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Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation

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Abstract

In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834–0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870–0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846–0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.

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References

  1. MacKenzie-Wood AR, Milton GW, Launey JW (1998) Melanoma: accuracy of clinical diagnosis. Australas J Dermatol 39:31–33

    Article  CAS  Google Scholar 

  2. Miller M, Ackerman AB (1992) How accurate are dermatologists in the diagnosis of melanoma? Degree of accuracy and implications. Arch Dermatol 128:559–560

    Article  CAS  Google Scholar 

  3. Morton C, Mackie R (1998) Clinical accuracy of the diagnosis of cutaneous malignant melanoma. Br J Dermatol 138:283–287

    Article  CAS  Google Scholar 

  4. Lui H, Zhao J, McLean D, Zeng H (2012) Real-time Raman spectroscopy for in vivo skin cancer diagnosis. Cancer Res 72:2491–500

    Article  CAS  Google Scholar 

  5. Huang Z, Zeng H, Hamzavi I, McLean DI, Lui H (2001) Rapid near-infrared Raman spectroscopy system for real-time in vivo skin measurements. Opt Lett 26:1782–4

    Article  CAS  Google Scholar 

  6. Zhao J, Lui H, McLean DI, Zeng H (2008) Integrated real-time Raman system for clinical in vivo skin analysis. Skin Res Technol 14:484–92

    Article  Google Scholar 

  7. Gniadecka M, Philipsen PA, Sigurdsson S, Wessel S, Nielsen OF, Christensen DH, Hercogova J, Rossen K, Thomsen HK, Gniadecki R, Hansen LK, Wulf HC (2004) Melanoma diagnosis by Raman spectroscopy and neural networks: structure alterations in proteins and lipids in intact cancer tissue. J Invest Dermatol 122:443–449

    Article  CAS  Google Scholar 

  8. Lieber CA, Majumder SK, Ellis DL, Billheimer D, Mahadevan-Jansen A (2008) In vivo nonmelanoma skin cancer diagnosis using Raman microspectroscopy. Lasers Surg Med 40:461–467

    Article  Google Scholar 

  9. Nijssen A, Maquelin K, Santos LF, Caspers PJ, Bakker Schut TC, den Hollander JC, Neumann MHA, Puppels GJ (2007) Discriminating basal cell carcinoma from perilesional skin using high wave-number Raman spectroscopy. J Biomed Opt 12:034004

    Article  Google Scholar 

  10. Wang S, Zhao J, Lui H, He Q, Bai J, Zeng H (2014) Monte Carlo simulation of in vivo Raman spectral measurements of human skin with a multi-layered tissue optical model. J Biophotonics 7:703–712

    Article  CAS  Google Scholar 

  11. Zhao J, Lui H, McLean DI, Zeng H (2007) Automated autofluorescence background subtraction algorithm for biomedical Raman spectroscopy. Appl Spectrosc 61:1225–32

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The project was supported in part by the Canadian Cancer Society, the Proof of Principle II grant co-funded by the Canadian Institutes of Health Research and Verisante Technology Inc., the Canadian Dermatology Foundation, the VGH & UBC Hospital Foundation, and the BC Hydro Employees Community Service Fund. Dr. David McLean, Wei Zhang, Mohammed AlJasser, and Soodabeh Zandi were acknowledged for consultation, recruiting patient, and clinical measurement.

Conflict of interest

J. Zhao, H. Lui, H. Zeng, and the British Columbia Cancer Agency hold Raman spectroscopy patents that are licensed to Verisante Technology Inc.

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Authors and Affiliations

  1. Photomedicine Institute, Department of Dermatology and Skin Science, University of British Columbia and Vancouver Coastal Health Research Institute, 835 West 10th Ave, Vancouver, BC, V5Z 4E8, Canada

    Jianhua Zhao, Harvey Lui, Sunil Kalia & Haishan Zeng

  2. Imaging Unit - Integrative Oncology Department, British Columbia Cancer Agency Research Center, 675 West 10th Ave, Vancouver, BC, V5Z 1L3, Canada

    Jianhua Zhao, Harvey Lui & Haishan Zeng

Authors
  1. Jianhua Zhao
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  2. Harvey Lui
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  3. Sunil Kalia
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  4. Haishan Zeng
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Corresponding author

Correspondence to Haishan Zeng.

Additional information

Published in the topical collection Raman4Clinics with guest editors Jürgen Popp and Christoph Krafft.

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Zhao, J., Lui, H., Kalia, S. et al. Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation. Anal Bioanal Chem 407, 8373–8379 (2015). https://doi.org/10.1007/s00216-015-8914-9

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  • DOI: https://doi.org/10.1007/s00216-015-8914-9

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