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qFibrosis:一种结合组织学特征的全定量创新方法,用于促进动物模型和慢性乙型肝炎患者的准确纤维化评分。

qFibrosis: a fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients.

作者信息

Xu Shuoyu, Wang Yan, Tai Dean C S, Wang Shi, Cheng Chee Leong, Peng Qiwen, Yan Jie, Chen Yongpeng, Sun Jian, Liang Xieer, Zhu Youfu, Rajapakse Jagath C, Welsch Roy E, So Peter T C, Wee Aileen, Hou Jinlin, Yu Hanry

机构信息

Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, #04-01, Singapore 138669, Singapore.

Computation and System Biology Program, Singapore-MIT Alliance, 4 Engineering Drive 3, E4-04-10, Singapore 117576, Singapore.

出版信息

J Hepatol. 2014 Aug;61(2):260-269. doi: 10.1016/j.jhep.2014.02.015. Epub 2014 Feb 26.

DOI:10.1016/j.jhep.2014.02.015
PMID:24583249
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4278959/
Abstract

BACKGROUND & AIMS: There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.

METHODS

qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.

RESULTS

qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93-0.99 for animal samples: 1-16 mm(2); AUC: 0.84-0.97 for biopsies: 10-44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.

CONCLUSIONS

qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice.

摘要

背景与目的

对肝纤维化/肝硬化进行准确评估的需求日益增加。我们旨在开发一种名为qFibrosis的全自动评估方法,该方法结合了组织病理学结构特征的量化,以满足慢性乙型肝炎(CHB)患者肝活检纤维化评估中尚未满足的需求。

方法

qFibrosis被确立为基于87个结构特征参数的综合指数。从25个硫代乙酰胺处理的大鼠样本和162个CHB肝活检样本中获取的图像用于训练和测试qFibrosis,并证明其可重复性。采用Metavir和Ishak纤维化分期作为标准参考对qFibrosis评分进行分析,并与胶原比例面积(CPA)测量结果进行比较。

结果

qFibrosis能够准确且可靠地重现Metavir纤维化评分,因为它能够识别动物样本(p<0.001)和人类活检样本(p<0.05)中所有阶段之间的差异。它对样本大小具有鲁棒性,能够区分不同大小样本中的不同阶段(曲线下面积(AUC):动物样本(面积为1 - 16 mm²)为0.93 - 0.99;活检样本(长度为10 - 44 mm)为0.84 - 0.97)。qFibrosis能够显著预测次优活检样本(<15 mm)中分期的低估情况以及不同病理学家评分的过低和过高情况(p<0.001)。qFibrosis还能够区分Ishak分期的5期和6期(AUC:0.73,p = 0.008),这表明监测期内肝硬化变化的可能性。最棒的是,qFibrosis在所有方面都表现出优于CPA的性能。

结论

qFibrosis可以提高纤维化评分的准确性和通量,从而在临床研究和实践中实现对抗纤维化治疗效果的可重复且可靠的分析。

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