A Raman Spectrometer for in vivo Real-Time Detection of Cancer

City of Hope
2016–17

Raman spectroscopy can discriminate between healthy and cancerous breast tissue. This report examines the potential to implement an inexpensive commercial Raman system and hand held probe for the in vivo, real-time detection of cancer in surgical margins. First, 785 nm and 1064 nm systems are compared, and the 785 nm system is identified as preferable because of its greater resolution, superior signal-to-noise ratio, and extended spectral range. A method to eliminate the greater fluorescent contribution resulting from excitation with 785 nm is described. In a second experiment, Raman spectra are collected along lines that transect cancer margins of two patients following lumpectomy. Spectra are classified as either healthy or cancerous according to histological assessment of collection location, and 15 spectral bands are identified as the most descriptive of spectral variation. Discriminant analysis performed on the two primary principal components of the bands is shown to classify tissue as healthy or cancerous with 100% accuracy. A third experiment expands the classification to naive spectra obtained from tissue samples of additional patients to assess cross-patient classification. Finally, a fourth experiment achieves 100% classification using substantially reduced spectral bins, demonstrating the potential for real-time in-vivo cancer detection.

Advisor(s): Michael C. Storrie-Lombardi.

Team: Sarah Marie Anderson ’17, Alexander Felipe Echevarria ’17, Nathaniel Loren Miller ’17, Connor Emerson Stashko ’17, and Willie Correa Zuniga ’17.