22.3.3 Ex Vivo Tissue Analysis
At the tissue level, great efforts have been done to confirm and quantify the
chemical differences between normal and cancer tissues via Raman spectroscopy.
The main advantage of Raman spectroscopy is its greatest shortcoming as well. As
each spectrum includes a lot of information, it is sometimes hard to extract exact
information. Despite this shortcoming, many previous studies have successfully
proved the ability to analyze diseased tissue. Taking Raman spectra at defined
points on excised parathyroid tissue allowed Das et al. [43] to demonstrate that
Raman spectroscopy could discriminate between parathyroid adenomas and
hyperplasia with 95% sensitivity. In addition, quantification of the chemical differences between normal and diseased tissues is crucial to improve the sensitivity
and specificity. In addition, quantification of the chemical differences between
normal and diseased tissues is crucial to improve the sensitivity and specificity. De
Jong et al. [44] utilized Raman spectroscopy in conjunction with numerous multivariate data analysis to discriminate cells in bladder tissues. As differentiation
between normal and cancer is pivotal, Chowdary et al. [45] demonstrated that
Raman spectroscopy could be utilized to discern between benign and cancer in
breast tissues.
22.3.4 In Vivo SERS Imaging
Several techniques have recently been developed for the rapid in vivo acquisition of
multiple Raman signals. As expected, the most straightforward approach is targeting the skin. Raman spectroscopy has been conducted at very early stages to
assess pigments and antioxidant levels. In recent years, near-infrared Raman
spectroscopy [46] has been used to diagnose skin cancers. Compared to
histopathological analysis, Raman spectroscopy of skin lesions has consistently
demonstrated high diagnostic performance while performing studies, thus showed
potential for clinical applicability. Interestingly, if only data from the high
wavenumber area of the Raman spectra (>2800 cm
−1 ) are evaluated, a similar
diagnostic performance was achieved when compared with the fingerprint region
(approximately 400rformanc
−1 ). Therefore, the probe’s design can be considerably
simplified because there is no need to build high-performance filters into the probe
head [47].
Raman spectroscopy data acquisition typically requires second range; however,
recent progress of camera and spectrometer technology make data acquisition time
to be the millisecond range, which could facilitate the real-time assessment of
in vivo lesions [48]. Several applications of in vivo spectroscopy have been shown,
including the various type of cancer diagnosis (Fig. 22.2). A recent in vivo Raman
study of atherosclerosis proved that Raman spectroscopy can detect vulnerable
plaques [49]. In another study, the same group found that in vivo Raman
418
Y. Kim and D. S. Lee
At the tissue level, great efforts have been done to confirm and quantify the
chemical differences between normal and cancer tissues via Raman spectroscopy.
The main advantage of Raman spectroscopy is its greatest shortcoming as well. As
each spectrum includes a lot of information, it is sometimes hard to extract exact
information. Despite this shortcoming, many previous studies have successfully
proved the ability to analyze diseased tissue. Taking Raman spectra at defined
points on excised parathyroid tissue allowed Das et al. [43] to demonstrate that
Raman spectroscopy could discriminate between parathyroid adenomas and
hyperplasia with 95% sensitivity. In addition, quantification of the chemical differences between normal and diseased tissues is crucial to improve the sensitivity
and specificity. In addition, quantification of the chemical differences between
normal and diseased tissues is crucial to improve the sensitivity and specificity. De
Jong et al. [44] utilized Raman spectroscopy in conjunction with numerous multivariate data analysis to discriminate cells in bladder tissues. As differentiation
between normal and cancer is pivotal, Chowdary et al. [45] demonstrated that
Raman spectroscopy could be utilized to discern between benign and cancer in
breast tissues.
22.3.4 In Vivo SERS Imaging
Several techniques have recently been developed for the rapid in vivo acquisition of
multiple Raman signals. As expected, the most straightforward approach is targeting the skin. Raman spectroscopy has been conducted at very early stages to
assess pigments and antioxidant levels. In recent years, near-infrared Raman
spectroscopy [46] has been used to diagnose skin cancers. Compared to
histopathological analysis, Raman spectroscopy of skin lesions has consistently
demonstrated high diagnostic performance while performing studies, thus showed
potential for clinical applicability. Interestingly, if only data from the high
wavenumber area of the Raman spectra (>2800 cm
−1 ) are evaluated, a similar
diagnostic performance was achieved when compared with the fingerprint region
(approximately 400rformanc
−1 ). Therefore, the probe’s design can be considerably
simplified because there is no need to build high-performance filters into the probe
head [47].
Raman spectroscopy data acquisition typically requires second range; however,
recent progress of camera and spectrometer technology make data acquisition time
to be the millisecond range, which could facilitate the real-time assessment of
in vivo lesions [48]. Several applications of in vivo spectroscopy have been shown,
including the various type of cancer diagnosis (Fig. 22.2). A recent in vivo Raman
study of atherosclerosis proved that Raman spectroscopy can detect vulnerable
plaques [49]. In another study, the same group found that in vivo Raman
418
Y. Kim and D. S. Lee