Physical density assessments may provide valuable insights for a range of diagnostic purposes in abdominal, pulmonary, and breast imaging. These purposes include differentiating iso-attenuating cysts from lesions, aiding in function tests of viral pneumonia, and quantifying breast cancer risk. Physical density assessments also provide a natural and intuitive measurement of human tissue that may be useful for measuring global body mass distributions and comparing measurement techniques. In this work, we present a spectral physical density map generated from clinical dual-energy computed tomography (DECT) datasets. We utilized available DECT estimates for effective atomic number, monoenergetic attenuation, and electron density as inputs into the Alvarez-Macovski model and the relation between a material’s physical and electron densities. To achieve higher accuracy assessments, these underlying equations were parametrized and fit to published tissue composition and density data that had been supplemented with simulated iodine enhancements. Validating the fits with phantom experiments, we observed measurements that are within ± 0.02 g/ml of their nominal values. Our assessments thus fall inside the margin-of-error for the ground-truth densities declared by the phantom manufacturer. Though we validated our density maps only on a dual-layer DECT implementation, the development and optimization of this new spectral result were independent of any other spectral CT technology. Because of this independence and the high accuracies of the maps, we encourage future clinical trials testing the potential applications of this new result for diagnostic imaging.
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