Fibro-C-Index: comprehensive, morphology-based quantification of liver fibrosis using second harmonic generation and two-photon microscopy

• Main Authors: Yu, Hanry (Contributor), So, Peter T. C. (Contributor), Rajapakse, Jagath (Contributor), Chen, Chien Shing (Author), Tang, Hui-Huan (Author), Chang, Shi (Author), Xiao, Guangfa (Author), Raja, Anju Mythreyi (Author), Wei, Chiang Li (Author), Wee, Aileen (Author), Cheng, Chee Leong (Author), Chia, Ser-Mien (Author), Kang, Chiang Huen (Author), Xu, Shuoyu (Author), Tan, Nancy (Author), Tai, Dean C. S. (Author)
• Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
• Format: Article
• Language: English
• Published: Society of Photo-Optical Instrumentation Engineers, 2010-03-16T19:54:26Z.
• Subjects: Article
• Online Access: Get fulltext

 We develop a standardized, fully automated, quantification system for liver fibrosis assessment using second harmonic generation microscopy and a morphology-based quantification algorithm. Liver fibrosis is associated with an abnormal increase in collagen as a result of chronic liver diseases. Histopathological scoring is the most commonly used method for liver fibrosis assessment, where a liver biopsy is stained and scored by experienced pathologists. Due to the intrinsic limited sensitivity and operator-dependent variations, there exist high inter- and intraobserver discrepancies. We validate our quantification system, Fibro-C-Index, with a comprehensive animal study and demonstrate its potential application in clinical diagnosis to reduce inter- and intraobserver discrepancies.