Non-invasive tests of fibrosis in the management of MASLD: revolutionising diagnosis, progression and regression monitoring

纤维化 医学 肝纤维化 临床实习 疾病 危险分层 重症监护医学 病理 内科学 物理疗法
作者
Gong Feng,Vincent Wai‐Sun Wong,Giovanni Targher,Christopher D. Byrne,Ming‐Hua Zheng
出处
期刊:Gut [BMJ]
卷期号:74 (10): 1741-1750 被引量:3
标识
DOI:10.1136/gutjnl-2025-335542
摘要

With the recent conditional approval of resmetirom by the US Food and Drug Administration, the treatment of metabolic dysfunction-associated steatotic liver disease (MASLD) has potentially entered a new era, requiring a comprehensive understanding of the strengths and weaknesses of non-invasive tests (NITs) for diagnosing and monitoring MASLD-related fibrosis. This article focuses on F2/F3 liver fibrosis and summarises the current application status of NITs, including serum biomarkers, imaging methods and their combined use in the management of MASLD. The article highlights the application of NITs in several areas, including diagnosis and baseline stratification, monitoring progression of fibrosis, prediction of liver-related clinical events, as well as assessment of disease regression, remission and long-term liver-related outcomes. Furthermore, we compare the advantages and limitations of NITs and propose practical strategies for integrating them into clinical practice. Additionally, we highlight the main challenges currently faced in the application of these NITs and potential future research avenues. We suggest that future studies prioritise the validation of NITs across diverse ethnic populations. We believe it essential to explore the role of NITs in dynamic monitoring and integration of multiomics technologies, artificial intelligence and personalised risk models to improve diagnostic accuracy and treatment planning.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
田様应助一二采纳,获得10
2秒前
Yiy完成签到 ,获得积分0
2秒前
3秒前
3秒前
BowieHuang发布了新的文献求助10000
4秒前
6秒前
chy完成签到,获得积分10
7秒前
7秒前
量子星尘发布了新的文献求助10
7秒前
在水一方应助乌鸦坐飞机采纳,获得10
7秒前
7秒前
JamesPei应助复杂黑夜采纳,获得10
8秒前
9秒前
燕烟完成签到,获得积分10
9秒前
9秒前
万安安完成签到,获得积分10
10秒前
10秒前
10秒前
xxxx完成签到 ,获得积分10
11秒前
11秒前
11秒前
杨小琪发布了新的文献求助10
11秒前
luobeimin发布了新的文献求助10
11秒前
11秒前
任娜完成签到,获得积分10
12秒前
FashionBoy应助风果然是风采纳,获得10
12秒前
12秒前
追寻归尘发布了新的文献求助10
13秒前
13秒前
14秒前
莫羽倾尘发布了新的文献求助10
15秒前
彭于晏应助参与者采纳,获得10
15秒前
15秒前
15秒前
超帅冥茗完成签到,获得积分10
16秒前
山药汤完成签到,获得积分10
17秒前
17秒前
99完成签到,获得积分10
18秒前
wushangyu发布了新的文献求助10
18秒前
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Basic And Clinical Science Course 2025-2026 3000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
人脑智能与人工智能 1000
花の香りの秘密―遺伝子情報から機能性まで 800
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5610075
求助须知:如何正确求助?哪些是违规求助? 4694567
关于积分的说明 14883242
捐赠科研通 4721068
什么是DOI,文献DOI怎么找? 2544999
邀请新用户注册赠送积分活动 1509890
关于科研通互助平台的介绍 1473023