**4.2.2 Digital radiography**

Digital radiography is a complementary method that has been available in dentistry for more than 25 years, but digital imaging has not replaced conventional film-based radiography completely. Studies have shown that the number of dental professionals using digital radiography in clinical practice range from 11% to 30%. This fact can be attributed to the financial investment required to replace conventional radiography with digital imaging and also for the hesitancy to use a new technology, since it requires additional training on basic computer skills. On the other hand, a professional who is starting his/her career will not find huge differences in costs to acquire a conventional or a digital radiography system. Practitioners should remember that conventional radiography also involves costs for items, such as radiographic films, film mounts, processing solutions and time needed for cleaning the film processor (van der Stelt, 2008).

Studies have shown many advantages of digital radiography compared with conventional radiography. These include image acquisition process in real time, since the image is displayed immediately after exposure and no processing had to be performed. Other benefits include reductions in radiation dose (between 5% to 50% of the dose needed for conventional radiography) to obtain quality diagnostic images, time savings and digital manipulation of the image to enhance viewing, avoiding unnecessary or repeated radiographs. Digital images facilitate communication and case discussion among dental professionals, being a visual aid to be shown to the patient on the computer screen, increasing the confidence and credibility in the treatment-decision making process. However, the primary disadvantages of digital systems include the rigidity and thickness of the sensors, the high initial system cost and unknown sensor lifespan (Bin-Shuwaish et al., 2008; van der Stelt, 2008; Wenzel, 1998).

It is imperative to understand the digital radiography system to understand the principle of image manipulation. A digital image consists of a set of cells that are ordered in rows and columns, forming a table. Each cell is characterized by three numbers: the x-coordinate, the y-coordinate and the gray value. The gray value is a number that corresponds with the Xray intensity at that location during the exposure of the digital sensor. Individual cells are called "picture elements", which had been shortened to "pixels". The numbers describing each pixel are stored in an image file in the computer. This feature is an essential difference between conventional and digital radiographs, once digital images can be modified after they have been produced. Thus, the user can apply mathematical operations (special algorithms or filters) to modify the pixel values, improving the image quality and modifying other characteristics, such as zoom, contrast, density and brightness of an image. The image numbers are converted into gray values and these are displayed on the computer screen as analog data. Then, the professional can assess and interpret the radiographic image produced (van der Stelt, 2008; Wenzel, 1998).

An example of useful image manipulation is the optimization of contrast and brightness of an image. This technique can be used to correct overexposure or underexposure of an image, although it is not an excuse to not pay attention to the correct exposure parameters. The manipulation can help to recover an image in which the exposure conditions were not optimal. This procedure may prevent the need for a radiograph remake, protecting the patient from an extra dose of radiation (van der Stelt, 2008).

Digital radiography is a complementary method that has been available in dentistry for more than 25 years, but digital imaging has not replaced conventional film-based radiography completely. Studies have shown that the number of dental professionals using digital radiography in clinical practice range from 11% to 30%. This fact can be attributed to the financial investment required to replace conventional radiography with digital imaging and also for the hesitancy to use a new technology, since it requires additional training on basic computer skills. On the other hand, a professional who is starting his/her career will not find huge differences in costs to acquire a conventional or a digital radiography system. Practitioners should remember that conventional radiography also involves costs for items, such as radiographic films, film mounts, processing solutions and time needed for cleaning

Studies have shown many advantages of digital radiography compared with conventional radiography. These include image acquisition process in real time, since the image is displayed immediately after exposure and no processing had to be performed. Other benefits include reductions in radiation dose (between 5% to 50% of the dose needed for conventional radiography) to obtain quality diagnostic images, time savings and digital manipulation of the image to enhance viewing, avoiding unnecessary or repeated radiographs. Digital images facilitate communication and case discussion among dental professionals, being a visual aid to be shown to the patient on the computer screen, increasing the confidence and credibility in the treatment-decision making process. However, the primary disadvantages of digital systems include the rigidity and thickness of the sensors, the high initial system cost and unknown sensor lifespan (Bin-Shuwaish et al.,

It is imperative to understand the digital radiography system to understand the principle of image manipulation. A digital image consists of a set of cells that are ordered in rows and columns, forming a table. Each cell is characterized by three numbers: the x-coordinate, the y-coordinate and the gray value. The gray value is a number that corresponds with the Xray intensity at that location during the exposure of the digital sensor. Individual cells are called "picture elements", which had been shortened to "pixels". The numbers describing each pixel are stored in an image file in the computer. This feature is an essential difference between conventional and digital radiographs, once digital images can be modified after they have been produced. Thus, the user can apply mathematical operations (special algorithms or filters) to modify the pixel values, improving the image quality and modifying other characteristics, such as zoom, contrast, density and brightness of an image. The image numbers are converted into gray values and these are displayed on the computer screen as analog data. Then, the professional can assess and interpret the radiographic image

An example of useful image manipulation is the optimization of contrast and brightness of an image. This technique can be used to correct overexposure or underexposure of an image, although it is not an excuse to not pay attention to the correct exposure parameters. The manipulation can help to recover an image in which the exposure conditions were not optimal. This procedure may prevent the need for a radiograph remake, protecting the

**4.2.2 Digital radiography** 

the film processor (van der Stelt, 2008).

2008; van der Stelt, 2008; Wenzel, 1998).

produced (van der Stelt, 2008; Wenzel, 1998).

patient from an extra dose of radiation (van der Stelt, 2008).

Digital image presents lower spatial resolution when compared to the image obtained by conventional radiography. The extension or palette for digital images is normally limited to 256 shades of gray, while more than a million shades of gray may appear for conventional X-ray film. Therefore, it can be speculated that the performance of digital radiography for caries detection would not be superior to that of conventional radiography. However, the performance of digital radiography for caries detection can be improved with image manipulation possibility, such as contrast modification. Thus, digital radiography systems seem to be as accurate as the conventional radiography system. According to a literature review, digital radiography showed high sensitivity for detecting occlusal caries lesions into dentin (60-80%), with false-positives results of 5-10% (Wenzel, 1998).

Undoubtedly, as technology evolves, it is supposed that the performance of digital radiography will be improved in a near future. The development of different sensors and software will support the reliability and viability of digital radiography applications by dental professionals, bringing this method to daily practice.

#### **4.2.3 Digital subtraction radiography**

Digital subtraction radiography (DSR) is a more advanced image analysis tools. This method allows professionals to distinguish small differences between subsequent radiographs that otherwise would have remained unobserved because of overprojection of anatomical structures or differences in density that are too small to be recognized by the human eye. The procedure is based on the principle that two digital radiographic images obtained under different time intervals, with the same projection geometry, are spatially and densitometrically aligned using specific software. When the two images are registered and intensities of corresponding pixels are subtracted of the gray scale values, a uniform difference image is produced, resulting in a new image representing the differences between the two, called the subtraction image. In this new image, if there is a change in the radiographic attenuation between the baseline and follow-up examination, all the anatomical structures that do no change between radiographs are shown as neutral gray background, while regions that had mineral loss or gain are shown as a darker or brighter area, respectively (van der Stelt, 2008; Wenzel, 2004).

For a successful DSR, reproducible exposure geometry, and also identical contrast and density of the serial radiographs, are essential prerequisites. Long experience shows that this technique is very sensitive to any physical noise occurring between the radiographs and even minor changes leads to large errors in the results (Hekmatian et al., 2005).

Digital subtraction radiography has been used in the assessment of the progression, arrest, or regression of caries lesions. Subtraction consists of subtracting the pixel values of the baseline image from the pixel values of the second image. If the two digital images are identical, this method will produce an image without details (the result is zero). However, if caries has regressed or progressed in the mean time, the result will be different from zero. When there is caries regression, the outcome will be a value above zero (increase in pixel values). In case of caries regression, the result is opposite and the outcome will be a value below zero (decrease in pixel values) (Hekmatian et al., 2005).

Few studies are found in the literature investigating the DRS for caries detection. The system works well for approximal and occlusal lesions in dentin, indicating that this method presents high potential for dental caries research (Neuhaus et al., 2009).

Traditional and Novel Caries Detection Methods 117

numeric values, which can vary from 0 to 99. Two optical tips are available: tip A for occlusal surfaces, and tip B for smooth surfaces. This device has shown good results in the detection of occlusal caries, however, it might not be used as the only method for treatment

decision-making process (Bader & Shugars, 2006; Rodrigues et al., 2008).

Fig. 5. DIAGNOdent 2095 – a laser fluorescence device for caries detection.

weights 140g and only one battery (1,5V) is needed.

(B) Occlusal tip. (C) Approximal tip.

Recently, a new and compact device - DIAGNOdent 2190 or DIAGNOdent pen – (KaVo, Biberach, Germany) (Figure 6) has been introduced in the market. This device functions on the same principle as the earliest. For this reason, the device was condensed and the tips were modified. The tips used in this device are made from sapphire fiber and the same solid single sapphire fiber tip is used for propagation of the excitation and for collection of the fluorescence light, but in opposite directions and different wavelengths (Lussi & Hellwig, 2006). There are two tips which can be coupled on this device: an occlusal and an approximal tip. However, its performance in approximal surfaces is still limited. The device

Fig. 6. (A) DIAGNOdent 2190 or DIAGNOdent pen calibration against the standard ceramic.

Recently, a digital subtraction radiographic system was evaluated on occlusal surfaces (Ricketts et al., 2007). In this in vitro study, accuracy and reproducibility of DSR was compared to visual assessment of paired digital images in detecting changes in mineral content within occlusal cavities. Intra-examiner and inter-examiner reproducibility for detection of demineralization from the subtraction images was significantly better than viewing the paired images side by side. The subtraction radiography system used was found to be more accurate and reproducible than visual assessment of paired digital images, showing promising results for monitoring occlusal lesion progression in clinical studies.

It is important to clarify that DSR will not necessarily improve the detection of a caries lesion, but will only provide important information on any changes occurring over time, and is therefore, suitable for monitoring lesion behavior. As a new method, other studies should be carried out in order to validate its use in monitoring caries lesions.
