New technologies for Secondary Ion Mass Spectrometry (SIMS) produce three-dimensional hyperspectral chemical
images with high spatial resolution and fine mass-spectral precision. SIMS imaging of biological tissues and
cells promises to provide an informational basis for important advances in a wide variety of applications, including
cancer treatments. However, the volume and complexity of data pose significant challenges for interactive visualization
and analysis. This paper describes new methods and tools for computer-based visualization and analysis
of SIMS data, including a coding scheme for efficient storage and fast access, interactive interfaces for visualizing
and operating on three-dimensional hyperspectral images, and spatio-spectral clustering and classification.
An investigation into the use of Raman optical tweezers to study urological cell lines is reported, with the ultimate aim of determining the presence of malignant CaP cells in urine and peripheral fluids. To this end, we trapped and analyzed live CaP cells (PC-3) and bladder cells (MGH-U1), because both prostate and bladder cells are likely to be present in urine. The laser excitation wavelength of 514.5 nm was used, with Raman light collected both in back- and forward-scattering geometric configurations. For the backscattering configuration the same laser was used for trapping and excitation, while for forward scattering a 1064 nm laser provided the trapping beam. Analysis of cell-diameter distributions for cells analyzed suggested normal distribution of cell sizes, indicating an unbiased cell-selection criterion. Principal components analysis afforded discrimination of MGH-U1 and PC-3 spectra collected in either configuration, demonstrating that it is possible to trap, analyze, and differentiate PC-3 from MGH-U1 cells using a 514.5 nm laser. By loading plot analysis, possible biomolecules responsible for discrimination in both configurations were determined. Finally, the effect of cell size on discrimination was investigated, with results indicating that separation is based predominantly on cell type rather than cell size.