Poster
Steatosis reduction assessed by MRI-PDFF was consistent with ML evaluation in patients with NASH cirrhosis
AASLD 2022
Study Background
• Liver biopsies evaluated by hepatopathologists are a key method for assessing treatment response in trials of non-alcoholic steatohepatitis (NASH).
– Artificial intelligence has shown promise in supporting liver biopsy assessment.
• Magnetic resonance imaging-proton density fat fraction (MRI-PDFF) is a non-invasive imaging technique that can assess total liver fat content.
• This post hoc analysis aimed to compare steatosis assessment by histologic evaluation (pathologist or PathAI’s machine learning [ML] models) and by MRI-PDFF.
– The analysis used data from a randomized, double-blind, placebo-controlled phase 2 trial investigating once-weekly subcutaneous semaglutide 2.4 mg in patients with NASH and compensated cirrhosis.
– Artificial intelligence has shown promise in supporting liver biopsy assessment.
• Magnetic resonance imaging-proton density fat fraction (MRI-PDFF) is a non-invasive imaging technique that can assess total liver fat content.
• This post hoc analysis aimed to compare steatosis assessment by histologic evaluation (pathologist or PathAI’s machine learning [ML] models) and by MRI-PDFF.
– The analysis used data from a randomized, double-blind, placebo-controlled phase 2 trial investigating once-weekly subcutaneous semaglutide 2.4 mg in patients with NASH and compensated cirrhosis.
Authors
Loomba et al.