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A Motion Artifact Correction Algorithm for Cone-Beam CT in Patients with Hepatic Malignancies Treated with Transarterial Chemoembolization.

Authors :
Kwon LM
Hwang JS
Lee Y
Kim HC
Chung JW
Choi JW
Source :
Journal of vascular and interventional radiology : JVIR [J Vasc Interv Radiol] 2022 Nov; Vol. 33 (11), pp. 1367-1374.e2. Date of Electronic Publication: 2022 Jul 13.
Publication Year :
2022

Abstract

Purpose: To evaluate the effect of a motion artifact correction algorithm (MACA) on cone-beam computed tomography (CT) during transarterial chemoembolization for hepatic malignancies.<br />Materials and Methods: From June 2020 to March 2021, 42 patients with mild-to-severe motion artifacts detected using single cone-beam CT scans were evaluated retrospectively. The image quality of native and motion-corrected data was compared. The maximum intensity, sharpness, and full width at half maximum (FWHM) of 5 segmental hepatic arteries were quantitatively measured. The overall quality of maximum intensity projection (MIP) images, conspicuity of tumor-supplying arteries, and need for selective angiography to ascertain the vascular anatomy were qualitatively evaluated by multiple readers. Paired t and Wilcoxon signed rank tests were used to compare the parameters.<br />Results: The mean maximum intensity and sharpness increased from 2,792.01 HU ± 451.36 to 3,148.40 HU ± 594.46 and from 0.31 ± 0.02/mm to 0.34 ± 0.02/mm, respectively, using the MACA (both P < .001). The MACA decreased the mean FWHM from 2.02 mm ± 0.27 to 1.78 mm ± 0.26 (P < .001). The overall quality of the MIP images and the conspicuity of the tumor-supplying artery were enhanced from 2.5 to 3.0 points and from 3.0 to 4.0 points, respectively (both P < .001). Selective angiography was expected to be omitted in 7 cases (16.7%, 7/42) after using the MACA.<br />Conclusions: The MACA significantly improved both quantitative and qualitative image quality of cone-beam CT in selected patients with motion artifacts during transarterial chemoembolization for hepatic malignancies.<br /> (Copyright © 2022 SIR. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1535-7732
Volume :
33
Issue :
11
Database :
MEDLINE
Journal :
Journal of vascular and interventional radiology : JVIR
Publication Type :
Academic Journal
Accession number :
35842027
Full Text :
https://doi.org/10.1016/j.jvir.2022.07.002