Paper
4 March 2014 High-speed stimulated Raman spectral imaging for digital staining of mouse cancer tissues
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Abstract
We previously reported the combination of the high-speed stimulated Raman scattering (SRS) microscope and the multivariate analysis (principal component analysis and independent component analysis) for the tissue imaging. The results indicated the visualization of tissue components without chemical staining. Here, we report the multi-area observation of the tumor-grafted mouse tissue based on the same approach. The tumor-grafted mouse (balb/cAcJ nu/nu) was prepared by injection of human pancreatic carcinoma cell line (SUIT-2) into the tail of pancreas. Both of the pancreas cancer and the liver metastasis were harvested and fixed in formalin. Tissues were cryo-sectioned with a thickness of 100 μm and observed. The multispectral images (130 μm square, 500 x 500 pixels) of C-H vibration range from 2800 to 3100cm-1 (91 different Raman shift images) were obtained at a frame rate of 30 frames/sec. The data acquisition both of pancreas and liver were continued for the 48 adjacent areas for the observation both of cancerous and non-cancerous region, respectively. All the datasets were combined to analyze for multivariate analysis. We propose a protocol for drastic data reduction, which we found to give reproducible results and allows fast calculation of ICA. The independent component images indicated the different shapes and compositions between the cancerous region and the non-cancerous region.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yoichi Otsuka, Shuya Satoh, Masafumi Kyogaku, Hiroyuki Hashimoto, Kazuyoshi Itoh, and Yasuyuki Ozeki "High-speed stimulated Raman spectral imaging for digital staining of mouse cancer tissues", Proc. SPIE 8947, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XII, 89470C (4 March 2014); https://doi.org/10.1117/12.2037494
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KEYWORDS
Tissues

Independent component analysis

Raman spectroscopy

Pancreas

Cancer

Principal component analysis

Data acquisition

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