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Full-Text Articles in Engineering
Comparing Implementations Of Magnetic-Resonance-Guided Fluorescence Molecular Tomography For Diagnostic Classification Of Brain Tumors, Scott C. Davis, Kimberley S. Samkoe, Julia A. O’Hara, Summer L. Gibbs-Strauss, Keith D. Paulsen, Brian W. Pogue
Comparing Implementations Of Magnetic-Resonance-Guided Fluorescence Molecular Tomography For Diagnostic Classification Of Brain Tumors, Scott C. Davis, Kimberley S. Samkoe, Julia A. O’Hara, Summer L. Gibbs-Strauss, Keith D. Paulsen, Brian W. Pogue
Dartmouth Scholarship
Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT …
Quantitative Imaging Reveals Heterogeneous Growth Dynamics And Treatment-Dependent Residual Tumor Distributions In A Three-Dimensional Ovarian Cancer Model, Jonathan P. Celli, Imran Rizvi, Conor L. Evans, Adnan O. Abu-Yousif, Tayyaba Hasan
Quantitative Imaging Reveals Heterogeneous Growth Dynamics And Treatment-Dependent Residual Tumor Distributions In A Three-Dimensional Ovarian Cancer Model, Jonathan P. Celli, Imran Rizvi, Conor L. Evans, Adnan O. Abu-Yousif, Tayyaba Hasan
Dartmouth Scholarship
Three-dimensional tumor models have emerged as valuable in vitro research tools, though the power of such systems as quantitative reporters of tumor growth and treatment response has not been adequately explored. We introduce an approach combining a 3-D model of disseminated ovarian cancer with high-throughput processing of image data for quantification of growth characteristics and cytotoxic response. We developed custom MATLAB routines to analyze longitudinally acquired dark-field microscopy images containing thousands of 3-D nodules. These data reveal a reproducible bimodal log-normal size distribution. Growth behavior is driven by migration and assembly, causing an exponential decay in spatial density concomitant with …