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Disease Markers
Volume 25, Issue 6, Pages 303-312

Characterization of Malignant Brain Tumor Using Elastic Light Scattering Spectroscopy

Jianmin Gong,1 Ji Yi,1 Vladimir M. Turzhitsky,1 Kenji Muro,2 and Xu Li1,3

1Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA
2Department of Neurological Surgery, Northwestern University, Chicago, IL 60611, USA
3Department of Electrical Engineering and Computer Science, Evanston, IL 60208, USA

Received 9 February 2009; Accepted 9 February 2009

Copyright © 2008 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We report a pilot study designed to test elastic light-scattering (ELS) spectroscopy for characterizing normal, tumor, and tumor-infiltrated brain tissues. ELS spectra were measured from 393 sites on 36 ex vivo tissue specimen obtained from 29 patients. We employed and compared the performances of three methods of spectral classification for tissue characterization, including spectral slope analysis, principle component analysis (PCA), and artificial neural network (ANN) classification. The ANN classifier yielded the best correlation between spectral pattern and histopathological diagnosis, with a typical sensitivity of 80% and specificity of 93% for differentiating tumor from normal brain tissues. We also demonstrate that all three classification methods discriminate between tumor and normal tissue and have the potential to identify and quantitatively characterize tumor-infiltrated brain tissues.