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Yang, H. ; Olefir, I. ; Tzoumas, S.* ; Ntziachristos, V.

Synthetic data framework to estimate the minimum detectable concentration of contrast agents for multispectral optoacoustic imaging of small animals.

J. Biophotonics 12:e201900021 (2019)
Postprint Research data DOI PMC
Open Access Green
The concentrations of contrast agents for optoacoustic imaging of small animals must usually be optimized through extensive pilot experiments on a case-by-case basis. The present work describes a streamlined approach for determining the minimum detectable concentration (MDC) of a contrast agent given experimental conditions and imaging system parameters. The developed Synthetic Data Framework (SDF) allows estimation of MDCs of various contrast agents under different tissue conditions without extensive animal experiments. The SDF combines simulated optoacoustic signals from exogenously administered contrast agents with in vivo experimental signals from background tissue to generate realistic synthetic multispectral optoacoustic images. In this paper, the SDF is validated with in vivo measurements and demonstrates close agreement between SDF synthetic data and experimental data in terms of both image intensity and MDCs. Use of the SDF to estimate MDCs for fluorescent dyes and nanoparticles at different tissue depths and for imaging lesions of different sizes is illustrated.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Detection Limit ; Mdc ; Molecular Sensitivity ; Optoacoustic ; Photoacoustic Imaging ; Spectral Unmixing; Sensitivity; Tomography; Tissue
Language english
Publication Year 2019
HGF-reported in Year 2019
ISSN (print) / ISBN 1864-063X
e-ISSN 1864-0648
Quellenangaben Volume: 12, Issue: 8, Pages: , Article Number: e201900021 Supplement: ,
Publisher Wiley
Publishing Place Postfach 101161, 69451 Weinheim, Germany
Reviewing status Peer reviewed
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-505500-001
Scopus ID 85065288941
PubMed ID 30891932
Erfassungsdatum 2019-03-27