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Updated: May 13, 2025

Point-of-Care Lung Ultrasound in Adults: Image Acquisition
Published on: March 3, 2023
Comparative Study of Sonazoid and SonoVue Contrast-Enhanced Ultrasound Quantitative Analysis Parameters in Peripheral
Guosheng Liang1, Wuxi Chen1, Jiaxin Tang2
1Department of Ultrasound, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China.
Purpose:
Lung cancer is a leading cause of death; however, its diagnosis needs to be improved. This study aimed to compare the performances of the contrast agents Sonazoid and SonoVue in quantitative analysis in the contrast-enhanced ultrasound (CEUS) of peripheral lung cancer lesions (PLCLs).
Methods:
This retrospective study included patients with PLCLs between January 2021 and January 2024. They were divided into the Sonazoid-CEUS (50 patients) and SonoVue-CEUS (53 patients) groups. In the CEUS video, lesions and adjacent normal lung tissues were selected as regions of interest to obtain time-intensity curves. Seven CEUS indicators were used to compare the performances of the two contrast agents.
Results:
The arrival times (ATs) were 13.1 ± 5.2 s and 11.5 ± 3.7 s for PLCLs (p = 0.087), respectively, and 8.0 ± 4.1 s and 7.0 ± 4.2 s for adjacent lung tissues (p = 0.197), respectively, in the Sonazoid and SonoVue groups. The peak intensity (PI) and area under the curve (AUC) of the lesions in the Sonazoid group were significantly lower than those in the SonoVue group (PI: 25.0 ± 11.5 vs. 35.8 ± 7.9, p < 0.001; AUC: 2365.2 ± 1708.2 vs. 4309.5 ± 1252.1, p < 0.001). The time to peak (TTP), mean transition time (MTT), and lesion-lung PI difference (ΔPI) in the Sonazoid group were significantly higher than those in the SonoVue group (TTP: 36.3 ± 13.8 s vs. 24.4 ± 8.7 s, p < 0.001; MTT: 119.6 ± 45.3 s vs. 80.6 ± 21.4 s, p < 0.001; ΔPI: 14.3 ± 10.9 vs. 8.4 ± 6.1, p < 0.01).
Conclusion:
Sonazoid and SonoVue exhibited comparable quantitative performances in CEUS of PLCLs; the higher ΔPI of Sonazoid suggests it may enhance the contrast between lesions and adjacent tissues. The study's findings could help improve lung cancer diagnosis.
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