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15 May 2003 Partially independent component analysis of tumor heterogeneities by DCE-MRI
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Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has emerged as an effective tool to access tumor vascular characteristics. DCE-MRI can be used to characterize noninvasively, microvasculature providing information about tumor microvessel structure and function (e.g., tumor blood volume, vascular permeability, tumor perfusion). However, pixels of DCE-MRI represent a composite of more than one distinct functional biomarker (e.g., microvessels with fast or slow perfusion) whose spatial distributions are often heterogeneous. Complementary to various existing methods (e.g., compartment modeling, factor analysis), this paper proposes a blind source separation method which allows for a computed simultaneous imaging of multiple biomarkers from composite DCE-MRI sequences. The algorithm is based on a partially-independent component analysis, whose parameters are estimated using a subset of informative pixels defining the independent portion of the observations. We demonstrate the principle of the approach on simulated image data set, and we then apply the method to the tissue heterogeneity characterization of breast tumors where spatial distribution of tumor blood volume, vascular permeability, and tumor perfusion, as well as their time activity curves (TACs) are simultaneously estimated.
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JunYing Zhang, Rujirutana Srikanchana, Jianhua Xuan, Peter Choyke, King Li, and Yue Joseph Wang "Partially independent component analysis of tumor heterogeneities by DCE-MRI", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003);

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