Naoumov, NV;
Kleiner, DE;
Chng, E;
Brees, D;
Saravanan, C;
Ren, Y;
Tai, D;
(2024)
Digital quantitation of bridging fibrosis and septa reveals changes in natural history and treatment not seen with conventional histology.
Liver International
, 44
(12)
pp. 3214-3228.
10.1111/liv.16092.
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Liver International - 2024 - Naoumov - Digital quantitation of bridging fibrosis and septa reveals changes in natural (4).pdf - Published Version Download (6MB) | Preview |
Abstract
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatohepatitis (MASH) with bridging fibrosis is a critical stage in the evolution of fatty liver disease. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence (AI) provides sensitive and reproducible quantitation of liver fibrosis. This methodology was applied to gain an in-depth understanding of intra-stage fibrosis changes and septa analyses in a homogenous, well-characterised group with MASH F3 fibrosis. METHODS: Paired liver biopsies (baseline [BL] and end of treatment [EOT]) of 57 patients (placebo, n = 17 and tropifexor n = 40), with F3 fibrosis stage at BL according to the clinical research network (CRN) scoring, were included. Unstained sections were examined using SHG/TPEF microscopy with AI. Changes in liver fibrosis overall and in five areas of liver lobules were quantitatively assessed by qFibrosis. Progressive, regressive septa, and 12 septa parameters were quantitatively analysed. RESULTS: qFibrosis demonstrated fibrosis progression or regression in 14/17 (82%) patients receiving placebo, while the CRN scoring categorised 11/17 (65%) as ‘no change’. Radar maps with qFibrosis readouts visualised quantitative fibrosis dynamics in different areas of liver lobules even in cases categorised as ‘No Change’. Measurement of septa parameters objectively differentiated regressive and progressive septa (p < .001). Quantitative changes in individual septa parameters (BL to EOT) were observed both in the ‘no change’ and the ‘regression’ subgroups, as defined by the CRN scoring. CONCLUSION: SHG/TPEF microscopy with AI provides greater granularity and precision in assessing fibrosis dynamics in patients with bridging fibrosis, thus advancing knowledge development of fibrosis evolution in natural history and in clinical trials.
| Type: | Article |
|---|---|
| Title: | Digital quantitation of bridging fibrosis and septa reveals changes in natural history and treatment not seen with conventional histology |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/liv.16092 |
| Publisher version: | https://doi.org/10.1111/liv.16092 |
| Language: | English |
| Additional information: | © 2024 The Author(s). Liver International published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | digital pathology with artificial intelligence, liver fibrosis, metabolic dysfunction-associated steatohepatitis, quantitative assessment fibrosis regression, second harmonic generation microscopy |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10202906 |
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