Unsupervised deconvolution of dynamic imaging reveals intratumor vascular heterogeneity and repopulation dynamics.
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.
Genetics Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States of America; Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, United States of America.
Li
L
Chen
Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States of America.
Peter L
PL
Choyke
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, United States of America.
Niya
N
Wang
Lombardi Comprehensive Cancer Center, Georgetown University, Washington, D. C. 20057, United States of America.
Robert
R
Clarke
Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States of America.
Zaver M
ZM
Bhujwalla
Department of Biomedical Engineering, Columbia University, New York, NY 10027, United States of America.
Elizabeth M C
EM
Hillman
Department of Biomedical Engineering, Biomedical Imaging Center, Rensselaer Polytechnic Institute, Troy, NY 12180, United States of America.
Ge
G
Wang
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, United States of America.
Yue
Y
Wang
D000465:Algorithms; D001940:Breast / Q000098:blood supply*; D001943:Breast Neoplasms / Q000098:blood supply*; D003287:Contrast Media; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*
D003287:Contrast Media