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Dong Y, Koch JBH, Löwe AL, Christen M, Wang WP, Jung EM, Mohaupt MG, Dietrich CF. VueBox® for quantitative analysis of contrast-enhanced ultrasound in liver tumors. Clin Hemorheol Microcirc 2021; 80:473-486. [PMID: 34897079 DOI: 10.3233/ch-211261] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Dynamic contrast-enhanced ultrasound (DCE-US) enables quantification of tumor perfusion. VueBox is a platform independent external software using DICOM cine loops which objectively provides various DCE-US parameters of tumor vascularity. This review summaries its use for diagnosis and treatment monitoring of liver tumors. The existing literature provides evidence on the successful application of Vuebox based DCE-US for characterization and differential diagnosis of focal liver lesions, as well as on its use for monitoring of local ablative therapies and of modern systemic treatment in oncology.
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Affiliation(s)
- Yi Dong
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jonas B H Koch
- Department General Internal Medicine, Hirslanden Clinics Beau-Site, Salem and Permancence, Bern, Switzerland
| | - Axel L Löwe
- Department General Internal Medicine, Hirslanden Clinics Beau-Site, Salem and Permancence, Bern, Switzerland
| | - Michael Christen
- Department General Internal Medicine, Hirslanden Clinics Beau-Site, Salem and Permancence, Bern, Switzerland
| | - Wen-Ping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ernst-Michael Jung
- Department of Radiology, University Medical Center Regensburg, Regensburg, Germany
| | - Markus G Mohaupt
- Department of Medicine, Teaching Hospital General Medicine Lindenhofgruppe, Berne, Switzerland
| | - Christoph F Dietrich
- Department General Internal Medicine, Hirslanden Clinics Beau-Site, Salem and Permancence, Bern, Switzerland
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Prada F, Vetrano IG, Gennari AG, Mauri G, Martegani A, Solbiati L, Sconfienza LM, Quaia E, Kearns KN, Kalani MYS, Park MS, DiMeco F, Dietrich C. How to Perform Intra-Operative Contrast-Enhanced Ultrasound of the Brain-A WFUMB Position Paper. ULTRASOUND IN MEDICINE & BIOLOGY 2021; 47:2006-2016. [PMID: 34045096 DOI: 10.1016/j.ultrasmedbio.2021.04.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 04/11/2021] [Accepted: 04/14/2021] [Indexed: 06/12/2023]
Abstract
Intra-operative ultrasound has become a relevant imaging modality in neurosurgical procedures. While B-mode, with its intrinsic limitations, is still considered the primary ultrasound modality, intra-operative contrast-enhanced ultrasound (ioCEUS) has more recently emerged as a powerful tool in neurosurgery. Though still not used on a large scale, ioCEUS has proven its utility in defining tumor boundaries, identifying lesion vascular supply and mapping neurovascular architecture. Here we propose a step-by-step procedure for performing ioCEUS analysis of the brain, highlighting its neurosurgical applications. Moreover, we provide practical advice on the use of ultrasound contrast agents and review technical ultrasound parameters influencing ioCEUS imaging.
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Affiliation(s)
- Francesco Prada
- Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy; Department of Neurological Surgery, University of Virginia Health Science Center, Charlottesville, VA, USA; Focused Ultrasound Foundation, Charlottesville, VA, USA.
| | - Ignazio G Vetrano
- Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Antonio G Gennari
- Department of Neuropediatrics, MR Research Center, University Children's Hospital, Zurich, Switzerland
| | - Giovanni Mauri
- Division of Interventional Radiology, European Institute of Oncology IRCCS, Milan, Italy
| | | | - Luigi Solbiati
- Division of Radiology, Humanitas Research Hospital, Rozzano, Italy
| | | | - Emilio Quaia
- Radiology Institute, Department of Medicine-DIMED, University of Padova, Padova, Italy
| | - Kathryn N Kearns
- Department of Neurological Surgery, University of Virginia Health Science Center, Charlottesville, VA, USA
| | - M Yashar S Kalani
- University of Oklahoma School of Medicine, St. John's Neuroscience Institute, Tulsa, OK, USA
| | - Min S Park
- Department of Neurological Surgery, University of Virginia Health Science Center, Charlottesville, VA, USA
| | - Francesco DiMeco
- Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurological Surgery, Johns Hopkins Medical School, Baltimore, MD, USA
| | - Christoph Dietrich
- Department of Internal Medicine, Caritas Krankenhaus Bad Mergentheim, Bern, Switzerland
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Quantitative analysis of in-vivo microbubble distribution in the human brain. Sci Rep 2021; 11:11797. [PMID: 34083642 PMCID: PMC8175375 DOI: 10.1038/s41598-021-91252-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 05/21/2021] [Indexed: 02/04/2023] Open
Abstract
Microbubbles (MB) are widely used as contrast agents to perform contrast-enhanced ultrasound (CEUS) imaging and as acoustic amplifiers of mechanical bioeffects incited by therapeutic-level ultrasound. The distribution of MBs in the brain is not yet fully understood, thereby limiting intra-operative CEUS guidance or MB-based FUS treatments. In this paper we describe a robust platform for quantification of MB distribution in the human brain, allowing to quantitatively discriminate between tumoral and normal brain tissues and we provide new information regarding real-time cerebral MBs distribution. Intraoperative CEUS imaging was performed during surgical tumor resection using an ultrasound machine (MyLab Twice, Esaote, Italy) equipped with a multifrequency (3-11 MHz) linear array probe (LA332) and a specific low mechanical index (MI < 0.4) CEUS algorithm (CnTi, Esaote, Italy; section thickness, 0.245 cm) for non-destructive continuous MBs imaging. CEUS acquisition is started by enabling the CnTI PEN-M algorithm automatically setting the MI at 0.4 with a center frequency of 2.94 MHz-10 Hz frame rate at 80 mm-allowing for continuous non-destructive MBs imaging. 19 ultrasound image sets of adequate length were selected and retrospectively analyzed using a custom image processing software for quantitative analysis of echo power. Regions of interest (ROIs) were drawn on key structures (artery-tumor-white matter) by a blinded neurosurgeon, following which peak enhancement and time intensity curves (TICs) were quantified. CEUS images revealed clear qualitative differences in MB distribution: arteries showed the earliest and highest enhancement among all structures, followed by tumor and white matter regions, respectively. The custom software built for quantitative analysis effectively captured these differences. Quantified peak intensities showed regions containing artery, tumor or white matter structures having an average MB intensity of 0.584, 0.436 and 0.175 units, respectively. Moreover, the normalized area under TICs revealed the time of flight for MB to be significantly lower in brain tissue as compared with tumor tissue. Significant heterogeneities in TICs were also observed within different regions of the same brain lesion. In this study, we provide the most comprehensive strategy for accurate quantitative analysis of MBs distribution in the human brain by means of CEUS intraoperative imaging. Furthermore our results demonstrate that CEUS imaging quantitative analysis enables discernment between different types of brain tumors as well as regions and structures within the brain. Similar considerations will be important for the planning and implementation of MB-based imaging or treatments in the future.
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