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A Risk-based Approach to Identifying Oligometastatic Disease on Imaging

1Cancer Research UK Imaging Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, UK.
2Department of Radiology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publication Date:
Int J Cancer
Volume Number:
Issue Number:
Int J Cancer. 2019 Feb 1;144(3):422-30.
PubMed ID:
imaging, metabolic, morphology, oligometastases, phenotype
Appears in Collections:
NCIGT, Prostate Group, SPL
CRUK support to the Cancer Imaging Centre at ICR and RMH C1060/A16464
NIHR funding to the Clinical Research Facility in Imaging (NM deSouza)
P41 EB015898/EB/NIBIB NIH HHS/United States
R01 CA111288/CA/NCI NIH HHS/United States
Clinical trial support from InSightec Inc.
Gilead Sciences and is on the scientific advisory board of Profound Medical
InSightec Inc.
Generated Citation:
deSouza N.M., Tempany C.M. A Risk-based Approach to Identifying Oligometastatic Disease on Imaging. Int J Cancer. 2019 Feb 1;144(3):422-30. PMID: 30098215. PMCID: PMC6492106.
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Recognition of <3 metastases in <2 organs, particularly in cancers with a known predisposition to oligometastatic disease (OMD) (colorectal, prostate, renal, sarcoma and lung), offers the opportunity to focally treat the lesions identified and confers a survival advantage. The reliability with which OMD is identified depends on the sensitivity of the imaging technique used for detection and may be predicted from phenotypic and genetic factors of the primary tumour, which determine metastatic risk. Whole-body or organ-specific imaging to identify oligometastases requires optimization to achieve maximal sensitivity. Metastatic lesions at multiple locations may require a variety of imaging modalities for best visualisation because the optimal image contrast is determined by tumour biology. Newer imaging techniques used for this purpose require validation. Additionally, rationalisation of imaging strategies is needed, particularly with regard to timing of imaging and follow-up studies. This article reviews the current evidence for the use of imaging for recognising OMD and proposes a risk-based roadmap for identifying patients with true OMD, or at risk of metastatic disease likely to be OM.