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Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics

Author

Listed:
  • Li Chen
  • Peter L Choyke
  • Niya Wang
  • Robert Clarke
  • Zaver M Bhujwalla
  • Elizabeth M C Hillman
  • Ge Wang
  • Yue Wang

Abstract

With the existence of biologically distinctive malignant cells originated within the same tumor, intratumor functional heterogeneity is present in many cancers and is often manifested by the intermingled vascular compartments with distinct pharmacokinetics. However, intratumor vascular heterogeneity cannot be resolved directly by most in vivo dynamic imaging. We developed multi-tissue compartment modeling (MTCM), a completely unsupervised method of deconvoluting dynamic imaging series from heterogeneous tumors that can improve vascular characterization in many biological contexts. Applying MTCM to dynamic contrast-enhanced magnetic resonance imaging of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. MTCM is readily applicable to other dynamic imaging modalities for studying intratumor functional and phenotypic heterogeneity, together with a variety of foreseeable applications in the clinic.

Suggested Citation

  • Li Chen & Peter L Choyke & Niya Wang & Robert Clarke & Zaver M Bhujwalla & Elizabeth M C Hillman & Ge Wang & Yue Wang, 2014. "Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    • Handle: RePEc:plo:pone00:0112143
    DOI: 10.1371/journal.pone.0112143
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    1. Rebecca A. Burrell & Nicholas McGranahan & Jiri Bartek & Charles Swanton, 2013. "The causes and consequences of genetic heterogeneity in cancer evolution," Nature, Nature, vol. 501(7467), pages 338-345, September.
    2. Melissa R. Junttila & Frederic J. de Sauvage, 2013. "Influence of tumour micro-environment heterogeneity on therapeutic response," Nature, Nature, vol. 501(7467), pages 346-354, September.
    3. Philippe L. Bedard & Aaron R. Hansen & Mark J. Ratain & Lillian L. Siu, 2013. "Tumour heterogeneity in the clinic," Nature, Nature, vol. 501(7467), pages 355-364, September.
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