title: Perfusion linearity and its applications in perfusion algorithm analysis.
abstract: Perfusion analysis computes blood flow parameters (blood volume, blood flow, and mean transit time) from the observed flow of a contrast agent passing through the patient's vascular system. Perfusion deconvolution has been widely accepted as the principal numerical tool for perfusion analysis, and is used routinely in clinical applications. The extensive use of perfusion in clinical decision-making makes numerical stability and robustness of perfusion computations vital for accurate diagnostics and patient safety. The main goal of this paper is to propose a novel approach for validating numerical properties of perfusion algorithms. The approach is based on the Perfusion Linearity Property (PLP), which is fundamental to virtually all perfusion data processing. PLP allows one to study perfusion values as weighted averages of the original imaging data. This, in turn, uncovers hidden problems with the existing perfusion techniques, and may be used to suggest more reliable computational approaches and methodology.
authors.affiliation: BIDMC, Harvard Medical School, Radiology, Boston, MA 02215, United States. opianykh@bidmc.harvard.edu
authors.forename: Oleg S
authors.initials: OS
authors.lastname: Pianykh
mesh_terms: D000465:Algorithms; D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging; D003287:Contrast Media / Q000493:pharmacokinetics; D006801:Humans; D010477:Perfusion / Q000706:statistics & numerical data; D011877:Radionuclide Imaging; D012449:Safety; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data
chemical_list: D003287:Contrast Media