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Journal of Biomedical Optics • Open Access

Visible and near-infrared spectroscopy for distinguishing malignant tumor tissue from benign tumor and normal breast tissues in vitro
Author(s): Yang Zhang; Yongjun Chen; Yuan Yu; Xingbo Xue; Valery V. Tuchin; Dan Zhu

Paper Abstract

The high incidence and mortality of breast cancer requires an effective, rapid, and cost-effective method for its diagnosis. Here, visible and near-infrared spectroscopy in the wavelength range of 400 to 2200 nm is utilized for distinguishing the malignant tumor tissue from benign tumor and normal breast tissues. Based on the absorption and scattering spectra of fixed samples, three spectral analysis methods are proposed which include an absorption spectral analysis, a scattering spectral analysis, and a combined spectral analysis of the two. By comparison with the histopathological examination, the sensitivity, specificity, and accuracy of the three analysis methods are calculated. The results showed that the combined spectral analysis method can significantly enhance the effectiveness when compared with the sole absorption or scattering spectral analysis method. The sensitivity, specificity, and accuracy of the combined spectral analysis method are 100%, 87.82%, and 87.50% for the benign tumor tissue and 81.82%, 100%, and 87.5% for malignant tumor tissue, respectively. All of the th8ree values are 100% for normal breast tissue. This study demonstrates that the combined spectral analysis method has better potential for in vitro optical diagnosis for breast lesions.

Paper Details

Date Published: 9 July 2013
PDF: 8 pages
J. Biomed. Opt. 18(7) 077003 doi: 10.1117/1.JBO.18.7.077003
Published in: Journal of Biomedical Optics Volume 18, Issue 7
Show Author Affiliations
Yang Zhang, Huazhong Univ. of Science and Technology (China)
Yongjun Chen, Huazhong Univ. of Science and Technology (China)
Yuan Yu, Huazhong Univ. of Science and Technology (China)
Xingbo Xue, Huazhong Univ. of Science and Technology (China)
Valery V. Tuchin, N.G. Chernyshevsky Saratov State Univ. (Russian Federation)
Dan Zhu, Huazhong Univ. of Science and Technology (China)


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