Abstract
OBJECTIVES: The use of ultrasound imaging for cancer diagnosis and screening can be enhanced with the use of molecularly targeted microbubbles. Nonlinear imaging strategies such as pulse inversion (PI) and "contrast pulse sequences" (CPS) can be used to differentiate microbubble signal, but often fail to suppress highly echogenic tissue interfaces. This failure results in false-positive detection and potential misdiagnosis. In this study, a novel acoustic radiation force (ARF)-based approach was developed for superior microbubble signal detection. The feasibility of this technique, termed ARF decorrelation-weighted PI (ADW-PI), was demonstrated in vivo using a subcutaneous mouse tumor model. MATERIALS AND METHODS: Tumors were implanted in the hindlimb of C57BL/6 mice by subcutaneous injection of MC38 cells. Lipid-shelled microbubbles were conjugated to anti-VEGFR2 antibody and administered via bolus injection. An image sequence using ARF pulses to generate microbubble motion was combined with PI imaging on a Verasonics Vantage programmable scanner. ADW-PI images were generated by combining PI images with interframe signal decorrelation data. For comparison, CPS images of the same mouse tumor were acquired using a Siemens Sequoia clinical scanner. RESULTS: Microbubble-bound regions in the tumor interior exhibited significantly higher signal decorrelation than static tissue (n = 9, P < 0.001). The application of ARF significantly increased microbubble signal decorrelation (n = 9, P < 0.01). Using these decorrelation measurements, ADW-PI imaging demonstrated significantly improved microbubble contrast-to-tissue ratio when compared with corresponding CPS or PI images (n = 9, P < 0.001). Contrast-to-tissue ratio improved with ADW-PI by approximately 3 dB compared with PI images and 2 dB compared with CPS images. CONCLUSIONS: Acoustic radiation force can be used to generate adherent microbubble signal decorrelation without microbubble bursting. When combined with PI, measurements of the resulting microbubble signal decorrelation can be used to reconstruct images that exhibit superior suppression of highly echogenic tissue interfaces when compared with PI or CPS alone.