Browsing by Author "Choyke, Peter L."

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    Modeling and Reconstruction of Mixed Functional and Molecular Patterns
    Wang, Yue; Xuan, Jianhua; Srikanchana, Rujirutana; Choyke, Peter L. (Hindawi, 2006-01-17)
    Functional medical imaging promises powerful tools for thevisualization and elucidation of important disease-causingbiological processes in living tissue. Recent research aims todissect the distribution or expression of multiple biomarkersassociated with disease progression or response, where the signalsoften represent a composite of more than one distinct sourceindependent of spatial resolution. Formulating the task as a blindsource separation or composite signal factorization problem, wereport here a statistically principled method for modeling andreconstruction of mixed functional or molecular patterns. Thecomputational algorithm is based on a latent variable model whoseparameters are estimated using clustered component analysis. Wedemonstrate the principle and performance of the approaches on thebreast cancer data sets acquired by dynamic contrast-enhancedmagnetic resonance imaging.
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    Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics
    Chen, Li; Choyke, Peter L.; Wang, Niya; Clarke, Robert; Bhujwalla, Zaver M.; Hillman, Elizabeth M. C.; Wang, Ge; Wang, Yue (PLOS, 2014-11-07)
    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.