| Abstract: | BACKGROUND AND AIMS: Liver fibrosis is a key prognostic determinant for clinical outcomes in non-alcoholic steatohepatitis (NASH). Current scoring systems have limitations, especially in assessing fibrosis regression. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence (AI) analyses provides standardized evaluation of NASH features, especially liver fibrosis and collagen fiber quantitation on a continuous scale. This approach was applied to gain in-depth understanding of fibrosis dynamics after treatment with tropifexor (TXR), a non-bile acid farnesoid X receptor (FXR) agonist in patients participating in FLIGHT-FXR study (NCT02855164). METHOD: Unstained sections from 198 liver biopsies (paired: baseline and end-of-treatment) from 99 patients with NASH (fibrosis stage F2 or F3) who received placebo (n=34), TXR 140 μg (n=37), or TXR 200 μg (n=28) for 48 weeks were examined. Liver fibrosis (qFibrosis ®), hepatic fat (qSteatosis®), and ballooned hepatocytes (qBallooning®) were quantitated using SHG/TPEF microscopy. Changes in septa morphology, collagen fiber parameters, and zonal distribution within liver lobules were also quantitatively assessed. RESULTS: Digital analyses revealed treatment-associated reduction of overall liver fibrosis (qFibrosis®), unlike conventional microscopy, as well as marked regression in perisinusoidal fibrosis in patients who had either F2 or F3 fibrosis at baseline. Concomitant zonal quantitation of fibrosis and steatosis revealed that patients with greater qSteatosis reduction also have greatest reduction in perisinusoidal fibrosis. Regressive changes in septa morphology and reduction in septa parameters were observed almost exclusively in F3 patients, who were adjudged as 'unchanged' with conventional scoring. CONCLUSION: Fibrosis regression following hepatic fat reduction occurs initially in the perisinusoidal regions, around areas of steatosis reduction. Digital pathology provides new insights in treatment-induced fibrosis regression in NASH, which are not captured by current staging systems. LAY SUMMARY: The degree of liver fibrosis in non-alcoholic steatohepatitis (NASH) is the principal feature that predicts clinical outcomes. Accurate assessment of liver fibrosis amount and architecture is fundamental for patients' enrolment in NASH clinical trials and determining treatment efficacy. Using digital microscopy with artificial intelligence analyses, the present study demonstrates that this novel approach has greater sensitivity and granularity in demonstrating treatment-induced reversal of fibrotic changes in the liver than current systems which use ordinal assessment of liver fibrosis in patients with NASH. Furthermore, additional details are obtained regarding the pathobiology of NASH disease and effects of therapy. |
