A semi-automatic method for the extraction of the portal venous input function in quantitative dynamic contrast-enhanced CT of the liver
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Abstract
OBJECTIVES
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 were examined. Dynamic images of the liver were reformatted into contiguous thin slices. A region of interest (ROI) was defined within a transverse section of the portal vein on a single contrast-enhanced image. This ROI 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, CCC, 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 (CCC in range [0.92, 0.95]).
CONCLUSIONS
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 DCE-CT.
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1748-880X
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Cambridge University Hospitals NHS Foundation Trust (CUH) (RG52525)