5.2.4. Melasma

Moncada et al. [55] used Raman spectroscopy in melasma patients treated with a triple combination cream (Tretinoin, Fluocinolona, and Hydroquinone) and found that the Raman skin spectra of the melasma patients showed differences in the peaks associated to melanin at 1352 and 1580 cm<sup>1</sup> (Figure 5). The Raman skin spectrum of patients who did not respond to treatment (Figure 1B) showed peaks that are not well defined, which are consistent with molecule degradation and protein breakdown. These results are consistent with the results reported previously by González et al. [56].

#### 5.2.5. Other in vivo applications: UV/Vis Raman, Raman imaging, and SERS

In most of the in vivo Raman applications, near infrared (NIR) excitation sources are preferred. NIR wavelengths in the range of 780–1100 nm result in lower fluorescence background in the tissue and simplify the analysis of the Raman bands in comparison to visible or UV excitation. The visible excitation sources have been used in various biomedical Raman applications [57]. However, the use of visible wavelengths has several disadvantages for in vivo biomedical Raman applications such as the decrease of penetration depth, autofluorescence, and heat generation. The UV radiation is not used for in vivo measurements due to the mutagenicity. In Raman imaging [58], a laser spot scans the sample area and acquires Raman spectra at every set point. The intensity of a specific Raman band or bands is used to build an image from cells and tissues. Also the Raman spectra can be discriminated by chemometric analysis and the result is an image of the sample that contains chemical information, also known as Raman chemical image. Other methods of Raman imaging include coherent anti-Stokes Raman spectroscopy (CARS) and stimulated Raman scattering. These methods have been applied to study biochemical interactions in cells and tissues. However, the in vivo applications have been limited to animal models. [59–61]. The Raman imaging has the disadvantage that long integration times are needed, which limit its use for in vivo measurement in humans. Surface-enhanced Raman spectroscopy (SERS)

signal particularly in biological samples. The background removing includes changes in instrumentation, which means high-complexity and high-cost systems. One alternative is the algorithm-based methods for fluorescence background removing. However, these methods cannot deal with all types of fluorescence without user intervention to adjust algorithm parameters. Additionally, the complexity of the fitting algorithms makes it difficult to use by nonexperts. Other limitation is that not all the molecules are Raman active, which means that some molecules do not give Raman signal. The potential of damaging the sample due to the laser exposure, which depends on the excitation wavelength, has to be taken for in vivo measurements. To solve this problem, lower energy excitation sources in the NIR range are preferred. Demonstrating the safety of these devices to regulatory agencies is a very important step for clinical implementation. For the in vivo diagnosis applications, larger studies are needed in order to test the reliability of the results. To date, a short number of studies involving a sufficient number of patients are reported. The lack of standardized and reliable methods for data analysis is an important limitation. Thus, standardization of measurement procedures, instrument calibration, processing, and evaluation of data is needed. Also the information provided by Raman spectra must be displayed in user-friendly, simple format, including

Raman Spectroscopy for In Vivo Medical Diagnosis http://dx.doi.org/10.5772/intechopen.72933 305

From the applications described in this chapter, it is clear that Raman spectroscopy has a great potential for in vivo measurements and identification of disease markers, which would make this technique a viable option for noninvasive medical diagnosis. Among the advantages of using Raman spectroscopy as a noninvasive tool for medical diagnosis is the fact that water is not Raman-active; therefore, it does not interfere with measurements. Also, the technique is noninvasive and fast and gives specific information about the structure and biochemical composition of samples, making it a viable option to identify molecules that are associated

Raman spectroscopy is likely to become a key player for in vivo and noninvasive medical diagnosis; however, in order to become a useful and reliable technique, it is important to use it along with signal processing methods and chemometrics in order to automatize and increase

An area of development that would accelerate the use of Raman spectroscopy in a clinical environment is the design of low-cost and portable Raman spectrometers, which would make their use more appealing for the medical community. Research in this area could also lead to an integrated optics Raman spectrometer, which would make the use of this technique useful in wearable health devices and monitoring of health parameters in a clinical

It is the authors' belief that the combination of optimized instrumentation, standardized measurement procedures, preprocessing, and data analysis will allow Raman spectroscopy to become a powerful tool for disease diagnostics and a common clinical tool in a hospital

the reliability of the measurements and the identification of the molecules of interest.

clinically relevant information for diagnosis.

7. Conclusions and outlook

with disease.

environment.

environment.

Figure 5. Raman skin spectra of all melasma patients, grouped by patients who responded to the treatment (A) and patients who did not respond to treatment (B). For each group, the central solid line corresponds to the mean of the spectra of each group, and the gray shadow around this line represents the standard deviation [55].

was used for in vivo biomedical applications to detect biomarkers in animal models [62–64]. However, the toxicity issues related to nanoparticles used for SERS make this method infeasible for in vivo Raman measurements of human tissue.

Other alternatives for in vivo biomedical applications are to combine Raman spectroscopy with other optical methods. For example, Raman spectroscopy has been combined with optical coherence tomography [65, 66], confocal reflectance microscopy [67, 68], diffuse reflectance, and fluorescence spectroscopy [46, 69]. The disadvantages of the multimodal approach are the higher cost and complexity of the system needed to perform the measurements. However, the multimodal approach has the advantage, when comparing with Raman spectroscopy alone that provides complementary and more detailed information about the disease and more accurate diagnosis in terms of both sensitivity and specificity.
