Clin Oral Invest
DOI 10.1007/s00784-016-2034-6
ORIGINAL ARTICLE
Semi-quantitative analysis of salivary gland scintigraphy
in Sjögren’s syndrome diagnosis: a first-line tool
Tiziana Angusti 1 & Emanuela Pilati 1 & Antonella Parente 1 & Renato Carignola 2 &
Matteo Manfredi 1 & Simona Cauda 3 & Elena Pizzigati 1 & Julien Dubreuil 4,5 &
Francesco Giammarile 4,5 & Valerio Podio 1 & Andrea Skanjeti 1,4,5
Received: 10 October 2016 / Accepted: 8 December 2016
# Springer-Verlag Berlin Heidelberg 2017
Abstract
Objective The aim of this study was the assessment of semiquantified salivary gland dynamic scintigraphy (SGdS) parameters independently and in an integrated way in order to
predict primary Sjögren’s syndrome (pSS).
Materials and methods Forty-six consecutive patients (41 females; age 61 ± 11 years) with sicca syndrome were studied
by SGdS after injection of 200 MBq of pertechnetate. In sixteen patients, pSS was diagnosed, according to AmericanEuropean Consensus Group criteria (AECGc).
Semi-quantitative parameters (uptake (UP) and excretion
fraction (EF)) were obtained for each gland. ROC curves were
used to determine the best cut-off value. The area under the
curve (AUC) was used to estimate the accuracy of each semiquantitative analysis.
To assess the correlation between scintigraphic results and
disease severity, semi-quantitative parameters were plotted
versus Sjögren’s syndrome disease activity index (ESSDAI).
A nomogram was built to perform an integrated evaluation of
all the scintigraphic semi-quantitative data.
* Andrea Skanjeti
askanjeti@gmail.com
1
Nuclear Medicine Unit, San Luigi Gonzaga University Hospital,
Orbassano, Italy
2
Medical Division, San Luigi Gonzaga University Hospital,
Orbassano, Italy
3
Service of Nuclear Medicine, Institute for Cancer Research and
Treatment, Candiolo, Italy
4
Nuclear Medicine Department, Hospices Civils de Lyon,
Lyon, France
5
Equipe Mixte de Recherche 3738, Université Claude Bernard Lyon
1, Lyon, France
Results Both UP and EF of salivary glands were significantly
lower in pSS patients compared to those in non-pSS
(p < 0.001). ROC curve showed significantly large AUC for
both the parameters (p < 0.05).
Parotid UP and submandibular EF, assessed by
univariated and multivariate logistic regression, showed
a significant and independent correlation with pSS diagnosis (p value <0.05). No correlation was found between
SGdS semi-quantitative parameters and ESSDAI. The
proposed nomogram accuracy was 87%.
Conclusion SGdS is an accurate and reproducible tool for the
diagnosis of pSS. ESSDAI was not shown to be correlated
with SGdS data.
Clinical relevance SGdS should be the first-line imaging
technique in patients with suspected pSS.
Keywords Sicca syndrome . Sjögren’s syndrome . Salivary
gland dynamic scintigraphy . Differential diagnosis .
Quantitative analysis
Introduction
Sjögren’s syndrome (SS) is a chronic, progressive, autoimmune disease, of unknown aetiology, characterized by focal
lymphocytic infiltration of exocrine glands with a significant
functional impairment, leading to sicca symptoms [1–3].
These symptoms could be also associated with connective
tissue disorders, autoimmune diseases (rheumatoid arthritis,
systemic sclerosis or systemic lupus erythematosus) or other
causes (such as previous head and neck radiotherapy or antidepressant drugs). Therefore, it is important to identify primary Sjögren’s syndrome (pSS) among various aetiologies given
that clinical and therapeutic approaches are different [4].
Clin Oral Invest
Diagnostic approach in pSS is impervious because the classification criteria, essential to ensure standardization in
multicentre studies, show good but not excellent accuracy in
clinical settings [5].
Among the various symptoms, xerostomia is an aspecific
one. Various methods are available to assess salivary gland
involvement, and each one measures different features of salivation: in addition, salivary gland biopsy, performed on minor labial glands, identifies only non-specific lymphocytic
infiltration [6].
Salivary gland dynamic scintigraphy (SGdS) has been proposed as a valid and non-invasive tool to evaluate salivary
gland involvement in xerostomic patients. It provides a detailed functional assessment of each salivary gland, and it
measures various quantitative parameters [6]. Over the past
decades, a variety of different quantitative values have been
suggested, but no consensus was reached on which parameters
will be more accurate for pSS diagnosis [1, 7–10].
The aim of this study was the assessment of semiquantified salivary gland dynamic scintigraphy (SGdS) parameters independently and in an integrated way in order to
predict pSS.
128 × 128, zoom 2, pixel size 2.33 mm, energy window
140 ± 10% keV). In the second step—the patient was
placed supine for an anterior head-neck dynamic imaging starting at pertechnetate i.v. administration (40
frames, 45 s per frame, 30 min). After 15 min, salivary secretion was stimulated with 5 ml of lemon juice, administered
with a straw avoiding patient’s head movements. Syringe
counts after injection—the empty syringe activity was measured as described in the first step.
Image analysis
The images were qualitatively assessed by two operators.
Afterwards, manual shaped regions of interest (ROIs) were
drawn on parotid and submandibular glands on both sides.
A rectangular background ROI was placed in the right frontal
region (Fig. 1). After background subtraction, data were plotted on separated time-activity curves for each region.
From time-activity curves, the maximum value before
juice administration and the minimum value after juice
administration were obtained; from these data, two
semi-quantitative parameters were computed according
to Eqs. (1) and (2): uptake (UP) and excretion fraction
(EF), respectively.
Materials and methods
Patient selection
ROIgland ðcounts=pxlÞ−ROIbackground ðcounts=pxlÞ *ROIglandsurface ðpxlsÞ
¼ UP
EAIðcountsÞ
ð1Þ
In this retrospective study, from September 2008 to
March 2012, 46 consecutive patients (5 males, 41 females;
61 ± 11 years mean ± DS), referred to our department for
suspected pSS and underwent SGdS.
The exclusion criteria were HCV infection, acquired immunodeficiency syndrome (AIDS), sarcoidosis and hyperthyroidism; no subject had a history of lymphoma or head and
neck radiation.
In order to confirm pSS diagnosis, one experienced rheumatologist applied the American-European Consensus Group
criteria (AECGc) [5]. In sixteen patients, pSS was diagnosed
according to AECGc.
The institution ethic committee approved this study, and
informed consent for the study was obtained from all the
participants.
Imaging technique
Imaging was performed using a gamma camera (Philips
Axis) equipped with low-energy and high-resolution
parallel-hole collimators (LEHR). Scintigraphy was performed in three steps: syringe counts before injection
(first step)—a syringe with 200 MBq pertechnetate
99m
TcO4− was placed at 20 cm from gamma camera
head, and the image was acquired during 45 s (matrix
EAI: effective activity injected = syringe counts before
injection − syringe counts after injection.
maximum counts before lemon juice − minimum counts after lemon juice
maximum counts before lemon juice − background uptake
¼ EF
ð2Þ
Since no significant difference was found between
the right and the left sides for both parotids and submandibulars glands (paired t test), averages of results
from the two sides were considered for accuracy purposes of this study.
To assess the inter-operator reproducibility, images were
independently analysed by three operators, with different experience (M.M, S.C. and E.P.). The data obtained by each
operator for every gland were compared with the corresponding data obtained by the other two operators.
Sjögren’s syndrome disease activity index and SGdS
European League Against Rheumatism (EULAR) promoted and developed the EULAR Sjögren’s syndrome
disease activity index (ESSDAI). This model is
Clin Oral Invest
Fig. 1 Two SGdS samples
processing and corresponding
time-activity curves. a SGdS
normal pattern of a 54-year-old
woman complaining of
moderately dry mouth since a
month; b SGdS abnormal pattern
of a 46-year-old woman affected
by sicca symptoms since a year,
subsequently classified as pSS, on
the basis of AECGc
composed of 12 organ-specific “domains” contributing
to disease activity. For each domain, features of disease
activity were classified in three or four levels according
to their severity [11].
ESSDAI was quantified as the sum of all domain weights.
For all pSS patients, ESSDAI was correlated with SGdS
results.
Statistical analysis
On the basis of AECGc, results were classified with
regards to pSS diagnosis; sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of semi-quantitative results were
analysed by ROC curves. The area under the curve
(AUC) was calculated to establish accuracy of SGdS
data.
On the basis of semi-quantitative data obtained for
each major salivary gland by the three operators, the
intra-class correlation coefficient (ICC) was calculated.
A multivariate analysis was performed to define the
disease probability according to scintigraphy data.
All statistical analyses were performed by using Med
Calc vers. 12 (MedCalc Software, Mariakerke, Belgium)
and SPSS vers. 19 (IBM Corporation, Armonk, NY,
USA). P value <0.05 was considered statistically
significant.
Results
Univariate analysis
All semi-quantitative values (both parotid and submandibular UP and EF) were significantly lower in pSS
patients compared to those in no-pSS patients. For each
semi-quantitative value, ROC-curve AUC was bigger
than 0.78, p value <0.05 (Table 1). The best cut-off
for each dataset is summarized in Table 1.
Multivariate analysis and integrated evaluation
of the salivary gland dynamic scintigraphy
The role of each parameter in a multivariate setting was
evaluated by logistic regression (stepwise with constraints 0.05; 0.1). Among the four data, only parotid
UP and submandibular EF showed to be independently
and significantly correlated with the final diagnosis (p
value <0.02 for both).
The logit function that described this correlation is as follows:
logitðpÞ ¼ 4:619−11:2582*P:UP–0:0628*S:EF
In order to estimate the probability of disease, a nomogram was built according to this logistic regression
(Fig. 2); values obtained with nomogram were analysed
Clin Oral Invest
Table 1 Semi-quantitative data of each pair of major salivary glands and relative cut-off values; both uptake (UP) and excretion fraction (EF) clustered by
diagnosis (pSS = primary Sjögren syndrome; no pSS = no primary Sjögren syndrome) according to AECG (American-European Consensus Group) criteria
DIAGN
No pSS
N
pSS
Mean
95% CI
N
Mean
95% CI
t test
ROC analysis
p value
AUC
p value
Cut-off
P. UP
P. EF
S. UP
30
30
30
0.369
62.280
0.277
0.277–0.461
57.180–67.379
0.224–0.330
16
16
16
0.163
35.886
0.130
0.110–0.216
21.050–50.722
0.082–0.178
0.0002
0.002
0.0005
0.846
0.788
0.820
0.0001
0.0001
0.0001
0.240
46.580
0.185
S. EF
30
52.440
47.422–57.452
16
29.375
18.588–40.163
0.0005
0.838
0.0001
43.245
N number of cases, 95% CI 95% confidence interval, AUC area under the curve, P parotid, S submandibular
by ROC curve: AUC was 0.91 (p = 0.0001) with sensitivity 75%, specificity 93% and accuracy 87%; best
disease probability threshold estimated by the nomogram was 56% (see Fig. 3).
nomogram results); R2 was lower than 0.18 for each data set
(Fig. 4).
Inter-operator reproducibility
Discussion
ICC showed a significant correlation (p < 0.0001)
among all the operators with all the coefficients in the
interval 0.87–0.96; however in all cases, ICC was
higher for gland UP than that for EF (Table 2).
No significant correlation has been found between ESSDAI
value and SGdS semi-quantitative parameters (UP, EF and
The diagnostic role of SGdS in pSS patients has been studied
for years, and several approaches have been proposed [1–4,
6]. Aung et al. and Loufti et al. proposed quantitative and
semi-quantitative parameters (uptake ratio, excretion ratio,
maximum activity and excretion velocity). Semi-quantitative
analysis showed to be able to define the clinical stage of pSS
in equivocal cases and was accurate in both diagnosis and
follow-up [9, 12]. Also Vinagre et al. confirmed that the use
of semi-quantitative values can increase SGdS accuracy [1].
Other authors suggested that a scoring system of dynamic
Fig. 2 Nomogram, built according to multivariate analysis, which
predicts pSS probability on the basis of parotid UP (p.UP) and
submandibular EF (s.EF). To calculate pSS probability, locate the
patient value of p.UP to the corresponding axis; from this value, draw a
line straight upward to the top point axis. Note the value. Repeat the
process for s.EF. Sum both values and locate the final sum on the total
point axis. Draw a line straight down on the bottom axis to find pSS
probability
Correlation between salivary gland dynamic scintigraphy
and disease activity
Clin Oral Invest
Fig. 3 pSS-integrated probability between parotid UP and
submandibular EF of each patient (no pSS on the left hand-side and
pSS on the right hand-side), according to the logistic regression
scintigraphy is an objective and reproducible method for evaluating salivary gland function in patients with pSS [6, 7, 13].
On the other hand, several colleagues expressed some concerns about the use of SGdS as a first-choice investigation in
patients with suspected pSS [6, 14]; others underlined the low
accuracy and the lack of standardized parameters as well as
interpretation of SGdS in order to impact the diagnosis and
management of pSS [8, 10]. Furthermore, Kim et al. affirmed
that qualitative analysis showed higher diagnostic utility than
semi-quantitative assessment [15].
Although previous studies have compared pSS patients with healthy volunteers [2, 16], in daily routine,
the definition of correct therapeutic approach requires
Table 2
Mean values for each operator and parameter, as well as ICC
Mean uptake %
OP 1 OP 2 OP 3
Right parotid
No pSS 0.35 0.35
pSS
0.21 0.24
Left parotid
No pSS 0.31 0.33
pSS
0.18 0.21
Right submandibular
no pSS 0.24 0.26
pSS
0.12 0.14
Left submandibular
No pSS 0.23 0.23
pSS
0.11 0.12
ICC
Mean EF %
ICC
OP 1 OP 2 OP 3
0.33
0.20
0.954 58.6
51.7
56.3
51.1
56.4
52.6
0.962
0.30
0.18
0.924 56.5
48.1
57.3
46.5
53.5
50.4
0.892
0.25
0.13
0.928 54.3
34.2
48.8
32.4
52.4
37.3
0.922
0.24
0.13
0.921 51.1
38.2
45.9
31.0
49.8
37.9
0.870
OP operator, EF excretion fraction, ICC intra-class correlation coefficient, pSS primary Sjögren syndrome
identification of pSS patients among subjects already
showing xerostomia. Our work points out the SGdS
key role in a group of patients affected by xerostomia.
As already stated, our data do not show any difference
between the salivary gland on the two sides. At univariate
analysis, each assessed semi-quantitative value (both parotid
and submandibular UP and EF) showed to be significantly
lower in patients with pSS: these results confirm other previous findings [1, 6, 7, 9, 12, 13].
Furthermore, multivariate analysis showed that only
parotid UP and submandibular EF were independently
correlated with pSS diagnosis. In fact, our results, in
keeping with other papers [12, 16], stress the essential
role of excretion fraction, in particular of submandibular
glands, in order to detect pSS in its earliest phases,
reflecting the particular and prior impairment of these
glands. Then, our study showed also the impairment
of parotid glands in patients affected by pSS; in particular, quantifying by their uptake, the reduction of these
glands is noteworthy, consequently to the parenchyma
destruction caused by the lymphocytic infiltration.
Moreover, a nomogram was built to define disease
probability (Fig. 2). To calculate pSS probability on this
nomogram, the reader should locate the patient value of
p.UP to the corresponding axis; from this value, should
draw a line straight upward to the top point axis. Then,
note the value. Repeat the process for s.EF. Sum both
values and locate the final sum on the total point axis.
Finally, the reader should draw a line straight down on
the bottom axis to find pSS probability.
To date, no nomogram or other statistical instruments
of integrated probability have been suggested in order to
predict pSS, except a hint in a recent work of Zou [2].
A nomogram is a simple and helpful tool which allows
clinicians to define the disease probability. Therefore, it
can be helpful in decision-making process.
Lack of standardization among nuclear medicine centres caused concerns about the utility of SGdS.
Standardization of procedures, according to Anjos et al.
(measure of injected activity, background subtraction), allows
a reproducible estimation of salivary glands UP and EF and
allows a comparison among centres as well as longitudinal
evaluations of disease [17].
Moreover, the standardization of procedures ensures
intra-operator reproducibility. In our settings, results
from the three operators showed an excellent agreement
despite the operators’ different experience, likely because the learning curve for semi-quantitative analysis
is faster than the know-how acquisition for qualitative
evaluation.
In our opinion, the lack of correlation between SGdS
data and ESSDAI reveals that accuracy of SGdS in
predicting pSS is independent from the disease severity,
Clin Oral Invest
ParoƟd EF/ESSDAI (R² = 0.062)
80
0,35
70
0,3
60
0,25
50
0,2
0,15
1,2
30
0,1
20
0,05
10
0
Integrated evaluaƟon with paroƟd UP and submandibular EF/ESSDAI (R² = 0.0164)
40
1
pUP [%] + sEF [%]
pEF [%]
pUP [%]
ParoƟd UP/ESSDAI (R² =0.0011)
0,4
0
0
2
4
6
8
10
0
2
4
ESSDAI
6
8
10
ESSDAI
Submandibular EF/ESSDAI (R² =0.1075)
Submandibular UP/ESSDAI (R² = 0.1763)
0,30
70
60
0,25
0,8
0,6
0,4
0,2
sEF [%]
sUP [%]
50
0,20
0,15
0,10
0
40
0
30
1
2
3
4
5
6
7
8
9
ESSDAI
20
10
0,05
0
0,00
0
2
4
6
8
ESSDAI
10
-10
0
2
4
ESSDAI
6
8
10
Fig. 4 Correlation between SGdS semi-quantitative parameters (UP, EF of parotid and submandibular glands and integrated evaluation with parotid
gland UP and submandibular gland EF) and ESSDAI value and the respective R2
even though we cannot exclude the impact of underpowered statistics.
Limitations of this study were its retrospective nature, the
small number of patients and the absence of quantitative evaluation on healthy control group.
Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the
institutional and/or national research committee and with the 1964
Helsinki declaration and its later amendments or comparable ethical
standards.
Informed consent Informed consent was obtained from all the individual participants included in the study.
Conclusion
References
The optimal reproducibility of semi-quantitative evaluation
and the accuracy of each gland parameter make SGdS an
instrument of primary importance in pSS diagnosis. In addition, its excellent accuracy seems to be unaffected by the disease severity. The proposed nomogram shows to be effective
in defining the disease probability; its results can be reported
by nuclear medicine physicians. Furthermore, SGdS is not a
very expensive exam; it delivers low radiation exposure to
patients and is quite widespread on both high- and lowincome countries.
Therefore, SGdS in sicca syndrome should be always carried out, and, even better, in our opinion, it should be a firstline instrumental investigation.
Acknowledgements The authors would like to thank Prof Alessandro
Giordano for his helpful suggestions and the Nuclear Medicine staff for
their support as well as Eda Koxhaku for the English editing.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Funding Financial funding was not required nor obtained: this research
received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
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