Radiogenomics and Radiomics in Liver Cancers

Area of Science:

• Computational imaging analysis
• Biomedical imaging
• Translational oncology

Background:

• Radiogenomics links imaging features with molecular data for non-invasive tumor profiling.
• Radiomics extracts quantitative data from images for prognosis and clinical decisions.
• These fields are advancing medical imaging from descriptive to predictive.

Purpose of the Study:

• To review recent advancements in radiogenomics and radiomics for liver cancers.
• To highlight the potential of these computational disciplines in oncology.

Main Methods:

• Review of current literature on radiogenomics and radiomics in liver cancer.
• Analysis of studies correlating imaging phenotypes with molecular data.
• Integration of quantitative imaging data with clinical information.

Main Results:

• Radiogenomics enables non-invasive prediction of tumor molecular characteristics.
• Radiomics provides prognostic information and aids clinical decision-making.
• Combined, these fields offer insights into pathophysiological mechanisms of liver cancer.

Conclusions:

• Radiogenomics and radiomics are transforming liver cancer diagnosis and management.
• These disciplines facilitate a deeper understanding of liver cancer through advanced imaging analysis.
• Future applications may further enhance personalized treatment strategies for liver malignancies.