found so that this

should not considered a major drawback, all the more as our purpose was to compare the different

software currently available and not to identify the best of them.

29

Conclusion

In patients with a normal-sized heart, quantitative estimates of left ventricular functional data

computed from gated myocardial perfusion SPET by different commercially available software

show excellent correlation. Inter-software, or even inter-version variability for an individual

software is however present, especially regarding the volume values. Technical parameters such as

matrix size or filter cutoff frequency have little influence on LVEF measurements but a sharper

filter significantly modify the calculated volumes. Consequently, definition of specific normal

limits should be advised for each algorithm, and software permutation should be avoided for

follow-up studies in an individual patient.

In small-sized hearts on the other hand, ejection fraction value in the (very) high range, most

probably overestimated, is observed in a significant number of cases, so that the accuracy of gated

SPET measured LVEF and volumes in these patients might be questioned. However, increasing the

matrix size or the filter cutoff frequency results in significantly lower, probably more realistic

LVEF with all the tested software except the SU-Segami. Although further confirmation of our

results and validation of the correctness of the measurements is required, a smaller pixel size and/or

a sharper filter might be suggested for quantitative gated SPET in patients with a small-sized heart.

Acknowledgments

The authors whish to thank H. Ham, MD, PhD, for his friendly comments and criticisms in the

review of this manuscript. None of the authors has a financial interest in any software package. This

study did not receive any vendor support.

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volumes in patients with ischaemic cardiomyopathy : gated single-photon emission computed

tomography versus two-dimentional echocardiography. Eur J Nucl Med 2001;28:1610-15.

11. Lum DP, Coel MN. Comparison of automatic quantification software for the measurement

of ventricular volume and ejection fraction in gated myocardial perfusion SPECT. Nucl Med Comm

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determination of left ventricular volume and ejection fraction: experimental validation using MRI. J

Nucl Med 2000; 41:874-882.

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Tonami N. Gated SPET quantification of small hearts: mathematical simulation and clinical

application. Eur J Nucl Med 2000;27:1372-79.

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gated SPECT in simulated left ventricles. J Nucl Med 2001;42:454-459.

15. Manrique A, Hitzel a, Gardin I, Dacher JN, Vera P. Influence of Wiener filter in

determining the left ventricle volume and ejection fraction using thallium-201 gated SPECT. Nucl

Med Comm 2003; 24: 907-914

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and gender-specific differences in left ventricular cardiac function and volumes determined by

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18. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of

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31

2.3 Clinical applications.

Clinical usefulness of ultrashort-lived Iridium-191m from a carbon-based generator system for the evaluation of the left ventricular function.

P.R. FRANKEN, A. DOBBELEIR, H.R. HAM, C. BRIHAYE, M. GUILLAUME, F.F. KNAPP and J. VANDEVIVERE. Nuclear Medicine, Middelheim Hospital, Antwerp and St-Peters Hospital , Brussels, Belgium. Cycloton Research Center, University of Liege, Belgium and Nuclear Medicine Group, Oak Ridge National Laboratory Tennessee, USA. Journal of Nuclear Medicine, 1989; 30: 1025-1031. Abstract

Ultrashort-lived

191mIr (4.96 sec; 63-74 and 129 keV photons) is potentially advantageous for first-pass radionuclide

angiocardiography, offering the opportunity to perform repeat studies with very low absorbed radiation dose to the

patient. Left ventricular (LV) first-pass studies were performed in 72 patients with 191m

Ir from a new bedside 1.3 Ci (48.1

GBq) 191Os/

191mIr generator system using an activated carbon support that offers high

191mIr yields (15-18%) and

consistent low 191Os breakthrough (2-4 x 10

-4 %/bolus). Using a single crystal digital gamma camera, uncorrected end-

diastolic counts in the left ventricular representative cycle ranged from 10 up to 30 k counts. The reproducibility of

repeated LV ejection fraction (LVEF) determination at 2-min intervals in 50 patients was r = 0.97, mean diff. = 2.08 ± 1.55

EF units. Comparison between 191m

Ir (80-120 mCi; 2960-4400 MBq) and 99mTc (20-25 mCi; 750-925 MBq) LV count rates

indicates a 3 wk useful shelf life of this new generator system for cardiac studies. Iridium-191m determined LVEF

correlated closely with 99mTc determined LVEF in 32 patients (r = 0.96, mean diff. = 1.87 ± 1.23 EF units). Parametric

images for LV wall motion analysis were comparable with both isotopes. We conclude that rapid, repeat, and

reproducible high count rate first-pass left ventricular studies can be obtained with 191m

Ir from this new 191Os/

191mIr

generator system using a single crystal gamma camera.

32

Comparison between exercise myocardial perfusion and wall motion

using 201Tl and 191mIr simultaneously.

P.R. FRANKEN, A. DOBBELEIR, H.R. HAM, R. RANQUIN, S. LIEBER, F. VAN DEN BRANDEN, P. VAN DEN HEUVEL, C. BRIHAYE, M. GUILLAUME, F.F. KNAPP and J. VANDEVIVERE. Nuclear Medicine and Cardiology, Middelheim Hospital, Antwerp, Belgium Nuclear Medicine St-Peters Hospital , Brussels, Belgium. Cycloton Research Center, University of Liege, Belgium and Nuclear Medicine Group, Oak Ridge National Laboratory Tennessee, USA.

Nuclear Medicine Communications, 1991; 12: 473-484. Summary

By exploiting the ultrashort halflive

191mIr as tracer for left ventricular first-pass angiocardiography and

201Tl as myocardial

perfusion agent, direct comparison between myocardial perfusion and regional wall motion was obtained during the

same exercise stress test in patients with non-significant coronary artery disease, in patients with recent myocardial

infarction, and in patients six weeks after successful percutaneous transluminal coronary angioplasty (PTCA). A good

agreement between regional myocardial perfusion and regional wall motion was observed in patients with non-significant

coronary artery disease and in most patients with recent myocardial infarction. In contrast, discrepancies occurred at

maximal exercise in patients studied six weeks after successful PTCA: only 38% of the patients with no evidence of

restenosis and with a completely normal myocardial perfusion scintigraphy had a normal regional wall motion at maximal

exercise stress. According to these results, a normal uptake of 201Tl six weeks after PTCA would mean that the

circulation has been successfully re-established but without predicting the functional capacities of the myocardial cells

which remain altered at least six weeks after the revascularization procedure in about two-thirds of the patients. We

conclude that 191m

Ir in combination with 201Tl offers the opportunity of performing myocardial perfusion and wall motion

studies simultaneously both at rest and during exercise.

201Tl myocardial perfusion score

2 1 0

Patients with <5% likelihood of CAD (group I)

2 28 2 0

1 0 0 0

191Irm left ventricular RNA

Wall motion

Score

0 0 0 0

Patients with recent

myocardial infarction (group II)

2 30 9 1

1 6 20 4

191Irm left ventricular RNA

Wall motion Score

0 1 5 14

Patients with successful PTCA (group III)

2 30 0 0

1 13 1 0

Comparison between regional myocardial perfusion score and regional wall motion

score at maximal exercise stress in the

anterior projection.

191Irm left ventricular RNA

Wall motion Score

0 1 0 0

Myocardial perfusion score: 2=normal, 1=moderate hypoperfusion,0=severe hypoperfusion. Regional wall motion score: 2=normal, 1=hypokinesis, 0=akinesis or dyskinesis.