Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction

Mohamed A. Naser, Diego R.T. Sampaio, Nina M. Munoz, Cayla A. Wood, Trevor M. Mitcham, Wolfgang Stefan, Konstantin V. Sokolov, Theo Z. Pavan, Rony Avritscher, Richard R. Bouchard

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

As photoacoustic (PA) imaging makes its way into the clinic, the accuracy of PA-based metrics becomes increasingly important. To address this need, a method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed and validated to accurately estimate oxygen saturation (SO 2 ) in tissue. With data from a Vevo LAZR system, performance of our LFC approach was assessed in ex vivo blood targets (37.6%-99.6% SO 2 ) and in vivo rat arteries. Estimation error of absolute SO 2 and change in SO 2 reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while the accuracy of the LFC method was correlated with the number of wavelengths acquired. This paper demonstrates the need for an SNR-regularized LFC to accurately quantify SO 2 with PA imaging.

Original languageEnglish (US)
Article number8458163
Pages (from-to)561-571
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume38
Issue number2
DOIs
StatePublished - Feb 2019

Keywords

  • Photoacoustic imaging
  • finite element modeling
  • image reconstruction methods
  • liver
  • ultrasound

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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