Improving the estimation of flow speed for laser speckle imaging with single exposure time

Dual-exposure temporal laser speckle imaging for simultaneously accessing microvascular blood perfusion and angiography

Laser speckle contrast imaging (LSCI) has gained significant attention in the biomedical field for its ability to map the spatio-temporal dynamics of blood perfusion in vivo. However, LSCI faces difficulties in accurately resolving blood perfusion in microvessels. Although the transmissive detecting geometry can improve the spatial resolution of tissue imaging, ballistic photons directly transmitting forward through tissue without scattering will cause misestimating in the flow speed by LSCI because of the lack of a quantitative theoretical model of transmissvie LSCI. Here, we develop a model of temporal LSCI which accounts for the effect of nonscattered light on estimating decorrelation time. Based on this model, we further propose a dual-exposure temporal laser speckle imaging method (dEtLSCI) to correct the overestimation of background speed when performing traditional transmissive LSCI, and reconstruct microvascular angiography using the scattered component extracted from total transmitted light. Experimental results demonstrated that our new method opens an opportunity for LSCI to simultaneously resolve the blood vessels morphology and blood flow speed at microvascular level in various contexts, ranging from the drug-induced vascular response to angiogenesis and the blood perfusion monitoring during tumor growth.

Quasi-analytic solution for real-time multi-exposure speckle imaging of tissue perfusion

Laser speckle contrast imaging (LSCI) is a widefield imaging technique that enables high spatiotemporal resolution measurement of blood flow. Laser coherence, optical aberrations, and static scattering effects restrict LSCI to relative and qualitative measurements. Multi-exposure speckle imaging (MESI) is a quantitative extension of LSCI that accounts for these factors but has been limited to post-acquisition analysis due to long data processing times. Here we propose and test a real-time quasi-analytic solution to fitting MESI data, using both simulated and real-world data from a mouse model of photothrombotic stroke. This rapid estimation of multi-exposure imaging (REMI) enables processing of full-frame MESI images at up to 8 Hz with negligible errors relative to time-intensive least-squares methods. REMI opens the door to real-time, quantitative measures of perfusion change using simple optical systems.

Optical Flow-Based Full-Field Quantitative Blood-Flow Velocimetry Using Temporal Direction Filtering and Peak Interpolation

The quantitative measurement of the microvascular blood-flow velocity is critical to the early diagnosis of microvascular dysfunction, yet there are several challenges with the current quantitative flow velocity imaging techniques for the microvasculature. Optical flow analysis allows for the quantitative imaging of the blood-flow velocity with a high spatial resolution, using the variation in pixel brightness between consecutive frames to trace the motion of red blood cells. However, the traditional optical flow algorithm usually suffers from strong noise from the background tissue, and a significant underestimation of the blood-flow speed in blood vessels, due to the errors in detecting the feature points in optical images. Here, we propose a temporal direction filtering and peak interpolation optical flow method (TPIOF) to suppress the background noise, and improve the accuracy of the blood-flow velocity estimation. In vitro phantom experiments and in vivo animal experiments were performed to validate the improvements in our new method.

A quasi-analytic solution for real-time multi-exposure speckle imaging of tissue perfusion

Laser speckle contrast imaging (LSCI) is a widefield imaging technique that enables high spatiotemporal resolution measurement of blood flow. Laser coherence, optical aberrations, and static scattering effects restrict LSCI to relative and qualitative measurements. Multi-exposure speckle imaging (MESI) is a quantitative extension of LSCI that accounts for these factors but has been limited to post-acquisition analysis due to long data processing times. Here we propose and test a real-time quasi-analytic solution to fitting MESI data, using both simulated and real-world data from a mouse model of photothrombotic stroke. This rapid estimation of multi-exposure imaging (REMI) enables processing of full-frame MESI images at up to 8 Hz with negligible errors relative to time-intensive least-squares methods. REMI opens the door to real-time, quantitative measures of perfusion change using simple optical systems.

Correcting sampling bias in speckle contrast imaging

When performing spatial or temporal laser speckle contrast imaging (LSCI), contrast is generally estimated from localized windows containing limited numbers of independent speckle grains N_S. This leads to a systematic bias in the estimated speckle contrast. We describe an approach to determine N_S and largely correct for this bias, enabling a more accurate estimation of the speckle decorrelation time without recourse to numerical fitting of data. Validation experiments are presented where measurements are ergodic or non-ergodic, including in vivo imaging of mouse brain.

Direct characterization of tissue dynamics with laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) has gained broad appeal as a technique to monitor tissue dynamics (broadly defined to include blood flow dynamics), in part because of its remarkable simplicity. When laser light is backscattered from a tissue, it produces speckle patterns that vary in time. A measure of the speckle field decorrelation time provides information about the tissue dynamics. In conventional LSCI, this measure requires numerical fitting to a specific theoretical model for the field decorrelation. However, this model may not be known a priori, or it may vary over the image field of view. We describe a method to reconstruct the speckle field decorrelation time that is completely model free, provided that the measured speckle dynamics are ergodic. We also extend our approach to allow for the possibility of non-ergodic measurements caused by the presence of a background static speckle field. In both ergodic and non-ergodic cases, our approach accurately retrieves the correlation time without any recourse to numerical fitting and is largely independent of camera exposure time. We apply our method to tissue phantom and in-vivo mouse brain imaging. Our aim is to facilitate and add robustness to LSCI processing methods for potential clinical or pre-clinical applications.

Adaptive processing for noise attenuation in laser speckle contrast imaging

BACKGROUND AND OBJECTIVE

Blood vessel visualization is an essential task to treat and evaluate diseases such as port-wine stain. Laser Speckle Contrast Imaging (LSCI) have applications in the analysis of the microvasculature. However, it is often limited to superficial depths because the tissue among skin and microvasculature introduces noise in the image. To analyze microvasculature, traditional LSCI methods compute a Contrast Image (CI) by using a shifting window of fixed size and shape, which is inadequate in images with structures different types of morphologies in it, as happens in LSCI. This work aims to reduce the noise in the CIs to improve the visualization of blood vessels at high depths (> 300 μ m).

METHODS

The proposed method processes the CIs with analysis windows that change their size and shape for each pixel to compute the contrast representation with pixels more representatives to the region.

RESULTS

We performed experiments varying the depth of the blood vessels, the number of frames required to compute the representation, and the blood flow in the blood vessel. We looked for an improvement in the Contrast to Noise Ratio (CNR) in the periphery of the blood vessels using an analysis of variance. Finding that the adaptive processing of the contrast images allows a significant noise attenuation, translated into a better visualization of blood vessels. An average CNR of 2.62 ± 1 and 5.26 ± 1.7 was reached for in-vitro and in-vivo tests respectively, which is higher in comparison with traditional LSCI approaches.

CONCLUSIONS

The results, backed by the measured CNR, obtained a noise reduction in the CIs, this means a better temporal and spatial resolution. The proposed awK method can obtain an image with better quality than the state-of-the-art methods using fewer frames.

Depth resolution in multifocus laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) can be used to evaluate blood flow based on spatial or temporal speckle statistics, but its accuracy is undermined by out-of-focus image blur. In this Letter, we show how the fraction of dynamic versus static light scattering is dependent on focus, and describe a deconvolution strategy to correct for out-of-focus blur. With the aid of a z-splitter, which enables instantaneous multifocus imaging, we demonstrate depth-resolved LSCI that can robustly extract multi-plane structural and flow-speed information simultaneously. This method is applied to in vivo imaging of blood vessels in a mouse cortex and provides improved estimates of blood flow speed throughout a depth range of 300µm.

Mixed scattering as a problem in laser speckle contrast analysis

Static scattering is detrimental to the accuracy of laser speckle contrast analysis (LASCA) measurements on skin when, instead of percentile change monitoring, absolute perfusion values are needed, e.g., for tissue injury examination. Perfusion values were calculated using two evaluation models, while changing the dynamic/static scattering ratio of monitored skin and tissue phantoms. Results were strongly affected by the significant increase of static contribution. Measurements on a modified tissue phantom showed that the changes in the measured perfusion values were mostly caused by the mixed scattering, which was omitted by the tested models. Dynamic ratio values obtained by multi-exposure LASCA could be used for perfusion data correction.

Quantitative laser speckle auto-inverse covariance imaging for robust estimation of blood flow

We present a quantitative model to provide robust estimation of the decorrelation time using laser speckle auto-inverse covariance. It has the advantages of independence from the statistical sample size, speckle size, static scattering, and detector noise. We have shown cerebral blood flow imaging through an intact mouse skull using this model. Phantom experiments and two animal models, middle cerebral artery occlusion, and cortical spreading depression were used to evaluate its performance.

Multiparameter wide-field integrated optical imaging system-based spatially modulated illumination and laser speckles in model of tissue injuries

In this report, an integrated optical platform based on spatial illumination together with laser speckle contrast technique was utilized to measure multiple parameters in live tissue including absorption, scattering, saturation, composition, metabolism, and blood flow. Measurements in three models of tissue injury including drug toxicity, artery occlusion, and acute hyperglycemia were used to test the efficacy of this system. With this hybrid apparatus, a series of structured light patterns at low and high spatial frequencies are projected onto the tissue surface and diffuse reflected light is captured by a CCD camera. A six position filter wheel, equipped with four bandpass filters centered at wavelengths of 650, 690, 800 and 880 nm is placed in front of the camera. Then, light patterns are blocked and a laser source at 650 nm illuminates the tissue while the diffusely reflected light is captured by the camera through the two remaining open holes in the wheel. In this manner, near-infrared (NIR) and laser speckle images are captured and stored together in the computer for off-line processing to reconstruct the tissue's properties. Spatial patterns are used to differentiate the effects of tissue scattering from those of absorption, allowing accurate quantification of tissue hemodynamics and morphology, while a coherent light source is used to study blood flow changes, a feature which cannot be measured with the NIR structured light. This combined configuration utilizes the strengths of each system in a complementary way, thus collecting a larger range of sample properties. In addition, once the flow and hemodynamics are measured, tissue oxygen metabolism can be calculated, a property which cannot be measured independently. Therefore, this merged platform can be considered a multiparameter wide-field imaging and spectroscopy modality. Overall, experiments demonstrate the capability of this spatially coregistered imaging setup to provide complementary, useful information of various tissue metrics in a simple and noncontact manner, making it attractive for use in a variety of biomedical applications.

Multi-exposure laser speckle contrast imaging using a video-rate multi-tap charge modulation image sensor

Multi-exposure laser speckle contrast imaging (MELSCI) systems based on high frame rate cameras are suitable for wide-field quantitative measurement of blood flow. However, high-speed camera-based MELSCI requires high power consumption, large memory, and high processing capability, which may lead to relatively large and expensive hardware. To realize a compact and cost-efficient MELSCI system, we discuss an application of the multi-tap CMOS image sensor originally designed for time-of-flight range imaging. This image sensor operated in the global shutter mode and every pixel was provided with multiple charge-storage diodes. Multiple images for different exposures were acquired simultaneously because exposure patterns were programmable to implement an arbitrary exposure duration for each tap. The frame rate was close to video frame rates (30 frames per second (fps)) regardless of the exposure pattern. The feasibility of the proposed method was verified by simulations that were performed with real speckle images captured by a high-speed camera at 40 kfps. Experiments with a four-tap CMOS image sensor demonstrated that a flow speed map was obtained at a moderate frame rate such as 35 fps for a moving ground glass plate and 45 fps for flowing Intralipose, which were linearly moved at speeds of 1-5 mm/s.

Enhancing vascular visualization in laser speckle contrast imaging of blood flow using multi-focus image fusion

Laser speckle contrast imaging (LSCI) is a full-field optical imaging method for monitoring blood flow and vascular morphology with high spatiotemporal resolution. However, due to the limited depth of field of optical system, it is difficult to capture a clear blood flow image with all blood vessels focused, especially for the non-planar biological tissues. In this study, a multi-focus image fusion method based on contourlet transform is introduced to reduce the misfocus effects in LSCI. The experimental results suggest that this method can provide an all-in-focus blood flow image, which is convenient to observe the blood vessels.

Fluctuations of temporal contrast in laser speckle imaging of blood flow

Laser speckle contrast imaging can be used to estimate changes in blood flow velocity in either the spatial or temporal domain. Temporal speckle contrast analysis provides higher spatial resolution than spatial speckle contrast does. However, owing to limitations of the statistical sample size in practical applications, the speckle contrast obtained consistently fluctuates around an accurate value. It is important to reveal the quantitative relationship between the statistical sample size and fluctuations of temporal speckle contrast. In this Letter, we present a new model for temporal speckle contrast that accounts for the effects of statistical size owing to the finite frames of the speckle images used for temporal analysis. Furthermore, an expression for estimating the fluctuations of temporal speckle contrast is derived. Both phantom and animal experiment results support our theoretical model.

Optically derived metabolic and hemodynamic parameters predict hippocampal neurogenesis in the BTBR mouse model of autism

In this study, we made use of dual-wavelength laser speckle imaging (DW-LSI) to assess cerebral blood flow (CBF) in the BTBR-genetic mouse model of autism spectrum disorder, as well as control (C57Bl/6J) mice. Since the deficits in social behavior demonstrated by BTBR mice are attributed to changes in neural tissue structure and function, we postulated that these changes can be detected optically using DW-LSI. BTBR mice demonstrated reductions in both CBF and cerebral oxygen metabolism (CMRO₂ ), as suggested by studies using conventional neuroimaging technologies to reflect impaired neuronal activation and cognitive function. To validate the monitoring of CBF by DW-LSI, measurements with laser Doppler flowmetry (LDF) were also performed which confirmed the lowered CBF in the autistic-like group. Furthermore, we found in vivo cortical CBF measurements to predict the rate of hippocampal neurogenesis, measured ex vivo by the number of neurons expressing doublecortin or the cellular proliferation marker Ki-67 in the dentate gyrus, with a strong positive correlation between CBF and neurogenesis markers (Pearson, r = 0.78; 0.9, respectively). These novel findings identifying cortical CBF as a predictive parameter of hippocampal neurogenesis highlight the power and flexibility of the DW-LSI and LDF setups for studying neurogenesis trends under normal and pathological conditions.