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AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: an exploratory study

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: an exploratory study
AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: an exploratory study
Background and aims: lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses can provide an automated quantitative assessment of fibrosis features on a continuous scale called qFibrosis. In this exploratory study, we used this approach to gain insight into the effect of lifestyle intervention-induced fibrosis changes in MASH.

Methods: we examined unstained sections from paired liver biopsies (baseline and end-of-intervention) from MASH individuals who had received either routine lifestyle intervention (RLI) (n = 35) or strengthened lifestyle intervention (SLI) (n = 17). We quantified liver fibrosis with qFibrosis in the portal tract, periportal, transitional, pericentral, and central vein regions.

Results: about 20% (7/35) and 65% (11/17) of patients had fibrosis regression in the RLI and SLI groups, respectively. Liver fibrosis tended towards no change or regression after each lifestyle intervention, and this phenomenon was more prominent in the SLI group. SLI-induced liver fibrosis regression was concentrated in the periportal region.

Conclusion: using digital pathology, we could detect a more pronounced fibrosis regression with SLI, mainly in the periportal region. With changes in fibrosis area in the periportal region, we could differentiate RLI and SLI patients in the placebo group in the MASH clinical trial. Digital pathology provides new insight into lifestyle-induced fibrosis regression and placebo responses, which is not captured by conventional histological staging.

1478-3223
Yuan, Hai-Yang
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Tong, Xiao-Fei
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Ren, Ya-Yun
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Li, Yang-Yang
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Wang, Xin-Lei
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Chen, Li-Li
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Chen, Sui-Dan
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Jin, Xiao-Zhi
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Wang, Xiao-Dong
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Targher, Giovanni
8a57cd78-c539-4b77-9ba8-1d7fff1c957f
Byrne, Christopher D.
1370b997-cead-4229-83a7-53301ed2a43c
Wei, Lai
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Wong, Vincent Wai-Sun
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Tai, Dean
4a85af4a-829f-4329-b499-a8a39b900fc3
Sanyal, Arun J.
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You, Hong
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Zheng, Ming-Hua
e4e24459-832c-465c-8f29-d1fbabb2dc3c
Yuan, Hai-Yang
88c640c0-0279-4102-89de-14b99aaaeeba
Tong, Xiao-Fei
fc440372-1dc3-453f-b858-35f73db4efa2
Ren, Ya-Yun
86de4046-9cb1-4d21-9d99-5460216e1708
Li, Yang-Yang
afd37561-0c99-4cc9-b29c-50825c6ea841
Wang, Xin-Lei
fe6b98d5-9f60-450c-af5d-823d43ec9bf6
Chen, Li-Li
6113f6ca-94c6-4d3d-b849-19e093f2dbca
Chen, Sui-Dan
3bc79c7a-9d51-4aac-97fe-8e0829a59353
Jin, Xiao-Zhi
0eb2d537-7143-4036-85ce-de8eb444985b
Wang, Xiao-Dong
7be2b34b-1c57-4c89-b660-778b4ed88858
Targher, Giovanni
8a57cd78-c539-4b77-9ba8-1d7fff1c957f
Byrne, Christopher D.
1370b997-cead-4229-83a7-53301ed2a43c
Wei, Lai
9d5eeba6-fbf0-4292-a0cd-1dda04618ce7
Wong, Vincent Wai-Sun
7cddf4bb-4720-45f1-a052-7b87fb64c6d6
Tai, Dean
4a85af4a-829f-4329-b499-a8a39b900fc3
Sanyal, Arun J.
f961c7d5-5194-41e6-9b51-1ca705840443
You, Hong
09754004-cf42-43eb-9df4-ca9394be3922
Zheng, Ming-Hua
e4e24459-832c-465c-8f29-d1fbabb2dc3c

Yuan, Hai-Yang, Tong, Xiao-Fei, Ren, Ya-Yun, Li, Yang-Yang, Wang, Xin-Lei, Chen, Li-Li, Chen, Sui-Dan, Jin, Xiao-Zhi, Wang, Xiao-Dong, Targher, Giovanni, Byrne, Christopher D., Wei, Lai, Wong, Vincent Wai-Sun, Tai, Dean, Sanyal, Arun J., You, Hong and Zheng, Ming-Hua (2024) AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: an exploratory study. Liver International. (doi:10.1111/liv.16025).

Record type: Article

Abstract

Background and aims: lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses can provide an automated quantitative assessment of fibrosis features on a continuous scale called qFibrosis. In this exploratory study, we used this approach to gain insight into the effect of lifestyle intervention-induced fibrosis changes in MASH.

Methods: we examined unstained sections from paired liver biopsies (baseline and end-of-intervention) from MASH individuals who had received either routine lifestyle intervention (RLI) (n = 35) or strengthened lifestyle intervention (SLI) (n = 17). We quantified liver fibrosis with qFibrosis in the portal tract, periportal, transitional, pericentral, and central vein regions.

Results: about 20% (7/35) and 65% (11/17) of patients had fibrosis regression in the RLI and SLI groups, respectively. Liver fibrosis tended towards no change or regression after each lifestyle intervention, and this phenomenon was more prominent in the SLI group. SLI-induced liver fibrosis regression was concentrated in the periportal region.

Conclusion: using digital pathology, we could detect a more pronounced fibrosis regression with SLI, mainly in the periportal region. With changes in fibrosis area in the periportal region, we could differentiate RLI and SLI patients in the placebo group in the MASH clinical trial. Digital pathology provides new insight into lifestyle-induced fibrosis regression and placebo responses, which is not captured by conventional histological staging.

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Accepted/In Press date: 23 June 2024
e-pub ahead of print date: 4 July 2024

Identifiers

Local EPrints ID: 491664
URI: http://eprints.soton.ac.uk/id/eprint/491664
ISSN: 1478-3223
PURE UUID: e604b48e-195a-47a9-8761-5173dd0b05d6
ORCID for Christopher D. Byrne: ORCID iD orcid.org/0000-0001-6322-7753

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Date deposited: 03 Jul 2024 09:49
Last modified: 12 Jul 2024 01:38

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Contributors

Author: Hai-Yang Yuan
Author: Xiao-Fei Tong
Author: Ya-Yun Ren
Author: Yang-Yang Li
Author: Xin-Lei Wang
Author: Li-Li Chen
Author: Sui-Dan Chen
Author: Xiao-Zhi Jin
Author: Xiao-Dong Wang
Author: Giovanni Targher
Author: Lai Wei
Author: Vincent Wai-Sun Wong
Author: Dean Tai
Author: Arun J. Sanyal
Author: Hong You
Author: Ming-Hua Zheng

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