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for the degree of Doctoral of Philosophy in Dental Science
Sang-Mi Nam
June 2020
ACKNOWLEDGEMENTS
Dr. Elbert
i
CONTENTS
LIST OF FIGURES v
LIST OF TABLES vii
ABSTRACT viii
I. INTRODUCTION 1
II. MATERIALS AND METHODS 9
2.1. Study design 9
2.2. In vitro study 11
2.2.1. Tooth selection 11
2.2.2. Preparation of the specimen 11
2.2.3. Pit and fissure sealant application and microleakage formation 12
2.2.4. QLF-D image taking 13
2.2.5. Fluorescence assessment and analysis using QLF-D 15
2.2.6. Histological analysis 17
2.3. Clinical image study 20
2.3.1. Study subject 20
ii
2.3.2. Image assessments of Q-ray pen 22
2.3.3. Fluorescence image assessment and analysis using Q-ray pen 22
2.4. Clinical trial 25
2.4.1. Study subject 25
2.4.2. Visual and tactile assessments 26
2.4.3. Q-ray view combined assessment 28
2.5. Statistical analysis 30
2.5.1. In vitro study (Study 1) 30
2.5.2. Clinical image study (Study 2) 30
2.5.3. Clinical trial (Study 3) 31
III. RESULTS 32
3.1. In vitro study results (Study 1) 32
3.1.1. Comparison of histological distribution by microleakage formation 32
3.1.2. Distribution of fluorescence variables according to the histological score
33
3.1.3. QLF-D images and magnification microscope images of microleakage in
pit and fissure sealant according to the histological score 35
3.1.4. Correlation of variable between histology and fluorescence values
36
iii
3.1.5. Validity of QLF-D 37
3.1.5.1. AUC analysis for diagnostic accuracy of fluorescence variables 37
3.1.5.2. Sensitivity, specificity, and AUC curves of fluorescence variables
at outer half microleakage of the pit and fissure sealant 38
3.1.5.3. Sensitivity, specificity, and AUC curves of fluorescence variables
at inner half microleakage of the pit and fissure sealant 39
3.1.5.4. Sensitivity, specificity, and AUC curves of fluorescence variables
at underlying fissure microleakage of the pit and fissure sealant 40
3.2. Clinical image study results (Study 2) 41
3.2.1. Study population 41
3.2.2. Distribution of fluorescence variables according to pit and fissure sealant
status 41
3.2.3. Interrater reliability between White-light image and Fluorescence with
white-light image 44
3.2.4. Distribution of marginal plaque between White-light image and
Fluorescence with white-light image 46
3.3. Clinical trial results (Study 3) 47
3.3.1. Study population 47
3.3.2. Interrater reliability between VT and Q-ray view with VT 48
3.3.3. Intrarater reliability between VT and Q-ray view with VT 51
iv
3.3.3.1. Intrarater reliability of marginal plaque assessment of pit and fissure
sealant 53
3.3.3.2. Intrarater reliability of marginal discoloration assessment of pit and
fissure sealant 54
3.3.3.3. Intrarater reliability of marginal integrity assessment of pit and
fissure sealant 55
3.3.3.4. Intrarater reliability of retention assessment of pit and fissure sealant
56
3.3.3.5. Intrarater reliability of caries assessment of pit and fissure sealant
57
IV. DISCUSSIONS 58
V. CONCLUSIONS 68
REFERENCES 70
ABSTRACT (IN KOREAN) 76
v
LIST OF FIGURES
Figure 1. A schematic diagram of the study design 10
Figure 2. QLF-D camera (QLF-D Biluminator TM) 14
Figure 3. (A) A representative occlusal fluorescence image. (B) A magnified image for analysis. (C) A designed patch area around margin of sealant. (D) A reconstructed image based on the fluorescence of the sound area. The blue line indicates the sound reference area, whereas the red line indicates the deactivated area. (E) The fluorescence difference between the original and reconstructed images. (F) Analysis results from the margin of sealant. (G) A total of 4 analyzed patches in single tooth sample. 16
Figure 4. Sample preparation for observing the cross-sectional view of mesial and distal pit
18
Figure 5. Schematic diagram of the cross-sectioned specimen for measuring microleakage and dye penetration 19
Figure 6. Q-ray pen TM 21
Figure 7. (A) A representative occlusal white light image. (B) A representative occlusal fluorescence image. (C) A reconstructed image based on the fluorescence of the sound area. The blue line indicates the sound reference area, whereas the red line indicates the deactivated area. (D) Analysis results from the margin of sealant. (E) Analyzed patches in single tooth sample. 24
Figure 8. Q-ray view TM 29
Figure 9. Box plot showing ΔF, ΔFmax values related to histological score 34
Figure 10. Representative QLF-D images (white-light and fluorescence images) and a magnification microscope images(×50) of specimens according to histological score 35
Figure 11. Sensitivity, specificity, and AUC curves of fluorescence variables at outer half microleakage of the pit and fissure sealant 38
vi
Figure 12. Sensitivity, specificity, and AUC curves of fluorescence variables at inner half microleakage of the pit and fissure sealant 39
Figure 13. Sensitivity, specificity, and AUC curves of fluorescence variables at underlying fissure microleakage of the pit and fissure sealant 40
Figure 14. Comparison of kappa values for interrater reliability between white-light image and fluorescence with white-light image 44
Figure 15. Comparison of mean kappa values for interrater reliability between VT and Q-ray view 49
Figure 16. Representative images of marginal plaque (A, B), marginal discoloration (C, D), and caries (E, F) at pit and fissure sealant margin. White-light image (A, C, E), Q-ray pen image (B, D, F) 50
Figure 17. Comparison of mean kappa values for intrarater reliability between VT and Q-ray view 52
Figure 18. Comparison of mean kappa values for intrarater reliability between VT and Q-ray view of marginal plaque assessment 53
Figure 19. Comparison of mean kappa values for intrarater reliability between VT and Q-ray view of marginal discoloration assessment 54
Figure 20. Comparison of mean kappa values for intrarater reliability between VT and Q-ray view of marginal integrity assessment 55
Figure 21. Comparison of mean kappa values for intrarater reliability between VT and Q-ray view of retention assessment 56
Figure 22. Comparison of mean kappa values for intrarater reliability between VT and Q-ray view of caries assessment 57
vii
LIST OF TABLES
Table 1. Photographing condition of QLF-D in this study 14
Table 2. Criteria of image evaluation for pit and fissure sealant status 23
Table 3. Criteria of evaluation for pit and fissure sealant status 27
Table 4. Histological distribution of specimens by microleakage formation 32
Table 5. Distribution of Fluorescence variables according to the histological score after microleakage formation 33
Table 6. Correlation coefficients between histology and fluorescence variables of microleakage 36
Table 7. Area under the ROC curve of fluorescence variables at each histology criteria 37
Table 8. Distribution of fluorescence variables according to pit and fissure sealant status 42
Table 9. Intrarater reliability of two images examination methods for evaluating pit and fissure sealant status 43
Table 10. Interrater reliability of two images examination methods for evaluating pit and fissure sealant status 45
Table 11. Interater reliability of two images examination methods for evaluating pit and fissure sealant status 45
Table 12. Distribution of marginal plaque in white-light image and fluorescence with white-light image 46
Table 13. Demographic data 47
Table 14. Interrater reliability of two examination methods for evaluating pit and fissure sealant status 49
Table 15. Intrarater reliability of two examination methods for evaluating pit and fissure sealant status 51
viii
Abstract
Pit and fissure sealant assessment using Quantitative light-
induced fluorescence (QLF) technology
Sang-Mi Nam
Department of Dentistry
The Graduate School, Yonsei University
(Directed by professor Baek-Il Kim)
Currently, the evaluation of the retention status of the pit and fissure sealant is subjective,
so limitations on validity and reliability have been reported. Attempts have been made to
evaluate the pit and fissure sealant using a variety of optical equipment, but it has been
difficult to utilize in clinical practice due to the limited objectivity and reproducibility. The
purpose of this study was to evaluate the validity and reliability of an optical technique
ix
(Quantitative light-induced fluorescence, QLF) that quantifies fluorescence reactions to
detect microleakage of pit and fissure sealants.
The first study used 160 specimens from a total of 40 human tooth with pit and fissure
sealants. Fluorescence images of tooth specimens, which captured by QLF technology,
were analyzed using a specific analysis program. The mesial and distal pit margin were
analyzed, and this was the same site as histological evaluation.
The fluorescence values (ΔF, ΔFmax) of QLF-D according to the depth of microleakage
were measured, and the correlation between depth and each fluorescence value was
analyzed. In addition, sensitivity, specificity and AUC were calculated according to
histological evaluation results. As a result, all fluorescence values of QLF-D showed a
strong correlation with the depth of microleakage (Spearman's correlation coefficients, rho;
-0.72; p <0.001). The diagnostic accuracy of good or better was shown at the threshold of
all microleakage depths (AUC = 0.83 – 0.93, p <0.001) in the AUC analysis result using
the ROC curve.
For the second study, 29 occlusal surfaces were captured from human tooth with pit
and fissure sealant using a Q-ray pen. Total 129 sites of interest from these images were
selected, and one trained examiner evaluated it according to each clinical evaluation
criterion. An examiner also analyzed fluorescence values (ΔF, ΔFmax, ΔR) to obtain
quantitative values. Another three clinicians trained four clinical evaluation criteria
(marginal plaque, marginal discoloration, retention, and caries), and then performed image
x
analysis. White light and fluorescent image captured by Q-ray pen was used for analysis,
and interrater agreement was calculated after each image evaluation. Fluorescence values
(ΔF, ΔFmax, ΔR) were calculated from fluorescent image, and these values (ΔF, ΔFmax)
except for ΔR showed significant differences according to clinical criteria in the retention
category (p <0.05). For evaluation retention and caries of pit and fissure sealant, interrater
agreement showed fair agreement - substantial agreement (0.26-0.41, 0.33-0.67) in white
light image, but it showed higher value in fluorescent image (0.43-0.57, 0.40-0.72), which
means moderate agreement- substantial agreement.
For study 3, total 58 teeth were examined from 15 volunteers among 3rd grade dental
hygiene departments who had at least one tooth that had been treated with pit and fissure sealant
six months ago. In order to compare conventional method (visual and tactile inspection) and
combination method with Q-ray view for tooth with pit and fissure sealant, interrater and
intrarater agreements were calculated from three trained examiners. For marginal plaque,
1 Presence of plaque accumulation limited to margin
Red fluorescence emission limited to margin
2 Presence of plaque accumulation around sealant including margin
Red fluorescence emission around sealant including margin
Marginal discoloration
0 No discoloration No fluorescence changes
1 Presence of marginal discoloration less than 50% Fluorescence loss less than 50%
2 Presence of marginal discoloration more than 50% Fluorescence loss more than 50%
Marginal integrity
0 Not detectable with an explorer Not detectable with an explorer
1 Margin detectable with an explorer
Margin detectable with an explorer
2 Crevice detectable with an explorer
Crevice detectable with an explorer along the margin of visible width and depth
Retention
0 Completely retained material Completely retained material
1 Partially lost material Partially lost material
2 Totally lost material Totally lost material
Caries
0 No caries No fluorescence changes
1 Initial caries (no cavity) Slight fluorescence loss and/or red fluorescence emission
2 Enamel or dentin caries (cavity formation)
Distinct fluorescence loss and/or red fluorescence emission
28
2.4.3. Q-ray view combined assessment
The same sealant tooth was evaluated using visual, palpation, and Q-ray views (Aiobio
Inc., Seoul, Korea, Figure 8), and all evaluation items were identical. Of the five evaluation
items, three items (marginal plaque, marginal discoloration, and caries) were modified for
fluorescence image evaluation.
First, the marginal plaque evaluation was evaluated with or without red fluorescence. This is
based on the rationale that it is possible to detect dental plaque with red fluorescence using QLF
technology (Kim 2011). The score was classified as follows; Score 0, no red fluorescence
observed; Score 1, red fluorescence was observed only at the margin of the sealant due to the
presence of dental plaque; Score 2, red fluorescence was observed around the teeth and sealant.
Next, the marginal discoloration item were modified based on the results of previous
studies (Lee et al. 2018) that can distinguish the discoloration characteristics using
fluorescence images. This previous study identified by using QLF technology that non-
cariogenic and cariogenic discoloration can be distinguished, and as the intensity of
discoloration increases, fluorescence disappears and dark discoloration is observed.
Accordingly, marginal discoloration was classified as follows; Score 0, no fluorescence
change; Score 1, the fluorescence loss less than 50%; Score 2, florescence loss more than
50%.
Evaluation criteria for caries were scored by setting criteria reflecting both fluorescence loss
and red fluorescence expression. QLF technology can quantify the mineral change of the initial
29
carious lesion with fluorescence loss (Ellwood, Gomez, and Pretty 2012), and detect the
increased bacterial activity in caries lesions with red fluorescence (Kim and Kim 2017). Based
on this rationale, caries evaluation items were classified as follow; Score 0, no fluorescence
change; Score 1, slight fluorescence loss and/or red fluorescence emission; Score 2, distinct
fluorescence loss and/or red fluorescence emission.
Figure 8. Q-ray view TM
30
2.5. Statistical analysis
All analyzes of this study were at a significance level of 0.05 using statistical programs
(R core team (2018). R: A language and environment for statistical computing. R
Foundation for Statistical computing, Vienna, Austria. URL https: //www.R-project.org/.).
2.5.1. In vitro study (Study 1)
The correlation between histological evaluation results (gold standard) and fluorescence
parameter values was calculated using Spearman's rank correlation. The sensitivity,
specificity, and area under the ROC (AUC) of each fluorescence variable were analyzed to
evaluate the validity of the fluorescence variables ΔF and ΔFmax that detect each score in
the histology classification.
2.5.2. Clinical image study (Study 2)
Independent sample t-test was performed to quantitatively analyze the pit and fissure
sealant using a fluorescent image. Cohen's kappa value was used to calculate the
consistency within the examiner. Fleiss kappa and Cohen's kappa values were used to
calculate the agreement between the three examiners on the results of white-light and
fluorescence image evaluation.
31
2.5.3. Clinical trial (Study 3)
Fleiss kappa and Cohen's kappa values were used to calculate the inter- and intra-
examiner agreement between conventional method (visual and tactile inspection) and
combination method with Q-ray view. In order to test whether the difference between the
mean kappa values of conventional and combination method was significant, it was
analyzed by paired t-test.
32
III. RESULTS
3.1. In vitro study results (Study 1)
3.1.1. Comparison of histological distribution by microleakage formation
Four of the 44 extracted teeth were damaged after histological evaluation and distilled
water deposition. In total, 160 tooth surfaces (40 specimens) were analyzed and it includes
22 sealants formed according to the manufacturer's instructions and 18 teeth forming
microleakage (Table 4).
Table 4. Histological distribution of specimens by microleakage formation
Histology Microleakage (N=160)
0 35 (21.88%)
1 39 (24.38%)
2 41 (25.63%)
3 45 (28.13%)
33
3.1.2. Distribution of fluorescence variables according to the histological score
In order to quantitatively evaluate the microleakage of the pit and fissure sealant,
variables of average fluorescence loss (ΔF) and maximum fluorescence loss (ΔFmax) were
used. In each histological evaluation, the absolute values of ΔF and ΔFmax increased as the
depth of microleakage by methylene blue dye penetration increased (Figure 9). The
fluorescence parameter from QLF-D increased with increasing histological classification
criteria at all stages (p<0.05, Table 5).
Table 5. Distribution of fluorescence variables according to the histological score after
microleakage formation
Histology N Fluorescence variables
ΔF ΔFmax
0 35 -6.1 ± 0.8a -7.3 ± 2.5 a
1 39 -7.2 ± 1.6b -11.2 ± 4.4 b
2 41 -9.5 ± 2.5c -15.9 ± 4.6 c
3 45 -11.0 ± 2.8d -19.4 ± 7.5 d
All values are expressed as mean ± standard deviations. Different letters within the same column indicate significant differences between groups by Games-Howell post hoc analysis at a=0.05.
34
Figu
re 9
. Box
plo
t sho
win
g ΔF
, ΔF m
ax v
alue
s rel
ated
to h
isto
logi
cal s
core
35
3.1.3. QLF-D images and magnification microscope images of microleakage in pit and
fissure sealant according to the histological score
Figure 10 shows the result of confirming the ΔFmax value and dye penetration pattern
according to the histological score stage. The absolute value of ΔFmax and dye penetration
increased with each step of the histological score.
Figure 10. Representative QLF-D images (white-light and fluorescence images) and a
magnification microscope images (×50) of specimens according to histological score
36
3.1.4. Correlation of variable between histology and fluorescence values
Fluorescence parameters (ΔF and ΔFmax) and histological score of the microleakage site
evaluated by QLF-D showed a statistically significant correlation (p<0.001, Table 6). The
correlation coefficient of histological classification and each variable showed high value
with both ΔF and ΔFmax of -0.72 (Table 6).
Table 6. Correlation coefficients between histology and fluorescence variables of microleakage
Histology Fluorescence variables
ΔF ΔFmax
Histology 1
ΔF -0.72*** 1
ΔFmax -0.72*** 0.95*** 1
*** Spearman’s rank correlation analysis, P<0.001
37
3.1.5. Validity of QLF-D
3.1.5.1. AUC analysis for diagnostic accuracy of fluorescence variables
The AUC of each fluorescence variables (ΔF, ΔFmax) was presented at optimal cutoff
points calculated from three diagnostic thresholds to evaluate the feasibility of diagnostic
ability according to the depth of microleakage of pit and fissure sealant using QLF-D (Table
7). In all diagnostic criteria, the AUC of the fluorescence parameters ΔF and ΔFmax values
showed high value. When the outer half microleakage of the pit and fissure sealant
(histological score 0 vs 1-3) was cutoff, the AUC of ΔFmax value was 0.91, which showed
very good diagnostic ability.
Table 7. Area under the ROC curve of fluorescence variables at each histology criteria
Histology criteria Fluorescence variables ROC
AUC 95% CI
Histo 0/1-3 ΔF 0.88 0.82-0.93
ΔFmax 0.91 0.87-0.96
Histo 0-1/2,3 ΔF 0.90 0.86-0.95
ΔFmax 0.89 0.84-0.94
Histo 0-2/3 ΔF 0.83 0.77-0.90
ΔFmax 0.83 0.76-0.89
AUC, Area under the curve; CI, confidence interval Histo; Histological score
38
3.1.5.2. Sensitivity, specificity, and AUC curves of fluorescence variables at outer half
microleakage of the pit and fissure sealant
Sensitivity, specificity and AUC were calculated respectively to assess the diagnostic
validity of distinguishing between no microleakage and outer half microleakage
(histological score 0 vs 1-3) in pit and fissure sealant. As a result of histological
examination, when the outer half microleakage was used as a diagnostic threshold, the
AUC value of ΔFmax was 0.91, which showed the highest validity. In ΔF value, the
sensitivity was 79.2, the specificity was 91.4, and in ΔFmax value, the sensitivity was 82.4,
and the specificity was 91.4 (Figure 11).
Figure 11. Sensitivity, specificity, and AUC curves of fluorescence variables at outer half
microleakage of the pit and fissure sealant
39
3.1.5.3. Sensitivity, specificity, and AUC curves of fluorescence variables at inner half
microleakage of the pit and fissure sealant
Sensitivity, specificity and AUC were calculated respectively to assess the diagnostic
validity of distinguishing between outer half microleakage and inner half microleakage
(histological score 0-1 vs 2-3) in pit and fissure sealant. Histological examination showed
that the AUC value of ΔF was 0.90 when the inner half microleakage was used as the
diagnostic threshold, which showed the highest validity. In ΔF value, sensitivity 84.9,
specificity was 82.4, in ΔFmax value, sensitivity was 95.3, and specificity was 68.9 (Figure
12).
Figure 12. Sensitivity, specificity, and AUC curves of fluorescence variables at inner half
microleakage of the pit and fissure sealant
40
3.1.5.4. Sensitivity, specificity, and AUC curves of fluorescence variables at underlying
fissure microleakage of the pit and fissure sealant
Sensitivity, specificity and AUC were calculated respectively to assess the diagnostic
validity of distinguishing between inner half microleakage and underlying fissure
microleakage (histological score 0-2 vs 3) in pit and fissure sealant. When the underlying
fissure microleakage was the diagnostic threshold, the AUC value of ΔF was the highest
validity (0.83) in histological examination. In ΔF value, sensitivity 80.0, specificity was
78.3, in ΔFmax value, sensitivity was 82.2, and specificity was 73.0 (Figure 13).
Figure 13. Sensitivity, specificity, and AUC curves of fluorescence variables at underlying
fissure microleakage of the pit and fissure sealant
41
3.2. Clinical image study results (Study 2)
3.2.1. Study population
In this study, images of occlusal surfaces of 41 pit and fissure sealant teeth from 28
volunteers were obtained. A total of 129 sites were evaluate except for 12 teeth that are difficult
to judge.
3.2.2. Distribution of fluorescence variables according to pit and fissure sealant status
Fluorescence images of pit and fissure sealant captured with a Q-ray pen were used for
analysis obtaining quantitative values such as the average fluorescence loss (ΔF), the maximum
fluorescence loss (ΔFmax), and the average red fluorescence change (Average change of red
fluorescence; ΔR). One examiner evaluated the presence or absence of sealant microleakage
for each fluorescence value. As a result, the absolute values of ΔF, ΔFmax, and ΔR increased
when microleakage was present excluding ΔR in the retention (p<0.05, Table 8). When
retesting to evaluate the reliability of results, the intrarater agreement showed a very good
reliability of 0.89 or more (Table 9).
42
Tabl
e 8.
Dis
tribu
tion
of fl
uore
scen
ce v
aria
bles
acc
ordi
ng to
pit
and
fissu
re se
alan
t sta
tus
Fluo
resc
ence
var
iabl
es
N
ΔF
ΔF
max
ΔR
M
ean±
SD
P-va
lue*
Mea
n±SD
P-
valu
e* M
ean±
SD
P-va
lue*
Mar
gina
l pl
aque
Non
e 27
-4
.62±
4.22
<
0.00
1 -7
.59±
10.6
6 <
0.00
1 1.
46±7
.60
< 0.
001
Pres
ence
10
2 -9
.08±
3.61
-18.
75±1
3.27
13.5
9±13
.73
Mar
gina
l di
scol
orat
ion
Non
e 10
9 -7
.74±
4.25
0.
009
-14.
57±1
2.09
<
0.00
1 10
.01±
13.1
9 0.
042
Pres
ence
20
-1
0.37
±2.6
7
-26.
43±1
6.59
16.7
2±14
.75
Ret
entio
n
Non
e 12
3 -7
.91±
3.89
0.
003
-15.
76±1
2.99
0.
013
10.6
0±13
.33
0.09
1
Pres
ence
6
-13.
04±6
.45
-2
9.66
±18.
41
20
.23±
17.1
6
Car
ies
Non
e 10
2 -7
.16±
3.56
<
0.00
1 -1
1.94
±7.9
0 <
0.00
1 7.
33±1
1.67
<
0.00
1
Pres
ence
27
-1
1.94
±4.1
3
-33.
28±1
6.83
25.1
3±11
.01
All
valu
es a
re e
xpre
ssed
as m
ean
± st
anda
rd d
evia
tions
. * P-
valu
es w
ere
obta
ined
by
inde
pend
ent s
ampl
e t-t
est.
43
Table 9. Intrarater reliability of two images examination methods for evaluating pit and
fissure sealant status
WL: white-light image assessment F: white-light with fluorescence image assessment All values represent Cohen’s kappa values.
3.2.3. Interrater reliability between White-light image and Fluorescence with white-
light image
The maintenance status of pit and fissure sealant was evaluated by classifying it into
four categories. First, the marginal plaque was not able to be analyzed because all values
were evaluated as score 0 in the white light image by two examiners. Interrater agreement
was higher when both white and fluorescence images were used (Table 10, 11, Figure 14).
Figure 14. Comparison of kappa values for interrater reliability between white-light image
and fluorescence with white-light image
45
Table 10. Interrater reliability of two images examination methods for evaluating pit and
fissure sealant status
WL: white-light image assessment F: white-light with fluorescence image assessment All values represent Cohen’s kappa values.
Table 11. Interrater reliability of two images examination methods for evaluating pit and
fissure sealant status
WL: white-light image assessment F: white-light with fluorescence image assessment All values represent Fleiss’ kappa values.
Inter
rater
Measurement parameters
Marginal
plaque
Marginal
discoloration Retention Caries
WL F WL F WL F WL F
A and B - 0.66 0.33 0.24 0.41 0.51 0.33 0.40
A and C - 0.59 0.40 0.31 0.26 0.57 0.29 0.67
B and C - 0.53 0.09 0.24 0.40 0.43 0.67 0.72
Interrater
Measurement parameters
Marginal
Plaque
Marginal
discoloration Retention Caries
WL F WL F WL F WL F
A and B and C - 0.59 0.28 0.25 0.33 0.50 0.46 0.60
46
3.2.4. Distribution of marginal plaque between White-light image and Fluorescence
with white-light image
When examining the presence or absence of plaque, the agreement rate between
examiners was 0.0 ̶ 33.3% in the white-light image, whereas the examination using both
white and fluorescence showed a higher agreement of 53.5 ̶ 72.1% (Table 12).
Table 12. Distribution of marginal plaque in white-light image and fluorescence with
white-light image
WL: white-light image assessment F: white-light with fluorescence image assessment All values represent n (%).
Rater
Marginal Plaque
WL F
None Plaque None Plaque
A 129 (100%) 0 (0%) 36 (27.9%) 93 (72.1%)
B 86 (66.7%) 43 (33.3%) 52 (40.3%) 77 (59.7%)
C 129 (100%) 0 (0%) 60 (46.5%) 69 (53.5%)
47
3.3. Clinical trial results (Study 3)
3.3.1. Study population
In this study, 58 teeth were evaluated in a total of 15 subjects. The average age of the study
subjects was 21.5 years, and the mandibular premolar ratio was the highest with 41.4% (Table
13).
Table 13. Demographic data
Variable Total (N=58)
Age (years)
Mean 21.5
Range 20-27
Sex
Female 15 (100%)
Male 0 (0%)
Dental arch
Maxilla 20 (34.5%)
Mandible 38 (65.5%)
Tooth
Premolar 37 (63.8%)
Molar 21 (36.2%)
48
3.3.2. Interrater reliability between VT and Q-ray view with VT
The evaluation of the maintenance status of the pit and fissure sealant was classified into
five categories. In all three categories, marginal plaque, marginal discoloration, and caries,
assessment with Q-ray view was statistically significantly higher than visual and tactile
assessments in interrater agreement (Figure 15, Table 14). Among them, the agreement rate
of marginal plaque and caries items was the same, and the difference in agreement rate
between visual and tactile assessment (0.22-0.57) and assessment with Q-ray view (0.81-
0.89) was the highest in the marginal plaque assessment items (Table 14).
The presence of dental plaques in the pit and fissure sealant margin is difficult to detect
with the naked eye, but red fluorescence from plaque was observed clearly at the margin
of the sealant when using Q-ray view (Figure 16-A, B). The marginal discoloration of the
sealant was detected as darker than the sound area due to loss of fluorescence in the
discolored area when observing the Q-ray view (Figure 16-C, D). In the case of initial caries,
it was difficult to confirm the initial caries by visual and tactile assessment, but the
fluorescence disappeared when observed with a Q-ray view. When using the Q-ray view,
the caries lesion showed relatively dark fluorescence or red fluorescence due to the activity
of the bacteria compared to the sound tooth (Figure 16-E, F).
49
Table 14. Interrater reliability of two examination methods for evaluating pit and fissure
sealant status
VT: visual and tactile assessment All values represent Cohen’s kappa values.
Figure 15. Comparison of mean kappa values for interrater reliability between VT and
Q-ray view VT: visual and tactile assessment *Exhibited significant differences in mean kappa value between two examination methods (paired t-test, p<0.05)
Inter rater
Measurement parameters
Marginal Plaque
Marginal discoloration
Marginal integrity
Retention Caries
VT Q-ray view
VT Q-ray view
VT Q-ray view
VT Q-ray view
VT Q-ray view
A and B 0.47 0.89 0.55 0.78 0.40 0.30 0.70 0.57 0.61 0.90
A and C 0.57 0.81 0.57 0.69 0.32 0.32 0.57 0.71 0.43 0.84
B and C 0.22 0.84 0.36 0.88 0.63 0.69 0.63 0.62 0.56 0.80
agreement (0.81-0.83, 0.57-0.89, and 0.69-0.91, respectively) than visual and tactile
assessment (0.49-0.54, 0.48-0.55, and 0.42-0.65, respectively).
From these research results, it was confirmed that QLF technology is a valid
technology for quantitatively classifying microleakage of pit and fissure sealant using
fluorescence properties. In addition, the Q-ray pen image and Q-ray view test showed
that it can be used clinically through high interrater agreement. Therefore, it is expected
to be useful for more accurate and objective evaluation and monitoring of the condition
of the pit and fissure sealant using QLF technology in the clinical field.
70
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ABSTRACT (IN KOREAN)
QLF technology
< >
.
.
(Quantitative light-
induced fluorescence, QLF) .
40 160
. QLF-D
77
. QLF-D
(ΔF, ΔFmax)
. , AUC
. QLF-D
(Spearman’s correlation coefficients, rho; -0.72; p <0.001).