Paper
9 February 2012 Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm
Landulfo Silveira Jr., Fabrício L. Silveira, Benito Bodanese, Marcos Tadeu T. Pacheco, Renato A. Zângaro
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Abstract
This work demonstrated the discrimination among basal cell carcinoma (BCC) and normal human skin in vivo using near-infrared Raman spectroscopy. Spectra were obtained in the suspected lesion prior resectional surgery. After tissue withdrawn, biopsy fragments were submitted to histopathology. Spectra were also obtained in the adjacent, clinically normal skin. Raman spectra were measured using a Raman spectrometer (830 nm) with a fiber Raman probe. By comparing the mean spectra of BCC with the normal skin, it has been found important differences in the 800-1000 cm-1 and 1250-1350 cm-1 (vibrations of C-C and amide III, respectively, from lipids and proteins). A discrimination algorithm based on Principal Components Analysis and Mahalanobis distance (PCA/MD) could discriminate the spectra of both tissues with high sensitivity and specificity.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Landulfo Silveira Jr., Fabrício L. Silveira, Benito Bodanese, Marcos Tadeu T. Pacheco, and Renato A. Zângaro "Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm", Proc. SPIE 8207, Photonic Therapeutics and Diagnostics VIII, 82070X (9 February 2012); https://doi.org/10.1117/12.910430
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Cited by 3 scholarly publications.
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KEYWORDS
Raman spectroscopy

Skin

Tissues

Principal component analysis

In vivo imaging

Proteins

Mahalanobis distance

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