Automatic quantification of liver fibrosis: design and validation of a newimage analysis method: comparison with semi-quantitative indexes of fibrosis

Citation
M. Masseroli et al., Automatic quantification of liver fibrosis: design and validation of a newimage analysis method: comparison with semi-quantitative indexes of fibrosis, J HEPATOL, 32(3), 2000, pp. 453-464
Citations number
26
Categorie Soggetti
Gastroenerology and Hepatology","da verificare
Journal title
JOURNAL OF HEPATOLOGY
ISSN journal
01688278 → ACNP
Volume
32
Issue
3
Year of publication
2000
Pages
453 - 464
Database
ISI
SICI code
0168-8278(200003)32:3<453:AQOLFD>2.0.ZU;2-Y
Abstract
Background/Aims: Liver fibrosis is one of the most important and characteri stic histologic alterations in progressive and chronic liver diseases, Thus , in both clinical and experimental practice, it is fundamental to have a r eliable and objective method for its precise quantification. Several semi-q uantitative scoring systems have been described, All are time-consuming and produce partially subjective fibrosis evaluations that are not very precis e, This paper describes the design and validation of an original image anal ysis-based application, FibroQuant, for automatically and rapidly quantifyi ng perisinusoidal, perivenular and portal-periportal and septal fibrosis an d portal-periportal and septal morphology in liver histologic specimens. Methods: The implemented image-processing algorithms automatically segment interstitial fibrosis areas, while extraction of portal-periportal and sept al region is carried out with an automatic algorithm and a simple interacti ve step. For validation, all automatically extracted areas were also manual ly segmented and quantified. Results: Statistical analysis showed significant intra- and interoperator v ariability in manual segmentation of all areas, Automatic quantifications d id not significantly differ from mean manual evaluations of the same areas, Comparison of our image analysis quantifications with staging histologic e valuations of liver fibrosis showed significant correlations (Spearman's, 0 .72<r<0.83; p<0.0001) and that the latter are based more on the distributio n patterns than on the quantity of fibrosis. Conclusions: FibroQuant is a sensitive, precise, objective and reproducible method of fibrosis quantification, which complements semi-quantitative his tologic evaluation systems, This novel tool could be of special value in cl inical trials and for improving the prognosis and follow-up among patients with fibrosis-inducing hepatic diseases.