Abstract
Contrast-enhanced ultrasound (CEUS) acquisitions of focal liver lesions are affected
by motion, which has an impact on contrast signal quantification. We therefore developed
and tested, in a large patient cohort, a motion compensation algorithm called the
Iterative Local Search Algorithm (ILSA), which can correct for both periodic and non-periodic
in-plane motion and can reject frames with out-of-plane motion. CEUS cines of 183
focal liver lesions in 155 patients from three hospitals were used to develop and
test ILSA. Performance was evaluated through quantitative metrics, including the root
mean square error and R2 in fitting time–intensity curves and standard deviation value of B-mode intensities,
computed across cine frames), and qualitative evaluation, including B-mode mean intensity
projection images and parametric perfusion imaging. The median root mean square error
significantly decreased from 0.032 to 0.024 (p < 0.001). Median R2 significantly increased from 0.88 to 0.93 (p < 0.001). The median standard deviation value of B-mode intensities significantly
decreased from 6.2 to 5.0 (p < 0.001). B-Mode mean intensity projection images revealed improved spatial resolution.
Parametric perfusion imaging also exhibited improved spatial detail and better differentiation
between lesion and background liver parenchyma. ILSA can compensate for all types
of motion encountered during liver CEUS, potentially improving contrast signal quantification
of focal liver lesions.
Key Words
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Article info
Publication history
Published online: August 12, 2022
Accepted:
June 3,
2022
Received in revised form:
May 23,
2022
Received:
February 17,
2022
Identification
Copyright
© 2022 World Federation for Ultrasound in Medicine & Biology. All rights reserved.
