|Year : 2021 | Volume
| Issue : 2 | Page : 62-65
Recent advances in dental caries diagnosis
S Sasidharan1, P Rahmath Meeral2
1 Sivam Dental and Maxillofacial Clinic, Chennai, Tamil Nadu, India
2 Best Dental Science College, Madurai, Tamil Nadu, India
|Date of Submission||27-Dec-2021|
|Date of Acceptance||30-Jan-2022|
|Date of Web Publication||26-Mar-2022|
Dr. S Sasidharan
Sivam Dental and Maxillofacial Clinic, Chennai, Tamil Nadu
Source of Support: None, Conflict of Interest: None
Dental caries, a progressive bacterial damage to teeth, is one of the most common diseases that affects 95% of the population and is still a major cause of tooth loss. Recent years have seen an increase in research activity surrounding diagnostic methods, particularly in the assessment of early caries lesions. The use of technologies as adjunct to clinical visual examination for caries diagnosis will facilitate preventive care in dentistry to lower treatment cost as well as reduce the cost and time for testing potential anticaries agents. This article describes the various technologies available to aid the dental practitioners in detecting and diagnosis of dental caries at the earliest stage of its formation, assessing the activities of the detected carious lesion, and quantitatively or qualitatively monitoring of the lesion over time.
Keywords: Anticaries, digital imaging fiber-optic transillumination, recent advances
|How to cite this article:|
Sasidharan S, Meeral P R. Recent advances in dental caries diagnosis. Int J Community Dent 2021;9:62-5
| Introduction|| |
The basis of the minimal intervention concept in dentistry comprises five main concepts: early detection of caries, if possible, at the stage when the lesion is still noncavitated; remineralization of these early lesions and reduction of the cariogenic bacteria present in the mouth; minimal surgical intervention if a cavitated lesion is present (including the use of hand instruments, air abrasion, sonic devices, ozone, chemomechanical and fluorescence-aided caries excavation use of specially designed burs, and modifications of cavity preparations); use of adhesive restorative materials; and preference of repairing instead of replacing restorations if needed, Clinical caries lesion detection implies some objective method of determining whether or not a disease is present, and many systems have been developed to improve the objectivity of examiners. In the International Consensus Workshop on Caries Clinical Trials held in 2002, the work on International Caries Detection and Assessment System was begun, and today, it has emerged as the leading international system for caries diagnosis. This article discusses the recent advances in the diagnosis of dental caries.
| Early Caries Detection|| |
Early caries detection is essential for minimal intervention dentistry because it could give the opportunity to reverse the process and eliminate or at least postpone the surgical treatment. The ideal caries detection device should be able to detect the caries from the earliest stages, when the organic matrix is still not damaged, to the latest stages of the cavitated lesion. There are a number of different methods for caries detection. The oldest method is the visual–tactile one (using a probe and a dental mirror). It remains the first step in detecting the presence or absence of caries. However, this method is not sensitive enough, especially for early lesions and those affecting the proximal tooth surfaces. Bitewing radiographs have also been used for a long time for the detection of proximal lesions, but they are not reliable for occlusal defects, especially when only the enamel is involved.
| Fiber-Optic Transillumination|| |
Another widely used method for caries diagnosis is fiber-optic transillumination (FOTI)., The device could be applied for both occlusal and proximal lesions and is noninvasive and cost-effective, but there are controversial data concerning its sensitivity compared with radiography and probing.
| Digital Imaging Fiber-Optic Transillumination|| |
Digital imaging FOTI (DIFOTI) is the digitized version of FOTI. It could be applied for the detection of advanced and incipient lesions, fractures, cracks, and secondary caries lesions, but it is not useful for the determination of the depth of penetration of the caries process. For example, the new DIAGNOcam (KaVo, Biberach, Germany) DIFOTI device uses wavelength in the invisible near-infrared light (780 nm) for transillumination. The light here is transmitted through the alveolar process, which makes the diagnostic image considerably better.
| Quantitative Light-Induced Fluorescence|| |
Quantitative light-induced fluorescence is a technology that was introduced long ago. It uses the autofluorescence of dental tissues, which diminishes with demineralization. Quite a lot of studies have used this method for the diagnosis of occlusal and smooth-surface caries, demineralization, and remineralization monitoring.,,, This method has high sensitivity, but it cannot distinguish between caries, developmental anomalies, and stain and calculus. A new device that uses this principle is SOPROLIFE.
| Laser-Induced Fluorescence|| |
Laser-induced fluorescence is used for the detection of demineralization and remineralization, and occlusal caries lesions. The latest version of the diagnostic device DIAGNOdent (KaVo) could be used for proximal surfaces, too. This method shows higher sensitivity compared to conventional ones, but its specificity is lower.,
| Vista Proof Fluorescence Camera|| |
Vista proof is based on the same principle, but it uses a different wavelength of excitation than DIAGNOdent and a video camera for the detection of fluorescence.
| Midwest Caries I.D.|| |
The Midwest Caries I.D. detects differences of optical behavior inside the tooth related to change in the tooth structure, and it is therefore not sensitive to bacterial content. The Midwest Caries I.D. uses infrared and red-light-emitting diodes and a fiber optic to distribute light to the observed area present at the probe tip. A second fiber optic collects light from the observed area to a photodetector that measures returned collected light. This photodetector then transmits the signal to a microprocessor that compares signal levels with defined parameters. One of the few studies evaluating this device reported the sensitivity and specificity to be higher than that of DIAGNOdent. Interproximal detection using the Midwest Caries I.D. and X-rays as a gold standard showed the sensitivity of 80% and specificity of 98%.
| The Canary System|| |
The Canary System is a low-powered laser that detects caries not yet discernible on X-rays or by examination. It detects decay, cracks, and defects by examining and measuring crystal structure breakdown lesions as small as 50 μ and up to 5 mm below the tooth surface can be detected.
| Dexis Carivu|| |
It uses transillumination technology that makes the enamel appear transparent, while porous lesions trap and absorb light and allow the clinician to see through the tooth, exposing its structure and the development of any carious lesions. It uses nonionizing radiation which is ideal for children, pregnant women, and patients who are X-ray averse.
| Spectra Caries Detection Aid|| |
Fluorescence technology indicates the extent of decay with color and numerical readings. Connects to computer with USB cable.
| Frequency Domain Laser-Induced Infrared Photothermal Radiometry and Modulated Luminescence|| |
This technology relies on absorption of IR laser light by the tooth with measurement of subsequent temperature change, which is in the 1°C or less range. The advantage compared with other methods of detection is that it can perform depth profilometry and very early caries detection and monitoring on tooth surfaces. When pulses of laser light hit the tooth surface, the tooth glows (luminescence) and releases heat (photothermal radiometry). It can provide depth profile by varying frequency of laser beam. Detected signal reflects the tooth condition. It detects 50 μ lesion up to 5 mm below the surface.
| Soprolife|| |
SOPROLIFE (light-emitting diode fluorescence tool) is two devices in one operating as a caries detection device and a high magnification intraoral camera SOPROLIFE is not software dependent, so it will work with most imaging and practice management software. During excavation, the margins of infected and affected dentin are clearly distinguishable, allowing the infected dentin (which shows up bright red) to be removed and the affected dentin (which shows up orange) to be retained to allow the remainder of the tooth to heal.
| Polarization-Sensitive Optical Coherence Tomography|| |
Optical coherence tomography (OCT) is based on confocal microscopy and low-coherence interferometry. OCT technology is an imaging modality that provides a tool for noninvasive evaluation of tissue microstructure by providing high spatial resolution (approximately 10–20 μm) and real-time, two-dimensional depth visualization. The principle of OCT is similar to B-mode ultrasound imaging, except that OCT uses near-infrared (NIR) light instead of sound. First demonstrated in 1991, OCT creates a two-dimensional map of the tissue microstructure by illuminating the tissue with low-power NIR light collecting the backscattered light and analyzing the intensity.
| Electronic Measurement of Caries|| |
Tooth demineralization due to the caries process causes increased porosity of tooth structure. This porosity contains fluid with ions in it. This increases the electrical conductivity but reduces the electrical impedance (resistance). Electronic countermeasure device uses 23 Hz of fixed frequency of (alternating current) which measures the resistance of tooth, for example, caries meter, vanguard caries detector.
| Deep Learning-Based Convolutional Neural Network Algorithm|| |
Deep convolutional neural networks (CNNs) are a rapidly emerging new area of medical research, and have yielded impressive results in diagnosis and prediction in the fields of radiology and pathology. Recently, one aspect of artificial intelligence and deep learning – CNNs – has demonstrated excellent performance in computer vision, including object, facial and activity recognition, tracking, and three-dimensional mapping and localization. Deep CNN algorithms perform edge detection very efficiently through multiple convolutional and hidden layers with hierarchical feature representations, and deep CNN-based dental caries detector can learn the location and morphological changes of dental carious lesions efficiently and detect them conveniently and reliably. Deep learning algorithms, such as ResNet and CapsNet, which have deeper or wider layers, or have modified layering methods, are continually being developed, and as a result, the accuracy of object detection and segmentation has been significantly and consistently improved., In particular, CapsNet, which has recently been developed, is reported to be very useful for processing visual factors from posture (location, size, and direction), modification, speed, reflection coefficient, hue, and texture, as well as for encoding.
| Ultrasound Devices|| |
Ultrasound devices are highly sensitive to proximal caries detection compared with bitewing radiographs. However, the drawback to this technique is that it can detect dental caries only after the tooth has been damaged to a certain extent, and after changes in enamel and dentin structure have already occurred.
| Logicon Caries Detector|| |
LOGICON Caries Detector™ Software (LCDS, Carestream Dental, GA, USA), the only commercially available computer-aided design, was developed to detect and diagnose dental caries based on traditional algorithms consisting of three-layer forward networks.
| Conclusion|| |
The shift in treatment philosophy from “extension for prevention” to “minimally invasive dentistry” has afforded the dentist the opportunity to diagnose and manage caries at an early stage. An ideal caries detection method should capture the whole continuum of caries process, from the earliest to the cavitation stage. It should be accurate, precise, easy to apply, and useful for all surfaces of teeth, as well as for caries adjacent to restorations.
More technologically, advanced measures based on optical properties (fluorescence and transillumination) are the most potent methods for the detection of incipient carious lesions.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Dalli M, Çolak H, Mustafa Hamidi M. Minimal intervention concept: A new paradigm for operative dentistry. J Investig Clin Dent 2012;3:167-75.
Frencken JE, Peters MC, Manton DJ, Leal SC, Gordan VV, Eden E. Minimal intervention dentistry for managing dental caries – A review: Report of a FDI task group. Int Dent J 2012;62:223-43.
Dwivedi S, Dwivedi CD, Baranwal HC. Minimal intervention dentistry-current concept and future strategies. Guident 2013;6.
Neuhaus KW, Ellwood R, Lussi A, Pitts NB. Traditional lesion detection aids. Monogr Oral Sci 2009;21:42-51.
Angnes V, Angnes G, Batisttella M, Grande RH, Loguercio AD, Reis A. Clinical effectiveness of laser fluorescence, visual inspection and radiography in the detection of occlusal caries. Caries Res 2005;39:490-5.
Young DA, Featherstone JD. Digital imaging fiber-optic trans-illumination, F-speed radiographic film and depth of approximal lesions. J Am Dent Assoc 2005;136:1682-7.
Young DA. New caries detection technologies and modern caries management: Merging the strategies. Gen Dent 2002;50:320-31.
Amaechi BT. Emerging technologies for diagnosis of dental caries: The road so far. J Appl Phys 2009;105:102047.
Söchtig F, Hickel R, Kühnisch J. Caries detection and diagnostics with near-infrared light transillumination: Clinical experiences. Quintessence Int 2014;45:531-8.
Pretty IA, Ellwood RP. The caries continuum: Opportunities to detect, treat and monitor the re-mineralization of early caries lesions. J Dent 2013;41 Suppl 2:S12-21.
Ando M, van Der Veen MH, Schemehorn BR, Stookey GK. Comparative study to quantify demineralized enamel in deciduous and permanent teeth using laser- and light-induced fluorescence techniques. Caries Res 2001;35:464-70.
Pretty IA, Ingram GS, Agalamanyi EA, Edgar WM, Higham SM. The use of fluorescein-enhanced quantitative light-induced fluorescence to monitor de-and re-mineralization of in vitro
root caries. J Oral Rehabil 2003;30:1151-6.
Pereira AC, Eggertsson H, Cabezas CG, Zero DT, Eckert GJ, Mialhe FL. Quantitative light-induced fluorescence (QLF) in relation to other technologies and conventional methods for detecting occlusal caries in permanent teeth. Braz J Oral Sci 2011;10:27-32.
Rechmann P, Rechmann BM, Featherstone JD. Caries detection using light-based diagnostic tools. Compend Contin Educ Dent 2012;33:582-4, 586, 588-93.
Tam LE, McComb D. Diagnosis of occlusal caries: Part II. Recent diagnostic technologies. J Can Dent Assoc 2001;67:459-63.
Karlsson L. Caries detection methods based on changes in optical properties between healthy and carious tissue. Int J Dent 2010;2010:270729.
Achilleos EE, Rahiotis C, Kakaboura A, Vougiouklakis G. Evaluation of a new fluorescence-based device in the detection of incipient occlusal caries lesions. Lasers Med Sci 2013;28:193-201.
Patel SA, Shepard WD, Barros JA, Streckfus CF, Quock RL. In vitro
evaluation of Midwest Caries ID: A novel light-emitting diode for caries detection. Oper Dent 2014;39:644-51.
Abrams SH, Sivagurunathan KS, Silvertown JD, Wong B, Hellen A, Mandelis A, et al.
Correlation with caries lesion depth of the canary system, DIAGNOdent and ICDAS II. Open Dent J 2017;11:679-89.
Horn AL. Comparison of Dexis CariVu to Traditional Bitewing Radiography for Diagnosis of Interproximal Caries (Doctoral Dissertation, University of Illinois at Chicago).
Gutta A, Merdad HE. In vitro
study of the diagnostic performance of the Spectra Caries Detection Aid. J Clin Dent 2015;26:17-22.
Jeon RJ, Matvienko A, Mandelis A, Abrams SH, Amaechi BT, Kulkarni G. Detection of interproximal demineralized lesions on human teeth in vitro
using frequency-domain infrared photothermal radiometry and modulated luminescence. J Biomed Opt 2007;12:034028.
Kockanat A, Unal M. In vivo
and in vitro
comparison of ICDAS II, DIAGNOdent pen, CarieScan PRO and SoproLife camera for occlusal caries detection in primary molar teeth. Eur J Paediatr Dent 2017;18:99-104.
de Boer JF, Hitzenberger CK, Yasuno Y. Polarization sensitive optical coherence tomography – A review [Invited]. Biomed Opt Express 2017;8:1838-73.
Sklan JE, Plassard AJ, Fabbri D, Landman BA. Toward content based image retrieval with deep convolutional neural networks. Proc SPIE Int Soc Opt Eng 2015;9417:94172C.
Wang R. Edge detection using convolutional neural network. In: Cheng L, Liu Q, Ronzhin A, editors. Advances in Neural Networks – ISNN 2016: 13th
International Symposium on Neural Networks, ISNN 2016, St. Petersburg, Russia, July 6–8, 2016, Proceedings. Cham: Springer International Publishing; 2016. p. 12-20.
He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. arXiv 2015.
Sabour S, Frosst N, Hinton GE. Dynamic routing between capsules. arXiv 2017.
Matalon S, Feuerstein O, Kaffe I. Diagnosis of approximal caries: Bite-wing radiology versus the Ultrasound Caries Detector. An in vitro
study. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2003;95:626-31.
Araki K, Matsuda Y, Seki K, Okano T. Effect of computer assistance on observer performance of approximal caries diagnosis using intraoral digital radiography. Clin Oral Investig 2010;14:319-25.