High-fidelity deep functional photoacoustic tomography enhanced by virtual point sources

Yuqi Tang, Shanshan Tang, Chengwu Huang, Paul Klippel, Chenshuo Ma, Nathan Caso, Shigao Chen, Yun Jing, Junjie Yao

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Photoacoustic tomography (PAT), a hybrid imaging modality that acoustically detects the optical absorption contrast, is a promising technology for imaging hemodynamic functions in deep tissues far beyond the traditional optical microscopy. However, the most clinically compatible PAT often suffers from the poor image fidelity, mostly due to the limited detection view of the linear ultrasound transducer array. PAT can be improved by employing highly-absorbing contrast agents such as droplets and nanoparticles, which, however, have low clinical translation potential due to safety concerns and regulatory hurdles imposed by these agents. In this work, we have developed a new methodology that can fundamentally improve PAT's image fidelity without hampering any of its functional capability or clinical translation potential. By using clinically-approved microbubbles as virtual point sources that strongly and isotropically scatter the local pressure waves generated by surrounding hemoglobin, we can overcome the limited-detection-view problem and achieve high-fidelity functional PAT in deep tissues, a technology referred to as virtual-point-source PAT (VPS-PAT). We have thoroughly investigated the working principle of VPS-PAT by numerical simulations and in vitro phantom experiments, clearly showing the signal origin of VPSs and the resultant superior image fidelity over traditional PAT. We have also demonstrated in vivo applications of VPT-PAT for functional small-animal studies with physiological challenges. We expect that VPS-PAT can find broad applications in biomedical research and accelerated translation to clinical impact.

Original languageEnglish (US)
Article number100450
JournalPhotoacoustics
Volume29
DOIs
StatePublished - Feb 2023

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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