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Cited by 262

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

Novel microbubble preparation technologies

Stride, Eleanor, Edirisinghe, Mohan·2008·Soft Matter

Abstract

Gas microbubbles, stabilised by a surfactant or polymer coating, have become well established over the past 20–30 years as the most effective type of contrast agent available for ultrasound radiography. More recently, their potential for use in therapeutic applications including targeted drug delivery, gene therapy, thrombolysis and focused ultrasound surgery has also been investigated. Developments in both diagnostic and therapeutic applications have greatly increased the need for more advanced preparation technologies which provide a high degree of control over microbubble size, composition, stability and uniformity. Conventional processing techniques such as sonication and high shear emulsification offer high yield and low cost production but poor control over microbubble size and uniformity. This is being addressed by the development of new technologies, such as membrane emulsification, inkjet printing, electrohydrodynamic atomisation and microfluidic processing which offer significant improvements in terms of control over microbubble characteristics. The aim of this paper is to review the range of techniques available for microbubble preparation and how these have evolved to keep pace with advances in clinical practice.

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Crossref · 10.1039/b809517p

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Metadata

Authors
Stride, E., & Edirisinghe, M.
Venue
Soft Matter
Published
2008
Volume
4
Issue
12
Pages
2350
ISSN
  • 1744-683X (ISSN-L)
  • 1744-6848
OpenAlex
W2056760267
Cited by
262
References
43
FWCI
11.94
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Novel microbubble preparation technologies. https://app.cochat.ai/papers/10.1039/b809517p
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Stride, E., & Edirisinghe, M. (2008). Novel microbubble preparation technologies. Soft Matter. https://doi.org/10.1039/b809517p

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.