Human hepatocellular carcinoma diagnosis by multiphoton autofluorescence microscopy
Name
Sun-2010-Human hepatocellular carcinoma.pdf
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Author(s)
So, Peter T. C.
Kim, Ki Hean
Sun, Tzu-Lin
Liu, Yuan
Sung, Ming-Chin
Chen, Hsiao-Ching
Yang, Chuen-Huei
Huang, Guan-Tarn
Lin, Wei-Chou
Chiou, Ling-Ling
Date Issued
February 2010
Journal
Proceedings of SPIE--the International Society for Optical Engineering; v.7555
Publisher
SPIE
Citation
Sun, Tzu-Lin et al. “Human hepatocellular carcinoma diagnosis by multiphoton autofluorescence microscopy.” Advanced Biomedical and Clinical Diagnostic Systems VIII. Ed. Tuan Vo-Dinh, Warren S. Grundfest, & Anita Mahadevan-Jansen. San Francisco, California, USA: SPIE, 2010. 75551L-9. ©2010 SPIE.
Version
Final published version
Abstract
Conventionally, the diagnosis of hepatocellular carcinoma (HCC) is performed by qualitative examination of histopathological specimens, which takes times for sample preparation in fixation, section and stain. Our objective is to demonstrate an effective and efficient approach to apply multiphoton microscopy imaging the HCC specimens, with the advantages of being optical section, label-free, subcellular resolution, minimal invasiveness, and the acquisition of quantitative information at the same time. The imaging modality of multiphoton autofluorescence (MAF) was used for the qualitative imaging and quantitative analysis of HCC of different grades under ex-vivo, label-free conditions. We found that while MAF is effective in identifying cellular architecture in the liver specimens, and obtained quantitative parameters in characterizing the disease. Our results demonstrates the capability of using tissue quantitative parameters of multiphoton autofluorescence (MAF), the nuclear number density (NND), and nuclear-cytoplasmic ratio (NCR) for tumor discrimination and that this technology has the potential in clinical diagnosis of HCC and the in-vivo investigation of liver tumor development in animal models.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
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DOI of Published Version
https://doi.org/10.1117/12.843157
