Dynamic light scattering imaging

Analysis of peripheral arterial disease (PAD) patients by laser speckle measurement techniques

Diabetic foot is a well-known problem among patients suffering from peripheral arterial diseases (PAD). This article presents an optical sensor for contactless measurement of the anatomical site based on laser speckle techniques. The sensor illuminates the inspected tissue and analyzes the captured back-reflected light from the time-changing speckle patterns. An occlusion test was implemented to provide a statistical parameter to differentiate between a low perfused and a healthy foot. A clinical study of 15 subjects was conducted. The video was analyzed by two methods: dynamic laser speckle (DLS) and laser speckle contrast analysis (LASCA). Data analysis included several classification models, where the KNN model exhibited maximum performance. These findings suggest that a simple and inexpensive system for PAD monitoring can be designed for home use and/or in community clinics.

Separating single- and multiple-scattering components in laser speckle contrast imaging of tissue blood flow

Random matrix theory provides new insights into multiple scattering in random media. In a recent study, we demonstrated the statistical separation of single- and multiple-scattering components based on a Wishart random matrix. The first- and second-order moments were estimated with a Wishart random matrix constructed using dynamically backscattered speckle images. In this study, this new strategy was applied to laser speckle contrast imaging (LSCI) of in vivo blood flow. The random matrix-based method was adopted and parameterized using electric field Monte Carlo simulations and in vitro blood flow phantom experiments. The new method was further applied to in vivo experiments, demonstrating the benefits of separating the single- and multiple-scattering components, and the method was compared with the traditional temporal laser speckle contrast analysis (LASCA) method. More specifically, the new method separates the stimulus-induced functional changes in blood flow and tissue perfusion in the superficial (<2l t , l t is the transport mean free path) and deep layers (1l t  ∼ 7l t ), extending LSCI to the evaluation of functional and pathological changes.

Dynamic speckle imaging of human skin vasculature with a high-speed camera

We demonstrate the ability of high-speed acquisition (up to 30 kHz) of dynamic speckle to provide images of the human vascularization at various scales. A comparative study involving the speckle contrast, the first term of the intensity autocorrelation function, and the zero-crossings of the field intensity is proposed, together with a proper preprocessing scheme based on image registration and filtering. Experimental results show the potential of the first term of the autocorrelation function to provide efficient model-free mapping of the microvascular activity (i.e. small-scale random motion associated with the presence of a vessel). With the help of this parameter, various scales of vascularization including large vessels in the wrist, microvessels in the ear and fingers, and thinner inflammatory structures are observed, which suggests the imaging abilities of this parameter are broad. The minimum acquisition time is shown to be of the order of 50 ms, demonstrating video imaging capabilities.

The Role of Plasma Extracellular Vesicles in Remote Ischemic Conditioning and Exercise-Induced Ischemic Tolerance

Ischemic conditioning and exercise have been suggested for protecting against brain ischemia-reperfusion injury. However, the endogenous protective mechanisms stimulated by these interventions remain unclear. Here, in a comprehensive translational study, we investigated the protective role of extracellular vesicles (EVs) released after remote ischemic conditioning (RIC), blood flow restricted resistance exercise (BFRRE), or high-load resistance exercise (HLRE). Blood samples were collected from human participants before and at serial time points after intervention. RIC and BFRRE plasma EVs released early after stimulation improved viability of endothelial cells subjected to oxygen-glucose deprivation. Furthermore, post-RIC EVs accumulated in the ischemic area of a stroke mouse model, and a mean decrease in infarct volume was observed for post-RIC EVs, although not reaching statistical significance. Thus, circulating EVs induced by RIC and BFRRE can mediate protection, but the in vivo and translational effects of conditioned EVs require further experimental verification.

Synthetic exposure with a CMOS camera for multiple exposure speckle imaging of blood flow

Speckle contrast imaging is an established technique to obtain relative blood flow maps over wide fields of view. A major improvement of the method relies on the acquisition of raw speckle images at different exposure times but requires simultaneous modulation of a laser pulse in duration and intensity and precise synchronization with a camera. This complex instrumentation has limited the use of multiple exposure speckle imaging. We evaluate here the use of a CMOS camera for a simplified approach based on synthetic exposure images created from the sum of successive frames acquired at a 1 ms exposure time. Both methods have been applied to evaluate controlled flows in micro-channels. The contribution of noises to the speckle contrast have been quantified and compared. Dark, readout and shot noise contributions to the total contrast remain constant for modulated exposure, while all these contributions decrease with increasing exposure time for synthetic exposure. The relative contribution of noises to speckle contrast depends on the level of illumination and the exposure time. Guidelines for flow measurements and limitations of the use of a CMOS camera with a limited frame rate for synthetic exposure acquisition scheme are discussed. The synthetic exposure method is simple to implement and should facilitate the translation of multiple exposure speckle imaging to clinical set-ups.

Modelling of the dynamic polarizability of macromolecules for single-molecule optical biosensing

The structural dynamics of macromolecules is important for most microbiological processes, from protein folding to the origins of neurodegenerative disorders. Noninvasive measurements of these dynamics are highly challenging. Recently, optical sensors have been shown to allow noninvasive time-resolved measurements of the dynamic polarizability of single-molecules. Here we introduce a method to efficiently predict the dynamic polarizability from the atomic configuration of a given macromolecule. This provides a means to connect the measured dynamic polarizability to the underlying structure of the molecule, and therefore to connect temporal measurements to structural dynamics. To illustrate the methodology we calculate the change in polarizability as a function of time based on conformations extracted from molecular dynamics simulations and using different conformations of motor proteins solved crystalographically. This allows us to quantify the magnitude of the changes in polarizablity due to thermal and functional motions.

Lens-free motion analysis via neuromorphic laser speckle imaging

Laser speckle imaging (LSI) is a powerful tool for motion analysis owing to the high sensitivity of laser speckles. Traditional LSI techniques rely on identifying changes from the sequential intensity speckle patterns, where each pixel performs synchronous measurements. However, a lot of redundant data of the static speckles without motion information in the scene will also be recorded, resulting in considerable resources consumption for data processing and storage. Moreover, the motion cues are inevitably lost during the "blind" time interval between successive frames. To tackle such challenges, we propose neuromorphic laser speckle imaging (NLSI) as an efficient alternative approach for motion analysis. Our method preserves the motion information while excluding the redundant data by exploring the use of the neuromorphic event sensor, which acquires only the relevant information of the moving parts and responds asynchronously with a much higher sampling rate. This neuromorphic data acquisition mechanism captures fast-moving objects on the order of microseconds. In the proposed NLSI method, the moving object is illuminated using a coherent light source, and the reflected high frequency laser speckle patterns are captured with a bare neuromorphic event sensor. We present the data processing strategy to analyze motion from event-based laser speckles, and the experimental results demonstrate the feasibility of our method at different motion speeds.

Dynamics of isoflurane-induced vasodilation and blood flow of cerebral vasculature revealed by multi-exposure speckle imaging

BACKGROUND

Anesthetized animal models are used extensively during neurophysiological and behavioral studies despite systemic effects from anesthesia that undermine both accurate interpretation and translation to awake human physiology. The majority of work examining the impact of anesthesia on cerebral blood flow (CBF) has been restricted to before and after measurements with limited spatial resolution.

NEW METHOD

We used multi-exposure speckle imaging (MESI), an advanced form of laser speckle contrast imaging (LSCI), to characterize the dynamics of isoflurane anesthesia induction on cerebral vasculature and blood flow in the mouse brain.

RESULTS

The large anatomical changes caused by isoflurane are depicted with wide-field imagery and video highlighting the induction of general anesthesia. Within minutes of exposure, both vessel diameter and blood flow increased drastically compared to the awake state and remained elevated for the duration of imaging. An examination of the dynamics of anesthesia induction reveals that blood flow increased faster in arteries than in veins or parenchyma regions.

COMPARISON WITH EXISTING METHODS

MESI offers robust hemodynamic measurements across large fields-of-view and high temporal resolutions sufficient for continuous visualization of cerebrovascular events featuring major changes in blood flow.

CONCLUSION

The large alterations caused by isoflurane anesthesia to the cortical vasculature and CBF are readily characterized using MESI. These changes are unrepresentative of normal physiology and provide further evidence that neuroscience experiments would benefit from transitioning to un-anesthetized awake animal models.

Transmissive-detected laser speckle contrast imaging for blood flow monitoring in thick tissue: from Monte Carlo simulation to experimental demonstration

Laser speckle contrast imaging (LSCI) is a powerful tool to monitor blood flow distribution and has been widely used in studies of microcirculation, both for animal and clinical applications. Conventionally, LSCI usually works on reflective-detected mode. However, it could provide promising temporal and spatial resolution for in vivo applications only with the assistance of various tissue windows, otherwise, the overlarge superficial static speckle would extremely limit its contrast and resolution. Here, we systematically investigated the capability of transmissive-detected LSCI (TR-LSCI) for blood flow monitoring in thick tissue. Using Monte Carlo simulation, we theoretically compared the performance of transmissive and reflective detection. It was found that the reflective-detected mode was better when the target layer was at the very surface, but the imaging quality would rapidly decrease with imaging depth, while the transmissive-detected mode could obtain a much stronger signal-to-background ratio (SBR) for thick tissue. We further proved by tissue phantom, animal, and human experiments that in a certain thickness of tissue, TR-LSCI showed remarkably better performance for thick-tissue imaging, and the imaging quality would be further improved if the use of longer wavelengths of near-infrared light. Therefore, both theoretical and experimental results demonstrate that TR-LSCI is capable of obtaining thick-tissue blood flow information and holds great potential in the field of microcirculation research.

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.

Emerging imaging methods to study whole-brain function in rodent models

In the past decade, the idea that single populations of neurons support cognition and behavior has gradually given way to the realization that connectivity matters and that complex behavior results from interactions between remote yet anatomically connected areas that form specialized networks. In parallel, innovation in brain imaging techniques has led to the availability of a broad set of imaging tools to characterize the functional organization of complex networks. However, each of these tools poses significant technical challenges and faces limitations, which require careful consideration of their underlying anatomical, physiological, and physical specificity. In this review, we focus on emerging methods for measuring spontaneous or evoked activity in the brain. We discuss methods that can measure large-scale brain activity (directly or indirectly) with a relatively high temporal resolution, from milliseconds to seconds. We further focus on methods designed for studying the mammalian brain in preclinical models, specifically in mice and rats. This field has seen a great deal of innovation in recent years, facilitated by concomitant innovation in gene-editing techniques and the possibility of more invasive recordings. This review aims to give an overview of currently available preclinical imaging methods and an outlook on future developments. This information is suitable for educational purposes and for assisting scientists in choosing the appropriate method for their own research question.

Simulation of statistically accurate time-integrated dynamic speckle patterns in biomedical optics

The simulation of statistically accurate time-integrated dynamic speckle patterns using a physics-based model that accounts for spatially varying sample properties is yet to be presented in biomedical optics. In this Letter, we propose a solution to this important problem based on the Karhunen-Loève expansion of the electric field and apply our method to the formalisms of both laser speckle contrast imaging and diffuse correlation spectroscopy. We validate our technique against solutions for speckle contrast for different forms of homogeneous field and also show that our method can readily be extended to cases with spatially varying sample properties.

Ensemble averaging laser speckle contrast imaging: statistical model of improvement as function of static scatterers

The appearance of the common artifacts of laser speckle contrast imaging (LSCI), namely the granularity in flow rate estimation caused by static scatterers, is a well-known phenomenon. This artifact can be greatly reduced in spatial speckle contrast calculation using interframe decorrelated illumination, forcing true ensemble averaging. We propose a statistical model, which describes the effect of multiple image acquisitions on the contrast map quality when the illumination stable and when the illumination is decorrelated frame by frame. We investigate the improvement as a function of the ratio of dynamic and static scatterers by formulating a statistical distribution based model, using in simulation, flow phantom and in vivo experiments. Our main finding is that the ensemble averaging yields limited improvement in several practical cases due to the highly heterogeneous scatterer structure of living tissues.

High-dynamic-range blood flow rate measurement in a large-diameter vessel

We propose a new, to the best of our knowledge, compound technique to measure high-dynamic-range blood flow rate in a large-diameter vessel, which combines the dynamic scattering light (DLS) and the laser speckle contrast imaging (LSCI) methods, possessing the advantages of the high temporal resolution of DLS and the robust property of LSCI. By controlling the second-order spatial correlations of the laser speckle through two imaging systems, the speckle temporal intensity autocorrelation function g²(t) and the decorrelation time τ_c are directly measured using a high-speed camera. It turns out the enhanced spatial second-order correlation helps to measure the blood flow with higher dynamic range and that the measured parameter β and the blood flow dynamics n were accurately determined. For further improvement the dynamic range, the modified LSCI method was adopted, and the decorrelation time as a function of blood flow rate was constructed. It reveals the feasibility of measuring the high flow rate in large-diameter vessels and provides significant guidance for the future biomedical study of the myocardial perfusion in coronary artery bypass grafting, ghost imaging, and ghost cytometry.

Choosing a model for laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a real-time full-field non-invasive technique, which is broadly applied to visualize blood flow in biomedical applications. In its foundation is the link between the speckle contrast and dynamics of light scattering particles-erythrocytes. The mathematical form describing this relationship, which is critical for accurate blood flow estimation, depends on the sample's light-scattering properties. However, in biological applications, these properties are often unknown, thus requiring assumptions to be made to perform LSCI analysis. Here, we review the most critical assumptions in the LSCI theory and simulate how they affect blood flow estimation accuracy. We show that the most commonly applied model can severely underestimate the flow change, particularly when imaging brain parenchyma or other capillary perfused tissue (e.g. skin) under ischemic conditions. Based on these observations and guided by the recent experimental results, we propose an alternative model that allows measuring blood flow changes with higher accuracy.

Tubuloglomerular Feedback Synchronization in Nephrovascular Networks

To perform their functions, the kidneys maintain stable blood perfusion in the face of fluctuations in systemic BP. This is done through autoregulation of blood flow by the generic myogenic response and the kidney-specific tubuloglomerular feedback (TGF) mechanism. The central theme of this paper is that, to achieve autoregulation, nephrons do not work as single units to manage their individual blood flows, but rather communicate electrically over long distances to other nephrons via the vascular tree. Accordingly, we define the nephrovascular unit (NVU) to be a structure consisting of the nephron, glomerulus, afferent arteriole, and efferent arteriole. We discuss features that require and enable distributed autoregulation mediated by TGF across the kidney. These features include the highly variable topology of the renal vasculature which creates variability in circulation and the potential for mismatch between tubular oxygen demand and delivery; the self-sustained oscillations in each NVU arising from the autoregulatory mechanisms; and the presence of extensive gap junctions formed by connexins and their properties that enable long-distance transmission of TGF signals. The existence of TGF synchronization across the renal microvascular network enables an understanding of how NVUs optimize oxygenation-perfusion matching while preventing transmission of high systemic pressure to the glomeruli, which could lead to progressive glomerular and vascular injury.

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.

Time varied illumination laser speckle contrast imaging

Laser speckle contrast imaging is a technique to determine blood flow rate with a limitation of low dynamic range. In this Letter, we introduce a varied illumination speckle contrast imaging method. It utilizes varying illumination during exposure to customize the correlation time (flow rate) to speckle contrast relation. The method can cover an order of magnitude larger range flow rate in a single exposure compared to constant illumination methods. The proposed method enables high dynamic range flow rate imaging, which is advantageous in studying larger vessels and small arteries. We demonstrate the theory by simulations and ex vivo and in vivo measurements.