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ImaGene: a web-based software platform for tumor radiogenomic evaluation and reporting.

Shrey S Sukhadia1,2, Aayush Tyagi3, Vivek Venkataraman1,2

  • 1Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD 4000, Australia.

Bioinformatics Advances
|January 26, 2023
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Summary

A new web platform, ImaGene, integrates tumor imaging and omics data for reproducible radiogenomic analysis. It identifies genotype-phenotype correlations using AI, aiding cancer research and knowledge base development.

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Area of Science:

  • Radiogenomics
  • Computational Biology
  • Bioinformatics

Background:

  • Radiographic imaging and omics data offer insights into tumor characteristics.
  • Connecting tumor genotype and phenotype traditionally requires correlation analyses.
  • A unified, reproducible software platform is lacking for radiogenomic studies.

Purpose of the Study:

  • To develop ImaGene, a web-based platform for integrated radiogenomic analysis.
  • To enable reproducible correlation analysis and AI model construction from tumor imaging and omics data.
  • To facilitate the identification of genotype-phenotype relationships in cancer.

Main Methods:

  • ImaGene accepts tumor omics and imaging datasets as input.
  • The platform performs correlation analyses between imaging features and omics data.
  • ImaGene constructs artificial intelligence (AI) models with modifiable parameters.

Main Results:

  • ImaGene successfully analyzed data for invasive breast carcinoma (IBC) and head and neck squamous cell carcinoma (HNSCC).
  • Potential associations were identified between imaging features and specific genes in IBC and HNSCC.
  • The platform generated diagnostic reports for the AI models.

Conclusions:

  • ImaGene provides a user-friendly, flexible, and reproducible solution for radiogenomic analysis.
  • The platform has the potential to become a standard tool in radiogenomics.
  • ImaGene contributes to building an emerging radiogenomic knowledge base.