Discriminating basal cell carcinoma from its surrounding tissue by Raman spectroscopy
- PMID: 12164926
- DOI: 10.1046/j.1523-1747.2002.01807.x
Discriminating basal cell carcinoma from its surrounding tissue by Raman spectroscopy
Abstract
The objective of this in vitro study was to explore the applicability of Raman spectroscopy to distinguish basal cell carcinoma from its surrounding noncancerous tissue; therefore, identifying possibilities for the development of an in vivo diagnostic technique for tumor border demarcation. Raman spectra were obtained in a two-dimensional grid from unstained frozen sections of 15 basal cell carcinoma specimens. Pseudo-color Raman images were generated by multivariate statistical analysis and clustering analysis of spectra and compared with histopathology. In this way a direct link between histologically identifiable skin layers and structures and their Raman spectra was made. A tissue classification model was developed, which discriminates between basal cell carcinoma and surrounding nontumorous tissue, based on Raman spectra. The logistic regression model, shows a 100% sensitivity and 93% selectivity for basal cell carcinoma. The Raman spectra were, furthermore, used to obtain information about the differences in molecular composition between different skin layers and structures. An interesting finding was that in four samples of nodular basal cell carcinoma, the collagen signal contribution in spectra of dermis close to a basal cell carcinoma, was markedly reduced. The study demonstrates the sensitivity of Raman spectroscopy to biochemical changes in tissue accompanying malignancy, resulting in a high accuracy when discriminating between basal cell carcinoma and noncancerous tissue.
Similar articles
-
Using Raman Spectroscopy to Detect and Diagnose Skin Cancer In Vivo.Dermatol Clin. 2017 Oct;35(4):495-504. doi: 10.1016/j.det.2017.06.010. Epub 2017 Aug 9. Dermatol Clin. 2017. PMID: 28886805 Review.
-
Paraconsistent analysis network applied in the treatment of Raman spectroscopy data to support medical diagnosis of skin cancer.Med Biol Eng Comput. 2016 Oct;54(10):1453-67. doi: 10.1007/s11517-016-1471-3. Epub 2016 Mar 28. Med Biol Eng Comput. 2016. PMID: 27021066 Review.
-
Polarized Raman microspectroscopy can reveal structural changes of peritumoral dermis in basal cell carcinoma.Appl Spectrosc. 2008 Oct;62(10):1088-94. doi: 10.1366/000370208786049187. Appl Spectrosc. 2008. PMID: 18926017
-
Discriminating basal cell carcinoma from perilesional skin using high wave-number Raman spectroscopy.J Biomed Opt. 2007 May-Jun;12(3):034004. doi: 10.1117/1.2750287. J Biomed Opt. 2007. PMID: 17614712
-
Infrared spectra of basal cell carcinomas are distinct from non-tumor-bearing skin components.J Invest Dermatol. 1999 Jun;112(6):951-6. doi: 10.1046/j.1523-1747.1999.00612.x. J Invest Dermatol. 1999. PMID: 10383744
Cited by
-
From Vibrations to Visions: Raman Spectroscopy's Impact on Skin Cancer Diagnostics.J Clin Med. 2023 Nov 30;12(23):7428. doi: 10.3390/jcm12237428. J Clin Med. 2023. PMID: 38068480 Free PMC article. Review.
-
Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review.Biosensors (Basel). 2023 May 18;13(5):557. doi: 10.3390/bios13050557. Biosensors (Basel). 2023. PMID: 37232918 Free PMC article. Review.
-
Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.PLoS One. 2022 Dec 30;17(12):e0279739. doi: 10.1371/journal.pone.0279739. eCollection 2022. PLoS One. 2022. PMID: 36584158 Free PMC article.
-
Novel aspects of Raman spectroscopy in skin research.Exp Dermatol. 2022 Sep;31(9):1311-1329. doi: 10.1111/exd.14645. Epub 2022 Jul 25. Exp Dermatol. 2022. PMID: 35837832 Free PMC article. Review.
-
Deep learning on reflectance confocal microscopy improves Raman spectral diagnosis of basal cell carcinoma.J Biomed Opt. 2022 Jun;27(6):065004. doi: 10.1117/1.JBO.27.6.065004. J Biomed Opt. 2022. PMID: 35773774 Free PMC article.
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical