Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization

Area of Science:

• Oncology
• Medical Imaging
• Bioinformatics

Background:

• Prostate cancer (PCa) management benefits from advanced research fields like radiomics and genomics.
• Radiomics extracts quantitative imaging features, while genomics decodes molecular information.
• Integrating these fields can enhance risk stratification and disease management for PCa patients.

Purpose of the Study:

• To review current literature on radiomics, genomics, and radiogenomics in prostate cancer research.
• To assess the role of these technologies in PCa diagnosis, treatment, and follow-up.
• To highlight the potential of radiogenomics in overcoming PCa heterogeneity.

Main Methods:

• Literature review of quantitative and qualitative results from well-designed studies.
• Analysis of radiomics feature extraction from medical imaging (e.g., MRI) using AI and machine learning.
• Integration of imaging data with genomic information for predictive modeling.

Main Results:

• Radiomics enhances the clinical value of imaging data for PCa management.
• AI and machine learning aid in extracting features and making clinical decisions.
• Radiogenomics shows potential in characterizing molecular features and overcoming PCa heterogeneity through non-invasive assessment.

Conclusions:

• Radiomics and genomics hold promise for improving PCa diagnosis, treatment, and follow-up.
• Further validation in large cohorts is needed to establish the role of radiogenomics.
• Non-invasive radiological assessment via radiogenomics can address PCa heterogeneity.