Learned spectral decoloring enables photoacoustic oximetry.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
22 03 2021
Historique:
received: 19 10 2020
accepted: 27 01 2021
entrez: 23 3 2021
pubmed: 24 3 2021
medline: 24 3 2021
Statut: epublish

Résumé

The ability of photoacoustic imaging to measure functional tissue properties, such as blood oxygenation sO[Formula: see text], enables a wide variety of possible applications. sO[Formula: see text] can be computed from the ratio of oxyhemoglobin HbO[Formula: see text] and deoxyhemoglobin Hb, which can be distuinguished by multispectral photoacoustic imaging due to their distinct wavelength-dependent absorption. However, current methods for estimating sO[Formula: see text] yield inaccurate results in realistic settings, due to the unknown and wavelength-dependent influence of the light fluence on the signal. In this work, we propose learned spectral decoloring to enable blood oxygenation measurements to be inferred from multispectral photoacoustic imaging. The method computes sO[Formula: see text] pixel-wise, directly from initial pressure spectra [Formula: see text], which represent initial pressure values at a fixed spatial location [Formula: see text] over all recorded wavelengths [Formula: see text]. The method is compared to linear unmixing approaches, as well as pO[Formula: see text] and blood gas analysis reference measurements. Experimental results suggest that the proposed method is able to obtain sO[Formula: see text] estimates from multispectral photoacoustic measurements in silico, in vitro, and in vivo.

Identifiants

pubmed: 33753769
doi: 10.1038/s41598-021-83405-8
pii: 10.1038/s41598-021-83405-8
pmc: PMC7985523
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

6565

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Auteurs

Janek Gröhl (J)

Computer Assisted Medical Interventions, German Cancer Research Center, Heidelberg, Germany. j.groehl@dkfz.de.
Medical Faculty, Heidelberg University, Heidelberg, Germany. j.groehl@dkfz.de.

Thomas Kirchner (T)

Institute of Applied Physics, Biomedical Photonics, Bern University, Bern, Switzerland.

Tim J Adler (TJ)

Computer Assisted Medical Interventions, German Cancer Research Center, Heidelberg, Germany.
Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany.

Lina Hacker (L)

Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge, CB3 0HE, UK.

Niklas Holzwarth (N)

Computer Assisted Medical Interventions, German Cancer Research Center, Heidelberg, Germany.
Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany.

Adrián Hernández-Aguilera (A)

Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.

Mildred A Herrera (MA)

Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.

Edgar Santos (E)

Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany.

Sarah E Bohndiek (SE)

Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge, CB3 0HE, UK.
Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK.

Lena Maier-Hein (L)

Computer Assisted Medical Interventions, German Cancer Research Center, Heidelberg, Germany. l.maier-hein@dkfz.de.
Medical Faculty, Heidelberg University, Heidelberg, Germany. l.maier-hein@dkfz.de.

Classifications MeSH