|Year : 2019 | Volume
| Issue : 5 | Page : 665-669
|Effect of different exposure times on caries detection and pixel value in a wireless digital system
Daniela Pita De Melo1, Andrea Dos Anjos Pontual2, Francisco Haiter-Neto3, Marcelo Correa Alves4, Frab Norberto Bóscolo3, Paulo Sérgio Flores Campos5
1 Department of Oral Diagnosis, Division of Oral Radiology, Campina Grande Dental School, State University of Paraíba (UEPB), Campina Grande, Paraíba, Brazil
2 Department of Clinical and Preventive Dentistry, Federal University of Pernambuco (UFPE), Camaragibe, Brazil
3 Department of Oral Diagnosis, Division of Oral Radiology, Piracicaba Dental School, Campinas University, São Paulo, Brazil
4 Department of Oral Medicine, Division of Oral Anatomy, Campinas University, São Paulo, Brazil
5 Department of Oral Diagnosis, Division of Oral Radiology, Piracicaba Dental School, Campinas University (UNICAMP), Piracicaba, São Paulo, Brazil
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|Date of Submission||28-May-2012|
|Date of Decision||19-Jul-2013|
|Date of Acceptance||13-Sep-2017|
|Date of Web Publication||18-Dec-2019|
| Abstract|| |
Objectives: The aim of this study was to assess, using the CDR Wireless®, the effect of different exposure times on caries detection and pixel intensity values. Materials and Methods: Forty teeth were x-rayed using a Schick CDR Wireless sensor at eight different exposure times – 0.06, 0.10, 0.13, 0.16, 0.20, 0.25, 0.30, and 0.32 s. Four observers evaluated the images for presence of carious lesions scoring proximal surfaces of each tooth on a 5-point scale. Scores were compared to histological sections of the teeth. Accuracy was evaluated by means of ROC curve analysis. Radiographs of an aluminum step wedge were obtained using the same eight exposure times. Pixel intensity measurements were obtained, and mean pixel values were statistically analyzed using linear regression. Results: The Az for each exposure time varied from 0.53 to 0.62. Two-way analysis of variance and Tukey test demonstrated that the exposure time of 0.25 s presented the best result and was significantly higher than 0.30 s and 0.35 s. In regard to mean pixel values, two different behaviors were observed, and the exposure time of 0.20 s presented mean pixel values in both phases. Conclusion: The performance of the exposure times from 0.06 s to 0.25 s was satisfactory for proximal caries detection, and 0.25 s is the best as indicated for this finality. Clinical Relevance: Considering that a reduction of exposure time represents a reduction of patient exposure dose, and this reduction cannot neglect image quality, the behavior of any digital system must be carefully evaluated.
Keywords: Caries detection, dental caries, dental radiography, digital imaging
|How to cite this article:|
Melo DP, Pontual AD, Haiter-Neto F, Alves MC, Bóscolo FN, Flores Campos PS. Effect of different exposure times on caries detection and pixel value in a wireless digital system. Indian J Dent Res 2019;30:665-9
|How to cite this URL:|
Melo DP, Pontual AD, Haiter-Neto F, Alves MC, Bóscolo FN, Flores Campos PS. Effect of different exposure times on caries detection and pixel value in a wireless digital system. Indian J Dent Res [serial online] 2019 [cited 2022 Jan 20];30:665-9. Available from: https://www.ijdr.in/text.asp?2019/30/5/665/273425
| Introduction|| |
Direct acquisition image detectors consist of a solid sensor containing a light-sensitive charged-couple device (CCD) or complementary metal oxide semiconductor (CMOS) chip and a scintillator layer that converts X-rays into light, which permits the use of lower exposure times than those normally used for conventional film.,, The images generated by those image receptors have demonstrated diagnostic precision comparable to conventional film when diagnosing proximal caries.,,
In 2003, Schick Technologies Inc., (Long Island City, USA) introduced the Schick CDR Wireless® digital system that uses CMOS technology and a radiofrequency transmitter inside the solid sensor instead of a traditional fiber optic cable. The Schick CDR Wireless® system innovates image acquisition because when its sensor is exposed to X-ray, Image data is transmitted to the base station using radiofrequency waves. This procedure takes only a few seconds to be done. The antenna converts the received information in electric signals that will be converted in binary digits that are sent to the computer by a fiber optic cable connected to the computer's USB port.
Even though digital radiography is considered a relatively modern method of diagnosis, the principle of common safety related to X-ray radiation stays unaltered: the amount of desired information must be obtained with the lowest amount of radiation reasonably possible. Literature shows that the exposure dose is usually lower in intraoral digital radiography than in conventional radiography, and that is the argument most frequently used by manufacturers to sell those systems. Because a radiographic examination is an important auxiliary method for proximal caries detection, to evaluate the effectiveness of digital systems on professional daily routine, it is common for digital systems to be tested for their quality on caries diagnosis.,,,,,,,,,,,,
Considering that a reduction of exposure time represents a reduction of the dose to which the patient is exposed and that this reduction cannot neglect radiographic diagnostic image quality, this study aims to evaluate the effect of different exposure times on caries diagnosis and mean pixel value.
| Material and Methods|| |
This study was approved by Piracicaba Dental School Ethics Committee (Protocol number 141/2009). Fifty extracted human teeth (10 canines, 20 premolars, and 20 molars) were mounted in 10 blocks of silicone, with four test teeth (two premolars and two molars) and one nontest tooth (canine) each. The premolars and molars had either no or little demineralization in their proximal surfaces.
The digital images were acquired using a GE 1000 (General Electric Company, Milwaukee, WI, USA) unit operating at 65 kVp and 10 mA. A 1.2-cm thick acrylic plate was placed adjacent to the models as a soft-tissue equivalent material. To ensure reproducible imaging geometry, the blocks of silicone were stabilized on a customized acrylic device that was used to provide a distance of 34 cm between the target and image receptor, a central X-ray beam orientation, and a 2 cm tooth-receptor distance.
The chosen exposure times were 0.06, 0.10, 0.13, 0.16, 0.20, 0.25, 0.30, 0.32 s, which corresponded in the X-ray system to impulses to 4, 6, 8, 10, 12, 15, 18, and 21i, respectively.
A Schick CDR Wireless® digital system sensor size 2 and its battery were used. Before exposure, each phantom was fixed to the acrylic apparatus. For each phantom, 4 images were obtained, one for each test tooth, and 40 radiographic images were made per exposure time, totaling 320 images. All images were acquired in 8 bits, stored in tiff format, and identified by a code indicating tooth, phantom, and exposure time.
Six independent observers, all of them oral radiologists with at least 5 years of experience, assessed all 320 images for the presence of caries lesions. The digital images were displayed on a 17” color monitor placed in a quiet room with dimmed light. The images were displayed in Microsoft PowerPoint in random order, 20 images at a time. Enhancement of the images was not allowed because the aim of the study was to evaluate the exposure time as an isolated criterion. The presence of proximal caries lesions was scored on a 5-point confidence scale where 1 = definitely not present, 2 = probably not present, 3 = unsure, 4 = probably present, and 5 = definitely present. For validating the presence of true caries, histological validation was performed as gold standard.
Pixel intensity analysis
To objectively evaluate the image data for the eight studied exposure times, pixel intensity analysis was performed. An aluminum step wedge with eight increments of 2 mm each was positioned on the same acrylic device used to acquire the images for the subjective analysis and was X-rayed using the same parameters established before. Ten images per exposure time were obtained. The images were analyzed using EMAGO/Advanced version 3.43 Software (Acta Oral Diagnostic Systems, Louwesweg, Amsterdam, The Netherlands). Pixel intensity measurements were made using the histogram analysis tool, on a rectangular region of interest set at the center of the step-wedge image including all steps right through the entire step-wedge length.
To assess the precision for diagnosis (accuracy) of the images acquired in different exposure times, the areas (Az) under the receiver operating characteristic (ROC) curve were calculated. Two-way analysis of variance was applied using an appropriate model for block experiments so that the exposure time was the main factor to be evaluated.
Average pixel intensity values for each exposure time were subjected to linear regression once it was desired to test a continuous numeric variable (pixel) treated as a response variable with the exposure time as a predicting variable.
| Results|| |
Of the 80 microscopically evaluated proximal surfaces, 48 (60%) were sound and 32 (40%) presented caries lesions in enamel.
The mean values for the area under the ROC curve, standard deviation, confidence intervals, and the differences between the modalities are shown in [Table 1].
|Table 1: Means, standard deviations, confidence intervals (95%), Receiver operating characteristic curve (Az) and Tukey's test (a=0.05)|
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The mean ROC curve areas varied between 0.53 and 0.62. For the Schick CDR Wireless® digital system, the exposure time of 0.25 s (15 i) presented the higher accuracy result. The time range from 0.06 s to 0.20 s (4–12 i) was considered an acceptable interval of exposure time for caries diagnosis using the wireless system and did not present statistical difference from the 0.25 s exposure time. The exposure times of 0.30 s and 0.35 s presented the worst results and were significantly different from the exposure time of 0.25 s.
The pixel mean values for the eight exposure times were determined using the pixel values of all the repetitions.
The linear regression model is shown in [Figure 1], where the 10 vertical diamond-shaped figures represent the 10 mean pixel values for each exposition of the aluminum step wedge for each exposure time evaluated, and the red squares represent the mean of those pixel values for the two different pixel value behaviors presented.
|Figure 1: Images acquired from one phantom in all the evaluated exposure times|
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[Figure 2] revealed the necessity to include a differential effect related to those two phases of pixel intensity values: the first one, when the pixel values are over 120, and a second phase, when the pixel values are under 120. The estimated model is represented in the following equation: Pixel = 180,5690–4,2718* (Phase = 1) – 6,4698* Time impulse + 4,4366* Time impulse* (Phase = 1)**
|Figure 2: Linear regression model for prediction of image pixel intensity related to 8 exposure times|
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The effects of the parameters were tested using the Student's t-test and are shown in [Table 2].
|Table 2: Analysis of the parameters of the linear regression model with dummy variable (pixel data × exposure times)|
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The tests strongly indicated (P < 0.01) the existence of a significant effect of the time and the interaction between time and phase on pixel values. There was no observed evidence (P > 0.05) of the existence of a significant effect of the phases isolated on the pixel values.
This indicates that in phase 1 (pixel values over 120), there is a time effect on the pixel, while in phase 0 (pixel values under 120), the time effect is higher for the pixel values, which indicates two distinct behaviors. During phase 0, the addition of one pulse time unit corresponds to a subtraction of 6.47 pixel units, which could be represented by the following equation: Pixel(Phase=0) = 180,5690–6,4698* Time impulse.
During phase 1, pixel values over 120, the addition of one exposure time pulse unit leads to the subtraction of 2.0332 pixels, represented by the following equation: Pixel(Phase=1) = 176,2972–2,0332* Timeimpulse
| Discussion|| |
Solid sensor features require a higher number of radiographic exposures to obtain the same quantity of information available in the images acquired using other image receptors, such as conventional film and phosphor-stimulable plates (PSP)., Sometimes, those characteristics can lead to repetitions, raising the exposition dose. Determining the ideal exposure time or the ideal range of exposure times to obtain high-quality digital images should not be neglected when using solid sensor systems.
Since each digital system has its own image resolution patterns, tests must be performed individually for each system. Evaluating five different methods of image acquisition, using a large range of exposure times, Berkhout et al. observed different results related to the preferred exposure time for each evaluated system. While solid-state digital systems presented preferred times of 0.13 s for Sirona and 0.35 s for MPDx, the phosphor plate systems presented high exposure times as 1.21s for Digora® and 1.16s for DenOptix®.
When analyzing subjectively the overall image quality, comparing the CMOS and CCD versions of wired Schick CDR systems, Kitagawa et al. varied exposure times from 0.05 to 0.40 s, obtaining the best results with exposure times of 0.09 s for the CMOS version and 0.12 s for the CCD version. Those results demonstrate that similar systems can present different ideal exposure time values. In this study, the wireless version of the Schick CDR was evaluated using histological confirmation, and the exposure time that presented higher results was found to be 0.25 s (15 i), and the acceptable time exposure range was 0.06–0.20s (4–12i), similar results to those found for the wired versions of Schick CDR.
When comparing different digital systems in the detection of proximal caries, Haiter-Neto et al., using the Schick CDR Wireless® system, chose the exposure time of 0.22 s for the premolar region and 0.26 s for the molar region, achieving an accuracy value of 64% for this system. Not only the accuracy value but also the selected exposure times are similar to the ones that achieved the best result in our study.
The most intriguing finding of this study was the behavior of the mean pixel value at the exposure time 0.20 s (12 i). At this exposure time, it was possible to notice two distinct behaviors. The mean pixel values evaluated were divided equally between phases 1 and 0, what could be an influence of the system's battery. It was expected that the mean pixel values would decrease with the increase of the exposure time since one is inversely proportional to the other. Furthermore, as the mean pixel value decreases, the image density increases. The exposure time with the highest ROC value was found in the beginning of the second phase, although the other acceptable exposure times for caries diagnosis were included on phase 1. It is known that the evaluation of caries lesions should be done in images with high density and contrast, but as it was observed in this study, there is a limit to the density value that shows the best results.
Kitagawa and Farman observed that the behavior of the mean pixel value curve differs among digital systems. For CCD systems, high gray levels (low mean pixel values) are observed when the exposure time is increased, but at a certain point, the gray level seems to saturate and stop increasing with higher exposure times, differing from what was observed in a PSP system, in which the increase of the exposure time causes a gradual increase of gray level in the resulting image. Our data differ for both of the systems evaluated in the referred study.
An important characteristic of this digital system is its wireless connection, as the acquired data are transmitted by radiofrequency waves. When the Schick CDR Wireless® digital receptor is exposed to radiation, the electric charge generated by the exposure of the silicon crystals is transformed in radiofrequency waves. Those waves are captured by system's base station antenna and transformed into binary units that are transmitted to the computer through a fiber optic cable. This system has a nonrechargeable battery that permits the data transmission to the base station antenna.
The objective results presented two distinct phases that may be related to the energy spent from the battery emitting radiofrequency waves. According to the manufacturer, the battery should be replaced only when the red light indicates that the battery has no charge. In the other two situations, green light and altering green and red lights, high-quality images are acquired with no interference of the battery charge on the energy spent during the use of the system. The manufacturer's website reports that the Schick CDR Wireless® system battery has a life cycle of 500 exposures. The battery used during this study was brand new and exposed 400 times, not exceeding the maximum limit of exposures.
A variation on the transmitted energy received could have occurred during the exposures with the exposure time of 0.20 s (12 i). The new battery, which should not allow charge variation, or if that were to happen, the natural tendency should be a decrease in charge with a consequent decrease of the image data transmitted, with a decrease of density and increase of mean pixel value.
Our findings differ from Tsuchida et al., a study that compared both Schick CDR versions, wired and wireless, and found similar behaviors between them when evaluating dose-response curves and mean pixel value. Their results found that with the increase of exposure dose, the mean pixel value would decrease until a point of stagnation, where it would not suffer any interference from the exposure dose. To better explain the differences between the studies, it is necessary to perform an evaluation with a higher number of sensors, and consequently different batteries.
| Conclusion|| |
The exposure times from 4i to 15i represent an acceptable exposure time range for caries diagnosis using Schick CDR Wireless system. The exposure times from 4i to 21i presented a distinct behavior during objective analysis. We do not know why the sensor abruptly changes its behavior, and also do not know why it happens in the same range of exposures, but it is known that this change permits an ideal mean pixel value for caries detection to be achieved with a low level of exposure time. The behavior of the Schick CDR Wireless® battery and its influence on the mean pixel value should be the objective of future specific evaluation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Haak R, Wicht MJ. Grey-scale reversed radiographic display in detection of approximal caries. J Dent 2005;33:65-71.
Hintze H, Wenzel. Influence of the validation method on diagnostic accuracy for caries. A comparison of six digital and two conventional radiographic systems. Dentomaxillofac Radiol 2002;31:44-49.
Hintze H, Wenzel A, Frydenberg M. Accuracy of caries detection with four storage phosphor systems and E-speed radiographs. Dentomaxillofac Radiol 2002;31:170-5.
Abreu, M Jr, Tyhndall, DA, Ludlow, JB. Detection of caries with conventional digital imaging and tuned aperture computed tomography using CRT monitor and laptop displays. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1999;88:234-8.
Haak R, Wicht MJ, Noack MJ. Conventional, digital and contrast-enhanced bitewing radiographs in the decision to restore approximal carious lesions. Caries Res 2001;35:193-9.
Haiter-Neto F, dos Anjos Pontual A, Frydenberg M, Wenzel A. A comparison of older and newer versions of intraoral digital radiography systems - Diagnosing noncavitated proximal carious lesions. J Am Dent Assoc 2007;138:1353-9.
Haiter-Neto F, dos Anjos Pontual A, Frydenberg M, Wenzel A. Detection of non-cavitated approximal caries lesions in digital images from seven solid-state receptors with particular focus on task-specific enhancement filters. An ex vivo
study in human teeth. Clin Oral Investig 2008;12:217-23.
Gelsky DE, Baker CG. The ALARA concept. Population exposures from x-rays in dentistry: As low as reasonably achievable? J Can Dent Assoc 1984;50:402-3.
Kathingal SM, Shrout MK, Comer C, Brady C. Rating the extent of surface scratches on photostimulable storage phosphor plates in dental school environment. Dentomaxillofac Radiol 2010;39:179-83.
Kitagawa H, Sheetz JP, Farman AG. Comparison of complementary metal oxide semiconductor and charge-coupled device intraoral X-ray detectors using subjective image quality. Dentomaxillofac Radiol 2003;32:408-11.
Wenzel A, Borg E, Hintze H, Gröndahl HG. Accuracy of caries diagnosis in digital images from charge-coupled device and storage phosphor systems: an in vitro
study. Dentomaxillofac Radiol 1995;24:250-4.
Møystad A, Svanaes DB, Risnes S, Larheim TA, Gröndahl HG. Detection of approximal caries with a storage phosphor system. A comparison of enhanced digital images with dental X-ray film. Dentomaxillofac Radiol 1996;25:202-6.
Nielsen LL, Hornoe M, Wenzel A. Radiographic detection of cavitation in approximal surfaces of primary teeth using a digital storage phosphor system and conventional film, and the relationship between cavitation and radiographic lesion depth: an in vitro
study. Int J Paediatric Dent 1996;6:167-72.
Svanaes DB, MØystad A, Risnes S, Larheim TA, Gröndahl HG. Intraoral storage phosphor radiography for approximal caries detection and effect of image magnification. Comparison with conventional radiography. Oral Surg Oral Med Oral Pathol Oral Radiol Oral Endod 1996;82:94-100.
Versteeg KH, sanderink GCH, Velders XL, van Ginkel FC, van der Stelt PF. In vivo
study of approximal caries depth on storage phosphor plate images compared with dental X-ray film Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1997;84:210-3.
Schamage P, Nergiz I, Pfeiffer P, Platzer U. Diagnostic accuracy of in vitro
digital radiographs. Dentomaxillofac Radiol 1997;26:274-5.
Syriopoulos K, Velders XL, Sanderink GCH, van der Stelt PF. Sensitometric and clinical evaluation of new F-speed dental X-ray film. Dentomaxillofac Radiol 2000;30:40-44.
Kitagawa H, Farman AG, Sheetz JP, Brown WP, Lewis J, Benefiel M, Kuroyanagi. Comparison of three intra-oral storage phosphor systems using subjective image quality. Dentomaxillofac Radiol 2000;29:272-6.
Wenzel A, Hintze H, Kold LM, Kold S. Accuracy of computer-automated caries detection in digital radiographs compared with human observers. Eur J Oral Sci 2002;110:199-203.
Hintze H, Wenzel A. Diagnostic outcome of methods frequently used for caries validation: A comparison of clinical examination, radiography and histology following hemisectioning and serial tooth sectioning. Caries Res 2003;37:115-24.
Berkhout WER, Sanderink GCH, van der Stelt PF. Does digital radiography increase the number of radiographs? A questionnaire study in Dutch dental practices. Dentomaxillofac Radiol 2003;32:124-7.
Berkhout WER, Beuger DA, Sanderink GCH, van der Stelt. The dynamic range of digital radiographic systems: dose reduction or risk of overexposure? Dentomaxillofac Radiol 2004;33:1-5.
Wenzel A. A review of dentists' use of digital radiography and caries diagnosis with digital systems. Dentomaxillofac Radiol 2006;35:307-14.
Schick Technologies. Inc., Schick CDR Wireless/ SDX Software User Guide. Long Island, NY; 2004.
Tsuchida R, Kazuyuki A, Endo A, Funahashi I, Okano T. Physical properties and ease of operation of a wireless intraoral x-ray sensor. Oral Surg Oral Med Oral Pathol Oral Radiol Oral Endod 2005;100:603-8.
Dr. Daniela Pita De Melo
R. Baraúnas, 351-Universitário, Campina Grande - PB, 58429-500 (83) 3315- 3300
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2]
[Table 1], [Table 2]
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