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Intra-arterial contrast-enhanced ultrasound (IA CEUS) for localization of hepatocellular carcinoma (HCC) supply during transarterial chemoembolization (TACE): a case series

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Title
Intra-arterial contrast-enhanced ultrasound (IA CEUS) for localization of hepatocellular carcinoma (HCC) supply during transarterial chemoembolization (TACE): a case series
Published in
Abdominal Radiology, December 2016
DOI 10.1007/s00261-016-1016-0
Pubmed ID
Authors

Ilya Lekht, Megha Nayyar, Brian Luu, Phillip L. Guichet, Jessica Ho, Ramon Ter-Oganesyan, Michael Katz, Mittul Gulati

Abstract

Transarterial chemoembolization (TACE) is a proven catheter-based locoregional therapy for treatment of hepatocellular carcinoma (HCC). Drug-eluting bead TACE involves delivering micrometer-sized particles preloaded with doxorubicin directly to the tumor via its arterial blood supply and results in vascular embolization with intra-tumoral drug release. Effective therapy requires mapping of the tumor arterial supply, which in some cases cannot be accomplished with conventional angiographic techniques alone. Contrast-enhanced ultrasound (CEUS) is an imaging technique which utilizes microbubble contrast agents to demonstrate blood flow and tissue perfusion, enabling tumor visualization in real time. CEUS with intravenous contrast administration is well established for evaluation of HCC. Intra-arterial (IA) CEUS, on the other hand, is an emerging technique that allows more selective evaluation of the arterial supply to the tumor. The three cases in this report illustrate the utility of intra-procedural IA CEUS during TACE. Specifically, IA CEUS aided TACE in cases where the HCC showed poor arterial enhancement, an extrahepatic arterial supply, and a portal venous supply, respectively.

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Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 20%
Student > Doctoral Student 1 7%
Other 1 7%
Researcher 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 8 53%
Readers by discipline Count As %
Medicine and Dentistry 6 40%
Computer Science 1 7%
Unknown 8 53%