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

被引：10
|
作者：
Cao, Yue [1 ]
Alspaugh, Jonathan
Shen, Zhou
Balter, James M.
Lawrence, Theodore S.
Ten Haken, Randall K.
机构：
[1] Univ Michigan, Dept Radiat Oncol, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Radiol, Ann Arbor, MI 48109 USA
来源：
MEDICAL PHYSICS | 2006年 / 33卷 / 08期
关键词：
liver perfusion; a single compartmental model; CT perfusion; linear least squares;
D O I：
10.1118/1.2219773
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
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 similar to 400, which makes it practical for use in clinical trials. (C) 2006 American Association of Physicists in Medicine.
引用
收藏
页码：3057 / 3062
页数：6
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