Purpose: Noninvasive diagnosis of liver fibrosis is a popular topic in the medical literature. Textural analysis on B-mode ultrasound is viewed as a noninvasive tool for fibrosis staging. A liver tissue model is proposed and used to simulate ultrasound images.
Methods: One hundred and twenty-five patients with chronic hepatitis C were included in this study. Patients were investigated using B-mode ultrasound and liver biopsy (Metavir scoring). A texture analysis tool consisting of 12 algorithms and a logistic regression classifier was implemented and validated. Tissue model parameters were varied and ultrasound images were generated.
Results: Texture analysis can discriminate between stages F0 and F4 using actual patient data (accuracy 69.5%) and synthetic images (accuracy 76.6%). A human expert is less sensitive than texture analysis in discriminating subtle changes in ultrasound images. High fibrosis detection accuracies are correlated with larger differences in portal space density (r (2) = 0.5). Accuracies measured when we varied only the fibrosis stage and kept the rest of the tissue parameters constant showed high detection rates only in a narrow parameter interval.
Conclusion: The texture analysis system shows limited performance in staging fibrosis and it cannot be used for accurate monitoring of fibrosis evolution over time.
Keywords: Fibrosis staging; Noninvasive diagnosis; Texture analysis; Tissue model.