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

Accepted version
Peer-reviewed

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Type

Article

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Authors

Gill, AB 
Hilliard, NJ 
Hilliard, ST 
Graves, MJ 
Lomas, DJ 

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.

Description

Keywords

Algorithms, Contrast Media, Humans, Iohexol, Iopamidol, Liver, Liver Diseases, Motion, Portal Vein, Radiographic Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Tomography, X-Ray Computed

Journal Title

British Journal of Radiology

Conference Name

Journal ISSN

0007-1285
1748-880X

Volume Title

90

Publisher

British Institute of Radiology
Sponsorship
Cambridge University Hospitals NHS Foundation Trust (CUH) (unknown)
Cambridge University Hospitals NHS Foundation Trust (CUH) (RG52525)
The study was funded by the Imaging Theme of the Cambridge NIHR Biomedical Research Council.