Download Perfusion characteristics of late radiation injury of parotid glands

Eur Radiol (2009) 19: 94–102
DOI 10.1007/s00330-008-1104-9
HEAD AN D NECK
Chun-Jung Juan
Cheng-Yu Chen
Yee-Min Jen
Hua-Shan Liu
Yi-Jui Liu
Chun-Jen Hsueh
Chao-Ying Wang
Yu-Ching Chou
Yao-Te Chai
Guo-Shu Huang
Hsiao-Wen Chung
Perfusion characteristics of late radiation
injury of parotid glands: quantitative evaluation
with dynamic contrast-enhanced MRI
Received: 11 December 2007
Revised: 28 May 2008
Accepted: 5 June 2008
Published online: 26 July 2008
# European Society of Radiology 2008
Y.-J. Liu
Department of Automatic Control
Engineering, Feng Chia University,
Taichung, Taiwan
C.-J. Juan . C.-Y. Chen . H.-S. Liu .
C.-J. Hsueh . C.-Y. Wang .
G.-S. Huang . H.-W. Chung
Department of Radiology, Tri-Service
General Hospital and National Defense
Medical Center,
Taipei, Taiwan, Republic of China
Y.-M. Jen
Department of Radiation Oncology,
Tri-Service General Hospital and
National Defense Medical Center,
Taipei, Taiwan, Republic of China
H.-S. Liu . C.-Y. Wang .
H.-W. Chung (*)
Department of Electrical Engineering,
National Taiwan University,
No. 1, Sec. 4, Roosevelt Road,
Taipei, Taiwan, 10764,
Republic of China
e-mail: [email protected]
Tel.: +886-2-33663628
Y.-C. Chou
School of Public Health,
National Defense Medical Center,
Taipei, Taiwan
Y.-T. Chai
Section of General Surgery,
Department of Surgery, Hualien Armed
Forces General Hospital,
Hualien, Taiwan
Abstract We aimed to quantitatively
investigate the alteration of parotid
perfusion after irradiation using dynamic contrast-enhanced magnetic
resonance imaging (DCE-MRI) based
on a two-compartment tracer kinetic
model. This study enrolled 19 patients
(53.2±14.9 years) treated by head and
neck radiotherapy and 19 age-relevant
and sex-matched subjects as a control
group. Perfusion parameters (Kel, k21
and A) of parotid glands were analyzed based on the Brix model from
T1-weighted DCE-MRI. Suitability of
Introduction
Parotid glands are highly radiosensitive. Occurring within
24 h after irradiation, early radiation injuries of the parotid
glands are known as acute radiation parotitis, manifesting
fever, dry mouth, pain, swelling and tenderness clinically
[1]. Late radiation injuries of the parotid glands usually
the Brix model was evaluated via
Monte Carlo simulation for the
goodness-of-fit. Analysis of nonlinear
goodness-of-fit showed that the Brix
model is appropriate in evaluating the
parotid perfusion (R2 =0.938±0.050).
The irradiated parotid glands showed
significantly lower Kel (P<0.0005)
and k21(P<0.05) and consequently
significantly higher value of peak
enhancement (P<0.0005) and time-topeak (P<0.0005) compared with nonirradiated ones, suggestive of gradual
and prolonged accumulation and
delayed wash-out of contrast agent
due to increased extracellular extravascular space and decreased vascular
permeability in the irradiated glands.
Linear regression analysis showed
dose-dependent perfusion changes of
the irradiated parotid glands. We
conclude that quantitative DCE-MRI
is a potential tool in investigating
parotid gland perfusion changes after
radiotherapy.
Keywords Radiation injury .
Parotid glands . Magnetic resonance
imaging . Perfusion
present as transient or permanent xerostomia, which further
increases the risk for developing dental caries, compromises the oral mucosal integrity, and results in oral pain,
loss of taste, difficulty with swallowing and chewing, sleep
disorders and worse quality of life [2]. Sialometric studies
disclose reduction of salivary flow in the acute setting [3]
as well as in the late stage [3, 4] after head and neck
95
radiation. On histopathological studies, acute radiation
injuries present as swelling, degeneration and necrosis of
acinar cells [5], while late radiation injuries further
demonstrate loss of acinar cells, dilatation of intercalated
ducts, fibrosis and atrophy of parotid lobules [4, 5]. The
functional impairment and morphological damage of the
parotid glands can persist as long as 24 months after
the irradiation [3]. Furthermore, the severity of acinar loss
has been positively correlated with the radiation dose in the
late stage. The parotid glands recover well without residual
damage after low-dose irradiation (2.5 Gy). A radiation
dose of 7.5 Gy [5] and 20 Gy [6] leads to slight loss and
marked reduction (50% in number) of acinar cells,
respectively. When the radiation dose reaches as high as
45 Gy, only 10% of acini survive [6, 7].
Although the severity of xerostomia can be assessed by the
Radiation Therapy Oncology Group (RTOG) criteria [8] or
by measuring the salivary flow, for example using the Saxon’s
test [9], these clinical observations do not depict any
morphological or physiological change of the irradiated
parotid glands. On the other hand, histopathological study
has a major disadvantage in its invasiveness, which makes
it an impractical tool to quantify the radiation injuries
of human parotid glands. Under this situation, imaging
studies unavoidably play an important role for in vivo and
noninvasive investigation of the morphological and physiological changes of the irradiated parotid glands. Contrastenhanced computed tomography (CT) and MR studies have
been used worldwide for diagnosing and monitoring the
response of treatment for head and neck cancer by providing
satisfactory morphological information of the head and neck
structures. The irradiated parotid glands appear swollen on
both CT and MR and show high T2 signal on MR images at
an early stage and later become smaller and exhibit low T1
and T2 signal [10]. Following intravenous administration of
contrast medium, the irradiated parotid glands often show
strong enhancement on CT and MR images [11–13] before
visually perceivable volume reduction [13, 14]. These
qualitative contrast-enhanced imaging features are suggestive
of alterations in parotid perfusion characteristics after radiotherapy. In other words, it seems plausible that the parameters
of perfusion characteristics could be used as quantitative
indices of radiation-induced injury of parotid glands.
Dynamic contrast-enhanced magnetic resonance imaging
(DCE-MRI) has the capability to exploit tissue perfusion
properties [15–18] via quantitative analysis using appropriate tracer kinetics models [19]. To the best of our
knowledge, the perfusion characteristics of the irradiated
parotid glands using DCE-MRI have not been documented.
Therefore, in this preliminary study we applied DCE-MRI to
investigate the perfusion changes of the parotid glands
following irradiation. Specifically, we hypothesized that the
perfusion alterations due to irradiation are dosage dependent
and that the physiological mechanism causing the difference
in perfusion alterations could be explored using quantitative
analysis. By applying DCE-MRI, the physiological changes
of the irradiated parotid glands can be further assessed
without additional injection of contrast agent compared to
the conventional contrast-enhanced MRI.
Materials and methods
Subjects
From January 2006 to April 2006, 19 subjects who had
undergone radiotherapy (radiotherapy group) and 19 agerelevant and sex-matched subjects who had not experienced
radiotherapy (control group) received perfusion-weighted
head and neck MR imaging with contrast administration in
our hospital. These subjects all gave written informed
consent before the MR examinations. The clinical indications for contrast-enhanced MR investigation in these
patients included clinically suspicious malignancy and
post-treatment follow-up of previously known head and
neck malignancy. The radiotherapy group consisted of 16
men and 3 women (aged 53.2±14.9 years) who had received
radiation therapy for head and neck cancer before the MR
study. The radiation dose delivered to the head and neck
tumors was 68.5±4.6 Gy using intensity-modulated radiation therapy (IMRT) in 14 cases and 3D conformal
radiotherapy (3DCRT) in 2 cases. The mean total cumulative
dose to the parotid glands was 36.0±15.9 Gy. The details of
clinical data, including the gender, age, primary tumor site,
the time interval after radiotherapy (called RT-to-MR interval
in this paper), initial and current grade of dry mouth, and
radiation dose to either parotid gland of the radiotherapy
group are listed in Table 1. The control group was comprised
of 16 men and 3 women (aged 49.4±16.7 years) who had not
received radiation therapy, including 7 cases with negative
results and 12 cases with fresh head and neck malignancy in
areas other than the parotid glands (nasopharyngeal carcinoma in 4, buccal cancer in 3, oral tongue cancer in 3,
palatine tonsil cancer in 1 and thyroid cancer in 1). Because
of the use of parotid-sparing radiotherapy techniques (IMRT
and 3DCRT), the parotid glands on either side received
different radiation doses according to the specific location of
the primary head and neck malignancy. Hence, the glands in
each subject were treated as two different glands in our study.
Clinical assessment of dry mouth
Clinically, the severity of dry mouth was assessed and
classified by a radiation oncologist (Y.M.J.) based on the
RTOG scoring criteria [8]: Grade 0 represented no symptom
of dry mouth; grade 1 described slight dryness of mouth with
good response on stimulation; grade 2 portrayed moderate
dryness with poor response on stimulation; grade 3 stood for
complete dryness with no response on stimulation; grade 4
characterized necrosis of the salivary glands. The total of 19
patients (38 glands) was further classified as low-grade dry
96
Table 1 Clinical data of the radiotherapy group
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Gender
M
M
M
M
M
F
M
M
M
F
M
M
M
M
M
M
M
F
M
Age (years)
54
53
74
59
45
50
34
27
56
53
64
53
74
62
57
24
34
71
68
Tumor site
NP
OP
HP
HP
NP
NP
Oral
NP
Sinus
NP
Oral
HP
NP
OP
NP
NP
NP
NP
NP
RT-to-MR interval (month)
7
13
10
2
36
37
2
23
4
3
24
2
16
26
20
43
13
17
25
Dry mouth grade (RTOG criteria)
RT dosage (Gy)
Initial
Current
Right
Left
2
2
3
2
1
1
2
2
1
2
1
2
2
2
2
2
2
2
2
2
1
3
2
0
1
2
0
1
1
1
1
1
2
2
0
1
2
2
39.4
41.7
44.3
46.0
21.4
24.3
37.9
30.0
0.7
61.6
45.6
39.1
65.1
31.0
54.2
53.8
32.1
40.8
36.5
40.2
40.7
38.2
42.7
22.4
20.5
43.8
24.6
1.5
51.9
48.1
35.0
39.5
71.3
48.3
30.5
29.2
37.6
37.3
Gender (M: male; F: female), tumor site (NP: nasopharynx; OP: oropharynx; HP: hypopharynx). Eight of 19 patients showed downgrading
of dry mouth at the time of MR study, while 11 remained unchanged
mouth subgroup (grade 0 and grade 1) and high-grade dry
mouth subgroup (grade 2 to grade 4).
Dynamic MR image acquisition
Axial dynamic contrast-enhanced perfusion-weighted MR
images were obtained on a 1.5-T MR system (ECLIPSE,
Philips Medical System, Cleveland, OH) using a multi-slice
2D T1-weighted fast spin-echo sequence with a field-ofview of 230 mm, matrix of 256×256, slice thickness of
5 mm, slice number of 6 and TR/TE of 372/12. A total of 20
dynamic phases at an interval of 10.4 s were acquired with a
total data acquisition time of 208 s. A 20-G catheter was
inserted into the antecubital vein before MRI. GadoliniumDTPA was manually injected as a bolus over a period of 3 s
with the standard dose of 0.1 mmol/kg of patient weight. The
RT-to-MR interval between the completion of radiotherapy
and DCE-MRI study was 17±12.7 months.
using Matlab (MathWorks, Natick, MA). Regions of
interest (ROIs) were manually drawn on the parotid
gland. All imaging processing, ROI drawing and data
analysis were performed by C.J.J., who is a neuroradiologist with 6 years’ experience in head and neck imaging
interpretation and has obtained a Ph.D. in electrical
engineering. The signal-time data (SIt) were first normalized to be converted to concentration-time data (Ct) based
on the following relationship [16, 17]:
Ct /
The MR image data were digitally transferred to a personal
computer from the MR operating console and then
processed by software developed in-house (by C.J.J.)
(1)
where SI0 is the baseline signal intensity of the parotid
glands before contrast administration. The concentration
time data were fitted, by means of a non-linear least square
curve fitting algorithm, to the two-compartment Brix
pharmacokinetic model [19] as shown in Eq. (2).
Ct ¼
Data analysis
SIt SI0
SI0
A
eKelt ek21t
k21 Kel
(2)
where A is an amplitude scaling constant for the concentration-time curve of the plasma, which is determined by
factors including the injected dose of contrast agent, the
97
blood volume of the parotid gland and so forth [16, 17]. Kel
is an elimination transfer rate constant that describes the
excretion of contrast agent through the kidneys, and k21 is a
transfer rate constant that describes the return of contrast
agent from the extracellular extravascular space (EES) of
parotid tissue to the plasma compartment. Goodness-of-fit
was assessed by R2 values used in nonlinear curve fitting
[20]. Following curve fitting, the analytical concentrationtime relationship was used to derive three indices: The peak
enhancement (Cmax) was defined as the maximal value of
contrast agent concentration, the time-to-peak (Tmax) was
defined as the time duration to reach Cmax, and the slope of
the wash-in phase was defined as Cmax/Tmax.
Error assessment
Possible error due to the finite temporal resolution of 10.4 s
in the estimation of perfusion parameters was assessed using
Monte Carlo simulation at different levels of additive noise.
For this purpose, an analytical Gd-DTPA concentration-time
curve obtained from one healthy subject was first taken as the
true reference curve, with the values of the perfusion
parameters recorded. The reference curve was then sampled
at the interval of 10.4 s. Subsequently, Gaussian white noise
was added to the concentration-time data at ten different
signal-to-noise ratio (SNR) levels ranging from 5 to 50, with
each SNR level containing 1,000 sets of random noise.
Nonlinear least-square-error fitting to the Brix model was
performed on these simulated data to derive three perfusion
parameters (A, k21, Kel), with errors expressed as percentage
deviation from the true values.
enhancement and time-to-peak. Fisher exact test was used to
test the dependence between the two categorical variables
(radiotherapy or not vs. gender distributions; perfusion
parameters vs. radiation doses between two glands in the
same patient). For these analyses, a P value<0.05 was
considered as statistically significant.
Results
Good curve fitting of the concentration-time data was
achieved in all subjects. The R2 values were 0.951±0.053
in the radiotherapy group and 0.925±0.044 in the control
group, respectively, suggesting that the use of the Brix
model is appropriate in curve-fitting the parotid perfusion
data. For the image acquisition protocol used in our study,
SNR of the concentration enhancement time curve was at
the level of about 30 in all subjects, corresponding to
imprecision of −0.93±7.84%, −1.25±9.44% and 5.14±
29.16% for A, Kel and k21, respectively. Among all
perfusion parameters, k21 was most susceptible to noise
and carried the largest error range.
The radiotherapy group did not differ from the control
group regarding the age (P=0.25) or gender (P=1). The
binary logistic regression analysis demonstrated a statistically significant relationship between the radiation dose
and the peak enhancement (P=0.009; odds ratio=7.84), the
amplitude scaling constant A (P=0.005; odds ratio=7.84)
and the kel (P=0.002; odds ratio=30), within the same
subjects.
Correlation between the perfusion parameters
and radiation dose (and RT-MR interval)
Statistical analysis
Linear regression analysis was performed to evaluate the
correlation between the changes of perfusion parameters
and radiation doses, and the correlation between the
changes of perfusion parameters and the RT-to-MR
interval. Difference in perfusion parameters among the
dry mouth subgroups, as well as other group comparisons,
was examined using Student’s t test. Since multiple
hypotheses were tested simultaneously regarding changes
in the perfusion parameters derived from DCE-MRI,
Bonferroni correction was used when assessing possible
statistical significance, i.e., a P value < 0.05/3=0.017 was
considered as statistically significant.
Binary logistic regression analysis was executed to
investigate the dependence of the perfusion changes on the
radiation doses between the two parotid glands in the same
patient. The parotid gland was coded as 1 for the higher
radiation dose and 0 for lower radiation dose. The perfusion
changes were coded as 1 for lower k21 and Kel and higher
value for peak enhancement and time-to-peak, and were
coded as 0 for higher k21 and Kel and lower value for peak
The peak enhanced T1-weighted images and percent signal
enhancement-time curves of the irradiated and controlled
parotid glands were demonstrated (Fig. 1). The correlations
between the radiation doses and changes in perfusion
parameters and between the RT-to-MR interval after radiation and changes in perfusion parameters assessed by linear
regression are shown in Table 2. The scatter plots of
perfusion parameters (peak enhancement, time-to-peak and
Kel) versus radiation dose were illustrated (Fig. 2). While the
radiation doses positively correlated with the peak enhancement (P=0.009; R=0.418), time-to-peak (P=0.0017; R=
0.491) and negatively correlated with the Kel (P=0.0008; R=
0.521) significantly, the RT-to-MR interval did not correlate
with the perfusion parameters significantly except marginally for the k21 (P=0.011; R=0.407).
Effect of dry mouth on the perfusion parameters
With regard to the severity of dry mouth at the time of MR
study, the low-grade dry mouth subgroup consisted of 11
98
Fig. 1 Peak-enhanced T1weighted images of irradiated
(a) and control (b) parotid
glands and their corresponding
signal enhancement-time curves
(c). Note the prominent enhancement in (a). Each of the
signal enhancement-time curves
represents the average value
within one encircled region-ofinterest from a single subject,
rather than the group average
patients (3 cases in grade 0; 8 cases in grade 1), while the
high-grade dry mouth subgroup consisted of 8 patients
(7 cases in grade 2; 1 case in grade 3). The low-grade
subgroup did not differ from the high-grade subgroup in Kel
(0.0011±0.0010 s−1 vs. 0.0009±0.0009 s−1; P=0.54), k21
(0.082±0.035 s−1 vs. 0.062±0.035 s−1; P=0.09), peak
enhancement (80.0±35.1% vs. 62.7±33.2%; P=0.13),
time-to-peak (77.3±40.7 s vs. 101.3±56.2 s; P=0.16) and
the amplitude scaling constant A (0.072±0.058 vs. 0.038±
0.029; P=0.02), but had statistically significantly higher
value for the wash-in slope (1.08±0.34%/s vs. 0.70±0.40%/s;
P=0.005). When comparing with the control group, the
Table 2 Correlation between the radiation doses (and RT-to-MR interval) and perfusion parameters using linear correlation regression
(y=y0+ax)
Radiation dose (Gy)
RT-to-MR interval (months)
PE
TTP
k21
Kel
PE
TTP
k21
Kel
Correlation coefficient (R)
y0
a
P value
0.418
0.491
0.165
0.521
0.298
0.012
0.407
0.136
34.23
24.54
0.090
0.0022
86.67
88.15
0.0092
0.0008
1.01
1.65
−0.0904
−3.3×10−5
−0.82
−0.046
0.0004
9.9×10−6
0.0090*
0.0017*
0.32
0.0008*
0.069
0.943
0.011*
0.41
PE (peak enhancement); TTP (time-to-peak); * denotes a significant difference between the paired subgroups
99
low-grade subgroup had significantly lower Kel (P<0.005),
insignificant changes in the amplitude scaling constant A
(P<0.05) and consequently higher values for peak enhancement (P<0.005) with insignificant difference in time
to peak (P<0.05). Likewise, the high-grade subgroup had
significantly lower Kel (P<0.005), but not k21 (P<0.05),
and consequently higher values for time to peak (P<0.01),
but not higher for peak enhancement (P<0.05) than the
control group.
Effect of radiation on the perfusion parameters
compared with control
The radiotherapy group had significantly lower Kel (0.0010±
0.0009 s−1 vs. 0.0023±0.0011 s−1; P<0.0005) and k21
(0.073±0.036 s−1 vs. 0.102±0.088 s−1; P<0.05) than the
control group (Fig. 3). The amplitude scaling constant A
was higher in the radiotherapy group (0.057±0.051 vs.
0.041±0.034), but not significantly (P=0.26). Alterations
in these perfusion parameters resulted in significantly
higher values for the peak enhancement (72.7±34.9% vs.
38.7±13.1%; P<0.0005) and time-to-peak (87.4±48.6 s vs.
54.7±32.0 s; P<0.0005) consistent with the common
observation of increased signal enhancement with contrast
administration, with insignificant changes in the wash-in
slope (0.92±0.41%/s) vs. 0.96±0.78%/s; P=0.45).
Fig. 2 Scatter plots of peak enhancement (a), time-to-peak (b) and
Kel (c) versus radiation dose. The dashed lines represent the 95%
confidence bands, while the dotted lines represent the 95%
prediction bands
Fig. 3 Perfusion parameters of irradiated and non-irradiated parotid
glands. The scales and units on the vertical axes are: ×10−1 for A,
×10−1 sec−1 for k21, ×10−3 sec−1 for Kel, ×1%. sec−1 for slope, and %
for peak enhancement, sec for time-to-peak, respectively. Data are
presented as mean + SD with P<0.05 (*) and P<0.0005 (**) being
statistically significantly different as compared to the control group
100
Discussion
Radiation injuries of the parotid glands include functional
impairment, structural changes and physiological alterations. Clinically, the functional impairment of the irradiated
parotid glands could be evaluated either by assessing the
severity of xerostomia using RTOG scoring criteria [8] or
by measuring the salivary flow [9]. However, the reduction
of salivary flow and the symptom of xerostomia are
attributed to dysfunction of the parotid and submandibular
glands and therefore are not specific for the parotid gland
injury alone. Although histopathological analysis provides
a standard tool to characterize the microstructural damage
of the irradiated parotid glands, it is not beneficial clinically
owing to the invasiveness of biopsy, which might
potentially endanger the facial nerves. Alternatively, the
structural changes of the irradiated parotid glands could be
investigated by cross-sectional imaging studies, such as CT
and MR imaging. Prior CT studies have demonstrated
increased enhancement of the irradiated parotid glands
after intravenous contrast injection [11–13], implying that
the parotid perfusion might alter after irradiation. Two
assumptions have been made to explain the post-irradiated
enhancement of parotid glands: One is that the radiation
results in changes of vascular permeability; the other
attributes the enhancement to the increase of EES secondary to acinar loss [12, 13].
The results from our dynamic MR imaging study show
that the increased peak enhancement following contrast
administration is predominantly determined by the significant alterations of Kel (the elimination transfer rate
constant describing the wash-out of contrast agents) and
k21, (the transfer rate constant describing the wash-in of
contrast agents). The statistically significant decrease in the
Kel is consistent with a continuous build up of Gd-DTPA
from the blood vessels to the EES and its prolonged wash
out, an outcome likely to originate from the increase of
EES secondary to acinar loss under radiation exposure. On
the other hand, the significantly lower k21 is suggestive of a
decrease of permeability and slower exchange of GdDTPA between the plasma and EES, leading to significantly prolonged time-to-peak and contrast stasis in the
EES. In other words, the decrease of vascular permeability
and the increase of EES together explain how the postirradiated parotid glands enhancement is seen on conventional CT and MR images [11–13].
Moreover, the radiation dosage received by the parotid
glands plays an important role in the perfusion change of
post-irradiated parotid glands. Linear regression analysis
reveals that the radiation doses are positively correlated
with the peak enhancement (P=0.009, R=0.418) and timeto-peak (P=0.0017, R=0.491) and are negatively correlated with the Kel (P=0.0008, R=0.521) with statistical
significance. The dose-dependent perfusion changes are
consistent with results from literature reports investigating
the functional loss of salivary glands using either direct
measurement of salivary flow [3, 21] or 11C-methionine on
positron emission tomography (PET) [22]. In particular, the
PET study shows that the net metabolic clearance of 11Cmethionine correlates positively with the salivary flow,
both of which reduce with increased radiation dose. The
dose-dependent perfusion changes of Kel, suggesting
increase of EES, are also consistent with the histopathological observations of acinar loss in animal studies,
showing dose-dependent acinar loss [23, 24].
Regarding the relationship between the severity of dry
mouth and the changes of perfusion parameters, our results
show that both the low-grade subgroup (grade 0 and 1) and
high-grade subgroup (grade 2 and 3) have significantly lower
Kel (P<0.005) than the control group, again suggestive of an
increase in EES secondary to acinar loss. Since the symptom
of dry mouth is partly attributed to the functional impairment
of the submandibular glands, which is beyond the scope of
the current preliminary study, we suggest not over-interpreting the relationship between the severity of dry mouth and
the parotid perfusion unless both parotid and submandibular
glands are investigated together.
One unique feature of our study is the quantification of
parotid perfusion parameters that, to the best of our
knowledge, has not been investigated before. While
contrast-enhanced dynamic MR imaging has been previously applied to the parotid glands for the purpose of
tumor differentiation [15, 18, 25], these approaches remain
qualitative. A quantitative investigation using curve fitting
to an appropriate model provides the important advantage
that the underlying changes can be examined physiologically and that the influence of noise or finite sampling
interval could be minimized. Certainly, sufficient SNR of
the concentration time curves during image acquisition and
proper choice of the perfusion model are two prerequisites
for the validity of a quantitative study. In our case, good
curve fitting of the concentration-time data could be
achieved in all subjects with high R2 values (0.938±0.050),
indicating appropriateness of the Brix model for use in the
parotid glands. Analysis of the fitting errors at routine SNR
(about 30 in our study) also gives satisfactory estimation
accuracy for the perfusion parameters. Therefore, the
effectiveness of the quantitative approach as shown in our
study may shed light on the future use of DCE-MRI as a
reliable tool to monitor the perfusion changes of the
irradiated parotid glands and, for example, the value of
radioprotection in new radiotherapy techniques or medications. One might question that a temporal resolution of 10.4
s seems insufficient in sampling the rapid wash-in kinetics,
leading to a relatively large error range of k21 (±29%) in
spite of good curve fitting. It could be remedied by using a
gradient echo sequence with a short TR (about 11 ms) or
using the parallel imaging technique, both allowing higher
temporal resolution by shortening the image acquisition
time. Nevertheless, the k21 already distinguished the
radiotherapy group from the control group significantly
in our study.
101
A prior study suggests that regeneration of acinar cells
might occur after irradiation [23]; thus, the RT-to-MR
interval may itself be a factor that needs to be controlled
before ruling out the possibility of perfusion changes due to
acinar regeneration. In our study, the possible relationship
between the RT-to-MR interval and the perfusion changes
were examined by linear regression analysis, showing that
the RT-to-MR interval does not correlate with the perfusion
parameters except only marginally for the k21 (P=0.011;
R=0.407). The lack of strong correlation partly supports
our hypothesis that the perfusion changes in parotid glands
are more likely due to irradiation dosage. The broad
RT-to-MR interval in our preliminary retrospective study,
however, does not allow us to further characterize the
perfusion changes related to the acinar regeneration. To
answer this question, a prospective time-course study
performed before radiotherapy and shortly and longer after
radiotherapy would be required, which is currently under
planning at our institute.
In conclusion, our study shows that quantitative analysis
of DCE-MRI with the Brix model is a potential tool
investigating the perfusion characteristics of the parotid
glands after radiotherapy. The dose-dependent change of
perfusion parameters, including Kel, peak enhancement and
time to peak, suggests that the persistent accumulation and
delayed wash-out of the contrast agent at late stage of
radiation injury reflects the increase of the EES of parotid
glands.
Acknowledgment The authors express gratitude to Miss Shih-I
Tsao for MR data archiving and reference preparation.
References
1. Cairncross JG, Salmon J, Kim JH,
Posner JB (1980) Acute parotitis and
hyperamylasemia following wholebrain radiation therapy. Ann Neurol
7:385–387
2. de Castro GJ, Federico MH (2006)
Evaluation, prevention and management of radiotherapy-induced xerostomia in head and neck cancer patients.
Curr Opin Oncol 18:266–270
3. Jen YM, Lin YC, Wang YB, Wu DM
(2006) Dramatic and prolonged decrease of whole salivary secretion in
nasopharyngeal carcinoma patients
treated with radiotherapy. Oral Surg
Oral Med Oral Pathol Oral Radiol
Endod 101:322–327
4. Li J, Shan Z, Ou G et al (2005)
Structural and functional characteristics
of irradiation damage to parotid glands
in the miniature pig. Int J Radiat Oncol
Biol Phys 62:1510–1516
5. Stephens L, King G, Peters L, Ang K,
Schultheiss T, Jardine J (1986) Acute
and late radiation injury in rhesus
monkey parotid glands. Evidence of
interphase cell death. Am J Pathol
124:469–478
6. Henriksson R, Frojd O, Gustafsson H
et al (1994) Increase in mast cells and
hyaluronic acid correlates to radiationinduced damage and loss of serous
acinar cells in salivary glands: the
parotid and submandibular glands differ in radiation sensitivity. Br J Cancer
69:320–326
7. Lotz S, Caselitz J, Tschakert H, Rehpenning W, Seifert G (1990) Radioprotection of minipig salivary glands by
orciprenaline-carbachol. An ultrastructural and semiquantitative light microscopic study. Virchows Arch A Pathol
Anat Histopathol 417:119–128
8. Cox JD, Stetz J, Pajak TF (1995)
Toxicity criteria of the Radiation Therapy Oncology Group (RTOG) and the
European Organization for Research
and Treatment of Cancer (EORTC). Int
J Radiat Oncol Biol Phys 31:1341–
1346
9. Kohler PF, Winter ME (1985) A quantitative test for xerostomia. The Saxon
test, an oral equivalent of the Schirmer
test. Arthritis Rheum 28:1128–1132
10. Shah GV (2004) MR imaging of salivary glands. Neuroimaging Clin N Am
14:777–808
11. Tartaglino LM, Rao VM, Markiewicz
DA (1994) Imaging of radiation
changes in the head and neck. Semin
Roentgenol 29:81–91
12. Bronstein AD, Nyberg DA, Schwartz
AN, Shuman WP, Griffin BR (1987)
Increased salivary gland density on
contrast-enhanced CT after head and
neck radiation. AJR Am J Roentgenol
149:1259–1263
13. Rabin BM, Meyer JR, Berlin JW,
Marymount MH, Palka PS, Russell EJ
(1996) Radiation-induced changes in
the central nervous system and head
and neck. Radiographics 16:1055–1072
14. Nomayr A, Lell M, Sweeney R, Bautz
W, Lukas P (2001) MRI appearance of
radiation-induced changes of normal
cervical tissues. Eur Radiol 11:1807–
1817
15. Yabuuchi H, Fukuya T, Tajima T,
Hachitanda Y, Tomita K, Koga M
(2003) Salivary gland tumors: diagnostic value of gadolinium-enhanced
dynamic MR imaging with histopathologic correlation. Radiology 226:345–
354
16. Buckley DL, Kerslake RW, Blackband
SJ, Horsman A (1994) Quantitative
analysis of multi-slice Gd-DTPA enhanced dynamic MR images using an
automated simplex minimization procedure. Magn Reson Med 32:646–651
17. Larsson HB, Stubgaard M, Frederiksen
JL, Jensen M, Henriksen O, Paulson
OB (1990) Quantitation of blood-brain
barrier defect by magnetic resonance
imaging and gadolinium-DTPA in patients with multiple sclerosis and brain
tumors. Magn Reson Med 16:117–131
18. Ikeda M, Motoori K, Hanazawa T et al
(2004) Warthin tumor of the parotid
gland: diagnostic value of MR imaging
with histopathologic correlation. AJNR
Am J Neuroradiol 25:1256–1262
19. Brix G, Semmler W, Port R, Schad LR,
Layer G, Lorenz WJ (1991) Pharmacokinetic parameters in CNS Gd-DTPA
enhanced MR imaging. J Comput
Assist Tomogr 15:621–628
20. Bates D, Watts D (1988) Nonlinear
regression analysis and its applications:
Wiley:33–66
21. Munter MW, Karger CP, Hoffner SG et
al (2004) Evaluation of salivary gland
function after treatment of head-andneck tumors with intensity-modulated
radiotherapy by quantitative pertechnetate scintigraphy. Int J Radiat Oncol
Biol Phys 58:175–184
102
22. Buus S, Grau C, Munk OL, Bender D,
Jensen K, Keiding S (2004) 11Cmethionine PET, a novel method for
measuring regional salivary gland
function after radiotherapy of head and
neck cancer. Radiother Oncol 73:289–
296
23. Gustafsson H, Franzen L, Henriksson R
(1995) Regeneration of parotid acinar
cells after high radiation doses. A
morphological study in rat. Acta Oncol
34:193–197
24. Radfar L, Sirois D (2003) Structural
and functional injury in minipig salivary glands following fractionated exposure to 70 Gy of ionizing radiation an
animal model for human radiationinduced salivary gland injury. Oral
Surg Oral Med Oral Pathol Oral Radiol
Endod 96:267–274
25. Suenaga S, Indo H, Noikura T (2001)
Diagnostic value of dynamic magnetic
resonance imaging for salivary gland
diseases: a preliminary study. Dentomaxillofac Radiol 30:314–318