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Updated: Jul 2, 2026
Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
Published on: November 23, 2019
Improving soft-tissue contrast in four-dimensional computed tomography images of liver cancer patients using a
He Wang1, Sunil Krishnan, Xiaochun Wang
1Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Purpose:
To investigate a deformable image registration method to improve soft-tissue contrast in four-dimensional (4D) computed tomography (CT) images of the liver.
Methods And Materials:
Ten patients with hepatocellular carcinoma underwent 4D CT scan for radiotherapy treatment planning on a positron emission tomography/CT scanner. Four-dimensional CT images were binned into 10 equispaced phases. The exhale phase served as the reference phase, and images from the other nine phases were coregistered to the reference phase image using an intensity-based, automatic deformable image registration method. Then the coregistered images were combined to create a single, high-quality reconstructed CT image at exhale phase as the new reference for target delineation. The extent of image quality enhancement was quantified relative to the original CT by calculating the signal-to-noise ratio and the contrast-to-noise ratio.
Results:
The soft tissue image contrast was noticeably better after deformable image registration than in the original scans. Signal-to-noise ratios inside the liver region of interest increased for all patients by a factor of 3.0 (range, 2.3-3.7). The improvement in image quality was not linearly proportionate to the number of images averaged. Using only 6 phases can achieve at least 85% of the contrast enhancement that can be achieved using all 10 phases. We also found that contrast enhancement was inversely proportional to the original image quality (p = 0.006), and the contrast enhancement is attained with little loss of spatial resolution.
Conclusions:
This deformable image registration method is feasible to improve soft-tissue image quality in 4D CT images.
