Real-time measurement of in vitro flow by Fourier-domain color Doppler optical coherence tomography

Leitgeb, Rainer A.; Schmetterer, Leopold; Hitzenberger, Christoph K.; Fercher, Adolf Friedrich; Berisha, Fatma; Wojtkowski, Maciej; Bajraszewski, Tomasz

doi:10.1364/ol.29.000171

Cited by 158 publications

(88 citation statements)

References 10 publications

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“…Besides structural imaging, OCT has been used extensively for functional imaging, where blood flow imaging in living tissue is arguably one of the most important applications. Blood flow imaging methods based on OCT can be divided into two categories: angiographic methods that image the structure of the vasculature in tissue [2][3][4][5][6][7][8], and velocimetric methods measuring the velocity of red blood cells [9][10][11][12][13][14][15][16][17][18]. While the former techniques use some form of motion contrast to yield a qualitative image of blood vessels, the latter allow a quantitative estimation of the blood flow speed.…”

Section: Introductionmentioning

confidence: 99%

Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography

Bouwens¹,

Szlag²,

Szkulmowski³

et al. 2013

Opt. Express

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Optical coherence tomography (OCT) and optical coherence microscopy (OCM) allow the acquisition of quantitative three-dimensional axial flow by estimating the Doppler shift caused by moving scatterers. Measuring the velocity of red blood cells is currently the principal application of these methods. In many biological tissues, blood flow is often perpendicular to the optical axis, creating the need for a quantitative measurement of lateral flow. Previous work has shown that lateral flow can be measured from the Doppler bandwidth, albeit only for simplified optical systems. In this work, we present a generalized model to analyze the influence of relevant OCT/OCM system parameters such as light source spectrum, numerical aperture and beam geometry on the Doppler spectrum. Our analysis results in a general framework relating the mean and variance of the Doppler frequency to the axial and lateral flow velocity components. Based on this model, we present an optimized acquisition protocol and algorithm to reconstruct quantitative measurements of lateral and axial flow from the Doppler spectrum for any given OCT/OCM system. To validate this approach, Doppler spectrum analysis is employed to quantitatively measure flow in a capillary with both extended focus OCM and OCT.

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Section: Introductionmentioning

confidence: 99%

Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography

Bouwens¹,

Szlag²,

Szkulmowski³

et al. 2013

Opt. Express

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“…Weiterhin zeigen die Bilder 4 und 5 eine Phasenverschiebung der stationären inneren und äußeren Gefäßrückwand der Glaskapillare (Bild 4: weiße Pfeile, Bild 5: schwarzer Pfeil). In einer früheren Publikation [15] wurde dieser Effekt bereits beobachtet und muss in weiteren Untersuchungen genau analysiert werden.…”

Section: In-vivo-mausmodellunclassified

Quantifizierung von Flussgeschwindigkeiten mit dem Verfahren der Fourier Domain Optische KohärenztomografieFlow Velocity Quantification with Fourier Domain Optical Coherence Tomography

Walther¹,

Müller

Morawietz

et al. 2009

Tm - Technisches Messen

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In dieser Studie werden zwei Methoden der Flussmessung, basierend auf dem Verfahren der Fourier Domain Optische Kohärenztomografie (FD OCT) vorgestellt. Das erste Verfahren beruht auf der Analyse der Phasenverschiebung zwischen konsekutiven Tiefensignalen durch axial bewegte Strukturen. Mit der zweiten Methode besteht die Möglichkeit höhere Geschwindigkeiten über den Signalabfall, hervorgerufen durch schnell bewegte Streuzentren, zu bestimmen.Schlagwörter: Optische Kohärenztomografie, Doppler, Signalabfall, Flussmessung Flow Velocity Quantification with Fourier Domain Optical Coherence TomographyIn this study, two methods of flow measurement based on optical coherence tomography are presented. The first technique determines the phase differences between consecutive depth profiles due to axial moving scatterers. The second one has the potential to ascertain higher velocities by using the signal power decrease caused by fast moving structures.

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“…Several OCTA algorithms have been developed and they could be based on phase [5][6][7][8], intensity [9][10][11][12], and complex value [13]. Among the OCTA algorithms, we developed an algorithm named split-spectrum amplitude-decorrelation angiography (SSADA) [12], which splits the spectrum into several spectral bands and calculates the decorrelation between two successive B-scans at the same position for each band.…”

Section: Introductionmentioning

confidence: 99%

Hematocrit dependence of flow signal in optical coherence tomography angiography

Yang¹,

Su²,

Wang³

et al. 2017

Biomed. Opt. Express

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Abstract:The hematocrit dependence of flow signal (split-spectrum amplitude decorrelation angiography-SSADA decorrelation value) was investigated in this paper. Based on the normalized field temporal correlation function and concentration dependent particle scattering properties, the relationship between hematocrit and flow signal was analytically derived. Experimental verification of the relationship was performed with custom-designed microfluidic chips and human blood with 45%, 40% and 32% hematocrit. It was found that, in large flow channels and blood vessels, the normal hematocrit is near the decorrelation saturation point and therefore a change in hematocrit has little effect on the SSADA decorrelation value (flow signal). However, in narrow channels in the capillary size range, the effective hematocrit (adjusted for the overlap between OCT beam and channel) is in the range of 6.7-9.5% and therefore variation in hematocrit does significantly affect the flow signal.

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Real-time measurement of in vitro flow by Fourier-domain color Doppler optical coherence tomography

Cited by 158 publications

References 10 publications

Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography

Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography

Quantifizierung von Flussgeschwindigkeiten mit dem Verfahren der Fourier Domain Optische KohärenztomografieFlow Velocity Quantification with Fourier Domain Optical Coherence Tomography

Hematocrit dependence of flow signal in optical coherence tomography angiography

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