The objective of this study was to evaluate the minimum microbubble dose for ultrasound molecular imaging to achieve statistically significant detection of angiogenesis in a mouse model.
The preburst minus postburst method was implemented on a Verasonics ultrasound research scanner using a multiframe compounding pulse inversion imaging sequence. Biotinylated lipid (distearoyl phosphatidylcholine–based) microbubbles that were conjugated with antivascular endothelial growth factor 2 (VEGFR2) antibody (MBVEGFR2) or isotype control antibody (MBControl) were injected into mice carrying adenocarcinoma xenografts. Different injection doses ranging from 5 × 104 to 1 × 107 microbubbles per mouse were evaluated to determine the minimum diagnostically effective dose.
The proposed imaging sequence was able to achieve statistically significant detection (P < 0.05, n = 5) of VEGFR2 in tumors with a minimum MBVEGFR2 injection dose of only 5 × 104 microbubbles per mouse (distearoyl phosphatidylcholine at 0.053 ng/g mouse body mass). Nonspecific adhesion of MBControl at the same injection dose was negligible. In addition, the targeted contrast ultrasound signal of MBVEGFR2 decreased with lower microbubble doses, whereas nonspecific adhesion of MBControl increased with higher microbubble doses.
The dose of 5 × 104 microbubbles per animal is now the lowest injection dose on record for ultrasound molecular imaging to achieve statistically significant detection of molecular targets in vivo. Findings in this study provide us with further guidance for future developments of clinically translatable ultrasound molecular imaging applications using a lower dose of microbubbles.
From the *Department of Biomedical Engineering, †Division of Cardiovascular Medicine, Cardiovascular Research Center, and ‡Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA.
Received for publication February 28, 2016; and accepted for publication, after revision, June 5, 2016.
Conflicts of interest and sources of funding: Supported by NIH R01 EB001826, NIH R01 HL111077, and the Virginia Center for Innovative Technology Commonwealth Research Commercialization Fund Award MF14F-002-LS. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The authors report no conflicts of interest.
Correspondence to: John A. Hossack, PhD, Department of Biomedical Engineering, University of Virginia, 415 Lane Rd, MR5 Bldg, Room 2121, Charlottesville, VA 22908. E-mail: firstname.lastname@example.org.