Imaging Genomics and Multiomics: A Guide for Beginners Starting Radiomics-Based Research

Shiva Singh, Bahram Mohajer, Shane A. Wells, Tushar Garg, Kate Hanneman, Takashi Takahashi, Omran AlDandan, Morgan P. McBee, Anugayathri Jawahar

Research output: Contribution to journalReview articlepeer-review

Abstract

Radiomics uses advanced mathematical analysis of pixel-level information from radiologic images to extract existing information in traditional imaging algorithms. It is intended to find imaging biomarkers related to the genomics of tumors or disease patterns that improve medical care by advanced detection of tumor response patterns in tumors and to assess prognosis. Radiomics expands the paradigm of medical imaging to help with diagnosis, management of diseases and prognostication, leveraging image features by extracting information that can be used as imaging biomarkers to predict prognosis and response to treatment. Radiogenomics is an emerging area in radiomics that investigates the association between imaging characteristics and gene expression profiles. There are an increasing number of research publications using different radiomics approaches without a clear consensus on which method works best. We aim to describe the workflow of radiomics along with a guide of what to expect when starting a radiomics-based research project.

Original languageEnglish (US)
JournalAcademic radiology
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© 2024 The Association of University Radiologists

Keywords

  • Genomics
  • Imaging
  • Multiomics
  • Radiomics
  • Texture analysis

PubMed: MeSH publication types

  • Journal Article
  • Review

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