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qFIBS: An Automated Technique for Quantitative Evaluation of Fibrosis, Inflammation, Ballooning, and Steatosis in Patients With Nonalcoholic Steatohepatitis.

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2020-05-07

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Liu, Feng
Goh, George Boon-Bee
Tiniakos, Dina
Wee, Aileen
Leow, Wei-Qiang
Zhao, Jing-Min
Rao, Hui-Ying
Wang, Xiao-Xiao
Wang, Qin
Wan, Wei-Keat

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Abstract

Nonalcoholic steatohepatitis (NASH) is a common cause of chronic liver disease. Clinical trials use the NASH Clinical Research Network (CRN) system for semiquantitative histological assessment of disease severity. Interobserver variability may hamper histological assessment, and diagnostic consensus is not always achieved. We evaluate a second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) imaging-based tool to provide an automated quantitative assessment of histological features pertinent to NASH. Images were acquired by SHG/TPEF from 219 nonalcoholic fatty liver disease (NAFLD)/NASH liver biopsy samples from seven centers in Asia and Europe. These were used to develop and validate qFIBS, a computational algorithm that quantifies key histological features of NASH. qFIBS was developed based on in silico analysis of selected signature parameters for four cardinal histopathological features, that is, fibrosis (qFibrosis), inflammation (qInflammation), hepatocyte ballooning (qBallooning), and steatosis (qSteatosis), treating each as a continuous rather than categorical variable. Automated qFIBS analysis outputs showed strong correlation with each respective component of the NASH CRN scoring (P  qFIBS is an automated tool that accurately quantifies the critical components of NASH histological assessment. It offers a tool that could potentially aid reproducibility and standardization of liver biopsy assessments required for NASH therapeutic clinical trials.

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Algorithms
Asian People
Biopsy
Dimensional Measurement Accuracy
Fatty Liver
Female
Hepatitis
Humans
Image Interpretation, Computer-Assisted
Liver
Liver Cirrhosis
Male
Middle Aged
Non-alcoholic Fatty Liver Disease
Reference Standards
Reproducibility of Results
Severity of Illness Index
White People

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