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- Title
Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma.
- Authors
Marta Larraona-Puy; Adrian Ghita; Alina Zoladek; William Perkins; Sandeep Varma; Iain H. Leach; Alexey A. Koloydenko; Hywel Williams; Ioan Notingher
- Abstract
We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90±9sensitivity and 85±9specificity in a 70 to 30 split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a âgeneralizationâ of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.
- Subjects
RAMAN spectroscopy; MEDICAL imaging systems; BASAL cell carcinoma; MOHS surgery; CANCER radiotherapy; HISTOPATHOLOGY; FEASIBILITY studies
- Publication
Journal of Biomedical Optics, 2009, Vol 14, Issue 5, p054031
- ISSN
1083-3668
- Publication type
Article
- DOI
10.1117/1.3251053