Abstract
Voxel-by-voxel estimation of liver perfusion using nonlinear least-squares fits of dynamic contrast enhanced computed tomography or magnetic resonance imaging data to a compartmental model is a computational expensive process. In this report, a "linear" least-squares method for estimation of liver perfusion is described. Simulated data and the data from an example case of a patient with intrahepatic cancer are presented. Compared to the nonlinear method, the new method can improve computational speed by a factor of approximately 400, which makes it practical for use in clinical trials.
Publication types
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Evaluation Study
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Research Support, N.I.H., Extramural
MeSH terms
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Algorithms
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Computer Simulation
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Contrast Media / pharmacokinetics*
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Humans
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Imaging, Three-Dimensional / methods
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Information Storage and Retrieval / methods
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Liver / blood supply
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Liver / diagnostic imaging
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Liver / metabolism
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Liver Neoplasms / diagnostic imaging*
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Liver Neoplasms / metabolism*
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Metabolic Clearance Rate
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Models, Biological*
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Radiographic Image Enhancement / methods*
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Radiographic Image Interpretation, Computer-Assisted / methods*
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Reproducibility of Results
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Sensitivity and Specificity
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Tomography, X-Ray Computed / methods*