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Reliability assessment for blood oxygen saturation levels measured with optoacoustic imaging

Significance: Quantitative optoacoustic (OA) imaging has the potential to provide blood oxygen saturation ([Formula: see text]) estimates due to the proportionality between the measured signal and the blood’s absorption coefficient. However, due to the wavelength-dependent attenuation of light in ti...

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Detalles Bibliográficos
Autores principales: Ulrich, Leonie, Held, Kai Gerrit, Jaeger, Michael, Frenz, Martin, Akarçay, Hidayet Günhan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7175414/
https://www.ncbi.nlm.nih.gov/pubmed/32323509
http://dx.doi.org/10.1117/1.JBO.25.4.046005
Descripción
Sumario:Significance: Quantitative optoacoustic (OA) imaging has the potential to provide blood oxygen saturation ([Formula: see text]) estimates due to the proportionality between the measured signal and the blood’s absorption coefficient. However, due to the wavelength-dependent attenuation of light in tissue, a spectral correction of the OA signals is required, and a prime challenge is the validation of both the optical characterization of the tissue and the [Formula: see text]. Aim: We propose to assess the reliability of [Formula: see text] levels retrieved from spectral fitting by measuring the similarity of OA spectra to the fitted blood absorption spectra. Approach: We introduce a metric that quantifies the trends of blood spectra by assigning a pair of spectral slopes to each spectrum. The applicability of the metric is illustrated with in vivo measurements on a human forearm. Results: We show that physiologically sound [Formula: see text] values do not necessarily imply a successful spectral correction and demonstrate how the metric can be used to distinguish [Formula: see text] values that are trustworthy from unreliable ones. Conclusions: The metric is independent of the methods used for the OA data acquisition, image reconstruction, and spectral correction, thus it can be readily combined with existing approaches, in order to monitor the accuracy of quantitative OA imaging.