Literature DB >> 25345858

Raman spectroscopy differentiates squamous cell carcinoma (SCC) from normal skin following treatment with a high-powered CO2 laser.

Sara A Fox1, Ashley A Shanblatt, Hugh Beckman, John Strasswimmer, Andrew C Terentis.   

Abstract

BACKGROUND AND OBJECTIVES: The number of cases of non-melanoma skin cancer (NMSC), which include squamous cell carcinoma (SCC) and basal cell carcinoma (BCC), continues to rise as the aging population grows. Mohs micrographic surgery has become the treatment of choice in many cases but is not always necessary or feasible. Ablation with a high-powered CO2 laser offers the advantage of highly precise, hemostatic tissue removal. However, confirmation of complete cancer removal following ablation is difficult. In this study we tested for the first time the feasibility of using Raman spectroscopy as an in situ diagnostic method to differentiate NMSC from normal tissue following partial ablation with a high-powered CO2 laser.
MATERIALS AND METHODS: Twenty-five tissue samples were obtained from eleven patients undergoing Mohs micrographic surgery to remove NMSC tumors. Laser treatment was performed with a SmartXide DOT Fractional CO2 Laser (DEKA Laser Technologies, Inc.) emitting a wavelength of 10.6 μm. Treatment levels ranged from 20 mJ to 1200 mJ total energy delivered per laser treatment spot (350 μm spot size). Raman spectra were collected from both untreated and CO2 laser-treated samples using a 785 nm diode laser. Principal Component Analysis (PCA) and Binary Logistic Regression (LR) were used to classify spectra as originating from either normal or NMSC tissue, and from treated or untreated tissue.
RESULTS: Partial laser ablation did not adversely affect the ability of Raman spectroscopy to differentiate normal from cancerous residual tissue, with the spectral classification model correctly identifying SCC tissue with 95% sensitivity and 100% specificity following partial laser ablation, compared with 92% sensitivity and 60% selectivity for untreated NMSC tissue. The main biochemical difference identified between normal and NMSC tissue was high levels of collagen in the normal tissue, which was lacking in the NMSC tissue.
CONCLUSION: The feasibility of a combined high-powered CO2 laser ablation, Raman diagnostic procedure for the treatment of NMSC is demonstrated since CO2 laser treatment does not hinder the ability of Raman spectroscopy to differentiate normal from diseased tissue. This combined approach could be employed clinically to greatly enhance the speed and effectiveness of NMSC treatment in many cases.
© 2014 Wiley Periodicals, Inc.

Entities:  

Keywords:  Raman spectroscopy; basal cell carcinoma; laser ablation; logistic regression; principal component analysis; skin cancer; squamous cell carcinoma

Mesh:

Year:  2014        PMID: 25345858     DOI: 10.1002/lsm.22288

Source DB:  PubMed          Journal:  Lasers Surg Med        ISSN: 0196-8092            Impact factor:   4.025


  6 in total

1.  Label-free discrimination of different stage nasopharyngeal carcinoma tissue based on Raman spectroscopy.

Authors:  Sufang Qiu; Qingting Huang; Lingling Huang; Jinyong Lin; Jun Lu; Duo Lin; Gang Cao; Chao Chen; Jianji Pan; Rong Chen
Journal:  Oncol Lett       Date:  2016-02-17       Impact factor: 2.967

2.  Reflectance confocal microscopy-guided laser ablation of basal cell carcinomas: initial clinical experience.

Authors:  Heidy Sierra; Oriol Yélamos; Miguel Cordova; Chih-Shan Jason Chen; Milind Rajadhyaksha
Journal:  J Biomed Opt       Date:  2017-08       Impact factor: 3.170

Review 3.  Matrix Effectors in the Pathogenesis of Keratinocyte-Derived Carcinomas.

Authors:  Rafaela-Maria Kavasi; Monica Neagu; Carolina Constantin; Adriana Munteanu; Mihaela Surcel; Aristidis Tsatsakis; George N Tzanakakis; Dragana Nikitovic
Journal:  Front Med (Lausanne)       Date:  2022-04-29

4.  Diagnosis accuracy of Raman spectroscopy in colorectal cancer: A PRISMA-compliant systematic review and meta-analysis.

Authors:  Qiang Zheng; Weibiao Kang; Changyu Chen; Xinxin Shi; Yang Yang; Changjun Yu
Journal:  Medicine (Baltimore)       Date:  2019-08       Impact factor: 1.889

5.  Deep learning data augmentation for Raman spectroscopy cancer tissue classification.

Authors:  Man Wu; Shuwen Wang; Shirui Pan; Andrew C Terentis; John Strasswimmer; Xingquan Zhu
Journal:  Sci Rep       Date:  2021-12-13       Impact factor: 4.379

Review 6.  Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue.

Authors:  Jing Zhang; Yimeng Fan; Yanlin Song; Jianguo Xu
Journal:  Medicine (Baltimore)       Date:  2018-08       Impact factor: 1.817

  6 in total

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