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

Salvatore Petta, Quentin M. Anstee, Kiat-Hon Lim, Chee-Kiat Tan, Pik-Eu Jason Chang, Stephen A. Harrison, Wei-Keat Wan, Aileen Wee, George Boon-Bee Goh, Wei-Qiang Leow, Xiao-Xiao Wang, Feng Liu, Dina Tiniakos, Lai Wei, Kiat-Hon Lim, Qin Wang, Feng Liu, Elisabetta Bugianesi, Dina Tiniakos, Manuel Romero-GomezLai Wei, Jing-Min Zhao, Hui-Ying Rao

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

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 novel 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 < 0.001) (qFibrosis [r = 0.776], qInflammation [r = 0.557], qBallooning [r = 0.533], and qSteatosis [r = 0.802]) and high area under the receiver operating characteristic curve (AUROC) values (qFibrosis [0.870-0.951; 95% confidence interval (CI), 0.787-1.000; P < 0.001], qInflammation [0.820-0.838; 95% CI, 0.726-0.933; P < 0.001 ), qBallooning [0.813-0.844; 95% CI, 0.708-0.957; P < 0.001], and qSteatosis [0.939-0.986; 95% CI, 0.867-1.000; P < 0.001]) and was able to distinguish differing grades/stages of histological disease. Performance of qFIBS was best when assessing degree of steatosis and fibrosis but performed less well when distinguishing severe inflammation and higher ballooning grades. Conclusion: 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
Original languageEnglish
Number of pages34
JournalHEPATOLOGY
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Hepatology

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