Transformation: (Vol 1 small volumes) (DA Shadow Phantom)
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Sample Chapter Oct 04, Provide feedback about this page. There's a problem loading this menu right now. Get fast, free shipping with Amazon Prime. Get to Know Us. English Choose a language for shopping. DLS-OCT measurement of the velocity and diffusion coefficient was further validated through phantom experiments. In order to verify measurement of the flow velocity, a piezoelectrically actuated static sample was used to simulate axial movements of particles while transverse movements were implemented by galvanometric lateral scanning of OCT beam.
As a result, the absolute and axial velocities were reliably measured across various true velocities and flow angles Fig. Microsphere samples of 0.
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For this phantom experiment, monodisperse polystyrene microspheres in 2. The gray line in B shows the Einstein-Stokes equation. The horizontal error bar in A resulted from the variation in the piezoelectric actuation. The 4D space and time complex-valued field reflectivity of the sample was obtained, and then was used to produce the 4D space and timelag autocorrelation function data.
The spatial averaging of the autocorrelation function is based on the assumption that the initial position of the particles will vary across the neighboring voxels whereas their dynamics will be similar. For this assumption to be as valid as possible, we chose the scanning step size slightly smaller than the conventional Nyquist sampling frequency. Analysis of the 4D autocorrelation function data led to 3D maps of the transverse and axial velocities, the diffusion coefficient, and the coefficient of determination R 2.
The axial velocity map showed the axial component of the flow velocity, which looked very similar to conventional Doppler OCT images. The flow direction determined by the axial and transverse velocities agreed with the structural direction of vessels. This agreement between the structural and flow direction can be more clearly seen in the cross-sectional maps Fig.
A The first image presents the maximum projection MP of the 3D map of the absolute velocity along the depth i. The images with the green boundary show the MP of absolute velocity and the SMP of the axial velocity along the transverse direction i. B The first image presents the en face MP of the 3D map of the diffusion coefficient. In the second image, the diffusion image yellow is overlaid with the absolute velocity image red. The 3X magnified images of the cyan boxes are presented to clearly show the characteristic dynamics of the vessel boundaries.
This merged image is presented with smaller ranges of the velocity and diffusion coefficient for higher contrast. D Examples of the autocorrelation function are presented for three voxels cyan crosses that are located in the plane indicated as the cyan box in C. The bottom row shows decay of the M F -terms. When the diffusion map is overlaid with the absolute velocity map Fig. Interestingly, the vessel boundaries also exhibited a characteristic low coefficient of determination Fig.
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Single-plane images clearly showed the result that the vessel boundaries exhibit high diffusion, low velocity, and low R 2. At the circular cross-sections of the vessels Fig. In particular, the low R 2 means that the motion was neither translational nor diffusive; we hypothesize that it might be oscillatory due to the interaction between blood flow and the tension of vessel walls. As can be seen in the examples of the autocorrelation functions Fig. When the voxel is located at the vessel boundary, it exhibited the characteristic dynamics with a low R 2 i.
As the present paper focuses on describing this new technique, a detailed interpretation of the brain imaging data will be described elsewhere. As for the application to blood flow imaging, laser Doppler flowmetry is used to measure blood flow at a fixed point [ 19 , 20 ], and its imaging corollary provides the 2D map of blood flow [ 21 ]. Doppler OCT enables 3D imaging of the axial flow velocity with microscopic resolution [ 22 ]. Compared to these techniques, DLS-OCT can simultaneously and independently measure the axial and transverse components of the flow velocity.
The R 2 map quantitatively images the degree of how much the motion is close to translational or diffusive ones; and for example it clearly revealed characteristic dynamics of the vessel boundaries. The M F map will quantify the fraction of moving particles in each voxel, which is similar to the mobile fraction suggested in non-ergodic DLS studies [ 10 , 11 ]. The velocity-dependent decay term is similar to that predicted in the study of the effect of the finite sample volume on DLS analysis [ 7 — 9 ], although the autocorrelation function in our theory was directly derived from the OCT signal whereas the finite size of the sample volume in the literature resulted from the illuminating and collecting optics.
The combined diffusion-oriented and flow-oriented decay terms were similarly introduced in the study of DLS where diffusion and flow are mixed [ 12 ]. Therefore, our theory can be understood as a mathematical combination of the phase-resolved OCT signal, the finite sample volume DLS model, the non-ergodic DLS model, and the model for the mixture of diffusion and flow.
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The validity of this assumption will depend on the measurement time and the magnitude of dynamics within a sample. When we used a longer measurement time ms , the autocorrelation function deviated from our model. In contrast, the fitting result was not reliable if only very short correlation times were used. Therefore, the correlation and measurement times for DLS-OCT imaging should be chosen carefully, taking into account both the scale of target dynamics and the fitting performance.
This study used the DLS-OCT theory for distinguishing whether the motion is translational or diffusive, not for measuring the mixture of the two motions. Nevertheless, the model seems to be able to measure the mixture of translational and diffusive motions. It was reported, however, that the diffusion is estimated inaccurately when mixed with large flow [ 12 ]. In this study, the relative magnitudes of flow and diffusion can be estimated based on how much they contribute to the decay in the autocorrelation function.
The coupling between diffusion and large flow will not be a critical problem in the studies investigating a sample where diffusion and flow are spatially separated. Meanwhile, considerable caution would be required if one wants to apply the present technique to the measurement of diffusion that is mixed with large flow within the resolution volume. On the other hand, the voxels with large blood flow in vessels often exhibited high diffusion, which can be either a real diffusive motion or decorrelation of the OCT signal that can be quantified by the exponential decay with the diffusion coefficient.
This high diffusion in vessels might be attributed to the mixture of non-translational motion of red blood cells including rotation, turbulence in blood flow, and the variance in the velocity distribution within the resolution volume. Since this interpretation has not been yet validated, and since the present study used the DLS-OCT theory for determining whether the motion is translational or not, we overlaid the diffusion map with the velocity map as in Figs.
Dynamic light scattering optical coherence tomography
This overlay means that our analysis gave priority to flow over diffusion so that diffusion is of interest only at the voxels with low flow. Therefore, the coupling between diffusion and large flow was not an important concern at those vessel boundaries. OCT uses coherence gating to collect light only scattered from the resolution volume and is known to effectively exclude multiply scattered photons [ 23 ]. However, strong multiple scattering can give rise to a distortion in the OCT signal, which often causes an undesired shadow of large vessels [ 13 ]. This multiple scattering also affected DLS-OCT estimation of dynamics at the voxels located beneath the surface vessels.
This effect can be seen clearly by comparing the merged images in Fig. High velocity and diffusion appeared in the shadow of the large surface vessels as shown in the single-plane image. This multiple scattering effect also can be found in the cross-section image of the velocity map of Fig. Although this multiple scattering would not cause a serious problem as one may generally build an en face image by including surface vessels as in Fig.
Future theoretical efforts should consider the possibility of measuring a mixture of translational and diffusive motions, and the effect of multiple scattering. Although there can be various modified versions of the DLS-OCT theory, the one described here will work well for 3D imaging of dynamics in a highly heterogeneous sample where static and moving particles can be mixed within the micrometer-scale resolution volume and the moving particles can exhibit either diffusion or flow, as long as it is used in the single-scattering regime.
We demonstrated a technique based on the integration of DLS and OCT for high-resolution 3D imaging of heterogeneous diffusion and flow. A theory for this purpose was proposed and validated with numerical simulations and phantom experiments. The DLS-OCT theory enabled us to simultaneously measure the axial and transverse velocities and the diffusion coefficient with the micrometer-scale resolution.
Editorial Reviews. About the Author. Nicole Hubbard and Elizabeth Stottlemyer wrote DA Transformation: (Vol 1 small volumes) (DA Shadow Phantom) - Kindle edition by Nicole Hubbard, Elizabeth Stottlemyer. Download it once and read it. Nicole Hubbard and Elizabeth Stottlemyer wrote DA Shadow Phantom right out of college. At first it was a way to keep in touch, branching from a short story, and .
We tested the utility of this technique by applying it to 3D in vivo imaging of translational blood flow and non-translational motion of the vessel boundary in the living animal brain cortex. Learn more about Kindle MatchBook. Kindle Cloud Reader Read instantly in your browser. Product details File Size: November 4, Sold by: Share your thoughts with other customers. Write a customer review. Showing of 2 reviews. Top Reviews Most recent Top Reviews.
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