Article Updated on 2nd December 2020
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Due to its noninvasive nature, Raman Spectroscopy has found its role in aiding diagnosis by investigating living tissue.
The optical technique analyzes the nature of the light scatter emitted from living tissue to determine its structural characteristics, leading to it being referred to as the optical biopsy. The benefit of this technique is that tissue can be investigated without destroying it. The medical sector has already welcomed the technology and Raman Spectroscopy is being used successfully in different areas of diagnosis.
Raman Spectroscopy for diagnosis
Raman scatter was acknowledged almost a century ago when Dr. C. V. Raman described the phenomena in a 1928 publication. He found that when light is shone onto a sample of a transparent chemical compound a small portion of the light photons gain energy from or give energy to molecules in the sample. This change in energy level alters the wavelength of a small percentage of the deflected light, which can be detected by Raman Spectroscopy to determine the molecular composition of the tissue. This analysis can be used in diagnosis to identify healthy samples from diseased ones.
Applications in medical diagnosis
Cancer is a major focus of Raman Spectroscopy for medical diagnoses. The major draw is that it offers the opportunity to study living samples without causing unnecessary damage.
2015 saw the development of a Raman probe with the capabilities of an in vivo diagnosis of lung cancer. The impact of integrating this method during autofluorescence bronchoscopy was that false positives were reduced.
The previous year saw scientists performing real-time diagnosis of gastrointestinal cancers. Dysplasia of Barret’s Esophagus was determined in real-time, producing an impressive diagnostic sensitivity of 87.0%. Further to this, Raman spectroscopy has been successfully used in studies to identify tumor lesion tissue from healthy tissue in mice with colon cancer.
Also in 2015, researchers were able to show that oral cancers could be identified through inspecting the Raman spectra of oral tissues, using Raman Spectroscopy to classify tissue as either benign or malignant with 77% sensitivity. Also, studies have shown that the method can be used to flag changes in oral mucosa as early detection of oral cancer.
Research has also shown that the diagnosis of melanoma and nonmelanoma skin cancers can be successfully achieved through using Raman spectroscopy alone, independent of reflectance and fluorescence.
Finally, recent innovations have been made to create a system that incorporates a Raman Spectroscopy guidance system within the tip of a brain biopsy needle, enabling surgeons to inspect brain tissue at the tip of the biopsy needle without damaging the tissue. The system is expected to allow surgeons to harvest cells from areas that are denser with cancer tissue to get a more accurate diagnosis.
Numerous studies have been able to use Raman Spectroscopy to determine the molecular structure of skin to diagnose atopic dermatitis. Further to this, the technique has been used to detect the presence of the protein filaggrin in the skin of babies, acting as an early signal of atopic dermatitis.
Principal component analysis of Raman Spectra has been used to determine chronological aging of the skin from photoinduced skin damage.
People with a nickel allergy present differences in skin structure compared to those without. Principal component analysis has been able to classify the Raman Spectral differences between these groups.
The Raman skin spectra of patients with melasma has been found to be unique in its melanin profile. Differences of the Raman skin spectrum has been found to be related to patients who do not respond well to treatment.
Diagnosis through Raman Spectroscopy demonstrates a huge potential for assisting in the diagnosis of a number of illnesses. Its full potential is yet to be realized, as results from more studies are leaving the lab all the time, showing the medical community how it can be used to improve diagnosis for a growing number of illnesses.
References and Further Reading