Improvement of Algorithm for Quantiﬁcationof Regional Myocardial Blood Flow Using
15O-Water with PET
Chietsugu Katoh, MD1,2; Koichi Morita, MD3; Tohru Shiga, MD3; Naoki Kubo, MD2; Kunihiro Nakada, MD3;
and Nagara Tamaki, MD3
1Department of Tracer Kinetics, Hokkaido University School of Medicine, Sapporo, Japan; 2Department of Health Science,
Hokkaido University School of Medicine, Sapporo, Japan; and 3Department of Nuclear Medicine, Hokkaido University School of
Medicine, Sapporo, Japan

15O-Water and dynamic PET allow noninvasive quantiﬁcation of

myocardial blood ﬂow (MBF). However, complicated image analyzing procedures are required, which may limit the practicalityof this approach. We have designed a new practical algorithm,
which allows stable, rapid, and automated quantiﬁcation ofregional MBF (rMBF) using 15O-water PET. We designed analgorithm for setting the 3-dimensional (3D) region of interest(ROI) of the whole myocardium semiautomatically. Subsequently, a uniform input function was calculated for each subject using a time–activity curve in the 3D whole myocardial ROI.
The uniform input function allows the mathematically simple
and robust algorithm to estimate rMBF. Methods: Thirty-six
volunteers were used in the static 15O-CO and dynamic 15Owater PET studies. To evaluate the reproducibility of the estimates, a repeated 15O-water scan was obtained under resting
condition. In addition, to evaluate the stability of the new algorithm in the hyperemic state, a 15O-water scan was obtainedwith adenosine triphosphate. This algorithm includes a procedure for positioning a 3D ROI of the whole myocardium from 3D
images and dividing it into 16 segments. Subsequently, theuniform input function was calculated using time–activity curvesin the whole myocardial ROI and in the LV ROI. The uniform
input function allowed this simple and robust algorithm to estimate the rMBF, perfusable tissue fraction (PTF), and spillover
fraction (Va) according to a single tissue compartment model.
These estimates were compared with those calculated using
the original method. A simulation study was performed to compare the effects of errors in PTF or Va on the MBF using the 2
methods. Results: The average operating time for positioning awhole myocardial ROI and 16 regional myocardial ROIs was ⬍5min. The new method yielded less deviation in rMBF (0.876 ⫾
0.177 mL/min/g, coefﬁcient of variation [CV] ⫽ 20.2%, n ⫽ 576)
than those with the traditional method (0.898 ⫾ 0.271 mL/min/g,
CV ⫽ 30.1%, n ⫽ 576) (P ⬍ 0.01). In the hyperemic state, the
new method yielded less deviation in rMBF (3.890 ⫾ 1.250
mL/min/g, CV ⫽ 32.1%) than those with the traditional method(3.962 ⫾ 1.762 mL/min/g, CV ⫽ 44.4%) (P ⬍ 0.05). This method
yielded signiﬁcantly higher reproducibility of rMBF (r ⫽ 0.806,

Received Jan. 23, 2004; revision accepted Jun. 3, 2004.
For correspondence or reprints contact: Chietsugu Katoh, MD, Departmentof Tracer Kinetics, Hokkaido University School of Medicine, N-15, W-7,
Kita-ku, Sapporo, Hokkaido, Japan 060-8638.
E-mail: chtgkato@med.hokudai.ac.jp

1908

n ⫽ 576) than the original method (r ⫽ 0.756, n ⫽ 576) (P ⬍0.05). Our new method yielded a better correlation in the repeated measurement values of rMBF and less variability among
the regions in the myocardium than with the original theory of
the 15O-water technique. The simulation study demonstrated
fewer effects of error in the PTF or Va on the MBF value with the
new method. Conclusion: We have developed a technique foran automated, simpliﬁed, and stable algorithm to quantify
rMBF. This software is considered to be practical for clinical use
in myocardial PET studies using 15O-water with a high reproducibility and a short processing time.
Key Words: myocardial blood ﬂow; 15O-water; PET
J Nucl Med 2004; 45:1908 –1916

P

revious animal and clinical studies with 15O-water and
PET have shown the feasibility of quantitative estimates ofregional myocardial blood ﬂow (rMBF) (1– 4). The use of
15O-water PET provides a noninvasive method for in vivo
quantiﬁcation of rMBF, perfusable tissue fraction (PTF),
and spillover fraction (Va). However, the original method
requires complicated image analyzing procedures, which
may limit the practicality of this approach. A crucial limitation of the original method is the manual positioning ofregional myocardial regions of interest (ROIs). It is a very
time-consuming procedure, especially when the operator isrequired to set the same myocardial ROIs on the paired restand stress studies. The manual approach remains operator
dependent. Moreover, in the original algorithm, the input
function is estimated using the time–activity curves in theregional myocardial ROI and in the left ventricular (LV)
ROI (5,6). When the input function is derived from theregional myocardial time–activity curve, it would not be
uniform for each regional myocardium in each subject (5).
We accessed the new algorithm using a uniform input
function, which may improve the stability and reproducibility of the estimates.
Several automatic algorithms are reported for setting
the myocardial ROI in myocardial SPECT studies (7–9);

THE JOURNAL OF NUCLEAR MEDICINE • Vol. 45 • No. 11 • November 2004

The algorithms permit short operating time as well as
operator-independent and robust results. For 15O-water
myocardial PET studies, we attempted the same approach. In this study, we developed a software algorithm,
which allows rapid, stable, and automated estimation of
the rMBF. We put particular emphasis on the performance of the software to achieve practical analysis times
for clinical deployment.
MATERIALS AND METHODSWe designed an algorithm for setting the 3-dimensional (3D)
ROI of the whole myocardium and dividing it into 16 segments
automatically, overcoming the difﬁculty of the process, which issigniﬁcantly time consuming if it is performed manually. Subsequently, a uniform input function was calculated for each subject
using time–activity curves in the whole myocardial ROI and in the
LV ROI. The uniform input function allows the mathematicallysimple and robust algorithm to estimate rMBF, PTF, and Va.
These estimates were compared with those calculated with theoriginal method.
Subjects
Thirty-six healthy volunteers (34 men, 2 women; mean age,
29.9 ⫾ 8.6 y) were studied in Hokkaido University Medical
Hospital. Data acquisitions were performed as a prospective study.
All subjects had normal laboratory tests and no symptoms or
history of cardiovascular disease. Heart rates and end-systolic andend-diastolic blood pressures were continuously monitored andrecorded. The nature, purpose, and potential risks of the study wereexplained to all subjects before they gave their voluntary consent
to participate. The study was approved by the ethical committee of
Hokkaido University Medical Hospital.
Production of 15O-CO and 15O-Water
For the production of 15O-labeled compounds, a low-energy
deuteron accelerator was used (CYPRIS-HM18; Sumitomo Heavy
Industries). 15O-Water was produced with a dialysis technique in acontinuously working water module. Sterility and pyrogen tests
were performed daily to verify the purity of the product. Gas
chromatographic analysis was performed to verify the purity of the
product before each study.
Image Acquisition
PET scans were obtained using an ECAT HR⫹ scanner (Siemens/CTI Corp.) equipped with 68Ge/68Ga retractable line sources
for transmission scans. All emissions and transmissions were acquired in the 2-dimensional mode and reconstructed using ﬁlteredbackprojection with a Hanning ﬁlter (cutoff, 0.4). The in-plane
resolution was 6.2-mm full width half maximum in a 128 ⫻ 128
matrix image. All data were corrected for dead time, decay, andmeasured photon attenuation.
The optimal imaging position was determined by a 1-minrectilinear scan. A 5-min transmission scan was then acquired
for the purpose of attenuation correction of all subsequentemission scans.
A blood-pool scan was obtained in the following manner. Eachsubject’s nostrils were closed and he or she inhaled 15O-CO(0.14% CO mixed with room air) for 1 min. After inhalation of the
tracer, a period of 3 min was allowed for the CO to combine withhemoglobin before a 5-min static scan was started. During the

5-min scan period, venous blood samples were drawn every 2 min,and the concentration of radioactivity in whole blood was measured with an automatic ␥-counter (ARC-400; ALOKA Inc.). The
inhaled dose in the CO examination was 2,000 MBq.
15O radioactivity returned to background levels 10 min after
the blood-pool scan. 15O-Water was infused into an antecubital
vein as a slow (2 min) infusion. The administrated dose of
15O-water was 500 MBq/min. A 20-frame dynamic PET scan,consisting of 6 ⫻ 5 s, 6 ⫻ 15 s, and 8 ⫻ 30 s frames, wasacquired for 6 min.
After allowing a further 10 min for decay, another dynamic scanusing 15O-water was acquired. Fifteen minutes later, adenosine
triphosphate (ATP) was infused for 7 min at 0.16 mg/kg/min. A
20-frame dynamic 15O-water PET scan was started 2 min after the
beginning of ATP infusion. Blood pressure and heart rate wererecorded before each scanning.
Data Processing
Original coincidence data were stored as sinograms and thennormalized, corrected for attenuation, and backprojected in a dedicated array processor to obtain the ﬁnal images. The analysis of
PET images was accomplished using an image analysis package(Dr. View; Asahi-Kasei) and software developed in our institute byuse of programming language C.
Processing Blood Volume Images. Functional blood volume
images were created by dividing the 15O-CO PET counts by theblood sample counts measured in the cross-calibrated well counter.
15O-Water washout images were calculated by subtracting theblood volume images from the sum of the 15O-water dynamic
images (10).
Calculation of Extravascular Density Images. The reconstructedtransmission data were normalized on a pixel-by-pixel basis to theactivity pixel counts in a ROI in the LV chamber of the transmission image and the density of blood. The extravascular images
were calculated by subtracting the vascular components from thenormalized transmission images using the blood volume images(10).
ROI Deﬁnition
Short axial blood volume images were generated semiautomatically, rotating horizontal and vertical long axial blood volume
images (Fig. 1). This process was performed to deﬁne the heartlong axis. This program generates short axial 15O-water dynamic
images and extravascular density images automatically, with thesame rotation angles used in the blood volume images.
The short axial blood volume images were used to deﬁne the
ROI in the left ventricle, showing 85% recovery of the true bloodtracer concentration (11) (Fig. 2). Early-phase short axial 15Owater images were calculated by summing ﬁrst the 2-min dynamic
images. A linear 6-parameter registration (12) was performed forregistration of the 15O-water images to the 15O-CO images. Shortaxial 15O-water washout images were generated calculating themean counts from 180- to 300-s frame images.
When the 15O-water washout images were superimposed on
extravascular images and analyzed with a semiautomated edgedetection routine, a whole myocardial ROI was determined. The
program is designed to extract a 3D region enclosing the whole
myocardial wall. The process is performed in the 3D matrices. At
ﬁrst, the apical and basal portion (valve plane) are pointed manually. The activity distribution of the midventricular and basal
portions is expressed in circular cylindric coordinates relative tothe heart long axis, assuming a shape of the heart that resembles a

IMPROVEMENT FOR QUANTIFICATION OF MBF • Katoh et al.

1909

FIGURE 1. Transaxial 15O-CO images
were rotated to generate short axial images in horizontal long axial and in verticalaxial slices. Rotation angles for each reorientation were set manually monitoring therotated images.

hemisphere in the apex and a cylindroid in the midventricular andbasal portions. For each possible ray in a radial direction from theheart long axis, the ﬁrst crossing of a given activity threshold (e.g.,60%) is detected and every point farther than the maximal possible
wall thickness (e.g., 2 cm) is excluded from calculation (13). Then,a 3 ⫻ 3 ⫻ 3 3D smoothing ﬁlter is applied to the edge of the ROI,
and a bullet-shaped ROI that encloses the whole myocardium isgenerated (Fig. 3A). Regional myocardial ROIs were positioned
automatically in 16 anatomic segments according to the rule in theAmerican Society of Echocardiography report (14) (Fig. 3B).
The LV time–activity curve was generated with the LV ROI anddynamic 15O-water data. The whole and regional myocardial tissuetime–activity curves were generated with these myocardial ROIs
and dynamic 15O-water data.
Original Method for Estimation of rMBF
A conventional theory to estimate rMBF using 15O-water is
described by the following equation for a single tissue compartment model (Fig. 4A):
dCt(t)/dt ⫽ F . Ca(t) ⫺ (F/p) . Ct(t),Eq. 1

where Ca(t) is the concentration of 15O-water in arterial whole
blood (cps/mL), Ct(t) is the concentration of 15O-water in myocardial tissue (cps/g), F is rMBF (mL/g/min), and p is the partition
coefﬁcient of water in the myocardium (0.91 mL/g), respectively.

The concentration of radioactivity in the LV ROI, LV(t), isexpressed as follows:
LV(t) ⫽ ␤ . Ca(t) ⫹ (1 ⫺ ␤) . ␳ . Ct(t),where ␳ is a myocardial tissue density (1.04 g/mL), and ␤ corresponds to a recovery coefﬁcient of the LV ROI concentration. The
value of ␤ is calculated using the 15O-CO blood volume scan as
follows (6): ␤ ⫽ LV ROI counts in the 15O-CO blood volume scan
(cps/mL)/sampled blood counts during the 15O-CO scan (cps/g)/
whole blood density (1.06 g/mL)
The measured tissue time–activity curve in a regional myocardial ROI, R(t) is described by:R(t) ⫽ PTF . Ct(t) ⫹ Va . Ca(t),Eq. 3

where PTF is the grams of perfusable tissue per 1 mL of myocardial ROI (g/mL) and Va is the arterial blood volume in the
myocardial ROI and spillover from the left ventricle into the
myocardial ROI (mL/mL).
The values of PTF, Va, and F are estimated by Equations 1–3
with a nonlinear least-squares regression analysis.
Modiﬁed Method for Estimation of rMBF
In the modiﬁed method in this study, we have developed asimpliﬁed algorithm (Fig. 4B). First, a uniform input function

FIGURE 2. Positioning of LV ROI on
short axial 15O-CO images. When a position in left ventricle is clicked on the image,the LV ROI is set automatically. Program
deﬁnes mean ROI count yields as 85% of
the true blood volume concentration.

1910

Eq. 2

THE JOURNAL OF NUCLEAR MEDICINE • Vol. 45 • No. 11 • November 2004

FIGURE 3. When 15O-water washout images are superimposed on extravascular
images and analyzed with semiautomatededge-detection routine, a whole myocardial ROI is determined. Program extracts
3D region enclosing the whole myocardial
wall; process is performed in the 3D matrices. Positioning of whole LV wall ROI on
15O-water washout images is evident. (A)Circles are placed semiautomatically inside and outside myocardial edges. (B)Program deﬁnes endocardial and epicardial borders of LV wall (B).

Cawhole(t) was derived using a whole myocardial ROI curve withthe original method. When the values of PTF, Va, and F for awhole myocardial ROI were determined by the non–least-squares
method, the input function curve Cawhole(t) was calculated by
Equations 1–3. Then, the following equations were used to determine the values of PTF, Va, and F for the regional myocardiumwith a nonlinear least-squares method:dCt(t)/dt ⫽ F . Ca whole (t) ⫺ (F/p) . Ct(t).
R(t) ⫽ PTF . Ct(t) ⫹ Va . Ca

whole

(t).

Eq. 4
Eq. 5

The following 4 sets of rMBF in each segment in the myocardial wall were estimated for each subject:rMBF1 was calculated using the ﬁrst 15O-water
dynamic data with a conventional method.
● Original rMBF2 was calculated using the second 15O-water
dynamic data with a conventional method.
● Modiﬁed rMBF1 was calculated using the ﬁrst 15O-water
dynamic data with a modiﬁed method.
● Modiﬁed rMBF2 was calculated using the second 15O-water
dynamic data with a modiﬁed method.
● OriginalIn addition, stability of rMBF in the hyperemic state was estimated for each subject:● Original rMBF was calculated using hyperemic 15O-water

dynamic data with a conventional method.
● Modiﬁed rMBF was calculated using hyperemic 15O-water

dynamic data with a modiﬁed method.
Estimates (MBF, PTF, and Va) in the apical, anterior, septal,
inferior, and lateral wall were calculated from apical, middle, andbasal regions as shown in Figure 5A. Our new program presents
rMBF on the polar map and on 15O-water images (Fig. 5B). Whenpaired rest and stress studies are performed, our program presents
rMBF at rest, rMBF in the hyperemic state, and coronary ﬂow
reserve in each region on the polar maps (Fig. 6).
Statistical Analysis
To evaluate the reproducibility of the results, Pearson correlation coefﬁcients were calculated and a Bland–Altman plot wasapplied for rMBF derived from a traditional method (OriginalrMBF1 vs. Original rMBF2) and from a modiﬁed method (Modiﬁed rMBF1 vs. Modiﬁed rMBF2). The differences in these cor-

FIGURE 4. Scheme of algorithm of original method (A) and modiﬁed method (B).
(A) R(t) and LV(t) correspond to measured
time–activity curves in regional myocardial
ROI and in left ventricle, respectively. Input
function Ca(t), tissue time–activity curveCt(t), and rMBF are derived from R(t) andLV(t). (B) W(t) corresponds to measured
time–activity curve in whole myocardial
ROI. Uniform input function Cawhole(t) is derived from W(t) and LV(t). Then, each rMBF
is estimated using a known input function
Cawhole(t) and R(t).

IMPROVEMENT FOR QUANTIFICATION OF MBF • Katoh et al.

1911

FIGURE 5. Program automatically divides whole myocardial ROI into 16 anatomic segments according to the rule in
the American Society of Echocardiographyreport (14). Quantiﬁed rMBF values arepresented automatically on polar map (A)and on 15O-water images (B).

relation coefﬁcients were compared using Fisher z-transformation.
To evaluate the regional variability of the estimates (MBF, PTF,
and Va), paired Student t tests were performed to examine thedifference between the original and modiﬁed methods. The ␹2 test
was performed to evaluate the differences in the variation of eachestimate. All data are presented as mean ⫾ SD. P ⬍ 0.05 is
considered to be statistically signiﬁcant in assessing the differences of correlation coefﬁcients and differences of variability.
Simulation Study
A simulation study was performed to assess the effects of errors
in the measurement of PTF or Va on the calculated value of MBF
in the original and modiﬁed methods.
The mean myocardial and LV time–activity curves were generated using data of the 36 subjects. The percentage error in MBF

was calculated when the percentage error of the PTF or Va waschanged from ⫺10% to ⫹10%.
RESULTSThe variables of systolic pressure, diastolic pressure, andheart rate in the ﬁrst and second 15O-water dynamic scans
were 105.3 ⫾ 8.4 and 105.9 ⫾ 9.1 mm Hg, 54.7 ⫾ 7.7 and53.4 ⫾ 8.8 mm Hg, and 60.3 ⫾ 8.5 and 60.8 ⫾ 7.3
beats/min, respectively. No signiﬁcant hemodynamicchange was observed during the 2 dynamic acquisitions. In
the hyperemic state, the variables of systolic pressure, diastolic pressure, and heart rate were 103.6 ⫾ 9.5 mm Hg,
52.1 ⫾ 8.7 mm Hg, and 87.2 ⫾ 8.4 beats/min.

FIGURE 6. When paired rest and stressstudies are performed, the new program
generates automatically polar maps of rest
MBF, stress MBF, and coronary ﬂow reserve.

1912

THE JOURNAL OF NUCLEAR MEDICINE • Vol. 45 • No. 11 • November 2004

TABLE 1
Comparison of rMBF, PTF, and Va in Resting State Between Original and Modiﬁed Methods
rMBF (mL/min/g)
RegionAmong subjects
ApicalAnterior
SeptalInferior
Lateral
Total†
Within a subject
Total‡PTF (g/mL)

Va (mL/mL)

Original

ModiﬁedOriginal

ModiﬁedOriginal

Modiﬁed

1.011 ⫾ 0.443
1.071 ⫾ 0.298
0.845 ⫾ 0.282
0.801 ⫾ 0.181
0.946 ⫾ 0.224
0.898 ⫾ 0.271

0.960 ⫾ 0.310*
1.018 ⫾ 0.216*
0.843 ⫾ 0.218
0.808 ⫾ 0.159
0.928 ⫾ 0.187*
0.876 ⫾ 0.177*

0.581 ⫾ 0.101
0.538 ⫾ 0.084
0.532 ⫾ 0.133
0.641 ⫾ 0.138
0.576 ⫾ 0.104
0.588 ⫾ 0.107

0.577 ⫾ 0.102*
0.533 ⫾ 0.085*
0.527 ⫾ 0.138
0.642 ⫾ 0.140
0.574 ⫾ 0.105*
0.584 ⫾ 0.110*

0.267 ⫾ 0.117
0.329 ⫾ 0.084
0.473 ⫾ 0.134
0.307 ⫾ 0.125
0.271 ⫾ 0.080
0.322 ⫾ 0.134

0.270 ⫾ 0.118*
0.333 ⫾ 0.084*
0.481 ⫾ 0.136
0.307 ⫾ 0.126
0.273 ⫾ 0.080*
0.325 ⫾ 0.136*

0.906 ⫾ 0.295

0.886 ⫾ 0.193*

0.590 ⫾ 0.149

0.551 ⫾ 0.101*

0.337 ⫾ 0.144

0.352 ⫾ 0.116**P ⬍ 0.05.
†n ⫽ 576.
‡n ⫽ 36.

The average analysis time to deﬁne a whole myocardial
ROI and 16 regional myocardial ROIs was ⬍5 min. With
the conventional manual ROI setting program, it took ⬎30
min. The use of the algorithm for deﬁning ROIs resulted in
the decrease of the analysis time. After positioning a whole
myocardial ROI and 16 regional myocardial ROIs, the procedure to estimate these rMBFs took only a few seconds
with both the original and our modiﬁed methods.
Table 1 shows a comparison of the variables of rMBF,
PTF, and Va at rest in the various regions of the myocardium among subjects and within a subject. The modiﬁed
method yielded less deviation and a lower rMBF than thosewith the traditional method. The apical, anterior, and lateralregions showed a signiﬁcant decrease in rMBF. The modiﬁed method yielded a lower PTF than those with the original method. The apical, anterior, and lateral regions showeda signiﬁcant decrease in PTF. The simpliﬁed method
yielded a higher Va than those with the traditional method.
The apical, anterior, and lateral regions yielded a signiﬁcant
increase in Va. Signiﬁcant differences and less deviation ofthese estimates in the resting condition were presented
within a subject between the original and modiﬁed methods.
Table 2 presents a comparison of the variables of themeasurement of rMBF in the hyperemic state among subjects. The new method yielded less deviation in rMBF
(3.890 ⫾ 1.250 mL/min/g, coefﬁcient of variation [CV] ⫽32.1%) than those with the traditional method (3.962 ⫾
1.762 mL/min/g, CV ⫽ 44.4%) (P ⬍ 0.05) in the hyperemic
condition. Signiﬁcant differences and less deviation of theseestimates in the hyperemic condition were presented withina subject between the original and modiﬁed methods.
Figure 7 shows plots of the correlations between rMBF
calculated from the ﬁrst and second 15O-water dynamic
scans using the original method and the modiﬁed algorithm.
The modiﬁed method yielded signiﬁcantly higher reproducibility than the original method (P ⬍ 0.05). The Bland–
Altman test shows better reproducibility with the modiﬁed
method.

Figure 8 shows the results of the simulation studies,
which demonstrated the error of the PTF or the Va propagated to the measured value of MBF with a simpliﬁed
method or a modiﬁed method. Fewer errors in the estimated
MBF were induced by errors in the PTF or the Va with a
modiﬁed method. In the original algorithm, an overestimation of 10% in the PTF caused an overestimation of approximately 28% in MBF, whereas, in the modiﬁed algorithm,
the overestimation was suppressed 20% in MBF. In theoriginal algorithm, an underestimation of 10% in the Va
caused an overestimation of approximately 26% in MBF,
whereas in the modiﬁed algorithm, the overestimation was
suppressed 20% in MBF.
DISCUSSION

In this study, we designed a software algorithm for setting
the 3D ROI of the whole myocardium and dividing it into
16 regions automatically with a clinically acceptable processing time. At the same time, the software was equipped

TABLE 2Comparison of rMBF (mL/min/g) in Hyperemic State
Between Original and Modiﬁed Methods
RegionAmong subjects
ApicalAnterior
SeptalInferior
Lateral
Total†
Within a subject
Total‡

Original

Modiﬁed4.234 ⫾ 1.834
4.160 ⫾ 1.799
3.785 ⫾ 1.489
3.613 ⫾ 1.303
4.072 ⫾ 1.622
3.962 ⫾ 1.762

4.017 ⫾ 1.411*
4.059 ⫾ 1.328*
3.674 ⫾ 1.236*
3.569 ⫾ 1.159*
3.953 ⫾ 1.174*
3.890 ⫾ 1.250*

3.985 ⫾ 1.521

3.801 ⫾ 1.308**P ⬍ 0.05.
†n ⫽ 576.
‡n ⫽ 36.

IMPROVEMENT FOR QUANTIFICATION OF MBF • Katoh et al.

1913

FIGURE 7. Reproducibility of rMBF withoriginal method (A) and modiﬁed algorithm(B) in 576 ROIs of 36 subjects. (Top) Regression lines and intervals of SEEs are
drawn. Correlation was signiﬁcantly higher
when calculated with modiﬁed methodthan with original method (P ⬍ 0.05). (Bottom) Bland–Altman plots.

with a simpliﬁed algorithm to calculate MBF using a uniform input function for each region for stable estimation.
We designed an algorithm for setting the 3D ROI of thewhole myocardium and dividing it into 16 segments automatically, overcoming the difﬁculty of the process, which issigniﬁcantly time consuming if it is performed manually. At
the present time, our ROI setting software requires manual
handling of a few processes, but it enables ROI deﬁnition
almost independently of the operator and allows stable
rMBF quantiﬁcation. Various approaches are used for automatic 3D delineation of the LV myocardium in myocardial SPECT studies (15–17). However, it might be difﬁcult

FIGURE 8. Simulations demonstrate the effect of error in PTF
or Va in calculated MBF values. In estimated MBF, fewer errors
were induced by errors in PTF or Va with modiﬁed method thanwith original method.

1914

to apply these algorithms for 15O-water PET data, because
the PET studies performed with 15O-labeled tracers yieldless delineated and less homogeneous images than SPECT
studies. We designed a simple method for positioning a 3D
ROI, which covers the whole LV myocardium. For estimating rMBF with 15O-water PET, is not necessary to set a tight
ROI tracing the contours of the myocardium (18).
To improve the reproducibility and stability of quantitative measurements of the rMBF, we applied a uniform input
function for each region. Our modiﬁed method yielded abetter correlation in the repeated measurement values ofrMBF and less variability among the regions in the myocardium than with a conventional theory of the 15O-watertechnique. Also, in the hyperemic state, the new method
yielded less deviation in rMBF than those with the original
method. A simulation study also showed that the modiﬁed
algorithm yielded fewer errors in the estimated MBF.
The main reason for the better reproducibility and stability in the modiﬁed method is explicable. In the original
method, a nonlinear least-squares method is used to determine 3 unknown values (PTF, Va, and MBF) and 2 unknown curves (Ca(t), Ct(t)) by ﬁtting 2 curves (PTF Ct(t) ⫹VaCa(t) and ␤Ca(t) ⫹ (1 ⫺ ␤)␳Ct(t)) to the 2 known curves(R(t) and LV(t)), respectively. The value (1 ⫺ ␤) is thecontribution ratio of the whole myocardial radioactivity (6);
it is an anatomic parameter for a whole LV myocardium.
The equation LV(t) ⫽ ␤Ca(t) ⫹ (1 ⫺ ␤)␳Ct(t) should be

THE JOURNAL OF NUCLEAR MEDICINE • Vol. 45 • No. 11 • November 2004

applied to the whole myocardial data. When the value (1 ⫺␤) is applied to estimate regional myocardial data, thecontribution ratio must be overestimated. Then the original
method might overestimate rMBF and underestimate theregional spillover fraction (Va).
Our present study demonstrated that the original method
yielded signiﬁcantly higher rMBF and a lower Va than themodiﬁed method, especially in the apical, anterior, andlateral regions. In these regions, Va is overestimated in theconventional method.
To improve the stability of quantitative measurement of
rMBF, we designed a new modiﬁed algorithm. In the modiﬁed method, using the known curve Cawhole(t), the parameters (PTF, Va, and MBF) are derived by ﬁtting only 1
curve (PTF Ct(t) ⫹ Va Cawhole(t)) to the known curve R(t).
This ﬁtting is mathematically simpliﬁed and more stable toestimate the parameters than that in the original algorithm.
The simulation study indicated that the modiﬁed method
showed fewer effects of error in the PTF and the Va on the
MBF compared with the original method.
Theoretically, whole myocardial ROI data are recommended to derive an input function (11); it was difﬁcult todetermine a whole myocardial ROI because the procedurerequires a 3D ROI setting technique. In this study, we havedeveloped a new program for the procedure that overcame
the difﬁculty of positioning the whole myocardial ROI. We
developed a new algorithm to improve the stability of theestimates calculated from 15O-water PET; however, it is alsoessential to improve the reconstruction method for achieving better image quality using 15O-water with PET (19).
The principal difﬁculty in validating the new approach is
the lack of a gold standard to determine the success of thealgorithm. Therefore, we relied primarily on the improvement of reproducibility and the decrease in the variability of
MBF among the regions in the myocardium. We conﬁrmed
these results and appropriate values of estimates (20).
In this study, we performed 15O-CO scanning once in the
protocol, which was not repeated before each 15O-water
PET scan. The 15O-CO image is used only for positioning
the LV ROI in our program, and each 15O-water PET image
is transferred appropriately with the registration algorithm.
It is ideal to acquire an 15O-CO image before every 15Owater scan for precise ROI setting in the left ventricle.
However, the algorithm to derive MBF in this study isequipped for estimating appropriate spillover in each myocardium (5); the estimated MBF with the present program
might be robust enough to detect the subtle difference in thesize or positioning of the LV ROI.
The limitation of this study is that we could not assess the
reproducibility of measured rMBF in the hyperemic state.
However, it was impossible to perform repeated 15O-water
PET studies with ATP because of ethical concerns. In thepresent study, we did not apply our new program to thepatients with ischemic heart disease. Further clinical validations are needed.

At present, our program requires a 15O-CO scan for
estimation of MBF because this program is designed not
only for calculating MBF but also for estimating extravascular tissue density and the PTF index in the myocardium(11). These parameters require 15O-CO images. Recently,
however, a new technique has been proposed for calculating
MBF images directly from dynamic 15O-water scans (21–23). When performing a PET study only for estimating
MBF, our program should be equipped with the algorithm
free from 15O-CO scan.
CONCLUSION

We have developed a practical and automatic algorithm
to quantify rMBF using 15O-water with PET. This method
includes a modiﬁed method, which is mathematically simpliﬁed and more stable than that in the original algorithm.
This software yields desirable performance to achieve highreproducibility and practical computational times for clinical use in myocardial PET studies with 15O-water.
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THE JOURNAL OF NUCLEAR MEDICINE • Vol. 45 • No. 11 • November 2004