Radiomics in liver diseases: Current progress and future opportunities

Area of Science:

• Medical Imaging
• Radiology
• Oncology

Background:

• Liver diseases present a significant global health challenge, with conventional imaging often providing insufficient diagnostic information.
• Accurate detection, characterization, and monitoring of liver pathologies remain clinically challenging.
• Radiomics offers a novel quantitative imaging analysis technique to overcome limitations of conventional methods.

Purpose of the Study:

• To review the methodological process of radiomics studies in liver diseases.
• To outline the applications of radiomics in liver disease diagnosis, staging, biological behavior evaluation, and prognosis.
• To discuss current limitations and future opportunities for radiomics in liver disease management.

Main Methods:

• Data acquisition, curation, and region of interest segmentation.
• Extraction of high-throughput, high-dimensional, liver-specific radiomic features from multi-modality imaging.
• Application of machine learning algorithms to develop clinical target-oriented imaging biomarkers.

Main Results:

• Radiomics effectively reflects the heterogeneity of liver lesions.
• The methodology covers the entire pipeline from image analysis to predictive modeling.
• Applications span diagnosis, staging, tumor behavior assessment, and prognosis across various liver diseases.

Conclusions:

• Radiomics shows significant promise as an efficient tool for personalized diagnosis and treatment decision-making in liver diseases.
• Further research is needed to address current limitations and fully realize the potential of radiomics in clinical practice.
• Radiomics-based imaging biomarkers can enhance the management of liver diseases, improving patient outcomes.