Label-Free Diagnosis of Human Hepatocellular Carcinoma by Multiphoton Autofluorescence Microscopy

Conventional diagnosis for hepatocellular carcinoma (HCC) is time consuming in sample preparation and deficient in quantitative examination. In this work, we developed multiphoton autofluorescence (MAF) microscopy as an effective and efficient tool in HCC diagnosis with qualitative imaging, and quantitative measurement. We found that MAF imaging effectively identifies cellular architecture in the liver specimens. Our results also demonstrate the capability of using tissue quantitative parameters of multiphoton autofluorescence intensity ratio, the nuclear number density, and nuclear-cytoplasmic ratio for tumor discrimination. This approach has the potential in clinical diagnosis of HCC and the in vivo investigation of liver tumor development in animal models