Authors:
Iyer JS, Juyal D, Le Q, Shanis Z, Pokkalla H, Pouryahya M, Pedawi A, Stanford-Moore SA, Biddle-Snead C, Carrasco-Zevallos O, Lin M, Egger R, Hoffman S, Elliott H, Leidal K, Myers RP, Chung C, Billin AN, Watkins TR, Patterson SD, Resnick M, Wack K, Glickman J, Burt AD, Loomba R, Sanyal AJ, Glass B, Montalto MC, Taylor-Weiner A, Wapinski I, Beck AH. 

Abstract:
Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalcoholic steatohepatitis) require histologic scoring for assessment of inclusion criteria and endpoints. However, variability in interpretation has impacted clinical trial outcomes. We developed an artificial intelligence-based measurement (AIM) tool for scoring MASH histology (AIM-MASH). AIM-MASH predictions for MASH Clinical Research Network necroinflammation grades and fibrosis stages were reproducible (κ = 1) and aligned with expert pathologist consensus scores (κ = 0.62–0.74). The AIM-MASH versus consensus agreements were comparable to average pathologists for MASH Clinical Research Network scores (82% versus 81%) and fibrosis (97% versus 96%). Continuous scores produced by AIM-MASH for key histological features of MASH correlated with mean pathologist scores and noninvasive biomarkers and strongly predicted progression-free survival in patients with stage 3 (P < 0.0001) and stage 4 (P = 0.03) fibrosis. In a retrospective analysis of the ATLAS trial (NCT03449446), responders receiving study treatment showed a greater continuous change in fibrosis compared with placebo (P = 0.02). Overall, these results suggest that AIM-MASH may assist pathologists in histologic review of MASH clinical trials, reducing inter-rater variability on trial outcomes and offering a more sensitive and reproducible measure of patient responses.

Nat Med 2024 Oct;30(10):2914-2923

doi: 10.1038/s41591-024-03172-7

Epub 2024 Aug 7

PMID: 39112795

PMCID: PMC11485234

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