Motion Rejection and Spectral Unmixing for Accurate Estimation of In Vivo Oxygen Saturation Using Multispectral Optoacoustic Tomography

Multispectral optoacoustic tomography (MSOT) uniquely enables spatial mapping in high resolution of oxygen saturation (SO2), with potential applications in studying pathological complications and therapy efficacy. MSOT offers seamless integration with ultrasonography, by using a common ultrasound (U...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on ultrasonics, ferroelectrics, and frequency control. - 1986. - 70(2023), 12 vom: 07. Dez., Seite 1671-1681
1. Verfasser: Sarkar, Mitradeep (VerfasserIn)
Weitere Verfasser: Perez-Liva, Mailyn, Renault, Gilles, Tavitian, Bertrand, Gateau, Jerome
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2023
Zugriff auf das übergeordnete Werk:IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
LEADER 01000caa a22002652 4500
001 NLM36102178X
003 DE-627
005 20250106231836.0
007 cr uuu---uuuuu
008 231226s2023 xx |||||o 00| ||eng c
024 7 |a 10.1109/TUFFC.2023.3306592  |2 doi 
028 5 2 |a pubmed24n1655.xml 
035 |a (DE-627)NLM36102178X 
035 |a (NLM)37603493 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Sarkar, Mitradeep  |e verfasserin  |4 aut 
245 1 0 |a Motion Rejection and Spectral Unmixing for Accurate Estimation of In Vivo Oxygen Saturation Using Multispectral Optoacoustic Tomography 
264 1 |c 2023 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 16.12.2023 
500 |a Date Revised 06.01.2025 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a Multispectral optoacoustic tomography (MSOT) uniquely enables spatial mapping in high resolution of oxygen saturation (SO2), with potential applications in studying pathological complications and therapy efficacy. MSOT offers seamless integration with ultrasonography, by using a common ultrasound (US) detector array. However, MSOT relies on multiple successive acquisitions of optoacoustic (OA) images at different optical wavelengths and the low frame rate of OA imaging makes the MSOT acquisition sensitive to body/respiratory motion. Moreover, the estimation of SO2 is highly sensitive to noise, and artifacts related to the respiratory motion of the animal were identified as the primary source of noise in MSOT. In this work, we propose a two-step image processing method for SO2 estimation in deep tissues. First, to mitigate motion artifacts, we propose a method of selection of OA images acquired only during the respiratory pause of the animal, using ultrafast ultrasound (US) images acquired immediately after each OA acquisition (US image acquisition duration of 1.4 ms and a total delay of 7 ms). We show that gating is more effective using US images than OA images at different optical wavelengths. Second, we propose a novel method that can estimate directly the SO2 value of a pixel and at the same time evaluate the amount of noise present in that pixel. Hence, the method can efficiently eliminate the pixels dominated by noise from the final SO2 map. Our postprocessing method is shown to outperform conventional methods for SO2 estimation, and the method was validated by in vivo oxygen challenge experiments 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Perez-Liva, Mailyn  |e verfasserin  |4 aut 
700 1 |a Renault, Gilles  |e verfasserin  |4 aut 
700 1 |a Tavitian, Bertrand  |e verfasserin  |4 aut 
700 1 |a Gateau, Jerome  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on ultrasonics, ferroelectrics, and frequency control  |d 1986  |g 70(2023), 12 vom: 07. Dez., Seite 1671-1681  |w (DE-627)NLM098181017  |x 1525-8955  |7 nnns 
773 1 8 |g volume:70  |g year:2023  |g number:12  |g day:07  |g month:12  |g pages:1671-1681 
856 4 0 |u http://dx.doi.org/10.1109/TUFFC.2023.3306592  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_22 
912 |a GBV_ILN_24 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 70  |j 2023  |e 12  |b 07  |c 12  |h 1671-1681