Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome
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Abstract
Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care. Clin Cancer Res; 21(2); 249–57. ©2014 AACR.
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In the past 10 years, radiomics and radiogenomics research in tomographic imaging has increased dramatically.
“In the past 10 years, radiomics and radiogenomics research in tomographic imaging (CT, MR imaging, and PET) has increased dramatically.”
From Radiomics: Images Are More than Pictures, They Are Data (2016) · cites this paper as [43]
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- Authors
- O'Connor, J. P. B., Rose, C. J., Waterton, J. C., Carano, R. A. D., Parker, G. J. M., & Jackson, A.
- Affiliations
- 1CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester, University of Manchester, Manchester, United Kingdom.
- Engineering and Physical Sciences Research Council (GB)
- AstraZeneca (United Kingdom) (GB)
- Genentech (US)
- Venue
- Clinical Cancer Research
- Published
- 2015-01-14
- Volume
- 21
- Issue
- 2
- Pages
- 249-257
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- PMC
- PMC4688961
- OpenAlex
- W2142266080
- Cited by
- 677
- References
- 88
- Citations by year
- 2026: 57 · 2025: 65 · 2024: 58 · 2023: 52 · 2022: 54 · 2021: 74 · 2020: 70 · 2019: 65 · 2018: 60 · 2017: 62 · 2016: 39 · 2015: 19
- FWCI
- 6.22
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Cancer Research UK (16465, 18097, A18097, A15267)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › MRI in cancer diagnosis
- Keywords
- intratumoral heterogeneity, tumor heterogeneity, treatment response, treatment resistance, tumor hypoxia, cancer metabolism, tumor perfusion, cell death, positron emission tomography, CT attenuation, molecular imaging, tumor subregions, prognostic factors
- MeSH terms
- Animals, Diagnostic Imaging, Humans, Image Interpretation, Computer-Assisted, Neoplasms, Genetic Heterogeneity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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