Nano Lett.: Ultrasound-responsive Conversion of Microbubbles to Nanoparticles to Enable Background-free in vivo Photoacoustic Imaging

time:2019-12-14Hits:91设置

Title:

Ultrasound-responsive Conversion of Microbubbles to Nanoparticles to Enable Background-free in vivo Photoacoustic Imaging

Authors:

Zhouqi Meng, Xuanfang Zhou, Jialin She, Yaojia Zhang, Liangzhu Feng, and Zhuang Liu*

Institutions:

Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu, 215123, China.

Abstract:

Photoacoustic (PA) imaging based on the photon-to-ultrasound conversion allows imaging of optical absorbers in deep tissues with high spatial resolution. However, the inherent optical absorbance of biomolecules (e.g. hemoglobin, melanin, etc.) would show up as tissue background signals to interfere in signals from the contrast agent during in vivo PA imaging, limiting the imaging sensitivity. Herein, an ultrasound (US)-responsive PA imaging probe based on microbubbles (MBs) containing gold nanoparticles (Au NPs) is designed for in vivo ‘background free’ PA imaging. The obtained Au@lip MBs with separated Au NPs decorated within the lipid shell of MBs show low PA signals under near-infrared (NIR) excitation. Interestingly, under exposure to US pulses, those Au@lip MBs would burst to form nanoscale aggregates of Au@lip NPs, which exhibit significantly enhanced NIR PA signals due to their red-shifted surface plasmon resonance. Therefore, by subtracting the PA image captured pre-US-burst from that post-US-burst, the tissue background PA signals could be deducted to enable background-free PA imaging with high sensitivities as demonstrated by multiple ex vivo and in vivo experiments. This work presents a simple yet effective strategy to deduct background signals during PA imaging, promising for accurate PA detection of targets in tissues with strong background.

IF:

12.279

Link:

https://pubs.acs.org/doi/abs/10.1021/acs.nanolett.9b03331


Editor:Wenchang Zhu

  


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