\r\n\tnano-optics, nonlinear plasmonics, and nonlinear metamaterials emerged in the last decades due to the progress in nanotechnology.
\r\n
\r\n\tThe essential subject of this book is the publication of novel theoretical and experimental results concerning the nonlinear optical phenomena in photonic and plasmonic nanostructures, nonlinear metamaterials including liquid crystals, and devices based on nonlinear optical waveguides. In particular, the following topics will be considered: the interaction of solid-state nanostructures with the intense electromagnetic fields, the surface plasmon polariton propagation and interaction near the metal-dielectric interface, active nano-photonic devices for lasing and optical sources, nonlinear metamaterials, the nonlinear optics of liquid crystals and the possible combination of liquid crystals with plasmonic and metamaterials. We do not limit the book to these topics.
\r\n
\r\n\tThe novel results in other fields of nonlinear optics would be also welcome. We hope that the proposed book will be interesting for researchers and engineers occupied in optical fiber telecommunications, optical signal processing, novel active materials, and devices.
",isbn:"978-1-83962-836-8",printIsbn:"978-1-83962-835-1",pdfIsbn:"978-1-83962-890-0",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"cfe87b713a8bee22c19361b86b03d506",bookSignature:"Dr. Boris I. Lembrikov",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10672.jpg",keywords:"Nonlinear Optics, Nano-Photonics, Surface Plasmon Polariton (SPP), Plasmonics, Plasmonic Nanostructure, Plasmonic Waveguide, Metamaterial, Nonlinearity, Nematic Liquid Crystals (NLC), TE Mode, TM Mode, Cholesteric Liquid Crystals (CLC)",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 29th 2021",dateEndSecondStepPublish:"February 26th 2021",dateEndThirdStepPublish:"April 27th 2021",dateEndFourthStepPublish:"July 16th 2021",dateEndFifthStepPublish:"September 14th 2021",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr.Lembrikov actively participated in numerous international scientific conferences, he is an author of a book, a large number of papers, and chapters in scientific books. He was an invited researcher at the Max Planck Institute High Magnetic Field Laboratory at Grenoble, France.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"2359",title:"Dr.",name:"Boris",middleName:"I.",surname:"Lembrikov",slug:"boris-lembrikov",fullName:"Boris Lembrikov",profilePictureURL:"https://mts.intechopen.com/storage/users/2359/images/system/2359.jpg",biography:"Boris I. Lembrikov is a senior lecturer at the Faculty of Electronics, Electrical and Communication Engineering of the Holon Institute of Technology (HIT), Holon, Israel. B. I. Lembrikov received his Ph.D. in Nonlinear Optics at the Technion – Israel Institute of Technology in 1996. Since then he was an invited researcher at the Haifa University, at the Max Planck Institute High Magnetic Field Laboratory at Grenoble, France, at the Technion, Haifa, Israel. Dr. B. I. Lembrikov is an author of the book \\Electrodynamics of Magnetoactive Media\\, a number of chapters in scientific books, a large number of papers in international peer reviewed journals and reports delivered at the international scientific conferences. He actively participated in a number of research projects concerning optics of nanoparticles, optical communications, UWB communications. The main research fields of interest of Dr. B. I. 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1. Introduction
Salt marshes are composed of various habitats contributing to high levels of habitat diversity and increased productivity (Kennish, 2002; Zharikov et al., 2005), making them among the most productive ecosystems on the Earth. The salt marsh consists of a halophytic vegetation community growing near saline waters (Mitsch & Gosselink, 2000) characterized by grasses, herbs, and low shrubs (Adam, 2002). Salt marshes exist between the upper limit of the high tide and the lower limit of the mean high water tide (Adam, 2002). They represent an important factor in the support of surrounding food chains, and due to the high level of productivity their economic and aesthetic value is increasing (Delaware Department of Natural Resources and Environmental Control, 2002; Zharikov et al. 2005). The survival and reproduction of many species of commercial fish and shellfish is dependent upon salt marshes (Zharikov & Skilleter, 2004). In addition, salt marshes provide critical habitat and food supply to crustaceans (Zharikov et al., 2005) and shorebirds (Potter et al., 1991). They are often considered as a primary indicator of the ecosystem health (Zhang et al., 1997). Because of their ability to transfer and store nutrients, salt marshes are an important factor in the maintenance and improvement of water quality (Delaware Department of Natural Resources and Environmental Control, 2002; Zhang et al., 1997). In addition, they provide significant economic value as a cost-effective means of flood and erosion control (Delaware Department of Natural Resources and Environmental Control, 2002; Morris et al., 2004). This economic value makes coastal systems the site of elevated human activity (Kennish, 2002).
Determining the effects of sea level rise on tidal marsh systems is currently a very popular research area (Temmerman et al., 2004). While average sea level has increased 10-25 cm in the past century (Kennish, 2002), the Atlantic coast has experienced a sea level rise of 30 cm (Hull & Titus, 1986). Local relative sea level has risen an average rate of 0.12 cm yr-1 in the past 2000 years, but at Breakwater Harbor in Lewes, DE sea level is rising at the average rate of 0.33 cm yr-1, nearly three times that rate (Kraft et al., 1992). According to the National Academy of Sciences and the Environmental Protection Agency, sea level rise within the next century could increase 60 cm to 150 cm (Hull & Titus, 1986).
The changes in sea level rise are particularly affecting tidal marshes, since they are located between the sea and the terrestrial edge (Adam, 2002; Temmerman et al., 2004). The prediction is that sea level rise will have the most negative effect on marshes in the areas where the landward migration of the marsh is restricted by dams and levees (Rooth & Stevenson, 2000). If sea level rises the almost certain prediction of 0.5 m by 2100 and marsh migration is prevented, then more than 10,360 km2 of wetlands will be lost (Kraft et al., 1992). If the sea level rises 1 m then 16,682 km2 of coastal marsh will be lost, which is approximately 65% of all extant coastal marshes and swamps in the United States (Kraft et al., 1992).
Due to an imminent potential threat which can jeopardize the Mid-Atlantic salt marshes, it is very important to examine the effect of sea level rise on these marshes. The marshes of the St. Jones River near Dover, DE, can be considered to be typical Mid-Atlantic marshes. These marshes are located in developing watersheds characterized by dams, ponds, agricultural lands, and increasing urbanization, providing an ideal location for studying the impacts of sea level rise on salt marsh extent and location. In order to determine the effect of sea level rise on the salt marshes of the St. Jones River, the change in salt marsh composition was quantified. Unfortunately, as for most marsh locations along the Atlantic seaboard, the data on sea level rise for this area was not available for comparison with marsh condition. However, a wide data set for this area is available through a water quality monitoring program, and if it could be properly processed and analyzed it could result in sea level rise data for the location of the interest.
In this chapter, we describe the application of signal processing on the water level data from the St. Jones River watershed. The emphasis is on adaptive filtering in order to remove the influence of upstream water level on the downstream levels.
2. Data
The St. Jones River, in central Delaware, is 22.3 km long (Pokrajac et al., 2007a). It has an average mean high water depth (MHW) of 4 m in the main stem, and an average width of 15 feet. The site’s watershed area is 19,778 ha, and the tidal reaches are influenced by fresh water runoff from the urbanized area upstream. An aerial photo of the St. Jones River is shown in Fig. 1.
Figure 1.
Aerial photo of St. Jones River.
The data used in this research were obtained from the Delaware National Estuarine Research Reserve (DNERR), which collected the data as part of the System Wide Monitoring Program (SWMP) under an award from the Estuarine Reserves Division, Office of Ocean and Coastal Resource Management, National Ocean Service, and the National Oceanic and Atmospheric Administration (Pokrajac et al. 2007a, 2007b). Through SWMP, researchers collect long term water quality data from coastal locations along Delaware Bay and elsewhere in order to track trends in water quality.
The original dataset contained 57,127 measurements, taken approximately every thirty minutes using YSI 6600 Data Probes (Fig. 2) (Pokrajac et al., 2007a, 2007b). The measurements were taken from January 31, 2002 through October 31, 2005. In order to determine if sea level rise is influencing the St. Jones River, the water level data were collected from two SWMP locations: Division Street and Scotton Landing (Pokrajac et al., 2007b). Probes were left in the field for two weeks at a time, collecting measurements of water level, temperature (Co), specific conductivity (mS cm-1), salinity (ppt), depth (m), turbidity (NTU), pH (pH units), dissolved oxygen percent saturation (%), and dissolved oxygen concentration (mg L-1). We used only the water level (depth) data for this study, which were collected using a non-vented sensor with a range from 0 to 9.1 m, an accuracy of 0.18 m, and a resolution of 0.001 m. Due to the fact that the probes are not vented, changes in atmospheric pressure appear as changes in depth, which results in an error of approximately 1.03 cm for every millibar change in atmospheric pressure (Mensinger, 2005). However, the exceptionally large dataset (57,127 data points) overwhelms this data error.
Figure 2.
YSI 6600 Data Probe.
The downstream location, Scotton Landing, is located at coordinates latitude 39 degrees 05’ 05.9160” N, longitude 75 degrees 27’ 38.1049” W (Fig. 3). It has been monitored by SWMP since July 1995. The average MHW depth is 3.2 m, and the river is 12 m wide (Mensinger, 2005). This location possesses a clayey silt sediment with no bottom vegetation, and has a salinity range from 1 to 30 ppt. The tidal range is from 1.26 m (spring mean) to 1.13 m (neap mean). The data collected at the Scotton Landing site are referred as downstream data (see Fig. 4).
The water level data from the Scotton Landing site alone were not sufficient. In addition to tidal forces, this site is influenced by upstream freshwater runoff, so changes in depth could not be isolated to sea level change. However, the data from a non-tidal upstream sampling site could be used for removing the upstream influence at Scotton Landing. Therefore, the data from an upstream location, Division Street, was included in the analysis. Its coordinates are latitude 39 degrees 09’ 49.4” N, longitude 75 degrees 31’ 8.7” W (see Fig. 3.). The Division Street sampling site is located in the mid portion of the St. Jones River, upstream from the Scotton Landing site. At this location, the river’s average depth is 3 m and width is 9 m. The site possesses a clayey silt sediment with no bottom vegetation, and has a salinity in the range from 0 to 28 ppt. The tidal range at this location varies from 0.855 m (spring mean) to 0.671 m (neap mean). The data were monitored from January 2002 (Mensinger, 2005). The data collected at the Division Street site are referred to as upstream data (see Fig. 4).
Figure 3.
Sampling locations for St. Jones data: Division Street (upstream data); Scotton Landing (downstream data).
Figure 4.
Original dataset (upstream and downstream data).
3. Data pre-processing
The data were sampled every Ts = 30 minutes, and the dataset consisted of “chunks” of continuous measurements. Some of the measurements were missing due to maintenance or malfunction of the equipment, probe replacement, etc. The length of the intervals with missing measurements varied between 1 h (1 missing measurement) and 1517.5 h (3036 missing measurements), but the majority of the intervals were shorter than 10 h.
Figure 5.
Spectrum of collected data before filtering (chunk 99, downstream data).
The discrete Fourier spectra (Proakis & Manolakis, 2006) of all the chunks contained three prominent peaks, which is shown in Fig. 5 using chunk 99 from the downstream data. The first peak corresponds to lunar semi-diurnal tides with a period of approximately 12.4 h, and the diurnal tides with a period of approximately 24.8 h. In addition, there is a peak that corresponds to solar tides, which have a period of approximately 12 h. These periodicities are also shown in Fig. 6.
Figure 6.
The periodicities of the downstream data.
The dataset had several problems that had to be rectified before further processing. One data sample (Sep 28, 2004, 09:00:00) had an incorrect time, which was located sometime between Sep 27, 2004, 23:30:00 and Sep 28, 2004, 00:30:00, and was corrected. Four data samples (Jul 24, 2003, 07:30:00; Jun 10, 2005, 09:00:00; Aug 11, 2005, 15:00:00; Aug 11, 2005, 15:30:00) had missing values. In addition, the number of intervals with no measurements (total of 99 “gaps” in experiment) represented a problem for signal processing (for example, for filtering). Fig. 7 shows the number of chunks as a function of the duration of the missing measurements. Due to the properties of the used data and the shortest period of 12 h, we decided to interpolate intervals shorter than 12 h. Also, we interpolated all the above mentioned samples with missing data values. The treatment of the missing values is shown in Fig. 8.
In order to interpolate data for each interval of missing measurements, first we approximated the existing data within 20 samples from the interval. We used a least squares approximation followed the combination of the 4th order polynomial and trigonometric functions:
x(t)=∑j=04ajtj+∑j=13Ajsin(2πtTj+θj)E1
Figure 7.
The number of chunks as function of the duration of missing measurements.
Figure 8.
The treatment of the missing values.
where T1 = 12.4 h, T2 = 24.8 h and T3 = 12 h. Then, we interpolated missing values using the computed approximation functions. The interpolation was performed on 866 samples, which represented less than 2% of the original number of samples. One example of the interpolated intervals is depicted in Fig. 9.
Figure 9.
An example of interpolated intervals.
The interpolation resulted in the merging of the majority of chunks, thus giving us only 11 chunks. The sizes of the new chunks were as follows: 4105, 5422, 4, 4, 7154, 14357, 10750, 5, 4491, 9423, and 2278. Three of those chunks (3, 4 and 8) have very small size, which made them suitable for discarding. Therefore, the interpolation process left us with only 8 chunks.
4. Filtering of the tidal components
We performed discrete filtering of both upstream and downstream data using the Filter Design and Analysis (FDA) Tool in Matlab Signal Processing Toolbox, v.6.2 in order to remove the tidal periodic components from the data. The first idea was to create and use the infinite impulse response (IIR) filter (Proakis & Manolakis, 2006), because it can potentially meet the design specifications with lower order than the corresponding finite impulse response (FIR) filter, which would also result in shorter time to buffer the data. However, several attempts (using the Yule-Walker method, notch or elliptic filters) didn’t achieve the expected results – the order was too high and the attenuation was less than specified (Pokrajac et al., 2007a). Hence, we designed the FIR filter. Since the spectrum of the data had peaks in two bands (see Fig. 5), two stopband filters were designed. Both of them had a passband ripple of 0.05, and the sampling frequency fs = (1/30) min-1 = 0.556 mHz (Pokrajac et al., 2007a). In order to have a stopband attenuation of at least 20 dB in the 11 – 11.4 μHz band, which corresponds to a 24.8 h period, the first created filter was of order 168. The attenuation of 40 dB in the 22.401 – 23.148 μHz band (which corresponds to periods of 12 and 12.4 h) was achieved with the second filter of order Nfilter = 354. Here, more attenuation was needed due to the very high corresponding peak in the spectrum. In Figs. 10 and 11, magnitude responses of the first and the second filters are shown. The result of applying both filters on chunk 99 and downstream data is illustrated in Fig. 12. At the beginning of each chunk, we had to discard Nfilter-1 data samples in order to perform filtering. This led to discarding less than 5% of the data. The standard deviation of the downstream data after the filtering was std(yFIR(t)) = 0.200. Also, we tried the alternative approach by applying a moving average (MA) filter of length Q = 25, which corresponds to a period of 12.4 h. Standard deviation of the downstream data after the MA filter was std(yMA(t)) = 0.223. The result of filtering the downstream data is shown in Fig. 13.
Figure 10.
Magnitude response of the first filter.
Figure 11.
Magnitude response of the second filter.
Figure 12.
Spectrum after filtering (chunk 99 and downstream data).
Figure 13.
Filtered downstream data.
5. Application of the adaptive filters
The downstream data yt can be considered as a non-stationary function of the delayed upstream data xt (see Fig. 14) (Pokrajac et al., 2007a, 2007b). It can be described as the discrete model yt=ft(xt, xt-Ts,…, xt-(L-1)Ts)+rt, where L is the maximal delay of the model and rt is the residual corresponding to the portion of the downstream data which cannot be explained by the upstream data.
Figure 14.
Removal of the upstream data influence.
If a function ft is linear, the adaptive linear model can be represented as follows:
yt=wtTxt+rtE2
where wt\n\t\t\t\t= [w0,t…wL-1,t]T are coefficients and xt\n\t\t\t\t= [xt…xt-(L-1)Ts]T is the upstream data vector. A linear regression model could be obtained if the coefficients w are held constant (Devore, 2007):
yt=wTxt+rtE3
The coefficient of determination, R2, is usually used to measure the accuracy of the model, (Devore, 2007). It is defined as a function of averaged squared residuals and the standard deviation of the response:
R2=1−r^t2¯std(yt)2E4
where the residuals are estimated with:
r^t=yt−wtTxtE5
The updating of the coefficients wt in Eq. (2) is performed using the Widrow-Hoff least mean squares (LMS) algorithm (Widrow & Stearns, 1985):
wt+1=wt+2μr^txtE6
where μ represents the adjustable learning rate, and r^t is estimated using Eq. (5). In addition to the Widrow-Hoff LMS algorithm, we applied time notching by adjusting the coefficients only when all the time instants, t,..., t-(L-1)Ts, belonged to the same chunk of interpolated data (Pokrajac et al., 2007a, 2007b), see Fig. 15.
Figure 15.
Time notching in adaptive filtering.
Using the linear regression given with Eq. (3) on the data yMA(t), which is processed by the MA filter, we were able to explain only 6% of the variance, i.e. R2 = 0.06 for L = 55. In Table 1 are shown the results of obtained std(r^(t)), for different values of the learning rate and the filter delay, when the adaptive filter given with Eqs. (2), (5) and (6) is used. Useful models were obtained when std(r^(t))<std(yMA(t)) = 0.200, and are shown in the shaded boxes in Table 1. As can be seen, the best results were obtained for L = 55, μ = 0.015, which yielded to R2 = 0.37. Small values of the learning rate, combined with small filter length, lead to unsatisfactory results. On the other hand, the learning becomes unstable if the filter length and learning rates are getting large.
/L
30
35
40
45
50
55
0.01
0.226
0.213
0.201
0.190
0.187
0.180
0.015
0.204
0.190
0.174
0.164
0.160
0.157
0.02
0.183
0.170
0.159
1.846
4.8e5
1.2e13
Table 1.
Std of residuals for different values of learning rate μ and the filter length L, for MA filter. Useful models are in shaded boxes.
When the designed FIR filter was used on the same data yMA(t), we received the results shown in Table 2. As can be seen, the results given in Table 1 are better. However, if L = 45 and μ = 0.015 (which yields to R2 = 0.24), the best performance of the designed FIR filter is achieved.
/L
20
30
35
40
45
50
55
0.01
0.25
0.23
0.21
0.21
0.19
0.19
0.17
0.015
0.23
0.20
0.20
0.18
0.17
24.9
5e4
0.02
0.21
0.19
0.47
2e6
5e16
3e30
1e48
Table 2.
Std of residuals for different values of learning rate μ and the filter length L, for designed FIR filter. Useful models are in shaded boxes.
Fig. 16 shows the residuals in time of the three useful adaptive filters, applied on data yMA(t) and processed by using the MA filter. The particular combination of the filter parameters was different, but the residuals showed similar behavior. Table 3 provides the time intervals when the relative residuals are larger than four standard deviations for the ada ptive filter with L = 55, μ = 1.5 e-2 (Pokrajac et al., 2007b). At the beginning of the learning process, the filter
Figure 16.
Residuals of the adaptive filters applied on yMA(t) data using three different combinations of the learning rate and the filter length.
coefficients were not adapted fully, which caused the identified peaks. These peaks corresponded to observations from February 2002. In addition, there are two other peaks, corresponding to Sep 4, 2002, and Oct 25, 2004, which can be explained by a transient behavior after the notching interval.
Year
Begin
End
Note
Year
Begin
End
Note
Date
Time
Date
Time
Date
Time
Date
Time
2002
02/08
23:00
02/10
00:00
Learning
2004
04/01
15:30
04/02
18:30
02/17
06:30
02/18
01:30
Learning
04/09
17:00
04/09
18:00
07/20
00:30
07/20
09:00
05/29
12:30
05/29
19:00
08/07
01:00
08/07
03:30
07/12
20:30
07/13
02:00
08/07
16:30
08/07
17:30
09/19
00:00
09/19
06:00
08/21
14:30
08/21
21:30
09/29
20:30
09/30
06:30
09/04
16:00
09/04
19:30
Transient
10/05
15:30
10/05
20:30
09/11
15:00
09/12
11:00
10/25
03:00
10/25
06:00
Transient
12/21
09:30
12/21
10:30
11/26
09:00
11/26
15:00
2003
01/09
02:00
01/09
04:00
2005
09/27
20:00
09/28
04:30
10/22
12:00
10/24
09:00
Table 3.
Identified intervals of large residuals (adaptive filtering on yMA(t) data, L = 55, μ = 1.5 e-2
6. Conclusion
We have described the application of the adaptive filtering for analyzing river hydrographic data. When determining the portion of the downstream data that is not influenced by the upstream data, the numerical results show that adaptive filtering is superior to linear regression.
Acknowledgments
This work was partially supported by the US Department of Commerce (award #NA06OAR4810164), NOAA (#NA06OAR4810164), NIH (#2P20RR016472-04), DoD/DoA (#45395-MA-ISP, #54412-CI-ISP, W81XWH-09-1-0062), and NSF (#0320991, CREST grant #HRD-0630388, #HRD-0310163).
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Introduction ",level:"1"},{id:"sec_2",title:"2. Data ",level:"1"},{id:"sec_3",title:"3. Data pre-processing ",level:"1"},{id:"sec_4",title:"4. Filtering of the tidal components ",level:"1"},{id:"sec_5",title:"5. Application of the adaptive filters",level:"1"},{id:"sec_6",title:"6. Conclusion",level:"1"},{id:"sec_7",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'AdamP.\n\t\t\t\t\t2002\n\t\t\t\t\tSaltmarshes in a time of change. 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Abid Noor, Salina Abdul Samad and Aini Hussain",authors:[{id:"24853",title:"Dr.",name:"Ali",middleName:"Owda",surname:"Abid Noor",fullName:"Ali Abid Noor",slug:"ali-abid-noor"},{id:"66437",title:"Prof.",name:"Salina",middleName:null,surname:"Abdul Samad",fullName:"Salina Abdul Samad",slug:"salina-abdul-samad"},{id:"66438",title:"Prof.",name:"Aini",middleName:null,surname:"Hussain",fullName:"Aini Hussain",slug:"aini-hussain"}]},{id:"17787",title:"Hirschman Optimal Transform (HOT) DFT Block LMS Algorithm",slug:"hirschman-optimal-transform-hot-dft-block-lms-algorithm",signatures:"Osama Alkhouli, Victor DeBrunner and Joseph Havlicek",authors:[{id:"28990",title:"Dr.",name:"Osama",middleName:null,surname:"Alkhouli",fullName:"Osama Alkhouli",slug:"osama-alkhouli"},{id:"76357",title:"Prof.",name:"Victor",middleName:null,surname:"DeBrunner",fullName:"Victor DeBrunner",slug:"victor-debrunner"},{id:"76358",title:"Prof.",name:"Joseph",middleName:null,surname:"Havlicek",fullName:"Joseph Havlicek",slug:"joseph-havlicek"}]},{id:"17788",title:"Real-Time Noise Cancelling Approach on Innovations-Based Whitening Application to Adaptive FIR RLS in Beamforming Structure",slug:"real-time-noise-cancelling-approach-on-innovations-based-whitening-application-to-adaptive-fir-rls-i",signatures:"Jinsoo Jeong",authors:[{id:"24639",title:"Dr.",name:"Jinsoo",middleName:null,surname:"Jeong",fullName:"Jinsoo Jeong",slug:"jinsoo-jeong"}]},{id:"17789",title:"Adaptive Fuzzy Neural Filtering for Decision Feedback Equalization and Multi-Antenna Systems",slug:"adaptive-fuzzy-neural-filtering-for-decision-feedback-equalization-and-multi-antenna-systems",signatures:"Yao-Jen Chang and Chia-Lu Ho",authors:[{id:"24766",title:"Dr.",name:"Yao-Jen",middleName:null,surname:"Chang",fullName:"Yao-Jen Chang",slug:"yao-jen-chang"},{id:"35428",title:"Prof.",name:"Chia-Lu",middleName:null,surname:"Ho",fullName:"Chia-Lu Ho",slug:"chia-lu-ho"}]},{id:"17981",title:"A Stereo Acoustic Echo Canceller Using Cross-Channel Correlation",slug:"a-stereo-acoustic-echo-canceller-using-cross-channel-correlation",signatures:"Shigenobu Minami",authors:[{id:"24783",title:"Dr.",name:"Minami",middleName:null,surname:"Shigenobu",fullName:"Minami Shigenobu",slug:"minami-shigenobu"}]},{id:"17791",title:"EEG-fMRI Fusion: Adaptations of the Kalman Filter for Solving a High-Dimensional Spatio-Temporal Inverse Problem",slug:"eeg-fmri-fusion-adaptations-of-the-kalman-filter-for-solving-a-high-dimensional-spatio-temporal-inve",signatures:"Thomas Deneux",authors:[{id:"25284",title:"Dr.",name:"Thomas",middleName:null,surname:"Deneux",fullName:"Thomas Deneux",slug:"thomas-deneux"},{id:"35752",title:"Prof.",name:"Olivier",middleName:null,surname:"Faugeras",fullName:"Olivier Faugeras",slug:"olivier-faugeras"}]},{id:"17792",title:"Adaptive-FRESH Filtering",slug:"adaptive-fresh-filtering1",signatures:"Omar A. Yeste Ojeda and Jesús Grajal",authors:[{id:"26339",title:"Dr.",name:"Omar",middleName:"A.",surname:"Yeste-Ojeda",fullName:"Omar Yeste-Ojeda",slug:"omar-yeste-ojeda"},{id:"36334",title:"Dr.",name:"Jesus",middleName:null,surname:"Grajal",fullName:"Jesus Grajal",slug:"jesus-grajal"}]},{id:"17793",title:"Transient Analysis of a Combination of Two Adaptive Filters",slug:"transient-analysis-of-a-combination-of-two-adaptive-filters",signatures:"Tõnu Trump",authors:[{id:"1241",title:"Dr.",name:"Tonu",middleName:null,surname:"Trump",fullName:"Tonu Trump",slug:"tonu-trump"}]},{id:"17794",title:"Adaptive Harmonic IIR Notch Filters for Frequency Estimation and Tracking",slug:"adaptive-harmonic-iir-notch-filters-for-frequency-estimation-and-tracking",signatures:"Li Tan, Jean Jiang and Liangmo Wang",authors:[{id:"26086",title:"Prof.",name:"Li",middleName:null,surname:"Tan",fullName:"Li Tan",slug:"li-tan"},{id:"36336",title:"Prof.",name:"Jean",middleName:null,surname:"Jiang",fullName:"Jean Jiang",slug:"jean-jiang"},{id:"36338",title:"Prof.",name:"Liangmo",middleName:null,surname:"Wang",fullName:"Liangmo Wang",slug:"liangmo-wang"}]},{id:"17795",title:"Echo Cancellation for Hands-Free Systems",slug:"echo-cancellation-for-hands-free-systems",signatures:"Artur Ferreira and Paulo Marques",authors:[{id:"34164",title:"Prof.",name:"Artur",middleName:null,surname:"Ferreira",fullName:"Artur Ferreira",slug:"artur-ferreira"},{id:"36277",title:"Dr.",name:"Paulo",middleName:null,surname:"Marques",fullName:"Paulo Marques",slug:"paulo-marques"}]},{id:"17796",title:"Adaptive Heterodyne Filters",slug:"adaptive-heterodyne-filters",signatures:"Michael A. Soderstrand",authors:[{id:"24806",title:"Prof.",name:"Michael",middleName:"Alan",surname:"Soderstrand",fullName:"Michael Soderstrand",slug:"michael-soderstrand"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"69234",title:"Non-Invasive Methods for Early Diagnosis of Oral Cancer",doi:"10.5772/intechopen.89280",slug:"non-invasive-methods-for-early-diagnosis-of-oral-cancer",body:'\n
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1. Introduction
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Oral health is part of general health and is essential to people’s well-being. Good oral health implies being free from chronic orofacial pain, oral and pharyngeal cancer, soft tissue changes in the mouth, congenital disabilities, and other issues affecting the craniofacial complex [1].
Active performance of the dentist in care and prevention actions
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Population characteristics: low sociocultural level, age, and gender
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Training of the oral health team on oral cancer
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HPV infection
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Implementation of new early detection strategies, according to the population served
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Prolonged use of dental prosthesis, especially in the absence of routine monitoring and evaluation by a professional
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Individual and collective educational actions on healthy living habits
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Lack of information about the disease, its risk factors and protection
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Routine screening for early detection of cancer, especially among the most vulnerable to oral cancer
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Lack of information to the population about health services and their flow when a suspected injury is diagnosed
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Integration of the oral health team with smoking control programs and other actions related to oral cancer control
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Lack of training of professionals working in care
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Systematic information to the population on reference sites for oral cancer diagnostic examination
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Lack of specific campaigns and information about oral cancer, its risk factors and protection
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Fight against lifestyle, environmental, and occupational factors that may be related to oral cancer
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Investigation of genetic factors associated with some specific types of cancer for the risk group
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Tracking of this pathology in at-risk populations by the health team
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Offering opportunities for evaluation of oral lesions (active search—through home visits or specific campaigns)
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Follow-up of suspected cases, creating a reference service if necessary and establishing partnerships between universities and other organizations for prevention, diagnosis, treatment, and recovery
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Training of professionals working in the front line of health care
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Table 1.
Summary of risk factors related to oral cancer and primary and secondary prevention methods.
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Method
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Indication
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Advantage
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Disadvantage
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Toluidine blue test
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Diagnosis and surgical approach to various mucosal tumors
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Painless, low-cost, easy application, fast result, and high sensitivity
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It can generate false-positive or false-negative results, being of low specificity
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Exfoliative cytology
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Initial assessment of incipient lesions and follow-up of areas that underwent previous surgical resection
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Painless, harmless, noninvasive, inexpensive
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It does not have the same efficacy as biopsy in the identification of the type of lesion; however it is very useful when biopsy is not possible. It can generate false-positive or false-negative results
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Fluorescence/autofluorescence
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Adjuvant method in oral clinical examination for detection of cellular disorders
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High sensitivity for cancer and dysplasia, ability to evaluate large areas of the oral mucosa at the moment of consultation, noninvasive, painless
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It can generate false-positive results
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Contact endoscopy
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A colposcope with optical magnification of up to 40 times is applied to help diagnose oral cavity lesions
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Painless, fast diagnosis
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Difficulties in relation to the device and the anatomical structures examined (lip and oral cavity) related to the contact of the lens surface, fine tremors, and slippage of the device
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In vivo microscopy
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Histopathological evaluation of suspected lesions at the moment of consultation
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High precision
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High cost
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Tumor biomarkers
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Diagnostic elucidation, tumor recurrence evaluation, or follow-up of treatment progress
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Early detection, noninvasive
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It can generate false-positive or false-negative results
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Oral inspection and palpation
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Identification of lesions, monitoring of oral health of the individual, screening of suspicious lesions for oral cancer
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Fast, painless, and low-cost
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It depends on the examiner’s skill and knowledge
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Table 2.
Noninvasive methods for diagnosis of oral cancer.
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Oral cancer (OC) is considered a public health problem because of its high mortality and morbidity rates. This problem also affects most people with low sociocultural level and who are alcoholics and smokers. However, there are other associated risk factors: chewing tobacco, use of a dental prosthesis, infection with human papilloma virus (HPV) type 16, nutritional deficiency, age, gender, poor oral hygiene, excess body fat, and chewing betel nut, among others [2, 3].
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Data published by the International Agency for Research on Cancer (IARC) regarding cancer cases in general reported in 2012 about 14.1 million new cases, 8.2 million deaths within 5 years of diagnosis, and 32.6 million people living with cancer in the world. Of these, approximately 57% of new cases, 65% of deaths, and 48% of cases diagnosed in the last 5 years are in developing countries [4]. In 2018, new data were released, indicating an increase in new cases of cancer, with 18.1 million new cases and 9.6 million deaths [5]. The significant increase of this disease is clear, indicating the need for new plans for prevention and early diagnosis.
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Regarding oral cancer, the highest rates have been observed in populations of Melanesia, Central-South Asia, Eastern and Western Europe, Africa, and Central America. Oral cancer is the sixth most common in the world, and most cases occur in India and Southeast Asia, according to the estimates for 2012 [6]. A change was seen in 2018 when oral cancer ranked in the 11th position among the most common cancers in the world. This type of cancer is quite common in Brazil, which has the third highest incidence in the world, behind only India and former Czechoslovakia [5].
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Oral cancer is a condition that negatively interferes with the general and oral health of the individual. These oral problems cause pain and infection, leading to psychological and physical distress. It is important to note that such dental conditions express social exclusion. In general, they are associated with poor education, low income, unemployment, and difficulty in accessing care services [7]. Thus oral cancer patients represent a group of people that should receive differentiated attention because, besides cancer itself, they are highly susceptible to other ills [2]. When this disease affects individuals, they may have to face consequences such as facial mutilation. Also, they may render them unable to work, with severe damage to their quality of life. The disease may sometimes be lethal, mainly because of late diagnosis.
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This pathology causes essential changes in the daily lives of the affected people, interfering with their body image, body functioning, and psychological, social, and family structure. The disease mostly affects the population in their working phase of life, causes indirect damage to the country. Late diagnosis is directly associated with shorter survival. However, if diagnosed early, it has a good prognosis and an average 5-year survival rate of 77.3% in stages I and II, but of 32.2% in stages III and IV [2].
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Morbidity and mortality rates are high, with diagnosis in advanced phases in 65–85% of the cases, reducing the likelihood of cure [2, 8, 9, 10, 11]. For most of these patients, palliative care is the only option available to achieve a better quality of life and control symptoms.
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Protective factors against this condition include general and specific measures. The adoption of healthy lifestyle habits, including adequate nutrition, physical exercise, and self-care, is part of the prevailing standards. In turn, specific practices include oral health care, routine inspection of the oral cavity, periodic dental evaluation, and cessation of smoking and alcoholism, and recent studies have shown the consumption green tea as a protective measure [12, 13].
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Although oral cancer is easily detected, its diagnosis is late in most cases. It is possible to improve diagnosis through the use of health promotion and prevention measures and improved access to health services, to promote early diagnosis [7, 14, 15]. Diagnosis is followed by curative treatment, preventing mutilating and disabling sequelae.
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The relevance of this disease and its early diagnosis should be considered for the possibility of curative treatment and promotion of the quality of life of patients. It is essential to know and recommend methods that act in favor of the early diagnosis of this pathology. It may mean identifying early malignant and even premalignant lesions, leading to the cure of these patients and rehabilitation to their social routine. It is equally important to act on factors that influence to late diagnosis of this pathology, through the planning of actions.
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2. Factors related to late diagnosis of oral cancer
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The problem of delayed diagnosis of OC is known worldwide, and each country or region has different strategies to address it. These factors are described in several studies [16, 17], showing that this is a global problem. Factors related to late diagnosis of OC concern the social determinants, health literacy, and characteristics of the health system:
Profile of the affected people concerning lifestyle habits: most people who develop OC were smokers and alcoholics and are in situations associated with other unhealthy lifestyles, such as poor diet and physical inactivity [2].
Lack of self-care in oral health: the most vulnerable populations, which are those with a low socioeconomic level, frequently have poor self-care due to their living conditions, especially in terms of oral health, besides other health problems. This problem directly interferes with their quality of life and interaction with peers. They also present a low search for health care, leading to the worsening of health problems and, in this case, late diagnosis of oral cancer [18].
Delayed perception of the lesion: due to poor self-care, most do not identify the presence of initial lesions in the oral cavity. Thus, injuries are only perceived when they cause discomfort, pain, bleeding, or other symptoms, and at that point, in most cases, the disease is already in an advanced stage [18].
Lack of information about oral cancer and its protective and risk factors: many campaigns for the dissemination of information on disease have been promoted, but specifically on oral cancer is still incipient. People asked to appear to not know about oral cancer, suspected lesions or risk, and protective factors, even patients who are undergoing treatment for this type of cancer [14, 19].
Lack of health promotion and prevention activities aimed at oral cancer: a few specific actions to promote and prevent this type of cancer are carried out. These actions are usually linked to other campaigns such as those focused on vaccination, smoking, and oral health in general [14].
Lack of training in oral cancer among oral health professionals and deficits in addressing this content in the curricula of undergraduate courses: oral health professionals are not routinely updated and trained on this content. Still, the approach during undergraduate training is deficient, producing professionals with little experience to approach patients with suspected lesions [14, 16].
Delayed search for professional assistance when the patient perceives the lesion: people usually notice the presence of the injury but do not seek a professional for confirmation. Often they refer to fear of confirming the diagnosis of the disease. This delay in seeking the diagnosis causes the lesion to continue growing, leading to late diagnosis [14].
Difficulties in accessing dental treatment: many people are unable to get adequate dental care due to the difficulty in accessing health services. In general, it is due to their vulnerable conditions or even because they do not seek health services [14].
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Regarding oral cancer prevention and health promotion activities, it is essential to highlight the urgency of designing public policies for long-term health education actions. If education is not changed, concepts and habits will not change after short campaigns. That points out to the need for permanent education programs, since the best way to combat oral cancer is prevention, early diagnosis, and the attempt to eliminate risk factors. Health education through programs aimed at valuing periodic evaluations and the importance of examining the oral cavity are the significant weapons available to reduce the high incidence of oral cancer in the community [14].
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The biopsy is undoubtedly the gold standard for the diagnosis of OC. However, there are several questions related to this method used in screening. It is an aggressive procedure, not readily accepted by people, especially when the lesion is asymptomatic and, even more so if it is proposed in oral health campaigns. The biopsy is limited by morbidity, once the procedure provokes another injury that may cause pain, bleeding, or other symptoms. Still, due to the resources required and the possibility of underdiagnosis, this method demands trained professionals to perform the procedure, trained pathologist, and facilities for the necessary reading of the exam. These characteristics mean a long time to receive the diagnosis, and patients experience discomfort caused by all the process [20].
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Although the factors related to early detection of OC have different natures, it is noteworthy that, after all, the primary responsibility lies with the health system. For that, health service and program must organize its strategies according to the characteristics of the users.
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Studies have been conducted to support measures aimed at solving the problem of late diagnosis, and the various approaches used to solve this problem are related to the factors abovementioned. In this text, we will address in particular the issue of noninvasive methods.
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3. Prevention of oral cancer
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Considering factors that interfere with the pathology diagnosis in question, the actions should be directed to them, to improve the care to the population.
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Prevention and early diagnosis of oral cancer are critical. Equally important is the need for a differentiated look in this issue, given the characteristics of the affected population, the role of the dentist, the continuing training of oral health professionals, and the implementation of new strategies for early detection of this pathology [16, 21].
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Actions related to the prevention of oral cancer and early diagnosis are foreseen within concepts widely worked in public health, which are health promotion and disease prevention. Health prevention requires firstly action based on knowledge of the natural history of the disease to prevent its progress [22]. Primary prevention is defined as a set of interventions to minimize the risk of specific ailments, reducing incidence and prevalence rates in the population and focusing on keeping individuals free from diseases.
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Health promotion, on the other hand, is broader, as it refers to measures that act in the health disease process. Here, the intention is to modify the lifestyle and living conditions of the population, thus not working on a specific disease. Health promotion depends on the individuals, the community, and the sectors of society, health professionals, and oral health professionals [23].
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Preventive measures may have a collective or individual approach. The collective approach includes interventions focused on health promotion. It means educational actions, periodic examinations of the most vulnerable people to the development of oral cancer, integration of the oral health team into smoking control programs, and other actions related to control of oral cancer. Besides that is a systematic provision of information on reference sites to the population about the diagnostic examination of oral cancer. In turn, the individual approach includes early diagnosis, treatment, and rehabilitation [17, 18].
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Some primary intervention and prevention measures would be ideal for reducing cancer, such as combating lifestyle, environmental, and occupational factors and investigating the genetic factors associated with some specific types of cancer [14]. Population screening is indicated as an important preventive measure. This process can favor the diagnosis of suspicious lesions, which are to be referred for differential diagnosis, making it possible to implement early intervention and increase the chance of cure [14, 24]. Studies indicate the relevance of the screening of this pathology in risk populations, such as smokers and alcoholics. And it is even more relevant given the delay in diagnosis. Although evidence from the use of the visual examination of the mouth on mortality rates is weak by OC, some authors suggest proceeding to the screening on individuals who are exposed to risk factors. For these people, it may result in an increased positive predictive factor [7].
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The approach to OC should involve prevention and control measures, including routine screening for early detection; offer of opportunities for evaluation of oral lesions (active search—through home visits or specific campaigns); follow-up of suspected cases, creating a referral service if necessary; and establishing partnerships between universities and other organizations for prevention, diagnosis, treatment, and recovery [18].
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Actions with this objective can be organized as primary prevention. They include activities geared at disseminating information to the population, intending to change unhealthy lifestyle habits to healthy ones and to reduce the prevalence and incidence rates. At this level, the emphasis is placed on drinking, smoking, diet, and exposure to sun and human papillomavirus (HPV) infection.
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Secondary prevention, in turn, occurs through the identification of precancerous lesions. For correct identification, it is essential to train health-care professionals with an emphasis on assessing potentially malignant cell lesions/disorders (PMD) (DPM) [17].
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Below in Table 1 is a summary of the risk factors and prevention methods.
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4. Noninvasive methods for diagnosis of OC
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Easy-to-handle, noninvasive diagnostic methods are useful for identifying precancerous lesions. The following noninvasive methods are cited: toluidine blue testing, exfoliative cytology, autofluorescence, contact endoscopy, and in vivo microscopy. However, there is no scientific evidence that these methods are more effective than oral inspection and palpation. Thus, more extensive studies are needed to justify the widespread use of these methods in the population. However, studies have shown that these methods can be useful if used in people with risk factors and non-healing lesions, favoring a faster diagnosis [20, 25, 26].
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The following noninvasive diagnostic methods should be used according to the possibilities and conditions of the context.
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4.1 Toluidine blue test
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Toluidine blue is a basic thiazine metachromatic dye that selectively marks acidic groups of tissue components (carboxylic radicals, sulfates, and phosphates), showing an affinity for nuclear DNA and cytoplasmic RNA, which fix the dye, becoming richly stained. The intensity of toluidine blue staining depends on the degree of involvement of the epithelial surface. In benign lesions, there is a faint coloration; in dysplasia and epithelial lesions and carcinomas, the coloration is more intense.
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The application maneuver consists of drying and isolating the region to be examined from salivary contamination by grasping the site with the fingers and using gauze. Employing a flexible cotton swab, 1% acetic acid (acid solution) is applied to clean the lesion surface, remove the glycoprotein barrier of cells, and promote slight dehydration of the mucosa. After 1 minute, the AT dye is applied with the other side of the cotton swab, and after 1 minute, the excess is cleaned with 1% acetic acid again and washed with plenty of water.
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The result is intended to highlight intensely stained areas compatible with areas of tissue degeneration. Indications: detection of epithelial dysplasias, in situ or early invasive carcinomas, delimitation of neoplastic epithelium margins, assessment of tumor recurrence after surgical or radiotherapy treatment, delimitation of areas of cancer action, screening of oral lesions in population groups exposed to risk factors for oral cancer, and in intraoperative actions for marginal control of carcinomas.
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It has the advantages of being painless, low-cost, and easy to apply, giving fast results, and having high sensitivity. As for disadvantages, it may generate false-positive or false-negative results and be of low and little specificity [10, 27].
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4.2 Exfoliative cytology
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It can be defined as the morphological and morphometric study of desquamated cells of the mucosa, mainly suprabasal cells, through optical microscopy. It consists in the examination of cells from various parts of the body to determine the cause or nature of the disease that affects them.
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There are reports of numerous methods for collection of these cells in the literature. Conventional exfoliative cytology and liquid-based exfoliative cytology are two of the most disseminated among them.
\n
Collecting the material in exfoliative cytology involves scraping the surface of the lesion with a spatula or brush, which is then smeared over the glass slide, and the material is fixed to the slide using 95% alcohol or 1:1 alcohol/ether solution.
\n
Exfoliation cytology in liquid media has been developed in recent years as a method that could replace the conventional exfoliative cytology proposed by Papanicolaou. Collection by this method is done using a brushing device with soft bristles arranged in a conical shape, which is then dipped in a methanol-based preservative liquid contained in a hermetically sealed tube. Such liquid has the function of preserving the cellular structure, the proteins, and principally the genetic material. The liquid undergoes a centrifugation or homogenization process, which helps to shrink some artifacts, and it is then filtered. The residual material in the filters is put in blades by contact imprinting. Debris, red blood cells, and mucus pass through the filter pores, which retain the epithelial cells to be analyzed.
\n
It has the advantages of being painless, harmless, noninvasive, and low-cost. As for disadvantages, it does not have the same efficacy as biopsy concerning identifying the type of lesion, but it is beneficial when the biopsy is not possible [20, 28, 29].
\n
\n
\n
4.3 Fluorescence/autofluorescence
\n
Optical fluorescence can be used as an aid to oral clinical examination. It allows, by autofluorescence, the detection of numerous changes in the oral cavity that could go unnoticed by the dentist or even be difficult to perceive with the visual method alone.
\n
The oral fluorescence system allows the observation of changes in dental hard tissues such as stains, dental plaque and calculus, incipient lesions, and marginal infiltrations and facilitates the differentiation between restorative materials such as composite resin and ceramic.
\n
In soft tissues, it is possible to detect potentially malignant lesions and tumoral lesions. Therefore, the optical fluorescence system allows the simple, noninvasive, and real-time diagnosis and identification of structures and alterations in the oral cavity, revealing lesions that would not be easily detected with conventional illumination.
\n
As advantages, this method is highly sensitive to cancer and dysplasia, allows the evaluation of large areas of the oral mucosa during a consultation, and is noninvasive and painless. However, it has the disadvantage of false-positive results [20].
\n
\n
\n
4.4 Contact endoscopy
\n
It is also known as contact microstomatoscopy. It consists of the contact of the endoscope lens with the mucosa, the vermilion, and or the lesion.
\n
It has the advantages of being painless and providing a fast diagnosis. However, a study by showed that the difficulties encountered about the device and the anatomical structures examined (lip and oral cavity) were related to the contact of the lens surface, fine tremors, and the sliding of the device; these difficulties varied according to topography. The quality depended on the site of the lesion, the extent of the ulceration, the volume of crusts, prior cleaning of the site, patient collaboration, the presence of more or less saliva, the mobility of the examined structure, and the support for the device [28, 30].
\n
\n
\n
4.5 In vivo microscopy
\n
High-resolution microendoscopy, optical coherence tomography, confocal reflectance microscopy, and multiphoton imaging are considered in this classification. These methods allow practitioners to see many of the same microscopic features used for histopathological evaluation at the consultation.
\n
Each technology measures different optical properties of the tissue and offers various features in parameters such as image depth, resolution, visual field, and acquisition time. Their development is at an early stage. We cite Raman spectroscopy as a promising technique for cancer diagnosis. This device is an analytical noninvasive technique that provides information about the molecular structure of the investigated sample, considering that the molecular structures of proteins and lipids differ between normal and neoplastic tissues.
\n
The advantage of these technologies is their accuracy, but the high cost of acquisition is a significant disadvantage [20, 31].
\n
\n
\n
4.6 Tumor biomarkers
\n
Tumor biomarkers are substances found in blood, urine, or other body fluids and tissues that may be in increased amounts when a particular type of cancer is present. These biomarkers are used for diagnostic elucidation through serology and histological methods. They are cellular, structural, and biochemical components that can be quantitatively measured by biochemical, immunological, and molecular methods in body fluids and tissues associated with neoplasms and possibly the organs where cancer originates.
\n
At present, no marker is used for cancer detection in the general population, only for people who are in the risk group for certain types of cancer. In this case, biomarkers can help to diagnose the disease in early stages.
\n
Research on the diagnosis of saliva using nanotechnology and molecular technologies to detect oral squamous cell carcinoma (OSCC) is currently being expanded. Collecting saliva for this assessment is a secure, noninvasive method, which is considered advantageous.
\n
Diagnosing saliva using nanotechnology and molecular technologies to detect OSCC has become an attractive field of study. New cancer-related proteins have been reported, as well as potent biomarkers for early diagnosis, further facilitating the application of quantification in proteomics for carcinogenesis research. Identifying transcripts and pathways that change at early stages of carcinogenesis provides potentially useful information for early diagnosis and prevention strategies.
\n
At the beginning of the research on this method, the hope was that all cancers could be detected at an early stage, preventing the death of millions of people. But only a few markers can detect cancer at an early stage. The disadvantages of this method are most people have a small amount of these markers that prevents detection, the levels of these markers tend to increase when the disease progresses, some cancer patients may never have high levels of markers, and even in the presence of elevated levels, they do not always indicate cancer, as they may be related to other disorders [6, 32, 33, 34, 35, 36].
\n
\n
\n
4.7 Oral inspection and palpation
\n
The main areas examined for oral cancer are the face, neck, lips, nostrils, and oral cavity. Before the screening, the patient should remove all removable dental appliances and devices to leave the entire area exposed. The patient must be seated or lying down, and the dentist must look for signs of asymmetry, edema, swelling, staining, ulceration, or other abnormalities.
\n
To examine the inside of the mouth, the practitioner will use good lighting and a mirror to see clearly; he will also use a tongue depressor to immobilize the organ and look at the back of the mouth. After or during the visual examination, the dentist will palpate the head, face, around the jaw, under the chin, and the oral cavity. The aim is to detect unusual lumps or masses. Another sign of a potential problem is immobility in some regularly moving tissue.
\n
The advantages are the fast, painless, low-cost characteristics of the method, and the disadvantage is that it relies heavily on the examiner’s skills and knowledge. Conventional oral examination (COE) alone is insufficient for risk stratification. COE is generally useful for identifying lesions but not for subsequent clinical follow-up for treatment planning [20].
\n
Despite the importance of the methods described above as adjuvants in the process of diagnosis of suspected lesions, the biopsy is considered the gold standard for definitive diagnosis [20].
\n
All of these methods have their advantages and disadvantages and can be used in care to facilitate diagnosis. These noninvasive alternatives are not much disseminated in health services, and visual inspection under white light and palpation by a physician or dentist remain as the gold standard for screening of oral cancer. This procedure, however, has the limitation of being dependent on the examiner’s experience; this limitation underlies the development of more objective diagnostic techniques.
\n
Despite the scarcity of evidence about the abovementioned noninvasive methods as the diagnosis of a lesion front line, they can be useful in several situations. For instance, in cases where the biopsy is not a reasonable procedure, either for cost or complexity, most of these methods can make a difference.
\n
They used to be inexpensive, can be performed by less specialized professionals, are generally handled with lighter technology, and are more easily implemented in less resourceful regions and within primary health care [25, 26]. In these situations, the aim is to replace noninvasive techniques where a biopsy cannot be performed promptly. More, it can facilitate the screening of lesions in apparently healthy people, with or without risk factors for cancer, since it is a recommended noninvasive method that makes it possible to differentiate malignant to benign lesions. Despite the several possibilities of diagnostic methods, the rates still indicate that patients are diagnosed in advanced stages of cancer [25, 26, 37].
\n
These adjuvant diagnostic methods may help dentists better evaluate lesions suggestive of oral cancer before a definitive biopsy. The existing adjuvants such as toluidine blue, acetowhitening, and autofluorescence imaging are not much specific and, therefore, generally not recommended. Recently, new in vivo microscopy technologies such as high-resolution microendoscopy, optical coherence tomography, reflectance confocal microscopy, and multiphoton imaging have shown to offer promising improvements and more accurate diagnosis of these lesions and are not invasive procedures. The advantages of these technologies are that they allow the visualization of the microscopic characteristics used for histopathological evaluation at the moment of consultation, making the diagnosis faster, besides being painful or uncomfortable to patients [20].
\n
Other measures discussed are those related to the reorganization of health services, screening of risk groups, and awareness campaigns. These measures are used in many countries around the world, but the problem of late diagnosis is still a worldwide reality [38, 39].
\n
New strategies to approach the population and to identify suspicious lesions are paramount in the dissemination of information and for the increase of early diagnosed cases. The cooperation of primary health-care teams and not only of oral health professionals is essential for the fight against late diagnosis. Because other sectors of the health area often assist the population and can identify the risk, and even suspicious lesions, they also should be able to refer patients to the oral health sector. Thus, with all professionals working together in primary health care, identifying risk factors and suspicious lesions, and referring to the responsible sector, this collaborative work may bring a great positive gain for the population [14, 38].
\n
Below in a Table 2 is a summary of the methods discussed above.
\n
\n
\n
4.8 Considerations
\n
Considering the real problem of oral cancer worldwide, actions aimed at reducing the negative impact on society should be carried out with planning to achieve excellence of care to the population.
\n
Some factors lead to late diagnosis of oral cancer. Thus, such elements must be identified in each population so that health professionals can act to interfere with these factors, leading to better care for the community. Knowing population profile to be assisted is required, as much to identify factors that interfere with the diagnosis of the pathology as in the action planning.
\n
Although the biopsy is considered as the gold standard for definitive diagnosis, there are some constraints for your full application. This method is invasive and expensive, the results may take some days to be disclosed, and it requires specialized training, thus limiting its use for screening. Therefore, noninvasive methods are valuable, becoming more suitable in specific contexts.\n
Nomenclature
\n\nOC\n\n
oral cancer
\n\n\n\nHPV\n\n
human papilloma virus
\n\n\n\nIARC\n\n
International Agency for Research on Cancer
\n\n\n\nMPD\n\n
malignant cell lesions/disorders
\n\n\n\nCOE\n\n
conventional oral examination
\n\n\n\n
\n
\n
\n\n',keywords:"oral health, prevention, primary health care, secondary health care, oral cancer",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/69234.pdf",chapterXML:"https://mts.intechopen.com/source/xml/69234.xml",downloadPdfUrl:"/chapter/pdf-download/69234",previewPdfUrl:"/chapter/pdf-preview/69234",totalDownloads:269,totalViews:0,totalCrossrefCites:0,dateSubmitted:"May 20th 2019",dateReviewed:"August 21st 2019",datePrePublished:"November 28th 2019",datePublished:"May 13th 2020",dateFinished:"September 25th 2019",readingETA:"0",abstract:"Oral cancer is a public health problem because of its high morbidity and mortality, and when not treated in a timely manner, it is significantly mutilating, causing damage to the physical and psychological aspects of patients and directly interfering with their quality of life. Several factors influence the early diagnosis of this pathology, including lack of self-care related to oral health, especially among people with prolonged use of dental prosthesis; delayed perception of the lesion; delayed search for professional assistance since the lesion is noticed by the patient; lack of information about oral cancer, its risk and protective factors, and oral lesions that may be suggestive of cancer; lack of health promotion and prevention activities aimed at oral cancer; and lack of training in oral cancer among oral health professionals. These factors must be tackled to promote the timely diagnosis of this pathology. The use of reliable noninvasive diagnosis methods is also important because they can be easily made available in low resource settings, increasing the coverage of people who are under risk of developing oral cancer.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/69234",risUrl:"/chapter/ris/69234",signatures:"Manoela Garcia Dias da Conceição, Ana Cláudia Figueiró and Vera Lucia Luiza",book:{id:"9387",title:"Oral Diseases",subtitle:null,fullTitle:"Oral Diseases",slug:"oral-diseases",publishedDate:"May 13th 2020",bookSignature:"Gokul Sridharan, Anil Sukumaran and Alaa Eddin Omar Al Ostwani",coverURL:"https://cdn.intechopen.com/books/images_new/9387.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83880-503-6",printIsbn:"978-1-83880-502-9",pdfIsbn:"978-1-83880-541-8",editors:[{id:"82453",title:"Dr.",name:"Gokul",middleName:null,surname:"Sridharan",slug:"gokul-sridharan",fullName:"Gokul Sridharan"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"305759",title:"Dr.",name:"Manoela",middleName:"Garcia Dias",surname:"Da Conceição",fullName:"Manoela Da Conceição",slug:"manoela-da-conceicao",email:"manu_dias1984@yahoo.com.br",position:null,institution:null},{id:"306004",title:"Dr.",name:"Vera Lucia",middleName:null,surname:"Luiza",fullName:"Vera Lucia Luiza",slug:"vera-lucia-luiza",email:"negritudesenior@gmail.com",position:null,institution:null},{id:"310149",title:"Dr.",name:"Ana Cláudia",middleName:null,surname:"Figueró",fullName:"Ana Cláudia Figueró",slug:"ana-claudia-figuero",email:"anaclaudiafiguero@gmail.com",position:null,institution:{name:"Escola Nacional de Saúde Pública",institutionURL:null,country:{name:"Brazil"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Factors related to late diagnosis of oral cancer",level:"1"},{id:"sec_3",title:"3. Prevention of oral cancer",level:"1"},{id:"sec_4",title:"4. Noninvasive methods for diagnosis of OC",level:"1"},{id:"sec_4_2",title:"4.1 Toluidine blue test",level:"2"},{id:"sec_5_2",title:"4.2 Exfoliative cytology",level:"2"},{id:"sec_6_2",title:"4.3 Fluorescence/autofluorescence",level:"2"},{id:"sec_7_2",title:"4.4 Contact endoscopy",level:"2"},{id:"sec_8_2",title:"4.5 In vivo microscopy",level:"2"},{id:"sec_9_2",title:"4.6 Tumor biomarkers",level:"2"},{id:"sec_10_2",title:"4.7 Oral inspection and palpation",level:"2"},{id:"sec_11_2",title:"4.8 Considerations",level:"2"}],chapterReferences:[{id:"B1",body:'\nWorld Health Organization. The World Oral Health Report 2003. Continuous improvement of oral health in the 21st century-the approach of the WHO Global Oral Health Programme. 2003\n'},{id:"B2",body:'\nToscano de Brito R, França Perazzo M, Santos Peixoto T, Weege-Nonaka CF, de Melo Brito Costa EM, Granville-Garcia AF. Profile of patients and factors related to the clinical staging of oral squamous cell carcinoma. Revista de Salud Pública Bogota. dezembro de. 2018;20(2):221-225\n'},{id:"B3",body:'\nChaturvedi P, Singh A, Chien C-Y, Warnakulasuriya S. Tobacco related oral cancer. BMJ. junho de. 2019;365:l2142\n'},{id:"B4",body:'\nFerlay J. Globocan 2012: Cancer Incidence and Mortality Worldwide. IARC; 2013\n'},{id:"B5",body:'\nFerlay J. Globocan 2018: Cancer Incidence and Mortality Worldwide. IARC; 2019\n'},{id:"B6",body:'\nMishra R. Biomarkers of oral premalignant epithelial lesions for clinical application. Oral Oncology. 06PY - 2012 de. 2012;48(7):578-584\n'},{id:"B7",body:'\nBhatt S, Isaac R, Finkel M, Evans J, Grant L, Paul B, et al. Mobile technology and cancer screening: Lessons from rural India. Journal of Global Health. 2018;8(2):020421-020421\n'},{id:"B8",body:'\nCarvalho AL, Singh B, Spiro RH, Kowalski LP, Shah JP. Cancer of the oral cavity: A comparison between institutions in a developing and a developed nation. janeiro de. 2004;26(1):31-38\n'},{id:"B9",body:'\nKowalski LP, Brentani MM, Coelho FRG. Bases da oncologia. São Paulo: Lemar; 2003\n'},{id:"B10",body:'\nRamos GHA, de Oliveira BV, Biasi LJ, Sampaio Júnior LA. Avaliação da citologia e do teste do azul de toluidina no diagnóstico dos tumores malignos da mucosa oral. Revista Brasileira de Cirurgia da Cabeça e Pescoço. 03PY - 2007 de. 2007;36(1):27-29\n'},{id:"B11",body:'\nda Silva MC, Marques EB, de Melo LC, de Bernardo JMP, Leite ICG. Fatores relacionados ao atraso no diagnóstico de câncer de boca e orofaringe em Juiz de Fora/MG. Revista Brasileira de Cancerologia. 2009;55(4):329-335\n'},{id:"B12",body:'\nRafieian N, Azimi S, Manifar S, Julideh H, ShirKhoda M. Is there any association between green tea consumption and the risk of head and neck squamous cell carcinoma: Finding from a case-control study. Archives of Oral Biology. 2019;98:280-284\n'},{id:"B13",body:'\nZhou H, Wu W, Wang F, Qi H, Cheng Z. Tea consumption is associated with decreased risk of oral cancer: A comprehensive and dose-response meta-analysis based on 14 case-control studies (MOOSE compliant). Med Baltimore. dezembro de. 2018;97(51):e13611\n'},{id:"B14",body:'\nAmorim NGC, Sousa AS, Alves SM. Prevenção e diagnóstico precoce do câncer bucal: Uma revisão de literatura. Revista Uningá. junho de. 2019;56(2):70-84\n'},{id:"B15",body:'\nNarvai PC, Frazão P. Saúde Bucal no Brasil muito além do céu da boca. Rio de Janeiro: Fiocruz; 2008. 148 p\n'},{id:"B16",body:'\nRangel EB, Lucietto DA, Stefenon L. Autopercepção de cirurgiões-dentistas sobre conhecimentos e práticas em relação ao câncer de boca. Revista Rede de Cuidados em Saúde. dezembro de. 2018;12(2):28-40\n'},{id:"B17",body:'\nTorres-Pereira CC, Angelim-Dias A, Melo NS, Lemos CA Jr, de Oliveira EMF. Abordagem do câncer da boca: Uma estratégia para os níveis primário e secundário de atenção em saúde Strategies for management of oral cancer in primary and secondary healthcare services. Cadernos de Saúde Pública. 2012;28(supl):s30-s39\n'},{id:"B18",body:'\nDias MG. Avaliação da Atenção em Saúde Bucal: contribuições para o controle do câncer de boca no município do Rio de Janeiro. Rio de Janeiro: Escola Nacional de Saúde Pública; 2018\n'},{id:"B19",body:'\nAl-Kaabi R, Gamboa ABO, Williams D, Marcenes W. Social inequalities in oral cancer literacy in an adult population in a multicultural deprived area of the UK. Journal of Public Health—Oxford Academic. 2016;38(3):474-482\n'},{id:"B20",body:'\nYang EC, Tan MT, Schwarz RA, Richards-Kortum RR, Gillenwater AM, Vigneswaran N. Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: Current limitations and future directions. Oral Surgery, Oral Medicine, Oral Pathology, and Oral Radiology. abril de. 2018;125(6):670-681\n'},{id:"B21",body:'\nAlvarenga ML, Couto MG, de Ribeiro AO, Milagres RCM, Messora MR, Kawata LT. Avaliação do conhecimento dos cirurgiões-dentistas quanto ao câncer bucal. RFO UPF [Internet]. 04PY - 2012 de 2012;17(1). Disponível em: http://files.bvs.br/upload/S/1413-4012/2012/v17n1/a2980.pdf\n\n'},{id:"B22",body:'\nLeavell H, Clark EG. Preventive Medicine for the Doctor in His Community. MacGraw Hill: Nova York; 1965\n'},{id:"B23",body:'\nSilva, da AN, Senna, de MAA, Jorge RC, da Albuquerque DMS, de Queiroz TF. Promoção da Saúde. In: Fundamentos em Saúde Bucal Coletiva. Rio de Janeiro: Medbook; 2013. pp. 1-14\n'},{id:"B24",body:'\nBrasil Instituto Nacional de Câncer—INCA. A Situação do câncer no Brasil. INCA; 2006\n'},{id:"B25",body:'\nWalsh T, Liu JL, Brocklehurst P, Glenny AM, Lingen M, Kerr AR, et al. Clinical assessment to screen for the detection of oral cavity cancer and potentially malignant disorders in apparently healthy adults. Cochrane Database of Systematic Reviews. 12PY - 2013 de. 2013;11:CD010173-CD010173\n'},{id:"B26",body:'\nSweeny L, Dean NR, Magnuson JS, Carroll WR, Clemons L, Rosenthal EL. Assessment of tissue autofluorescence and reflectance for oral cavity cancer screening. Otolaryngology–Head and Neck Surgery. 12PY - 2011 de. 2011;145(6):956-960\n'},{id:"B27",body:'\nSharbatdaran M, Abbaszadeh H, Siadati S, Ranaee M, Hajian-Tilaki K, Rajabi-Moghaddam M. Assessment of oral cytological features in smokers and nonsmokers after application of toluidine blue. Diagnostic Cytopathology. março de. 2017;45(6):513-519\n'},{id:"B28",body:'\nDias MG, Figueiró AC, Luiza VL. Prevention and early diagnosis of oral cancer—A literature review. Revista Odonto Ciência. 25 de julho de. 2018;32(4):204\n'},{id:"B29",body:'\nLucena EE de S, Miranda AM, Araújo FA da C, Galvão CAB, de Medeiros AMC. Método de coleta e a qualidade do esfregaço de mucosa oral. Revista de Cirurgia e Traumatologia Buco Maxilo Facial. junho de. 2011;11(2):55-62\n'},{id:"B30",body:'\nRamos GHA, Tavares MR, Dedivitis RA, França CM, Oliveira BV, Pedruzzi PA. Endoscopia de contato (microestomatoscopia) nas lesões da boca e do lábio: Avaliação do método. Revista do Colégio Brasileiro de Cirurgiões. 2008;35(6):355-360\n'},{id:"B31",body:'\nPelc R, Masek V, Llopis-Torregrosa V, Bour P, Wu T. Spectral counterstaining in luminescence-enhanced biological Raman microscopy. Chemical Communications. julho de. 2019;55(57):8329-8332\n'},{id:"B32",body:'\nJiang W-P, Wang Z, Xu L-X, Peng X, Chen F. Diagnostic model of saliva peptide finger print analysis of oral squamous cell carcinoma patients using weak cation exchange magnetic beads. Julho de. 2015;35(3). Disponível em: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4613719/?tool=pubmed\n\n'},{id:"B33",body:'\nGuerrero-Preston R, Soudry E, Acero J, Orera M, Moreno-López L, Macía-Colón G, et al. NID2 and HOXA9 promoter hypermethylation as biomarkers for prevention and early detection in oral cavity squamous cell carcinoma tissues and saliva. Cancer Prevention Research (Phila). 07PY - 2011 de. 2011;4(7):1061-1072\n'},{id:"B34",body:'\nMankapure PK, Barpande SR, Bhavthankar JD, Mandale M. Serum big endothelin-1 as a biomarker in oral squamous cell carcinoma patients: An analytical study. Journal of Applied Oral Science. novembro de. 2015;23(5):491-496\n'},{id:"B35",body:'\nLingen MW. Screening for oral premalignancy and cancer: What platform and which biomarkers? Cancer Prevention Research (Phila). 09PY - 2010 de. 2010;3(9):1056-1059\n'},{id:"B36",body:'\nBrinkmann O, Kastratovic DA, Dimitrijevic MV, Konstantinovic VS, Jelovac DB, Antic J, et al. Oral squamous cell carcinoma detection by salivary biomarkers in a Serbian population. Oral Oncology. 02PY - 2011 de. 2011;47(1):51-55\n'},{id:"B37",body:'\nMehrotra R, Gupta DK. Exciting new advances in oral cancer diagnosis: Avenues to early detection. Head and Neck Oncology. 2011;3\n'},{id:"B38",body:'\nBulgareli JV, Diniz OCCF, de Faria ET, de Vazquez FL, Cortellazzi KL, Pereira AC. Prevenção e detecção do câncer bucal: planejamento participativo como estratégia para ampliação da cobertura populacional em idosos. Ciênc Saúde Coletiva. 12PY - 2013 de. 2013;18(12):3461-3473\n'},{id:"B39",body:'\nde Scheufen RC, Almeida FCS, da Silva DP, de Araujo ME, Palmiere M, Pegoretti T, et al. Prevenção e detecção precoce do câncer de boca: Screening em populações de risco. Pesquisa Brasileira em Odontopediatria e Clínica Integrada. 02PY - 2012 de. 2012;11(02). Disponível em: http://revista.uepb.edu.br/index.php/pboci/article/viewFile/1442/683\n\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Manoela Garcia Dias da Conceição",address:"manu_dias1984@yahoo.com.br",affiliation:'
Sergio Arouca National School of Public Health, ENSP, Oswaldo Cruz Foundation, FIOCRUZ, Brazil
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