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Rat Model of the Associating Liver Partition and Portal Vein Ligation for Staged Hepatectomy ALPPS Procedure
Published on: August 14, 2017
A semi-automatic method for the extraction of the portal venous input function in quantitative dynamic
Andrew B Gill1,2, Nicholas J Hilliard3, Simon T Hilliard3
11 Department of Radiology, University of Cambridge, Cambridge, UK.
Objective:
To aid the extraction of the portal venous input function (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. Advances in knowledge: This technique provides a quick, simple and effective solution to the problems incurred by respiration motion and partial volume factors in the determination of the PVIF in liver dynamic contrast-enhanced CT.
