7. Conclusions and outlook

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

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].

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

Among the disadvantages of Raman spectroscopy for biomedical applications is the weakness of the Raman effect, which most of the time is often accompanied by a stronger background

for in vivo Raman measurements of human tissue.

6. Limitations

304 Raman Spectroscopy

accurate diagnosis in terms of both sensitivity and specificity.

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 with disease.

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

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 environment.

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 environment.
