Radiogenomic Analysis of Oncological Data: A Technical Survey

Area of Science:

• Biomedical research
• Computational biology
• Medical imaging

Background:

• Biomedical research generates vast, complex datasets, including genetic and radiomic information.
• Radiogenomics integrates imaging features with gene expression data.
• Advanced analytical techniques are crucial for extracting meaningful insights from complex data.

Purpose of the Study:

• To review state-of-the-art techniques in radiomics and genomics.
• To focus on analysis methods using molecular and multimodal probes.
• To discuss the impact of these techniques in oncologic research.

Main Methods:

• Review of current radiomics and genomics analysis techniques.
• Focus on methods utilizing molecular and multimodal probes.
• Analysis of data from imaging and gene expression.

Main Results:

• Radiogenomics leverages non-conventional data analysis for cancer decision support.
• Techniques are being developed to correlate imaging features with gene expression.
• The impact of single and combined techniques on oncologic diseases is under investigation.

Conclusions:

• Radiogenomics offers powerful tools for cancer diagnosis and treatment.
• Further research is needed to fully understand the potential of integrated radiomic and genomic approaches.
• Advanced analytical methods are key to unlocking the full potential of radiogenomics in oncology.