A semi-automatic method for the extraction of the portal venous input function in quantitative dynamic contrast-enhanced CT of the liver

作者：Gill Andrew B^*; Hilliard Nicholas J; Hilliard Simon T; Graves Martin J; Lomas David J; Shaw Ashley

来源：British Journal of Radiology, 2017, 90(1075): 20160875.

DOI：10.1259/bjr.20160875

Objective: To aid the extraction of the portal venous input PVIF) from axial dynamic contrast-enhanced CT images of the liver, eliminating the need for full manual outlining of the vessel across time points.
Methods: A cohort of 20 patients undergoing perfusion CT imaging of the liver was examined. Dynamic images of the liver were reformatted into contiguous thin slices. A region of interest was defined within a transverse section of the portal vein on a single contrast-enhanced image. This region of interest was then computationally projected across all thin slices for all time points to yield a semi-automated PVIF curve. This was compared against the "gold-standard" PVIF curve obtained by conventional manual outlining.
Results: Bland-Altman plots of curve characteristics indicated no substantial difference between automated and manual PVIF curves [concordance correlation coefficient in the range (0.66, 0.98)]. No substantial differences were shown by Bland-Altman plots of derived pharmacokinetic parameters when a suitable kinetic model was applied in each case [concordance correlation coefficient in range (0.92, 0.95)].
Conclusion: This semi-automated method of extracting the PVIF performed equivalently to a "gold-standard" manual method for assessing liver function.

• 出版日期2017