Space-directional approach to improve blood vessel visualization and temporal resolution in laser speckle contrast imaging

Blood flow is a parameter used to diagnose vascular diseases based on flow speed, blood pressure, and vessel size. Different techniques have been developed to estimate the relative blood flow speed and to improve the visualization of deep blood vessels; one such technique is laser speckle contrast imaging (LSCI). LSCI images contain a high level of noise mainly when deep blood vessels are imaged. To improve their visualization, several approaches for contrast computation have been developed. However, there is a compromise between noise attenuation and temporal resolution. On the one hand, spatial approaches have low spatial resolution, high temporal resolution, and significant noise attenuation, while temporal approaches have the opposite. A recent approach combines a temporal base with a directional process that allows improving the visualization of blood vessels. Nevertheless, it still contains a high level of noise and requires a high number of raw frames for its base. We propose, a space-directional approach focused on improving noise attenuation and temporal resolution for contrast computation. The results of reference approaches and the proposed one are compared quantitatively. Moreover, it is shown that the visualization of blood vessels in LSCI images can be improved by a general morphological process when the noise level is reduced.

Laser speckle auto-inverse covariance imaging for mean-invariant estimation of blood flow

Laser speckle contrast imaging maps the changes in blood flow by estimating the decorrelation time of a scattered light field. However, speckle contrast is a biased statistics estimator that results in a theoretic bias between its expected value and the true value. Moreover, the average of speckle contrast depends on the statistical sampling size, which further hinders the estimation of decorrelation time from speckle contrast. Here, we present a new, to the best of our knowledge, unbiased statistics analysis based on auto-inverse covariance to improve the estimation of decorrelation time using laser speckle. Theoretical and experimental results demonstrate that the speckle auto-inverse covariance analysis is mean-invariant, so that the average of the estimation is not dependent on the sampling size. Furthermore, it can produce less statistical fluctuation, especially for slow flow, and consume less computation time than that of speckle contrast analysis.

Wavelet Analysis of the Temporal Dynamics of the Laser Speckle Contrast in Human Skin

OBJECTIVE

Spectral analysis of laser Doppler flowmetry (LDF) signals has been widely used in studies of physiological vascular function regulation. An alternative to LDF is the laser speckle contrast imaging method (LSCI), which is based on the same physical principle. In contrast to LDF, LSCI provides non-scanning full-field imaging of a relatively wide skin area and offers high spatial and temporal resolutions, which allows visualization of microvascular structure. This circumstance, together with a large number of works which had shown the effectiveness of temporal LSCI analysis, gave impetus to experimental studies of the relation between LDF and LSCI used to monitor the temporal dynamics of blood flow.

METHODS

Continuous wavelet transform was applied to construct a time-frequency representation of a signal.

RESULTS

Analysis of 10 minute LDF and LSCI output signals recorded simultaneously revealed rather high correlation between oscillating components. It was demonstrated for the first time that the spectral energy of oscillations in the 0.01-2 Hz frequency range of temporal LSCI recordings carries the same information as the conventional LDF recordings and hence it reflects the same physiological vascular tone regulation mechanisms.

CONCLUSION

The approach proposed can be used to investigate speckle pattern dynamics by LSCI in both normal and pathological conditions.

SIGNIFICANCE

The results of research on the influence of spatial binning and averaging on the spectral characteristics of perfusion monitored by LSCI are of considerable interest for the development of LSCI systems optimized to evaluate temporal dynamics.

Oxygen Delivery Therapy with EPIFLO Reduces Wound Hyperperfusion in Patients with Chronic Leg Ulcers: A Laser Speckle Contrast Analysis

BACKGROUND

Today transdermal continuous oxygen therapy (TCOT) is used in wound care to promote healing by improving local hypoxia and preventing infection, and it has been described to reduce local inflammation over 1 month of administration. The present study aims to investigate the effects of this treatment on wound microcirculation through laser speckle contrast analysis (LASCA).

METHODS

20 adult patients (mean age: 76 ± 11.5 years) were prospectively enrolled. Inclusion criteria were presence of venous or mixed lower limb ulcers from three or more months without dimension reduction and without indication to surgery and weekly treatment by our outpatient clinic with silver dressings. Subjects underwent 1 month of TCOT (EPIFLO®) in addition to foam dressing. The primary endpoint was the comparison of ulcer and healthy skin perfusion through LASCA, performed before and after the treatment period. Secondary considered endpoints were wound area, wound area severity index and PUSH Tools 3.0 ulcer severity scales, and pain assessment (Numerical Rating Scale [NRS]).

RESULTS

Before treatment, the wound area was significantly more perfused than healthy skin (+45%; P = 0.005). At the end of the study, this difference was not significant anymore (+20.5%; P = 0.11). Ulcer perfusion decreased (-12.5%, P = 0.047), whereas healthy skin perfusion did not vary significantly. A reduction of the wound dimension (median difference: 2 cm; P = 0.009) and pain (median difference: 2 NRS point; P < 0.001) after therapy were assessed.

CONCLUSIONS

LASCA shows that 1 month of TCOT can help reduce hyperperfusion of ulcer bed in patients with chronic lower limb ulcers, strengthening the hypothesis that this treatment effectively contrasts inflammation. This could correlate with the area and pain reduction assessed; however, the absence of a control group in this study does not allow a generalization of this hypothesis. Larger, controlled trials are needed to properly assess the relationship between TCOT effects on wound microenvironment and effective healing process.

Gaussian sliding window for robust processing laser speckle contrast images

The laser speckle contrast analysis (LASCA) is one of the most applicable tools in microcirculation studies. While the basic idea, as well as experimental setup for this method, are fairly simple, there is still the room for advancing of data processing algorithms. Specifically, the conventional realizations of LASCA method may limit the spatial and/or temporal resolution and thus fail in the detection of very small contrast objects since they based on the fixed-size rectangular sliding window function. We suggest an alternative data processing algorithm based on the usage of the Gaussian sliding filter for a sequential determination of both spatial and temporal parts of the speckle contrast. The suggested replacement of conventional box filter leads to the monotonic damping of high-frequency spectral components that results in a better elimination of ringing and aliasing effects in the spatio-temporal speckle contrast outputs. Additionally, we show that such sliding filtration increases robustness with respect to the processing of a sequence of nonstabilised images. We support this consideration with representative examples of processing both surrogate and real experimental data.

Multiple speckle exposure imaging for the study of blood flow changes induced by functional activation of barrel cortex and olfactory bulb in mice

Speckle contrast imaging allows in vivo imaging of relative blood flow changes. Multiple exposure speckle imaging (MESI) is more accurate than the standard single-exposure method since it allows separating the contribution of the static and moving scatters of the recorded speckle patterns. MESI requires experimental validation on phantoms prior to in vivo experiments to ensure the proper calibration of the system and the robustness of the model. The data analysis relies on the calculation of the speckle contrast for each exposure and a subsequent nonlinear fit to the MESI model to extract the scatterers correlation time and the relative contribution of moving scatters. We have designed two multichannel polydimethylsiloxane chips to study the influence of multiple and static scattering on the accuracy of MESI quantitation. We also propose a method based on standard C++ libraries to implement a computationally efficient analysis of the MESI data. Finally, the system was used to obtain in vivo hemodynamic data on two distinct sensory areas of the mice brain: the barrel cortex and the olfactory bulb.

Machine learning in multiexposure laser speckle contrast imaging can replace conventional laser Doppler flowmetry

Laser speckle contrast imaging (LSCI) enables video rate imaging of blood flow. However, its relation to tissue blood perfusion is nonlinear and depends strongly on exposure time. By contrast, the perfusion estimate from the slower laser Doppler flowmetry (LDF) technique has a relationship to blood perfusion that is better understood. Multiexposure LSCI (MELSCI) enables a perfusion estimate closer to the actual perfusion than that using a single exposure time. We present and evaluate a method that utilizes contrasts from seven exposure times between 1 and 64 ms to calculate a perfusion estimate that resembles the perfusion estimate from LDF. The method is based on artificial neural networks (ANN) for fast and accurate processing of MELSCI contrasts to perfusion. The networks are trained using modeling of Doppler histograms and speckle contrasts from tissue models. The importance of accounting for noise is demonstrated. Results show that by using ANN, MELSCI data can be processed to LDF perfusion with high accuracy, with a correlation coefficient R  =  1.000 for noise-free data, R  =  0.993 when a moderate degree of noise is present, and R  =  0.995 for in vivo data from an occlusion-release experiment.

Application of optical flow algorithms to laser speckle imaging

Since of its introduction in 1980s, laser speckle imaging has become a powerful tool in flow imaging. Its high performance and low cost made it one of the preferable imaging methods. Initially, speckle contrast measurements were the main algorithm for analyzing laser speckle images in biological flows. Speckle contrast measurements, also referred as Laser Speckle Contrast Imaging (LSCI), use statistical properties of speckle patterns to create mapped image of the blood vessels. In this communication, a new method named Laser Speckle Optical Flow Imaging (LSOFI) is introduced. This method uses the optical flow algorithms to calculate the apparent motion of laser speckle patterns. The differences in the apparent motion of speckle patterns are used to identify the blood vessels from surrounding tissue. LSOFI has better spatial and temporal resolution compared to LSCI. This higher spatial resolution enables LSOFI to be used for autonomous blood vessels detection. Furthermore, Graphics Processing Unit (GPU) based LSOFI can be used for quasi real time imaging.

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.

Monitoring blood-flow in the mouse cochlea using an endoscopic laser speckle contrast imaging system

Laser speckle contrast imaging (LSCI) enables continuous high-resolution assessment of microcirculation in real-time. We applied an endoscope to LSCI to measure cochlear blood-flow in an ischemia–reperfusion mouse model. We also explored whether using xenon light in combination with LSCI facilitates visualization of anatomical position. Based on a previous preliminary study, the appropriate wavelength for penetrating the thin bony cochlea was 830 nm. A 2.7-mm-diameter endoscope was used, as appropriate for the size of the mouse cochlea. Our endoscopic LSCI system was used to illuminate the right cochlea after dissection of the mouse. We observed changes in the speckle signals when we applied the endoscopic LSCI system to the ischemia-reperfusion mouse model. The anatomical structure of the mouse cochlea and surrounding structures were clearly visible using the xenon light. The speckle signal of the cochlea was scattered, with an intensity that varied between that of the stapes (with the lowest signal), the negative control, and the stapedial artery (with the highest signal), the positive control. In the cochlear ischemia–reperfusion mouse model, the speckle signal of the cochlea decreased during the ischemic phase, and increased during the reperfusion phase, clearly reflecting cochlear blood-flow. The endoscopic LSCI system generates high-resolution images in real-time, allowing visualization of blood-flow and its changes in the mouse cochlea. Anatomical structures were clearly matched using LSCI along with visible light.

Roadmap on optical sensors

Sensors are devices or systems able to detect, measure and convert magnitudes from any domain to an electrical one. Using light as a probe for optical sensing is one of the most efficient approaches for this purpose. The history of optical sensing using some methods based on absorbance, emissive and florescence properties date back to the 16th century. The field of optical sensors evolved during the following centuries, but it did not achieve maturity until the demonstration of the first laser in 1960. The unique properties of laser light become particularly important in the case of laser-based sensors, whose operation is entirely based upon the direct detection of laser light itself, without relying on any additional mediating device. However, compared with freely propagating light beams, artificially engineered optical fields are in increasing demand for probing samples with very small sizes and/or weak light-matter interaction. Optical fiber sensors constitute a subarea of optical sensors in which fiber technologies are employed. Different types of specialty and photonic crystal fibers provide improved performance and novel sensing concepts. Actually, structurization with wavelength or subwavelength feature size appears as the most efficient way to enhance sensor sensitivity and its detection limit. This leads to the area of micro- and nano-engineered optical sensors. It is expected that the combination of better fabrication techniques and new physical effects may open new and fascinating opportunities in this area. This roadmap on optical sensors addresses different technologies and application areas of the field. Fourteen contributions authored by experts from both industry and academia provide insights into the current state-of-the-art and the challenges faced by researchers currently. Two sections of this paper provide an overview of laser-based and frequency comb-based sensors. Three sections address the area of optical fiber sensors, encompassing both conventional, specialty and photonic crystal fibers. Several other sections are dedicated to micro- and nano-engineered sensors, including whispering-gallery mode and plasmonic sensors. The uses of optical sensors in chemical, biological and biomedical areas are described in other sections. Different approaches required to satisfy applications at visible, infrared and THz spectral regions are also discussed. Advances in science and technology required to meet challenges faced in each of these areas are addressed, together with suggestions on how the field could evolve in the near future.

Use of kurtosis for locating deep blood vessels in raw speckle imaging using a homogeneity representation

Visualization of deep blood vessels in speckle images is an important task as it is used to analyze the dynamics of the blood flow and the health status of biological tissue. Laser speckle imaging is a wide-field optical technique to measure relative blood flow speed based on the local speckle contrast analysis. However, it has been reported that this technique is limited to certain deep blood vessels (about ? = 300 ?? ? m ) because of the high scattering of the sample; beyond this depth, the quality of the vessel’s image decreases. The use of a representation based on homogeneity values, computed from the co-occurrence matrix, is proposed as it provides an improved vessel definition and its corresponding diameter. Moreover, a methodology is proposed for automatic blood vessel location based on the kurtosis analysis. Results were obtained from the different skin phantoms, showing that it is possible to identify the vessel region for different morphologies, even up to 900 ?? ? m in depth.

Quantitative imaging of heterogeneous dynamics in drying and aging paints

Drying and aging paint dispersions display a wealth of complex phenomena that make their study fascinating yet challenging. To meet the growing demand for sustainable, high-quality paints, it is essential to unravel the microscopic mechanisms underlying these phenomena. Visualising the governing dynamics is, however, intrinsically difficult because the dynamics are typically heterogeneous and span a wide range of time scales. Moreover, the high turbidity of paints precludes conventional imaging techniques from reaching deep inside the paint. To address these challenges, we apply a scattering technique, Laser Speckle Imaging, as a versatile and quantitative tool to elucidate the internal dynamics, with microscopic resolution and spanning seven decades of time. We present a toolbox of data analysis and image processing methods that allows a tailored investigation of virtually any turbid dispersion, regardless of the geometry and substrate. Using these tools we watch a variety of paints dry and age with unprecedented detail.