Diagnosis of liver fibrosis using digital analysis

Abstract

Liver fibrosis is a pathological process in which excessive deposition of connective tissueoccurs in the liver. It is a response to chronic liver damage caused by viral agents, alcoholabuse, drug abuse, or autoimmune diseases. Diagnosis and assessment of liver fibrosisare important in staging the disease, prognosticating its progression, and making treatmentdecisions. The diagnosis of liver fibrosis involves clinical interview, laboratory tests, imaging, and – the “gold diagnostic standard” – histopathological examination. Biopsyingthe liver allows for precise assessment of fibrosis and potential identification of other liverdiseases; however, it is an invasive procedure and may carry some risk of complications. Inaddition, pathomorphological interpretation is often subjective. In order to minimize errorsand improve the accuracy of diagnosis, digital image analysis and artificial intelligencetechnologies are being developed for histopathological examinations. In recent years, AIbasedmethods have been designed to support the assessment of liver fibrosis throughanalysis of imaging and clinical data. AI can help automatically recognize patterns characteristicof liver fibrosis, which could contribute to faster and more precise diagnosis.However, the final decision on the diagnosis and treatment of liver fibrosis should still bemade by a qualified specialist.