Dynamic light scattering imaging

Unsupervised Adaptive Deep Learning Framework for Video Denoising in Light Scattering Imaging

Light scattering is a powerful tool that has been widely applied in various scenarios, such as nanoparticle analysis, single-cell measurement, and blood flow monitoring. However, noise is always a concerning and challenging issue in light scattering imaging (LSI) due to the complexity of noise sources. In this work, a deep learning-based adaptive denoising framework has been established to explore the temporal information on LSI videos, aiming to provide an unsupervised and self-learning denoising strategy for various application scenarios of LSI. This novel framework consists of three stages: noise distribution maps for describing the characteristics of LSI noise, video denoising based on the unsupervised learning of the FastDVDNet network, and denoising effect discrimination to screen the best denoised result for further processing. The denoising performance is validated by two common LSI applications: nanoparticle analysis and label-free identification of single cells. The result shows that our method compares favorably to existing methods in suppressing the background noise and enhancing the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of LSI. Consequently, the successful analysis of both particle size distribution and cell classification can be notably improved. The proposed unsupervised adaptive denoising method is expected to offer a powerful tool toward a fully automated denoising and improved accuracy in extensive applications of LSI.

Validity of laser speckle contrast imaging for predicting wound healing potential in burns: A critical examination

BACKGROUND

Accurate assessment of burn depth is imperative for the efficacious management of burns. Although clinical assessment is commonly used, its accuracy ranges only between 50 % and 70 %. Laser Doppler imaging (LDI) is considered as a gold standard - with an accuracy exceeding 95 %, - for the objective measurement of Healing Potential (HP), HP being the output of the LDI device, as colour-coded on LDI blood flow images. Despite its proven efficacy, widespread adoption is impeded by practical challenges. Laser Speckle Contrast Imaging (LSCI) emerges as a possible alternative. This study investigated the performance and accuracy of LSCI in comparison with LDI for predicting the HP of burns; LDI was assumed to provide 'ground truth' for the assessment of HP.

METHODS

Hospitalized burn patients underwent LDI and LSCI scans between day 2 and day 5 postburn. Analysis involved selecting corresponding regions of interest (ROI) in target wounds prioritized by LDI and LSCI perspectives.

RESULTS

In 19 patients, 112 ROI within LDI-priority ranges were collected from 50 target wounds. 130 ROI within LSCI-priority ranges were collected from 52 target wounds. Positive predictive values (PPV) were low, at only 50.8 % and 68.2 % for HP14-21 and HP21, respectively, and 86.9 % for HP14.

CONCLUSION

Objective assessment by LSCI for burns is not recommended, as it fails to detect deep dermal blood flow, leading to an overestimation of burn severity and potential inadequacies in therapy.

Choice of numerical implementation of spatial contrast calculation impacts microcirculation quantitation in laser speckle contrast imaging

Significance

Laser speckle contrast imaging (LSCI) allows noninvasive imaging of microcirculation. Its scope of clinical applications is growing, yet the literature lacks a comparison of the accuracy of methods used to compute the spatial contrastK s from which the blood flow index is derived.

Aim

We aim to evaluate the impact on flow quantitation of different computational approaches used to deriveK s .

Approach

We compare numerical calculation ofK s in Python and ImageJ applied to noise-free simulated data and to experimental data acquired in vivo in anesthetized mice. The estimation of the decorrelation timeτ c , inversely proportional to the blood flow index, is carried out following two approaches: LSCI asymptotic estimation and fitting the multiple exposure speckle imaging (MESI) model toK s ( T ) .

Results

For simulation data, we found variations of up to 58% for the blood flow index in the LSCI approach. Nonlinear fitting of the MESI model was less affected with discrepancies of only a few percent. Considering experimental data, the LSCI approximation led toK s with relative differences (up to 35%) depending on the calculation methods. The noise and limited exposure time strongly limited the accuracy of the LSCI asymptotic estimation. Adjustment of the MESI model to the data led to consistent values ofτ c in the 0.05 to 1 ms range with significant variations depending on the method used to calculateK s .

Conclusions

Numerical methods used to calculateK s should be precisely acknowledged and validated against direct calculation to ensure accuracy. Uniform filter approach leads to accurateK s values and is 100 times more computationally efficient than the D i r e c t calculation. Other investigated methods lead to various levels of errors in flow index estimation using LSCI. Errors are minimized using larger kernels. MESI derivation ofτ c is not immune but less affected by such methodological biases.

Monte Carlo-based realistic simulation of optical coherence tomography angiography

Optical coherence tomography angiography (OCTA) offers unparalleled capabilities for non-invasive detection of vessels. However, the lack of accurate models for light-tissue interaction in OCTA jeopardizes the development of the techniques to further extract quantitative information from the measurements. In this manuscript, we propose a Monte Carlo (MC)-based simulation method to precisely describe the signal formation of OCTA based on the fundamental theory of light-tissue interactions. A dynamic particle-fixed model is developed to depict the spatial-temporal behaviors of the tissue phantom: the particles are initialized and fixed in specific locations with wavelength-dependent scattering cross-sections and are allowed to travel over time. We then employ a full-spectrum MC engine to faithfully simulate the formation of OCT and OCTA images. A simulation on a vessel-mimicking phantom demonstrated that speckle characteristics in OCT as well as decorrelation maps in OCTA could be successfully reproduced. We further illustrate the usefulness of our method on the quantitative OCTA by extending it to simulate the gradual saturation of decorrelation in OCTA-based velocimetry. We believe our method will serve as a valuable tool for studying OCTA theory and inspire better solutions and metrics for non-invasive flow velocity measurement.

Bessel beam optical coherence microscopy enables multiscale assessment of cerebrovascular network morphology and function

Understanding the morphology and function of large-scale cerebrovascular networks is crucial for studying brain health and disease. However, reconciling the demands for imaging on a broad scale with the precision of high-resolution volumetric microscopy has been a persistent challenge. In this study, we introduce Bessel beam optical coherence microscopy with an extended focus to capture the full cortical vascular hierarchy in mice over 1000 × 1000 × 360 μm3 field-of-view at capillary level resolution. The post-processing pipeline leverages a supervised deep learning approach for precise 3D segmentation of high-resolution angiograms, hence permitting reliable examination of microvascular structures at multiple spatial scales. Coupled with high-sensitivity Doppler optical coherence tomography, our method enables the computation of both axial and transverse blood velocity components as well as vessel-specific blood flow direction, facilitating a detailed assessment of morpho-functional characteristics across all vessel dimensions. Through graph-based analysis, we deliver insights into vascular connectivity, all the way from individual capillaries to broader network interactions, a task traditionally challenging for in vivo studies. The new imaging and analysis framework extends the frontiers of research into cerebrovascular function and neurovascular pathologies.

Full-field amplitude speckle decorrelation angiography

We propose a new simple and cost-effective optical imaging technique, full-field amplitude speckle decorrelation angiography (FASDA), capable of visualizing skin microvasculature with high resolution, and sensitive to small, superficial vessels with slow blood flow and larger, deeper vessels with faster blood flow. FASDA makes use of a laser source with limited temporal coherence, can be implemented with cameras with conventional frame rates, and does not require raster scanning. The proposed imaging technique is based on the simultaneous evaluation of two metrics: the blood flow index, a contrast-based metric used in laser speckle contrast imaging, and the adaptive speckle decorrelation index (ASDI), a new metric that we defined based on the second-order autocorrelation function that considers the limited speckle modulation that occurs in partially-coherent imaging. We demonstrate excellent delineation of small, superficial vessels with slow blood flow in skin nevi using ASDI and larger, deeper vessels with faster blood flow using BFI, providing a powerful new tool for the imaging of microvasculature with significantly lower hardware complexity and cost than other optical imaging techniques.

Tunable dynamical tissue phantom for laser speckle imaging

We introduce a novel method to design and implement a tunable dynamical tissue phantom for laser speckle-based in-vivo blood flow imaging. This approach relies on stochastic differential equations (SDE) to control a piezoelectric actuator which, upon illuminated with a laser source, generates speckles of pre-defined probability density function and auto-correlation. The validation experiments show that the phantom can generate dynamic speckles that closely replicate both surfaces as well as deep tissue blood flow for a reasonably wide range and accuracy.

Ergodic speckle contrast optical coherence tomography velocimetry of rapid blood flow

Visualizing a 3D blood flow velocity field through noninvasive imaging is crucial for analyzing hemodynamic mechanisms in areas prone to disorders. However, traditional correlation-based optical coherence tomography (OCT) velocimetry techniques have a maximum measurable flow velocity depending on the A-line rate. We presented the ergodic speckle contrast OCT (ESCOCT) to break the bottleneck in measuring the rapid blood flow velocity. It achieved a measurement of blood flow velocity ranging from 9.5 to 280 mm/s using a 100 kHz swept-source (SS) OCT based on 100 A-repeats scanning mode. Addressing the non-ergodic problem of temporal OCT signals by integrating more consecutive A-scans, ESCOCT can enable the estimation for lower velocity flows by increasing A-repeats. ESCOCT provided a wide dynamic range with no upper limit on measuring blood flow velocity with an adequate signal-to-noise ratio and improved the sensitivity and accuracy of the hemodynamic assessment.

Animal models to study cognitive impairment of chronic kidney disease

Mild cognitive impairment (MCI) is common in people with chronic kidney disease (CKD), and its prevalence increases with progressive loss of kidney function. MCI is characterized by a decline in cognitive performance greater than expected for an individual age and education level but with minimal impairment of instrumental activities of daily living. Deterioration can affect one or several cognitive domains (attention, memory, executive functions, language, and perceptual motor or social cognition). Given the increasing prevalence of kidney disease, more and more people with CKD will also develop MCI causing an enormous disease burden for these individuals, their relatives, and society. However, the underlying pathomechanisms are poorly understood, and current therapies mostly aim at supporting patients in their daily lives. This illustrates the urgent need to elucidate the pathogenesis and potential therapeutic targets and test novel therapies in appropriate preclinical models. Here, we will outline the necessary criteria for experimental modeling of cognitive disorders in CKD. We discuss the use of mice, rats, and zebrafish as model systems and present valuable techniques through which kidney function and cognitive impairment can be assessed in this setting. Our objective is to enable researchers to overcome hurdles and accelerate preclinical research aimed at improving the therapy of people with CKD and MCI.

Speckle-enabled in vivo demixing of neural activity in the mouse brain

Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.

Spatially Multiplexed Speckle on 1D Sensors for High-Speed 2D Sensing Applications

Speckle pattern-based remote vibration monitoring has recently become increasingly valuable in industrial, commercial, and medical applications. The dynamic and random nature of speckle patterns offers practical applications for imaging and measurement systems. The speckle pattern is an interference pattern generated by light scattered from a rough surface onto a remote plane. It is typically sensed using area scan cameras (2D), which are limited to framerates of 2-4 kHz and can only capture a small region of interest (ROI). In this work, we propose a technique that enables the capture of synthetic 2D speckle patterns using a 1D high-acquisition-rate sensor and a diffractive optical element (DOE) to produce image replicas. The multiple replicas are scanned by the 1D sensor simultaneously at different spatial positions. This method provides an ability to sense remote vibrations in all directions, contrary to the case with a simple 1D sensing system.

Dynamic Light Scattering in Biomedical Applications: feature issue introduction

The feature Issue on "Dynamic Light Scattering in Biomedical Applications" presents a compilation of research breakthroughs and technological advancements that have shaped the field of biophotonics, particularly in the non-invasive exploration of biological tissues. Highlighting the significance of dynamic light scattering (DLS) alongside techniques like laser Doppler flowmetry (LDF), diffusing wave spectroscopy (DWS), and laser speckle contrast imaging (LSCI), this issue underscores the versatile applications of these methods in capturing the intricate dynamics of microcirculatory blood flow across various tissues. Contributions explore developments in fluorescence tomography, the integration of machine learning for data processing, enhancements in microscopy for cancer detection, and novel approaches in optical biophysics, among others. Innovations featured include a high-resolution speckle contrast tomography system for deep blood flow imaging, a rapid estimation technique for real-time tissue perfusion imaging, and the use of convolutional neural networks for efficient blood flow mapping. Additionally, studies delve into the impact of skin strain on spectral reflectance, the sensitivity of cerebral blood flow measurement techniques, and the potential of photobiomodulation for enhancing brain function. This issue not only showcases the latest theoretical and experimental strides in DLS-based imaging but also anticipates the continued evolution of these modalities for groundbreaking applications in disease detection, diagnosis, and monitoring, marking a pivotal contribution to the field of biomedical optics.

Rolling shutter speckle plethysmography for quantitative cardiovascular monitoring

We propose a new speckle-based plethysmography technique, termed rolling shutter speckle plethysmography (RSSPG), which can quantitatively measure the velocity and volume fluctuations of blood flow during the cardiac cycle. Our technique is based on the rolling shutter speckle imaging, where the short row-by-row time differences in the rolling shutter image sensors are used to measure the temporal decorrelation behavior of vertically elongated speckles from a single image capture. Temporal analysis of the speckle field provides rich information regarding the dynamics of the scattering media, such as both the dynamic scattering fraction and the speckle decorrelation time. Using a sequence of images, RSSPG can monitor fluctuations in the blood flow dynamics while separating velocity and volume changes in blood vessels and obtaining high-quality plethysmography waveforms compared to regular photoplethysmography. We demonstrate the quantitative RSSPG based on accurate fitting of the speckle dynamics model, as well as the qualitative RSSPG based on simple row-by-row correlation (RIC) calculation for fast and robust analysis. Based on exploratory in vivo experiment, we show that RSSPG can reliably measure pulsatile waveforms and heart rate variations in various conditions, potentially providing physiologically relevant information for cardiovascular monitoring.

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.

Wide-field intensity fluctuation imaging

The temporal intensity fluctuations contain important information about the light source and light-medium interaction and are typically characterized by the intensity autocorrelation function, g2(τ). The measurement of g2(τ) is a central topic in many optical sensing applications, ranging from stellar intensity interferometer in astrophysics, to fluorescence correlation spectroscopy in biomedical sciences and blood flow measurement with dynamic light scattering. Currently, g2(τ) at a single point is readily accessible through high-frequency sampling of the intensity signal. However, two-dimensional wide-field imaging of g2(τ) is still limited by the cameras' frame rate. We propose and demonstrate a 2-pulse within-exposure modulation approach to break through the camera frame rate limit and obtain the quasi g2(τ) map in wide field with cameras of only ordinary frame rates.

Improvements and validation of spatiotemporal speckle correlation model for rolling shutter speckle imaging

Rolling shutter speckle imaging (RSSI) is a single-shot imaging technique that directly measures the temporal dynamics of the scattering media using a low-cost rolling shutter image sensor and vertically elongated speckles. In this paper, we derive and validate a complete spatiotemporal intensity correlation (STIC) model for RSSI, which describes the row-by-row correlation of the dynamic speckles measured with a rolling shutter in the presence of static scattering. Our new model accounts for the finite exposure time of the detector, which can be longer than the sampling interval in RSSI. We derive a comprehensive model that works for all correlation times of rolling shutter measurements. As a result, we can correctly utilize all data points in RSSI, which improves the measurement accuracy and ranges of speckle decorrelation time and dynamic scattering fraction, as demonstrated by phantom experiments. With simulations and experiments, we provide an understanding of the design parameters of RSSI and the measurement range of the speckle dynamics.

Combining near infrared fluorescence and laser speckle imaging with optical tissue clearing for in vivo transcranial monitoring of cerebral blood vessels damaged by photodynamic nanoformulation

In vivo near infrared (NIR) fluorescence imaging and laser speckle contrast imaging (LSCI) are emerging optical bioimaging modalities, which can provide information on blood vessels morphology, volume and the blood flow velocity. Optical tissue clearing (OTC) technique addresses a light scattering problem in optical bioimaging, which is imperative for the transcranial brain imaging. Herein, we report an approach combining NIR fluorescence and LSC microscopy imaging with OTC. A liposomal nanoformulation comprising NIR fluorescent dye ICG and photosensitizer BPD was synthesized and injected intravenously into mouse with OTC treated skull. Transcranial excitation of BPD in nanoliposomes resulted in the localized, irradiation dose dependent photodynamic damage of the brain blood vessels, which was manifested both in NIR fluorescence and LSC transcranial imaging, revealing changes in the vessels morphology, volume and the blood flow rate. The developed approach allows for bimodal imaging guided, localized vascular PDT of cancer and other diseases.

Laser speckle imaging of the hippocampus

Research on hippocampal blood flow is essential for gaining insight into its involvement in learning and memory and its role in age-related cognitive impairment and dementia. In this study, we applied laser speckle contrast imaging (LSCI) and dynamic light scattering imaging (DLSI) to monitor perfusion in mouse hippocampus via a chronic, optically transparent window. LSCI scans showed hippocampal blood vessels appear more out of focus than similar caliber vessels in the mouse cortex. We hypothesize that it is caused by the inverse vascular topology and increased contribution of multiply-scattered photons detected from the upper layers of the hippocampus. We support the hypothesis with DLSI, showing a 1300% increased contribution of multiple-scattering unordered dynamics regime in large hippocampal vessels.

Dynamic light scattering and laser speckle contrast imaging of the brain: theory of the spatial and temporal statistics of speckle pattern evolution

Dynamic light scattering (DLS) and laser speckle contrast imaging (LSCI) are closely related techniques that exploit the statistics of speckle patterns, which can be utilized to measure cerebral blood flow (CBF). Conventionally, the temporal speckle intensity auto-correlation function g 2 t ( τ ) is calculated in DLS, while the spatial speckle contrast Ks is calculated in LSCI measurements. Due to the rapid development of CMOS detection technology with increased camera frame rates while still maintaining a large number of pixels, the ensemble or spatial average of g 2 s ( τ ) as well as the temporal contrast Kt can be easily calculated and utilized to quantify CBF. Although many models have been established, a proper summary is still lacking to fully characterize DLS and LSCI measurements for spatial and temporal statistics, laser coherence properties, various motion types, etc. As a result, there are many instances where theoretical models are misused. For instance, mathematical formulas derived in the diffusive regime or for ergodic systems are sometimes applied to small animal brain measurements, e.g., mice brains, where the assumptions are not valid. Therefore, we aim to provide a review of the speckle theory for both DLS and LSCI measurements with detailed derivations from first principles, taking into account non-ergodicity, spatial and temporal statistics of speckles, scatterer motion types, and laser coherence properties. From these calculations, we elaborate on the differences between spatial and temporal averaging for DLS and LSCI measurements that are typically ignored but can result in inaccurate measurements of blood flow, particularly the spatially varying nature of the static component in g 2 t ( τ ) and Kt. We also obtained g 2 s ( τ ) maps in in vivo mouse brain measurements using high frame rate CMOS cameras which have not been demonstrated before, and compared with g 2 t ( τ ) and Ks,t. This work provides a useful guide for choosing the correct model to analyze spatial and temporal speckle statistics in in-vivo DLS and LSCI measurements.

Choosing a polarisation configuration for dynamic light scattering and laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is applied in various biomedical applications for full-field characterization of blood flow and tissue perfusion. The accuracy of the contrast interpretation and its conversion to the blood flow index depends on specific parameters of the optical system and scattering media. One such parameter is the polarisation of detected light, which is often adjusted to minimize specular reflections and image artefacts. The polarisation's effect on the detected light scattering dynamics and, therefore, the accuracy of LSCI data interpretation requires more detailed investigation. In this study, we used LSCI and Dynamic Light Scattering Imaging to evaluate the effects of the detected light polarisation when imaging perfusion in the mouse cortex. We found that cross-polarisation results in a shorter decorrelation time constant, a higher coherence degree and stronger dynamic scattering compared to the parallel-polarisation or no-polariser configurations. These results support the cross-polarisation configuration as the most optimal for brain cortex imaging and suggest against direct or calibrated comparisons between the contrast recordings made with different polarisation configurations.

Advances in laser speckle imaging: From qualitative to quantitative hemodynamic assessment

Laser speckle imaging (LSI) techniques have emerged as a promising method for visualizing functional blood vessels and tissue perfusion by analyzing the speckle patterns generated by coherent light interacting with living biological tissue. These patterns carry important biophysical tissue information including blood flow dynamics. The noninvasive, label-free, and wide-field attributes along with relatively simple instrumental schematics make it an appealing imaging modality in preclinical and clinical applications. The review outlines the fundamentals of speckle physics and the three categories of LSI techniques based on their degree of quantification: qualitative, semi-quantitative and quantitative. Qualitative LSI produces microvascular maps by capturing speckle contrast variations between blood vessels containing moving red blood cells and the surrounding static tissue. Semi-quantitative techniques provide a more accurate analysis of blood flow dynamics by accounting for the effect of static scattering on spatiotemporal parameters. Quantitative LSI such as optical speckle image velocimetry provides quantitative flow velocity measurements, which is inspired by the particle image velocimetry in fluid mechanics. Additionally, discussions regarding the prospects of future innovations in LSI techniques for optimizing the vascular flow quantification with associated clinical outlook are presented.

Wide dynamic range measurement of blood flow in vivo using laser speckle contrast imaging

Significance

Laser speckle contrast imaging (LSCI) is a real-time wide-field technique that is applied to visualize blood flow in biomedical applications. However, there is currently a lack of relevant research to demonstrate that it can measure velocities over a wide dynamic range (WDR), which is critical for monitoring much higher and more pulsatile blood flow in larger size myocardial vessels, such as the coronary artery bypass graft, and visualizing the spatio-temporal evolution of myocardial blood flow perfusion in cardiac surgery.

Aim

We aim to demonstrate that the LSCI technique enables measuring velocities over a WDR from phantom experiments to animal experiments. In addition, LSCI is preliminarily applied to imaging myocardial blood flow distribution in vivo on rabbits.

Approach

Phantom and animal experiments are performed to verify that the LSCI method has the ability to measure blood velocities over a wide range. Our method is also validated by transit time flow measurement, which is the gold standard for blood flow measurement in cardiac surgery.

Results

Our method is demonstrated to measure the blood flow over a wide range from 0.2 to 635    mm / s . To validate the phantom results, the varying blood flow rate from 0 to 320    mm / s is detected in the rat carotid artery. Additionally, our technique also obtains blood flow maps of different myocardial vessels, such as superficial large/small veins, veins surrounded by fat, and myocardial deeper arteriole.

Conclusions

Our study has the potential to visualize the spatio-temporal evolution of myocardial perfusion in coronary artery bypass grafting, which would be of great benefit for future research in the life sciences and clinical medicine.

Quantifying tissue properties and absolute hemodynamics using coherent spatial imaging

Significance

Measuring hemodynamic function is crucial for health assessment. Optical signals provide relative hemoglobin concentration changes, but absolute measurements require costly, bulky technology. Speckleplethysmography (SPG) uses coherent light to detect speckle fluctuations. Combining SPG with multispectral measurements may provide important physiological information on blood flow and absolute hemoglobin concentration.

Aim

To develop an affordable optical technology to measure tissue absorption, scattering, hemoglobin concentrations, tissue oxygen saturation (StO 2 ), and blood flow.

Approach

We integrated reflectance spectroscopy and laser speckle imaging to create coherent spatial imaging (CSI). CSI was validated against spatial frequency domain imaging (SFDI) using phantom-based measurements. In vivo arterial and venous occlusion experiments compared CSI with diffuse optical spectroscopy/diffuse correlation spectroscopy (DOS/DCS) measurements.

Results

CSI and SFDI agreed on tissue absorption and scattering in phantom tests. CSI and DOS/DCS showed similar trends and agreement in arterial occlusion results. During venous occlusion, both uncorrected and corrected blood flow decreased with increasing pressure, with an ∼ 200 % difference in overall blood flow decrease between the methods. CSI and DOS/DCS data showed expected hemoglobin concentrations, StO 2 , and blood flow trends.

Conclusions

CSI provides affordable and comprehensive hemodynamic information. It can potentially detect dysfunction and improve measurements, such as blood pressure, S p O 2 , and metabolism.

pH-Responsive NIR-II phototheranostic agents for in situ tumor vascular monitoring and combined anti-vascular/photothermal therapy

Developing nanoplatforms integrating superior fluorescence imaging ability in second near-infrared (NIR-II) window and tumor microenvironment responsive multi-modal therapy holds great potential for real-time feedback of therapeutic efficacy and optimizing tumor inhibition. Herein, we developed a pH-sensitive pyrrolopyrrole aza-BODIPY-based amphiphilic molecule (PTG), which has a balanced NIR-II fluorescence brightness and photothermal effect. PTG is further co-assembled with a vascular disrupting agent (known as DMXAA) to prepare PTDG nanoparticles for combined anti-vascular/photothermal therapy and real-time monitoring of the tumor vascular disruption. Each PTG molecule has an active PT-3 core which is linked to two PEG chains via pH-sensitive ester bonds. The cleavage of ester bonds in the acidic tumor environment would tricker releases of DMXAA for anti-vascular therapy and further assemble PT-3 cores into micrometer particles for long term monitoring of the tumor progression. Furthermore, benefiting from the high brightness in the NIR-II region (119.61 M-1 cm-1) and long blood circulation time (t1/2 = 235.6 min) of PTDG nanoparticles, the tumor vascular disrupting process can be in situ visualized in real time during treatment. Overall, this study demonstrates a self-assembly strategy to build a pH-responsive NIR-II nanoplatform for real-time monitoring of tumor vascular disruption, long-term tracking tumor progression and combined anti-vascular/photothermal therapy.

Optimizing the precision of laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a rapidly developing technology broadly applied for the full-field characterization of tissue perfusion. Over the recent years, significant advancements have been made in interpreting LSCI measurements and improving the technique's accuracy. On the other hand, the method's precision has yet to be studied in detail, despite being as important as accuracy for many biomedical applications. Here we combine simulation, theory and animal experiments to systematically evaluate and re-analyze the role of key factors defining LSCI precision-speckle-to-pixel size ratio, polarisation, exposure time and camera-related noise. We show that contrary to the established assumptions, smaller speckle size and shorter exposure time can improve the precision, while the camera choice is less critical and does not affect the signal-to-noise ratio significantly.

Quantitative hemodynamic imaging: a method to correct the effects of optical properties on laser speckle imaging

Significance

Studying cerebral hemodynamics may provide diagnostic information on neurological conditions. Wide-field imaging techniques, such as laser speckle imaging (LSI) and optical intrinsic signal imaging, are commonly used to study cerebral hemodynamics. However, they often do not account appropriately for the optical properties of the brain that can vary among subjects and even during a single measurement. Here, we describe the combination of LSI and spatial-frequency domain imaging (SFDI) into a wide-field quantitative hemodynamic imaging (QHI) system that can correct the effects of optical properties on LSI measurements to achieve a quantitative measurement of cerebral blood flow (CBF).

Aim

We describe the design, fabrication, and testing of QHI.

Approach

The QHI hardware combines LSI and SFDI with spatial and temporal synchronization. We characterized system sensitivity, accuracy, and precision with tissue-mimicking phantoms. With SFDI optical property measurements, we describe a method derived from dynamic light scattering to obtain absolute CBF values from LSI and SFDI measurements. We illustrate the potential benefits of absolute CBF measurements in resting-state and dynamic experiments.

Results

QHI achieved a 50-Hz raw acquisition frame rate with a 10 × 10    mm field of view and flow sensitivity up to ∼ 4    mm / s . The extracted SFDI optical properties agreed well with a commercial system (R 2 ≥ 0.98 ). The system showed high stability with low coefficients of variations over multiple sessions within the same day (< 1 % ) and over multiple days (< 4 % ). When optical properties were considered, the in-vivo hypercapnia gas challenge showed a slight difference in CBF (- 1.5 % to 0.5% difference). The in-vivo resting-state experiment showed a change in CBF ranking for nine out of 13 animals when the correction method was applied to LSI CBF measurements.

Conclusions

We developed a wide-field QHI system to account for the confounding effects of optical properties on CBF LSI measurements using the information obtained from SFDI.

Dynamic light scattering microscopy sensing mitochondria dynamics for label-free detection of triple-negative breast cancer enhanced by deep learning

We established a deep learning-based dynamic light scattering (DLS) microscopy sensing mitochondria dynamic for label-free identification of triple-negative breast cancer (TNBC) cells. The capacity of DLS microscopy to detect the intracellular motility of subcellular scatters was verified with the analysis of the autocorrelation function. We also conducted an in-depth examination of the impact of mitochondrial dynamics on DLS within TNBC cells, employing confocal fluorescent imaging to visualize the morphology of the mitochondria. Furthermore, we applied the DLS microscopy incorporating the two-stream deep learning method to differentiate the TNBC subtype and HER2 positive breast cancer subtype, with the classification accuracy achieving 0.89.

Interferometric speckle visibility spectroscopy (iSVS) for measuring decorrelation time and dynamics of moving samples with enhanced signal-to-noise ratio and relaxed reference requirements

Diffusing wave spectroscopy (DWS) is a group of techniques used to measure the dynamics of a scattering medium in a non-invasive manner. DWS methods rely on detecting the speckle light field from the moving scattering medium and measuring the speckle decorrelation time to quantify the scattering medium's dynamics. For DWS, the signal-to-noise (SNR) is determined by the ratio between measured decorrelation time to the standard error of the measurement. This SNR is often low in certain applications because of high noise variances and low signal intensity, especially in biological applications with restricted exposure and emission levels. To address this photon-limited signal-to-noise ratio problem, we investigated, theoretically and experimentally, the SNR of an interferometric speckle visibility spectroscopy (iSVS) compared to more traditional DWS methods. We found that iSVS can provide excellent SNR performance through its ability to overcome camera noise. We also proved an iSVS system has more relaxed constraints on the reference beam properties. For an iSVS system to function properly, we only require the reference beam to exhibit local temporal stability, while incident angle, reference phase and intensity uniformity do not need to be constrained. This flexibility can potentially enable more unconventional iSVS implementation schemes.

Laser speckle contrast imaging based on spatial frequency domain filtering

We proposed a novel method to separate static and dynamic speckles based on spatial frequency domain filtering. First, the raw speckle image sequence is processed frame by frame through 2D Fourier transform, low-pass and high-pass filtering in the spatial frequency domain, and inverse Fourier transform. Then, we can obtain low- and high-frequency image sequences in the spatial domain. Second, we averaged both sequences in the time domain. After the above processing, we obtain the mean intensities of the dynamic and static speckle components in the spatial domain. Finally, we calculated the time-averaged modulation depth to map the 2-D blood flow distribution. Both phantom and vivo experiments demonstrated that the proposed method could effectively suppress the background non-uniformity and has the advantage of high computational efficiency. It also can effectively improve image contrast, contrast-to-noise ratio, and imaging dynamic range.

Design and validation of a convolutional neural network for fast, model-free blood flow imaging with multiple exposure speckle imaging

Multiple exposure speckle imaging has demonstrated its improved accuracy compared to single exposure speckle imaging for relative quantitation of blood flow in vivo. However, the calculation of blood flow maps relies on a pixelwise non-linear fit of a multi-parametric model to the speckle contrasts. This approach has two major drawbacks. First, it is computer-intensive and prevents real time imaging and, second, the mathematical model is not universal and should in principle be adapted to the type of blood vessels. We evaluated a model-free machine learning approach based on a convolutional neural network as an alternative to the non-linear fit approach. A network was designed and trained with annotated speckle contrast data from microfluidic experiments. The neural network performances are then compared to the non-linear fit approach applied to in vitro and in vivo data. The study demonstrates the potential of convolutional networks to provide relative blood flow maps from multiple exposure speckle data in real time.

Reduced tubuloglomerular feedback activity and absence of its synchronization in a connexin40 knockout rat

Introduction: Tubuloglomerular feedback (TGF) is the negative feedback component of renal blood flow (RBF) autoregulation. Neighbouring nephrons often exhibit spontaneous TGF oscillation and synchronization mediated by endothelial communication, largely via connexin40 (Cx40). Methods: We had a knockout (KO) rat made that lacks Cx40. One base pair was altered to create a stop codon in exon 1 of Gja5, the gene that encodes Cx40 (the strain is WKY-Gja55em1Mcwi). Blood pressure (BP)-RBF transfer functions probed RBF dynamics and laser speckle imaging interrogated the dynamics of multiple efferent arterioles that reach the surface (star vessels). Results: The distribution of wild type (WT), heterozygote, and KO pups at weaning approximated the Mendelian ratio of 1:2:1; growth did not differ among the three strains. The KO rats were hypertensive. BP-RBF transfer functions showed low gain of the myogenic mechanism and a smaller TGF resonance peak in KO than in WT rats. Laser speckle imaging showed that myogenic mechanism had higher frequency in KO than in WT rats, but similar maximum spectral power. In contrast, the TGF frequency was similar while peak power of its oscillation was much smaller in KO than in WT rats. In WT rats, plots of instantaneous TGF phase revealed BP-independent TGF synchronization among star vessels. The synchronization could be both prolonged and widespread. In KO rats TGF synchronization was not seen, although BP transients could elicit short-lived TGF entrainment. Discussion: Despite the reduced TGF spectral power in KO rats, there was sufficient TGF gain to induce oscillations and therefore enough gain to be effective locally. We conclude that failure to synchronize is dependent, at least in part, on impaired conducted vasomotor responses.

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.

Wide-field Intensity Fluctuation Imaging

The temporal intensity fluctuations contain important information about the light source and light-medium interaction and are typically characterized by the intensity autocorrelation function, g 2 ( τ ) . The measurement of g 2 ( τ ) is a central topic in many optical sensing applications, ranging from stellar intensity interferometer in astrophysics, to fluorescence correlation spectroscopy in biomedical sciences and blood flow measurement with dynamic light scattering. Currently, g 2 ( τ ) at a single point is readily accessible through high-frequency sampling of the intensity signal. However, two-dimensional wide-field measurement of g 2 ( τ ) is still limited by camera frame rates. We propose and demonstrate a 2-pulse within-exposure modulation approach to break through the camera frame rate limit and obtain the quasi g 2 ( τ ) map in wide field with cameras of only ordinary frame rates.

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.

CASPI: collaborative photon processing for active single-photon imaging

Image sensors capable of capturing individual photons have made tremendous progress in recent years. However, this technology faces a major limitation. Because they capture scene information at the individual photon level, the raw data is sparse and noisy. Here we propose CASPI: Collaborative Photon Processing for Active Single-Photon Imaging, a technology-agnostic, application-agnostic, and training-free photon processing pipeline for emerging high-resolution single-photon cameras. By collaboratively exploiting both local and non-local correlations in the spatio-temporal photon data cubes, CASPI estimates scene properties reliably even under very challenging lighting conditions. We demonstrate the versatility of CASPI with two applications: LiDAR imaging over a wide range of photon flux levels, from a sub-photon to high ambient regimes, and live-cell autofluorescence FLIM in low photon count regimes. We envision CASPI as a basic building block of general-purpose photon processing units that will be implemented on-chip in future single-photon cameras.

Pyrrolopyrrole aza-BODIPY-based NIR-II fluorophores for in vivo dynamic vascular dysfunction visualization of vascular-targeted photodynamic therapy

Real-time monitoring vascular responses is crucial for evaluating the therapeutic effects of vascular-targeted photodynamic therapy (V-PDT). Herein, we developed a highly-stable and bright aggregation induced emission (AIE) fluorophore (PTPE3 NP) for dynamic fluorescence (FL) imaging of vascular dysfunction beyond 1300 nm window during V-PDT. The superior brightness (ϵ_maxΦ_{f>1000 nm} ≈ 180.05 M^-1 cm^-1) and high resolution of PTPE3 NP affords not only high-clarity images of whole-body and local vasculature (hindlimbs, mesentery, and tumor) but also high-speed video imaging for tracking blood circulation process. By virtue of the NPs' prolonged blood circulation time (t_1/2 ≈ 86.5 min) and excellent photo/chemical (pH, RONS) stability, mesenteric and tumor vascular dysfunction (thrombosis formation, vessel occlusion, and hemorrhage) can be successfully visualized during V-PDT by FL imaging for the first time. Furthermore, the reduction of blood flow velocity (BFV) can be monitored in real time for precisely evaluating efficacy of V-PDT. These provide a powerful approach for assessing vascular responses during V-PDT and promote the development of advanced fluorophores for biological imaging.

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.

Random matrix-based laser speckle contrast imaging enables quasi-3D blood flow imaging in laparoscopic surgery

Laser speckle contrast imaging (LSCI) provides full-field and label-free imaging of blood flow and tissue perfusion. It has emerged in the clinical environment, including the surgical microscope and endoscope. Although traditional LSCI has been improved in resolution and SNR, there are still challenges in clinical translations. In this study, we applied a random matrix description for the statistical separation of single and multiple scattering components in LSCI using a dual-sensor laparoscopy. Both in-vitro tissue phantom and in-vivo rat experiments were performed to test the new laparoscopy in the laboratory environment. This random matrix-based LSCI (rmLSCI) provides the blood flow and tissue perfusion in superficial and deeper tissue respectively, which is particularly useful in intraoperative laparoscopic surgery. The new laparoscopy provides the rmLSCI contrast images and white light video monitoring simultaneously. Pre-clinical swine experiment was also performed to demonstrate the quasi-3D reconstruction of the rmLSCI method. The quasi-3D ability of the rmLSCI method shows more potential in other clinical diagnostics and therapies using gastroscopy, colonoscopy, surgical microscope, etc.

Intrinsic, widefield optical imaging of hemodynamics in rodent models of Alzheimer's disease and neurological injury

The complex cerebrovascular network is critical to controlling local cerebral blood flow (CBF) and maintaining brain homeostasis. Alzheimer's disease (AD) and neurological injury can result in impaired CBF regulation, blood-brain barrier breakdown, neurovascular dysregulation, and ultimately impaired brain homeostasis. Measuring cortical hemodynamic changes in rodents can help elucidate the complex physiological dynamics that occur in AD and neurological injury. Widefield optical imaging approaches can measure hemodynamic information, such as CBF and oxygenation. These measurements can be performed over fields of view that range from millimeters to centimeters and probe up to the first few millimeters of rodent brain tissue. We discuss the principles and applications of three widefield optical imaging approaches that can measure cerebral hemodynamics: (1) optical intrinsic signal imaging, (2) laser speckle imaging, and (3) spatial frequency domain imaging. Future work in advancing widefield optical imaging approaches and employing multimodal instrumentation can enrich hemodynamic information content and help elucidate cerebrovascular mechanisms that lead to the development of therapeutic agents for AD and neurological injury.

All fiber-based illumination system for multi-exposure speckle imaging

Monitoring blood flow is critical to treatment efficacy in many surgical settings. Laser speckle contrast imaging (LSCI) is a simple, real-time, label-free optical technique for monitoring blood flow that has emerged as a promising technique but lacks the ability to make repeatable quantitative measurements. Multi-exposure speckle imaging (MESI) is an extension of LSCI that requires increased complexity of instrumentation, which has limited its adoption. In this paper, we design and fabricate a compact, fiber-coupled MESI illumination system (FCMESI) that is substantially smaller and less complex than previous systems. Using microfluidics flow phantoms, we demonstrate that the FCMESI system measures flow with an accuracy and repeatability equivalent to traditional free space MESI illumination systems. With an in vivo stroke model, we also demonstrate the ability of FCMESI to monitor cerebral blood flow changes.

Light-sheet laser speckle imaging for cilia motility assessment

Mucociliary clearance is an important innate defense mechanism predominantly mediated by ciliated cells in the upper respiratory tract. Ciliary motility on the respiratory epithelium surface and mucus pathogen trapping assist in maintaining healthy airways. Optical imaging methods have been used to obtain several indicators for assessing ciliary movement. Light-sheet laser speckle imaging (LSH-LSI) is a label-free and non-invasive optical technique for three-dimensional and quantitative mapping of velocities of microscopic scatterers. Here, we propose to use an inverted LSH-LSI platform to study cilia motility. We have experimentally confirmed that LSH-LSI can reliably measure the ciliary beating frequency and has the potential to provide many additional quantitative indicators for characterizing the ciliary beating pattern without labeling. For example, the asymmetry between the power stroke and the recovery stroke is apparent in the local velocity waveform. PIV (particle imaging velocimetry) analysis of laser speckle data could determine the cilia motion directions in different phases.

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.

Laser speckle simulation tool based on stochastic differential equations for bio imaging applications

Laser speckle-based blood flow imaging is a well-accepted and widely used method for pre-clinical and clinical applications. Although it was introduced as a method to measure only superficial blood flow (< 1mm depth), several recently introduced variants resulted in measuring deep tissue blood flow (a few cm) as well. A means of simulating laser speckles is often necessary for the analysis and development of these imaging modalities, as evident from many such attempts towards developing simulation tools in the past. Such methods often employ Fourier transforms or statistical tools to simulate speckles with desired statistical properties. We present the first method to use a stochastic differential equation to generate laser speckles with a pre-determined probability density function and a temporal auto-correlation. The method allows the choice of apriori gamma distribution along with simple exponential or more complex temporal auto-correlation statistics for simulated speckles, making it suitable for different blood flow profiles. In contrast to the existing methods that often generate speckles associated with superficial flow, we simulate both superficial and diffuse speckles leading to applications in deep tissue blood flow imaging. In addition, we have also incorporated appropriate models for noise associated with the detectors to simulate realistic speckles. We have validated our model by comparing the simulated speckles with those obtained from in-vivo studies in mice and healthy human subject.

Inter-day repeatability assessment of human retinal blood flow using clinical laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) can generate retinal blood flow maps inexpensively and non-invasively. These flow maps can be used to identify various eye disorders associated with reduced blood flow. Despite early success, one of the major obstacles to clinical adoption of LSCI is poor repeatability of the modality. Here, we propose an LSCI registration pipeline that registers contrast maps to correct for rigid movements. Post-registration, intra(same)-day and inter(next)-day repeatability are studied using various quantitative metrics. We have studied LSCI repeatability intra-day by using the coefficient of variation. Using the processing pipelines and custom hardware developed, similar repeatability was observed when compared to previously reported values in the literature. Inter-day repeatability analysis indicates no statistical evidence (p = 0.09) of a difference between flow measurements performed on two independent days. Further improvements to hardware, environmental controls, and participant control must be made to provide higher confidence in the repeatability of blood flow. However, this is the first time that repeatability across two different days (inter-day) using multiple exposure speckle imaging (MESI) has been analyzed and reported.

Echo speckle imaging of dynamic processes in soft materials

We present a laser-speckle imaging technique, termed Echo speckle imaging (ESI), that quantifies the local dynamics in biological tissue and soft materials with a noise level around or below 10% of the measured signal without affecting the spatial resolution. We achieve this through an unconventional speckle beam illumination that creates changing, statistically independent illumination conditions and substantially increases the measurement accuracy. Control experiments for dynamically homogeneous and heterogeneous soft materials and tissue phantoms illustrate the performance of the method. We show that this approach enables us to precision-monitor purely dynamic heterogeneities in turbid soft media with a lateral resolution of 100 µm and better.

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.

Evaluation of Blood Coagulation by Optical Vortex Tracking

Blood coagulation is a complicated dynamic process that maintains the blood's fluid state and prevents uncontrollable bleeding. The real-time monitoring of coagulation dynamics is critical for blood transfusion guidance, emergency management of trauma-induced coagulopathy, perioperative bleeding, and targeted hemostatic therapy. Here, we utilize optical vortex dynamics to detect the blood coagulation dynamic process in a rapid and non-contact manner. To characterize the temporal changes in viscoelastic properties of blood during coagulation, we track the stochastic motion of optical vortices in the time-varying speckles reflected from 100 blood samples with varied coagulation profiles. The mean square displacement (MSD) of the vortices increases nonlinearly with time lag during blood coagulation reminiscent of the particles in viscoelastic fluids. The MSD curves with coagulation time are similar to the tracings of thromboelastography (TEG) during the blood coagulation. The retrieved coagulation parameters, such as reaction time and activated clotting time measured using the optical vortex method, exhibit a close correlation to those parameters acquired from TEG. These results demonstrate the feasibility of the optical vortex method for monitoring blood coagulation at the point of care. Our method is also applicable to measuring the viscoelasticity of complex fluids and turbid soft matters.

Spatially-Resolved Network Dynamics of Poly(vinyl alcohol) Gels Measured with Dynamic Small Angle Light Scattering

Hydrogels are cross-linked polymer networks swollen in water. The large solvent content enables hydrogels to have unique physical properties and allows them to be used in diverse applications such as tissue engineering, drug delivery, and absorbents. Gel properties are linked to internal dynamics. While bulk gel dynamics have been studied extensively, how gel networks respond locally to deformation has yet to be understood. Here, poly(vinyl alcohol) (PVA) gels have been stretched to study the effects of deformation on gel dynamics parallel and perpendicular to the stretching direction using dynamic small angle light scattering (DSALS). The implementation of DSALS is described and compared to traditional DLS for PVA gels with different crosslink densities, ranging from 0.75–2%. Despite the orders of magnitude difference in the scattering vector, q, range of the techniques, the dynamics match, and the apparent elastic diffusion coefficient, D_A increases linearly with the crosslink density for unstretched gels at a constant 2 wt% concentration. We observe that the elastic motion depends on the direction of stretch, decreasing perpendicular to stretching and increasing at parallel direction. Using DSALS can therefore be an effective tool to evaluate local hydrogel response to deformation.

Novel Elastography-Inspired Approach to Angiographic Visualization in Optical Coherence Tomography

In this paper, we present a new approach to contrast-agent-free angiographic visualization in optical coherence tomography (OCT). The proposed approach has much in common with imaging of local interframe strains in OCT-based elastography and utilizes the fact that the interframe motion of blood particles leads to discontinuity of strains within the vessel cross section. By this reasoning, we call this approach “elastography-inspired”. Here, we first elucidate the essence and main features of the elastography-inspired approach using numerical simulation of OCT data. The simulations allow one to introduce both moving scatterers imitating blood flow in vessels as well as various masking motions imitating natural motions of living “solid” tissue surrounding the vessels. Second, using real OCT signals, we present comparative results of angiographic processing using the proposed elastography-inspired approach and a realization of OCA based on high-pass filtering of temporal variability of a series of OCT B-scans. The two methods can use the same initial dataset and the high-pass filtering OCA has already been routinely applied in both animal experiments and on patients. The new elastography-inspired method has a similar computational efficiency, and it is intrinsically able to compensate spatially-inhomogeneous masking tissue motions and demonstrates high robustness with respect to motion artefacts. Thus, the new approach looks very promising for enabling wider application of OCA in both laboratory studies on animals and, most importantly, for wider clinical applications on patients.

Correction of overexposure in laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a method to visualize and quantify tissue perfusion and blood flow. A common flaw in LSCI variants is their sensitivity to the optical setup parameters and that they operate well only on statistics of undistorted laser speckle patterns. The signal saturation of the sensors makes the contrast calculation misleading; hence the illumination level must be well controlled. We describe the theoretical explanation for the saturation-caused degradation. We introduce a linear extrapolation method to eliminate the overexposure induced error up to an extent of 60-70% saturated pixel count. This, depending on the contrast value and use case, enables to use 3-8 times higher external illumination level with no deterioration of the contrast calculation and thus the measured blood flow index. Our method enables a higher signal-to-noise ratio in darker areas by allowing the use of higher illumination, utilizing a larger portion of the dynamic range of the sensors, and making the illumination level setting less cumbersome.