Evidence map›Paper›PMID 40369524›Full record

ArticleJournal of nanobiotechnology2025

PEGylated gas vesicles: a promising novel ultrasound contrast agent for diagnosis and guiding radiofrequency ablation of liver tumor.

Kezhi Yu, Yongquan Huang, Yuanyuan Wang, Qunyan Wu, Zihang Wang, Fei Li, Jianri Chen, Maierhaba Yibulayin, Shushan Zhang, Zhongzhen Su and 1 more

Erratum issuedAbstract read
In one paragraph

Article in Journal of nanobiotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. αvβ3-targeted gas vesicles for ultrasound molecular imaging of tumors.Frontiers in bioengineering and biotechnology · 2026
    Article
  5. Article
  6. Review
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Kezhi YuDepartment of Ultrasound, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, China.
Yongquan HuangDepartment of Ultrasound, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, China. huangyq39@mail.sysu.edu.cn.
Yuanyuan WangKey Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055, Guangdong Province, China.
Qunyan WuDepartment of Ultrasound, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, China.
Zihang WangDepartment of Echocardiography, Xinjiang Key Laboratory of Ultrasound Medicine, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province, China.
Fei LiResearch Center for Advanced Detection Materials and Medical lmaging Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China.
Jianri ChenResearch Center for Advanced Detection Materials and Medical lmaging Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China.
Maierhaba YibulayinDepartment of Echocardiography, Xinjiang Key Laboratory of Ultrasound Medicine, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province, China.
Shushan ZhangDepartment of Ultrasound, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, China.
Zhongzhen SuDepartment of Ultrasound, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, China. suzhzh3@mail.sysu.edu.cn.
Fei YanKey Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055, Guangdong Province, China. fei.yan@siat.ac.cn.

Funding

Fei Yan 2020YFA0908800; 32171365; D2301012; 82371975Yongquan Huang 2023A1515010620Zhongzhen Su 2024A1515013242; ZH22017003210009PWC; WYYXQN-2021010; 310103050302-220904094228
6 · The paper itself

Abstract

Ultrasound contrast agents (UCAs) play an important role in diagnosis and the imaging-guided treatment of liver tumor in clinical settings. However, most commercially available UCAs are micro-sized and fabricated through a chemical synthesis route. Here, we developed a new class of biosynthesized nanoscale contrast agent (PEG-GVs) and comprehensively compared its physicochemical characteristics and imaging performance with commercial Sonovue and Sonazoid. Our results revealed PEG-GVs may produce more stable and durable contrast signals, contributing to their penetration beyond blood vessels and long-time retention in liver. Interestingly, we found that PEG-GVs did not exhibit a continuously enhanced accumulation in the liver tumor due to the EPR effect, but displayed a rapid regression. The long-time retention of PEG-GVs in normal liver tissue and rapid regression from liver tumor lead to distinct display of liver tumor boundaries, enabling the early diagnosis of small liver metastases and presenting advantages in guiding radiofrequency ablation of liver tumor. Moreover, we have also verified that PEG-GVs exhibit excellent imaging performance and biosafety in macaques. Our study provides new insights into the roles of PEG-GVs in liver tumor diagnosis and ablation guidance.

Indexed as

Contrast MediaLiver NeoplasmsPolyethylene GlycolsRadiofrequency AblationAnimalsCell Line, TumorFerric CompoundsGasesHumansIronLiverMaleMiceOxidesPhospholipidsSulfur HexafluorideContrast MediaFerric CompoundsGasesIronOxidesPhospholipidsPolyethylene GlycolsSonazoidSulfur HexafluorideBiosynthesisDiagnosisGas vesiclesLiver tumorUltrasound contrast agents

Identifiers

PMID40369524
PMCPMC12076873

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.