ReviewJournal of medical ultrasonics (2001)2020
Ultrasound fusion imaging technologies for guidance in ablation therapy for liver cancer.
Review in Journal of medical ultrasonics (2001), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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.
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Who cites it
9 citing papers in PubMed, 24 citations in OpenAlex.
- Real-Life Clinical Use and Outcomes of Fusion Imaging-Guided Percutaneous Microwave Ablation of Hepatocellular Carcinoma: Experience from Two Italian Centers.Diagnostics (Basel, Switzerland) · 2025Article
- Using multimodal ultrasound technology to improve the success rate of liver tumor puncture for lesions with poor visibility on conventional ultrasound imaging.Quantitative imaging in medicine and surgery · 2025Article
- Diagnostic superiority of contrast-enhanced ultrasound combined with elastography for early hepatocellular carcinoma in cirrhotic patients.American journal of translational research · 2025Article
- Precise liver tumor ablation: the clinical potential of US-US overlay fusion guidance.Ultrasonography (Seoul, Korea) · 2024Article
- Role of Immunological Cells in Hepatocellular Carcinoma Disease and Associated Pathways.ACS pharmacology & translational science · 2023Review
- Utility of fusion imaging for the evaluation of ultrasound quality in hepatocellular carcinoma surveillance.Ultrasonography (Seoul, Korea) · 2023Article
- Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures.Journal of clinical medicine · 2022Review
- Image Guidance in Ablation for Hepatocellular Carcinoma: Contrast-Enhanced Ultrasound and Fusion Imaging.Frontiers in oncology · 2021Review
- Comparative Study of Application of Computed Tomography/Ultrasound and Computed Tomography Imaging Guidance Methods in the Microwave Ablation of Liver Cancer.Journal of computer assisted tomographyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With advances in imaging technology, images from ultrasound (US) and computed tomography (CT) or magnetic resonance imaging (MRI) can be displayed simultaneously and in real time, according to the angle of the transducer. CT/MR-US fusion imaging improves the visualization of inconspicuous hepatocellular carcinoma (HCC) and helps us to understand the three-dimensional relationship between the liver vasculature and HCC. US fusion imaging guidance facilitates improvement in the treatment response for HCC with poor conspicuity, and the rates of technical success of ablation and local tumor progression for inconspicuous HCC range from 94.4 to 100% and 0 to 8.3%, respectively. Moreover, the development of image fusion has made it possible to compare and overlay pre- and post-ablation US images. This US-US fusion imaging allows side-by-side comparison of the ablative margin, while US-US overlay fusion can visualize the ablative margin because the tumor image is projected onto the ablative hyperechoic zone. Thus, US-US overlay fusion guidance is highly effective for safety margin achievement in local ablation therapy for HCC, providing a lower risk of local tumor progression. This manuscript reviews the current status of ultrasound fusion imaging for percutaneous ablation therapy of HCC.
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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.