A practical approach for quantitative estimates of voxel‐by‐voxel liver perfusion using DCE imaging and a compartmental model | Zendy

Cao Yue | Zendy; Alspaugh Jonathan | Zendy; Shen Zhou | Zendy; Balter James M. | Zendy; Lawrence Theodore S. | Zendy; Ten Haken Randall K. | Zendy

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A practical approach for quantitative estimates of voxel‐by‐voxel liver perfusion using DCE imaging and a compartmental model

Author(s) -

Cao Yue,

Alspaugh Jonathan,

Shen Zhou,

Balter James M.,

Lawrence Theodore S.,

Ten Haken Randall K.

Publication year - 2006

Publication title -

medical physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.473

H-Index - 180

eISSN - 2473-4209

pISSN - 0094-2405

DOI - 10.1118/1.2219773

Subject(s) - voxel , magnetic resonance imaging , computer science , nonlinear system , liver perfusion , non linear least squares , medical imaging , contrast (vision) , nuclear medicine , perfusion , mathematics , artificial intelligence , algorithm , radiology , estimation theory , medicine , physics , quantum mechanics

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 ∼ 400 , which makes it practical for use in clinical trials.

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