Abstract
Liver disease has been targeted as the fifth most common cause of death worldwide and tends to steadily rise. In the last three decades, several publications focused on the quantification of liver fibrosis by means of the estimation of the collagen proportional area (CPA) in liver biopsies obtained from digital image analysis (DIA). In this paper, early and recent studies on this topic have been reviewed according to these research aims: the datasets used for the analysis, the employed image processing techniques, the obtained results, and the derived conclusions. The purpose is to identify the major strengths and “gray-areas” in the landscape of this topic.
Highlights
Diagnosis and accurate staging have always been considered essential for the determination of a treatment strategy
During the PRISMA selection method, when the gathered papers were sorted by methodological approach, a corresponding number of groups were formed in the following tables (Tables 2–5) to summarize all results after the end of the discussion
Results from Earlier Works Employing digital image analysis (DIA) and HAI Systems In Jimenez et al [11], the morphometric method indicated that the proportion of fibrosis was significantly higher in biopsies with cirrhosis than in those with steatosis (p < 0.001) or chronic hepatitis (p < 0.001) only
Summary
Diagnosis and accurate staging have always been considered essential for the determination of a treatment strategy. Nearly 35 million people globally have died due to hepatic diseases [1]. During the last few decades, the clinical management of chronic liver disease (CLD) has been increasingly focused on the prevention of the development or progression of fibrosis. Liver fibrosis develops as a result of chronic damage, which eventually leads to cirrhosis, marking the final stage of liver disease. Thick collagen fibers have been targeted as the main source of fibrosis (Figure 1). Stellate hepatocytes are activated and transformed into a myofibroblast-like phenotype forming an extracellular matrix (ECM). The main causes of stimulating these cells include tissue inflammation, cytokine production from injured parenchymal cells, and disruption of the extracellular matrix [2]
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