Corresponding Author: Adi
Sismadi
Email: [email protected]
INTRODUCTION
Developments The development of digital radiography
technology has had a significant impact on the field of radiology (Ma, 2019). The use of digital radiography has been proven to be
more effective and useful in diagnosing organ diseases and diagnosing diseases (Alshqaqeeq et al.,
2020) ; (Mun et al., 2021). The use of Image Plate (IP) as a Computed
Radiography (CR) component is a material used in digital radiography, apart
from being able to store and capture latent X-ray images, IP can also increase
the accuracy of radiographic images (Setyawan & Suryono, 2014). The use of digital radiography has also led to the development of digital
intraoral dental radiography techniques, such as X-ray, panorama, and X-ray
spectroscopy (Gigi & Padang, 2015). In 2018, 90% of Belgian
radiologists used digital radiography, with 70% using digital detectors and 30%
using sensors (Gijbels et
al., 2005).
CR tools designed explicitly
for intraoral dental examinations have been widely used in dental health,
including in Indonesia (Nuraisya, 2023). However, in reality, the
results displayed by a unique CR dental tool from one of the brands circulating
in Indonesia during a demonstration of the tool at the Pramita Main Clinic,
Martadinata Bandung branch, were not yet able to provide a digital image
display that could be processed such as 100% and 200% image enlargement. The
image processing parameters on the CR console are not many compared to the CR
they already have, so management still wants intraoral radiographic dental
examinations to use the existing CR tool to fulfil the request of several
dentists to get comparative digital radiographic image results of 100% and
200%. The image can be processed in more detail with the help of various tools
during intraoral dental examinations at the Pramita Main Clinic. The existing
use of CR does not produce cassettes and IPs with dimensions as large as films
for intraoral dental examinations. There are 2 types of IP CR, namely the ST
type with dimensions: 35 cm x 43 cm, 35 cm x 35 cm, 24 cm x 30 cm, 18 cm x 24
cm, and 15 cm x 30 cm and there is also the HR type with dimensions: 24 cm x 30
cm, 18 x 24 cm (Kashima et
al., 1994). The choice of IP, often not paid attention to
and can affect image quality, often occurs due to limited knowledge in
selecting IP, so information is needed regarding the IP type and firmness in
selecting the IP to be used (Amtha et al., 2020).
Based on this background, the
aim of this research is to assess the quality of digital images from 18 x 24 cm
Imaging Plates of the ST (Standard) and HR (High-Resolution) types by
engineering the dimensions on intraoral dental radiographic examinations, so
that quality differences can be identified�images on each type of Imaging Plate
Computed Radiography. The benefit of this research is knowledge of the IP FCR's
ability to obtain digital images of intraoral dental radiographs, where the IP
FCR has differences. Dimensional engineering is carried out so that it can fit
into the mouth. It can provide information about how much influence different
types of IP FCR have on the resulting digital image so that it can be used in
intraoral dental radiology examinations by fellow radiographers as a medical
support tool.
METHOD
This type of
research is experimental using the subjective quality assessment method of
digital images in intraoral dental radiographic examinations using IP FCR ST
and HR. The current research population is all data in digital images of
intraoral dental radiographs examined at the Pramita Main Clinic, Matraman
branch, Jakarta. 2. This research sample was taken from a portion of the
research population that met the inclusion and exclusion criteria. The criteria
are a) Inclusion of patients with an explicit diagnostic record in the
dentist's introduction and images with sufficient collimation (not cut or
superposed) so that the desired object is achieved. b) Exclusion of patients
whose image does not show the object of interest and also has an unexposed area
around it (clear at the top/bottom/right/left), the object is cut off and there
is superposition. The instruments required in this research are Planmeca Promax
dental X-ray aircraft, IP FCR (ST and HR), digital image processing (FCR), and
data processing (laptop, Matlab/MathWorks, SPSS IBM).
RESULTS AND DISCUSSION
Digital Image Data Analysis of Intraoral Dental Radiography
Kappa Test
The research involved two respondents filling out a
questionnaire, respondents practising in the same location, different ages, and
dental graduates. The results of the two doctors' assessments were analyzed
using the kappa test, shown in Table 1. Respondents assessed the image in terms of whether it
appeared clearly or less clearly.
Table 1. Kappa Test for Respondent 1 and Respondent 2
|
|
|
Value
|
Asymptotic Standard Error a
|
Approximate T b
|
Approximate Significance
|
|
Measures of Agreement
|
Kappa
|
,618
|
,167
|
2,868
|
,004
|
|
N of Valid Cases
|
|
14
|
|
|
|
a. I am not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null
hypothesis.
Bivariate
Analysis
1) Normality test
Table 3
displays the initial steps in the analysis before proceeding to the next stage,
namely the normality test of the variables presented in this research.
Table 2. PIQE, MSE and PSNR Score Normality Test.
|
|
Kolmogorov
Smirnov a
|
Shapiro-Wilk
|
|
IP ST and
HR
|
Statistics
|
df.
|
Sig.
|
Statistics
|
df.
|
Sig.
|
|
PIQE Score.
Error
Value.
Ratio
Signal Value.
|
.109
,257
,202
|
60
60
60
|
,072
,000
,000
|
,984
,840
,872
|
60
60
60
|
,598
,000
,000
|
*. This
is a lower bound of the true significance
a. Lilliefors Significance Correction
It can be
seen from Table 3 that the Shapiro-Wilk Sig value. PIQE score sig value. 0.598
(> 0.05) normal distribution, MSE value sig. 0.000 (< 0.05) non-normal
distribution, PSNR value sig. 0.000 (< 0.05) non-normal distribution, one
normal distribution (PIQE Score) and two other data non-normal distributions (MSE
and PSNR).
2)
Mann-Whitney Difference Test
The results of the normality test show that the results are not normally
distributed, so the Non-Parametric test is continued. Because the two materials
were tested with different samples, the difference test was continued with the
Mann-Whitney test. Table 4 displays the results of the
Mann-Whitney Test on these four variables.
Table. 3 Mann-Whitney Test PIQE, MSE and PSNR scores between
Pixel 10 and Pixel 20 Test Statistics
|
|
PIQE Score
|
Error Value
|
Ratio
Signal Value
|
|
Mann-Whitney U
Wilcoxon W
Z
Asymo. Sig.
(2-tailed)
|
280,000
745,000
-2,513
.012
|
312,000
777,000
-2,040
.041
|
312,000
777,000
-2,040
.041
|
a.
Grouping Variables: ST and HR
Hypothesis table 3
H0 = Both Populations are
Identical (Digital et al. of Both IPs Influence Image Quality but Are Not
Significantly Different)
H1 = The two populations are
not identical (the digital image results of both IPs influence image quality
but are significantly different)
Asymp value. Sig (2-tailed) PIQE score 0.012 (< 0.05), MSE 0.041 (<
0.05) and PSNR 0.041 (< 0.05), so all values are < 0.05. This value is
based on decision-making in the Mann-Whitney Test, it is stated that IP FCR ST
and IP FCR HR have different image quality. H0 = REJECTED.
Steps for Testing the Quality of Digital Images of Intraoral Dental
Examination Radiographs at the Paramita Main Clinic, Matraman branch
Testing involves direct patient samples on the basis that the IP used has
been tested to provide good results for all radiographic examinations other
than intraoral dental examinations by engineering the dimensions to suit the
dimensions of conventional dental film, namely 3.1 x 4.1 cm, so it can fit into
the mouth. The patient being examined also brings a referral letter from the
dentist for an intraoral dental examination according to the doctor's and
patient's needs so that the cover letter can be used as a consent form for
taking dental images. Patient data and patient safety can be guaranteed because
the Laboratory Information System (LIS) system owned by the research site is
excellent, and K3 patient handling is running well.
Testing involving researchers in collecting and processing data must have
a good and correct basis and reference. This is done so that the results
obtained are maximum so that conclusions and suggestions are not doubtful and
precise when making decisions. With the help of applications, consultations and
media, constructive input and output can be accounted for.
Testing involving respondents as assessors of the image displayed is
sufficient to provide options for making decisions other than existing
applications. Although this assessment is based on the respondent's experience,
it can at least represent the many respondents in this study.
The data in the form of digital dental images is displayed in the form of
a selection of the best data for both ST and HR based on the researcher's
observations without any intervention from other parties. This selection is
carried out so that no element of favouring one of the instruments studied
exists.
The application used in this research is also a standard for medical
digital imaging purposes, namely the Fuji System and PACS, which can provide
output and input in the form of DICOM. External image processing also uses the
Matlab application (Yudha et al., 2023). Researchers also use the best application from IBM
(SPSS) for statistics.
The use of the PIQE score which has the ability to provide a score on
digital images without the need for intervention on the original image, MSE and
PSNR are also digital image quality parameters that can be obtained after
intervention on the original digital image (Gaussian filter).
Digital Image Quality Testing of Intraoral Dental Examination Radiography
at the Pramita Main Clinic, Matraman branch.
The results of assessing digital image quality parameters based on the
selection of images taken provide a variety of numbers that are directly
calculated from the Matlab application, both online and offline. The commands
used are standardized to make it easier to process all data. The PIQE Score
value taken directly from the image has been converted to grayscale; for the
MSE and PSNR values, additional intervention was given to get the value out;
the researcher used the Gaussian filter command. The MSE and PSNR values are
obtained after taking a digital image given a filter.
The data is then processed statistically, starting with a normality test,
which produces a non-normal distribution, so the next test step is the
Mann-Whitney test. Test results p value sig. All below 0.05 (PIQE Score 0.012,
MSE 0.041 and PSNR 0.041).
The images displayed as attachments to the questionnaire are separated
between sheets one and 2, where the code is given randomly; respondents have to
choose whichever image seems less clear. After being given the attachment, both
respondents stated that the appearance was good enough to be evaluated.
However, because the aim was to compare the image quality between the two IPs
with different pixel sizes, the respondents were willing to give clear, unclear
and unclear values to the image displayed.
The results of respondent 2's assessment were that the percentage of
"Clear" scores on ST was 42.86% and HR was 57.14%, "Not
Clear" on ST was 42.86% and HR was 28.57%, the score was "Not
Clear", ST and HR have the same value, namely 14.29%.
Digital Image Data Analysis of Intraoral Dental Radiography
For respondent consistency, it can be seen from the accumulated
assessments using the Kappa test that Respondent 1 and Respondent 2 have a
p-value of 0.004. Kappa value 0.618. Differences in MSE, PSNR, and PIQE score
when using ST and HR, a different test must be carried out, previously a
normality test for MSE, PSNR, and PIQE Score must be carried out. It can be
seen from Table 4.6 Shapiro-Wilk Normality Test that the Sig value. Of the 6
data, one has a Normal distribution (Signal et al. on ST), and the other 5 have
a non-normal distribution. So, the normality test is not normally distributed,
so non-parametric tests are an option in the next test.
For respondent consistency, it can be seen from the accumulated
assessments using the Kappa test that Respondent 1 and Respondent 2 have a
p-value of 0.004. Kappa value 0.618. For differences in MSE, PSNR, and PIQE
scores when using ST and HR, a different test must be carried out; previously,
a normality test for MSE, PSNR, and PIQE Scores must be carried out. It can be
seen from Table 2 that the Shapiro-Wilk Normality Test value Sig. Of the 3 data, 1 has a
normal distribution, and the other 2 data have a non-normal distribution. So,
the normality test is not normally distributed, so non-parametric tests are an
option in the next test.
Selection of 2 types of IP FCR ST and HR, two gradations to ordinal with
test results for three image quality parameters not normally distributed, then
non-parametric test using Mann Whitney Test, test results p value sig. All
below 0.05 (PIQE score 0.012, MSE 0.041 and PSNR 0.041) means that H0 is
rejected, meaning that the IP FCR types ST and HR types have differences in
image quality between ST and HR.
The IP FCR HR used for mammography has almost the same characteristics as
the IP FCR ST for other radiology applications. However, there are some
differences to note. One of the most striking differences is pixel size. IP FCR
HR has a smaller pixel size, namely 75 x 75 microns. This smaller pixel size
allows the FCR IP to capture more image details, resulting in better image
quality. Another difference to note is sensitivity. IP FCR HR has a higher
sensitivity, namely 1500 mJ/mm2. This higher sensitivity allows IP FCR HR to produce
images with better contrast, even in dense breast conditions. The following is
a comparison table of pixel characteristics between IP FCR HR and IP FCR ST for
other radiology applications:
The following is a comparison table of pixel characteristics between IP
FCR HR and IP FCR ST for other radiology applications:
Table 4 . Characteristics of P FCR HR and ST
|
Characteristics
|
IP FCR HR
|
IP FCR ST
|
|
Pixel size
Resolution
Sensitivity
|
75 x 75 microns
500dpi
1500 mJ/mm2
|
100 x 100 microns
500dpi
1000 mJ/mm2
|
There is no difference in the possibility that the type of IP used has
almost the same characteristics as both ST and HR; even though the IP product
code provides names for ST (10 pixels) and HR (10 pixels), the coding provided
by the product is limited as a differentiator, between IP specifically for
mammography (HR) and non-mammography (ST). This may also occur because the
control variables are not appropriate, so HR and ST should be the same
regarding the results of calculating digital parameters, but there is no
difference.
In research (Sudin
et al., 2015) using a CR system using step
wedge samples, the aim was to determine the effect of different IP pixel sizes
(0.168 mm, 0.115 mm and 0.097 mm) on the quality of digital radiographic
images, with the results obtained being greater The pixel size used, the greater
the density and contrast values in the digital radiographic image, so that the
values obtained improve the quality of the digital radiographic image.
In research (Ningtias
et al., 2016) using a CR system and a sample
in the form of a phantom made of copper measuring 15 x 15 cm with a thickness
of 1 mm, the aim was to determine the quality of digital images by using
spatial resolution calculations with the Matlab-based MTF method. The results
are that the higher the voltage used, the better the image quality with an
optimal current in the 4-8 mAs range with an average spatial resolution value
of 7.26 lp/mm.
In research (Kuramoto
et al., 2020), the phantom as the object used
in this research is a self-made step phantom which consists of 12 steps with a
thickness interval of 1.0 mm. Each step has seven holes with a diameter of 1.0
mm drilled at sequentially increasing depths from 0.05 to 0.35 mm. This phantom
is used for visual evaluation in research. This research also uses three types
of PSP pixels, namely High Speed (HS), High Resolution (HR), and Super High
Resolution (SHR), and evaluated with Modulation Transfer Function (MTF) and
Normalized Noise Power Spectrum (NNPS) to show that the pixel size of a digital
intraoral radiography system has a significant influence on the characteristics
of the resulting image. The smaller the pixel size, the higher the resulting
image resolution, but the larger the image file size, the longer the scanning
time.
In research (Watanabe
et al., 2022) using a CR and PSP system in the form of a Dual
Imaging Plate (DIP) and Conventional Single Imaging Plate (CSIP) with samples
using a Porcine Mandible Embedded in Acrylic Resin phantom, aiming to evaluate
the CNR, spatial resolution and subject quality of the DIP. The results are
that the CNR value on DIP is higher when compared to the CNR value on FIP, the
decrease in spatial resolution is limited on DIP, and the subjective image
quality on DIP is higher than on FIP.
(Kamburoğlu
et al., 2022) this study aims to compare the
performance of CMOS and PSP intraoral detectors in terms of digital image
quality of dental radiography, measuring the patient's radiation dose, and the
length of time carrying out intraoral dental examinations. This study also aims
to evaluate patient preferences and levels of satisfaction with CMOS and PSP.
The results show that the CMOS intraoral detector has advantages in terms of
time efficiency and patient comfort, while the PSP detector provides better
digital radiographic image quality. However, there was no significant
difference in patient radiation dose between CMOS and PSP.
The novelty of the research is an attempt to manually engineer
conventional IP CR dimensions into dimensions that can be used for intraoral
dental research, without using a special scanner. When using real objects,
namely patients, comparisons between different sizes give almost no difference.
Both can display an image that can be assessed by respondents.
CONCLUSION
Based on the
research results, it can be concluded that the effect of different pixel sizes
on digital image quality can be proven that: 1) Manual dimensional engineering
can provide digital images that are readily accepted for IP ST and HR, even
though IP HR has a value of "Clear" (57.14 %) and IP ST (42.86%). 2)
Significance analysis test related to image quality <0.05 on the PIQE score
(0.012), MSE (0.041), and PSNR (0.041) shows that there is a difference in
quality between the two IPs. 3) significant differences exist between the two
IPs, which could be the best choice between the FCR IP and the FCR HR IP.
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