Mitchell A. Davis

Imaging depth and multiple scattering in laser speckle contrast imaging

Abstract. Laser speckle contrast imaging (LSCI) is a powerful and simple method for full field imaging of blood flow. However, the depth dependence and the degree of multiple scattering have not been thoroughly investigated. We employ three-dimensional Monte Carlo simulations of photon propagation combined with high resolution vascular anatomy to investigate these two issues. We found that 95% of the detected signal comes from the top 700 μm of tissue. Additionally, we observed that single-intravascular scattering is an accurate description of photon sampling dynamics, but that regions of interest (ROIs) in areas free of obvious surface vessels had fewer intravascular scattering events than ROI over resolved surface vessels. Furthermore, we observed that the local vascular anatomy can strongly affect the depth dependence of LSCI. We performed simulations over a wide range of intravascular and extravascular scattering properties to confirm the applicability of these results to LSCI imaging over a wide range of visible and near-infrared wavelengths.

Flux or speed? Examining speckle contrast imaging of vascular flows.

Speckle contrast imaging enables rapid mapping of relative blood flow distributions using camera detection of back-scattered laser light. However, speckle derived flow measures deviate from direct measurements of erythrocyte speeds by 47 ± 15% (n = 13 mice) in vessels of various calibers. Alternatively, deviations with estimates of volumetric flux are on average 91 ± 43%. We highlight and attempt to alleviate this discrepancy by accounting for the effects of multiple dynamic scattering with speckle imaging of microfluidic channels of varying sizes and then with red blood cell (RBC) tracking correlated speckle imaging of vascular flows in the cerebral cortex. By revisiting the governing dynamic light scattering models, we test the ability to predict the degree of multiple dynamic scattering across vessels in order to correct for the observed discrepancies between relative RBC speeds and multi-exposure speckle imaging estimates of inverse correlation times. The analysis reveals that traditional speckle contrast imagery of vascular flows is neither a measure of volumetric flux nor particle speed, but rather the product of speed and vessel diameter. The corrected speckle estimates of the relative RBC speeds have an average 10 ± 3% deviation in vivo with those obtained from RBC tracking.

Expanding applications, accuracy, and interpretation of laser speckle contrast imaging of cerebral blood flow

Laser speckle contrast imaging (LSCI) provides a rapid characterization of cortical flow dynamics for functional monitoring of the microcirculation. The technique stems from interactions of laser light with moving particles. These interactions encode the encountered Doppler phenomena within a random interference pattern imaged in widefield, known as laser speckle. Studies of neurovascular function and coupling with LSCI have benefited from the real-time characterization of functional dynamics in the laboratory setting through quantification of perfusion dynamics. While the technique has largely been relegated to acute small animal imaging, its scalability is being assessed and characterized for both chronic and clinical neurovascular imaging.

Sensitivity of laser speckle contrast imaging to flow perturbations in the cortex

Laser speckle contrast imaging has become a ubiquitous tool for imaging blood flow in a variety of tissues. However, due to its widefield imaging nature, the measured speckle contrast is a depth integrated quantity and interpretation of baseline values and the depth dependent sensitivity of those values to changes in underlying flow has not been thoroughly evaluated. Using dynamic light scattering Monte Carlo simulations, the sensitivity of the autocorrelation function and speckle contrast to flow changes in the cerebral cortex was extensively examined. These simulations demonstrate that the sensitivity of the inverse autocorrelation time, [Formula: see text], varies across the field of view: directly over surface vessels [Formula: see text] is strongly localized to the single vessel, while parenchymal ROIs have a larger sensitivity to flow changes at depths up to 500 μm into the tissue and up to 200 μm lateral to the ROI. It is also shown that utilizing the commonly used models the relate [Formula: see text] to flow resulted in nearly the same sensitivity to the underlying flow, but fail to accurately relate speckle contrast values to absolute [Formula: see text].

Depth dependence of vascular fluorescence imaging

In vivo surface imaging of fluorescently labeled vasculature has become a widely used tool for functional brain imaging studies. Techniques such as phosphorescence quenching for oxygen tension measurements and indocyanine green fluorescence for vessel perfusion monitoring rely on surface measurements of vascular fluorescence. However, the depth dependence of the measured fluorescence signals has not been modeled in great detail. In this paper, we investigate the depth dependence of the measured signals using a three-dimensional Monte Carlo model combined with high resolution vascular anatomy. We found that a bulk-vascularization assumption to modeling the depth dependence of the signal does not provide an accurate picture of penetration depth of the collected fluorescence signal in most cases. Instead the physical distribution of microvasculature, the degree of absorption difference between extravascular and intravascular space, and the overall difference in absorption at the excitation and emission wavelengths must be taken into account to determine the depth penetration of the fluorescence signal. Additionally, we found that using targeted illumination can provide for superior surface vessel sensitivity over wide-field illumination, with small area detection offering an even greater amount of sensitivity to surface vasculature. Depth sensitivity can be enhanced by either increasing the detector area or increasing the illumination area. Finally, we see that excitation wavelength and vessel size can affect intra-vessel sampling distribution, as well as the amount of signal that originates from inside the vessel under targeted illumination conditions.

Rapid computation of the amplitude and phase of tightly focused optical fields distorted by scattering particles

We develop an efficient method for accurately calculating the electric field of tightly focused laser beams in the presence of specific configurations of microscopic scatterers. This Huygens-Fresnel wave-based electric field superposition (HF-WEFS) method computes the amplitude and phase of the scattered electric field in excellent agreement with finite difference time-domain (FDTD) solutions of Maxwells equations. Our HF-WEFS implementation is 2-4 orders of magnitude faster than the FDTD method and enables systematic investigations of the effects of scatterer size and configuration on the focal field. We demonstrate the power of the new HF-WEFS approach by mapping several metrics of focal field distortion as a function of scatterer position. This analysis shows that the maximum focal field distortion occurs for single scatterers placed below the focal plane with an offset from the optical axis. The HF-WEFS method represents an important first step toward the development of a computational model of laser-scanning microscopy of thick cellular/tissue specimens.

Dynamic light scattering Monte Carlo: a method for simulating time-varying dynamics for ordered motion in heterogeneous media

Few methods exist that can accurately handle dynamic light scattering in the regime between single and highly multiple scattering. We demonstrate dynamic light scattering Monte Carlo (DLS-MC), a numerical method by which the electric field autocorrelation function may be calculated for arbitrary geometries if the optical properties and particle motion are known or assumed. DLS-MC requires no assumptions regarding the number of scattering events, the final form of the autocorrelation function, or the degree of correlation between scattering events. Furthermore, the method is capable of rapidly determining the effect of particle motion changes on the autocorrelation function in heterogeneous samples. We experimentally validated the method and demonstrated that the simulations match both the expected form and the experimental results. We also demonstrate the perturbation capabilities of the method by calculating the autocorrelation function of flow in a representation of mouse microvasculature and determining the sensitivity to flow changes as a function of depth.

Go with what Flow? Interpreting Speckle Contrast Imagery in the Multiple Scattering Limit

There are significant deviations between speckle contrast imaging flow measures and RBC speeds between vessels of disparate calibers. We highlight and attempt to alleviate this discrepancy by accounting for the effects of multiple dynamic scattering.

Computational modeling of STED microscopy through multiple biological cells under one- and two-photon excitation

While superresolution optical microscopy techniques afford enhanced resolution for biological applications, they have largely been used to study structures in isolated cells. We use the FDTD method to simulate the propagation of focused beams for STED microscopy through multiple biological cells. We model depletion beams that provide 2D and 3D confinement of the fluorescence spot and assess the effective PSF of the system as a function of focal depth. We compare the relative size of the STED effective PSF under one- and two-photon excitation. PSF calculations suggest that imaging is possible up to the maximum simulation depth if the fluorescence emission remains detectable.

Monte Carlo simulation of fluorescence imaging of microvasculature

Little numerical analysis has been done on in vivo vascular fluorescence imaging. Here, we use a 3D fluorescence Monte Carlo model to evaluate a microvasculature geometry obtained via two-photon microscopy. We found that a bulk-vascularization assumption does not pro- vide an accurate picture of penetration depth of the collected fluorescence signal. Instead the degree of absorption difference between extravascular and intravascular space, and the degree of stokes shift must be taken into account to determine the depth distribution. Additionally, we found that using targeted illumination can provide for superior surface vessel sensi- tivity over wide-field illumination, with small area detection offering an even greater amount of sensitivity to surface vasculature. Depth sensitivity can be enhanced by either increasing the detector area or increasing the illumination area. Finally, we see that excitation wavelength and vessel size can affect intra-vessel sampling distribution, as well as the amount of signal that originates from inside the vessel under targeted illumination conditions.