This research project has been co-financed by the European Union (European Regional Development Fund- ERDF) and Greek national funds through the Operational Program “THESSALY- MAINLAND GREECE AND EPIRUS ” of the National Strategic Reference Framework (NSRF ) A novel computer-assisted system for the management and analysis of liver biopsies Nikolaos Giannakeas 1, Zoi Tsianou 1, Alexandros T. Tzallas 2, Markos G. Tsipouras 1, Pinelopi Manousou 3 & Epameinondas V. Tsianos st Division of Internal Medicine And Division of Gastroenterology, Faculty of Medicine School of Health Sciences, University of Ioannina, P.O. Box 1186, Ioannina, Greece 2 School of Applied Technology, Department of Computer Engineering, Technological Educational Institute of Epirus, Kostakioi, Gr 47100, Arta, Greece 3 The Royal Free Sheila Sherlock Liver Unit, Royal Free Hospital & UCL Institute for Liver & Digestive Health, London, UK

This research project has been co-financed by the European Union (European Regional Development Fund- ERDF) and Greek national funds through the Operational Program “THESSALY- MAINLAND GREECE AND EPIRUS ” of the National Strategic Reference Framework (NSRF ) Background  Collagen proportional area (CPA) assessment through digital image analysis (DIA) has been presented in the literature since early 90`s and has proven to be more accurate compared to semiquantitative scores.  However, it is not widely used in clinical practice, due to the lack of specialized computer-assisted tools for image analysis. Aim  The aim of this study is the development of a computer-assisted user friendly and easy to install system for management of digital images of liver tissue, and the design, implementation and validation of a novel and robust methodology for image analysis.  The system is able to manage patients’ data and microscopy images, and perform DIA for CPA assessment. A B A. Αctivity Diagram & B. Sequence Diagram AB

This research project has been co-financed by the European Union (European Regional Development Fund- ERDF) and Greek national funds through the Operational Program “THESSALY- MAINLAND GREECE AND EPIRUS ” of the National Strategic Reference Framework (NSRF ) Web-service tools & open-source information technologies Structural Collagen Methods  The system was designed and developed as a web -service tool, thus being accessible through any web browser.  Open-source information technologies were employed in all stages of the development. Results  Currently, the system includes three major datasets from three medical centers, with a total of 197 liver biopsy images, from different patients.  The DIA techniques include image segmentation and region detection and classification (liver tissue/no-tissue) techniques. Royal Free Hospital Dataset Image Merging Algorithm Capture images with a optical 4x zoom lens UOI & UOP Hospital Datasets

This research project has been co-financed by the European Union (European Regional Development Fund- ERDF) and Greek national funds through the Operational Program “THESSALY- MAINLAND GREECE AND EPIRUS ” of the National Strategic Reference Framework (NSRF ) Conclusion The development of a user friendly computer-assisted system will facilitate the transition from the broadly used semiquantitative scores to the CPA assessment through DIA. References 1.Caballero T, et al., Liver fibrosis assessment with semiquantitative indexes and image analysis quantification in sustained-responder and non-responder interferon-treated patients with chronic hepatitis C, JoH, 34: , Calvaruso V, et al., Computer-Assisted image analysis of liver Collagen: Relation to Ishak Scoring and Hepatic venous Pressure Gradient, Hepatology; 49: , Raftopoulos SC, et al., Comparison of noninvasive models of fibrosis in chronic hepatitis B. Hepatol Int 2012; 6 : 457–67. 4.Manousou P, et al., Digital image analysis of collagen assessment of progression of fibrosis in recurrent HCV after liver transplantetion, JoH; 58: , Campos CFF, et al., An inexpensive and worldwide available digital image analysis technique for histological fibrosis quantification in chronic hepatitis C, Journal of Viral Hepatitis; 21: 216–222, Huang Y, et al., Image analysis of liver biopsy samples measures fibrosis and predicts clinical outcome, JoH; 61:22-27, Xu S, et al., qFibrosis: A fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients, JoH; 61: , CPA assessment through Digital Image Analysis C D CPA: 13.14%