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Multiparametric MRI and radiomics in prostate cancer: a review

  • Yu SunEmail author
  • Hayley M. Reynolds
  • Bimal Parameswaran
  • Darren Wraith
  • Mary E. Finnegan
  • Scott Williams
  • Annette Haworth
Review Paper

Abstract

Multiparametric MRI (mpMRI) is an imaging modality that combines anatomical MR imaging with one or more functional MRI sequences. It has become a versatile tool for detecting and characterising prostate cancer (PCa). The traditional role of mpMRI was confined to PCa staging, but due to the advanced imaging techniques, its role has expanded to various stages in clinical practises including tumour detection, disease monitor during active surveillance and sequential imaging for patient follow-up. Meanwhile, with the growing speed of data generation and the increasing volume of imaging data, it is highly demanded to apply computerised methods to process mpMRI data and extract useful information. Hence quantitative analysis for imaging data using radiomics has become an emerging paradigm. The application of radiomics approaches in prostate cancer has not only enabled automatic localisation of the disease but also provided a non-invasive solution to assess tumour biology (e.g. aggressiveness and the presence of hypoxia). This article reviews mpMRI and its expanding role in PCa detection, staging and patient management. Following that, an overview of prostate radiomics will be provided, with a special focus on its current applications as well as its future directions.

Keywords

Prostate cancer Multiparametric MRI Radiomics Machine learning Tumour Heterogeneity 

Notes

Acknowledgements

The authors would like to acknowledge Peter MacCallum Cancer Centre, The University of Melbourne and Cancer Therapeutics CRC for providing the resources to perform the literature survey. The authors would also like to show their gratitude to Courtney Savill and Lauren Caspersz for their contributions in data collection.

Funding

This study is supported by PdCCRS grant 628592 with funding partners: Prostate Cancer Foundation of Australia, and the Radiation Oncology Section of the Australian Government of Health and Aging and Cancer Australia. Yu Sun is funded by the Melbourne International Research Scholarship, a Movember Young Investigator Grant through Prostate Cancer Foundation of Australia (PCFA) and Cancer Therapeutics Top-up Funding. Hayley Reynolds is funded by a Movember Young Investigator Grant through PCFA’s Research Program.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical Approval

This article does not directly involve human participants or animals, but contains example prostate MR images from another study approved by Human Research Ethics Committee (HREC).

Informed Consent

Informed consent was obtained from all individual participants.

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Copyright information

© Australasian College of Physical Scientists and Engineers in Medicine 2019

Authors and Affiliations

  1. 1.University of SydneySydneyAustralia
  2. 2.Peter MacCallum Cancer CentreMelbourneAustralia
  3. 3.Imaging AssociatesMelbourneAustralia
  4. 4.Queensland University of TechnologyBrisbaneAustralia
  5. 5.Imperial College Healthcare NHS TrustLondonUK
  6. 6.Imperial College LondonLondonUK

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