Laser Speckle Contrast Images Research Articles

Method for measuring blood flow and depth of blood vessel based on laser speckle contrast imaging using 3D convolutional neural network: A preliminary study

Laser speckle contrast imaging (LSCI) is a technology that can acquire real-time two-dimensional perfusion images non-invasively. However, measuring perfusion velocity under a tissue is difficult due to its optical properties. Dynamic scattered light occurs by perfusion is diffused by the surrounding tissue and it depends on the depth of tissue. We aimed to develop a three-dimensional convolutional neural network (3D-CNN) model based on laser speckle contrast images to measure the flow velocity and the depth of tissue using a flow phantom. The training data was selected as a region containing both static speckles and dynamic speckles, and the model was trained on the laser speckle contrast image data. The trained model showed a measurement accuracy of more than 90 % for velocity and 99 % for depth measurement. This study has the potential of a deep-learning model based on LSCI to analyze the blood flow and depth of blood vessels in bio-applications.

Projection mapping system for laser speckle contrast image: feasibility study for clinical application.

Laser speckle contrast images (LSCIs) have been utilized to monitor blood flow perfusion. However, they have conventionally been observed on monitor screens, resulting in potential spatial mismatching between the imaging region of interest (IROI) and monitor screen. This study proposes a projection mapping (PM) system for LSCIs (PMS_LSCI) that projects LSCIs to directly observe the blood flow perfusion in the IROI. The PMS_LSCI consists of a camera, imaging optics, a laser projector, and graphic user interface software. The spatial matching in the regions of interest was performed by adjusting the software screen of the LSCI in the IROI and evaluated by conducting in-vitro and in-vivo studies. An additional in-vivo study was performed to investigate the feasibility of real-time PM of the LSCI. The spatial mismatching in the regions of interest was ranged from 2.74% to 6.47% depending on the surface curvature. The PMS_LSCI could enable real-time PM of LSCI at four different blood flow states depending on blood pressure. The PMS_LSCI projects the LSCI in the IROI by interacting with a projector instead of the monitor screen. The PMS_LSCI presented clinical feasibility in the in-vitro and in-vivo studies.

Robust vessel segmentation in laser speckle contrast images based on semi-weakly supervised learning

Objective. The goal of this study is to develop a robust semi-weakly supervised learning strategy for vessel segmentation in laser speckle contrast imaging (LSCI), addressing the challenges associated with the low signal-to-noise ratio, small vessel size, and irregular vascular aberration in diseased regions, while improving the performance and robustness of the segmentation method. Approach. For the training dataset, the healthy vascular images denoted as normal-vessel samples were manually labeled, while the diseased LSCI images involving tumor or embolism were denoted as abnormal-vessel samples and annotated as pseudo labels by the traditional semantic segmentation methods. In the training phase, the pseudo labels were constantly updated to improve the segmentation accuracy based on DeepLabv3+. Objective evaluation was conducted on the normal-vessel test set, while subjective evaluation was performed on the abnormal-vessel test set. Main results. The proposed method achieved an IOU of 0.8671, a Dice of 0.9288, and a mean relative percentage difference (mRPD) with supervised learning of 0.5% in the objective evaluation. In the subjective evaluation, our method significantly outperformed other methods in main vessel segmentation, tiny vessel segmentation, and blood vessel connection. Additionally, our method exhibited robustness when abnormal-vessel style noise was added to normal-vessel samples using a style translation network. Significance. The proposed semi-weakly supervised learning strategy demonstrates high efficiency and excellent robustness for vascular segmentation in LSCI, providing a potential tool for assessing the morphological and structural features of vessels in clinical applications.

Abstract 538: Local Hydrogen Sulfide Therapy Augments Angiogenesis And Ischemic Wound Healing

Introduction: Hydrogen sulfide (H 2 S) is an important signaling molecule in cellular O 2 sensing, wound healing and angiogenesis. Low H 2 S levels have been shown in diabetes and cardiovascular disease and H 2 S impairment may play a role in chronic non-healing ischemic wounds. H 2 S promotes angiogenesis in cell culture but in vivo data are lacking. We utilized a novel local H 2 S delivery method to investigate the effects of H 2 S therapy in rodents. Methods: Sprague Dawley rats (n=6-10/group) underwent dorsal myocutaneous ischemic flap wound creation under anesthesia. NaHS solution (100 μM) was delivered locally to the wound every 12 hours via implanted microtubing externalized and attached to a fluid delivery vest. Sham rats received saline solution while a third group received H 2 S blocker DL-propargylglycine (PAG). Laser speckle contrast images (LSCI) were recorded over 14 days. Flap tissue was collected for histologic analysis of tissue viability and degree of ischemic insult. Neovascularization was quantified by CD31 immunohistochemistry (IHC). VEGF protein expression was quantified by Western blot. Results: H 2 S treated flaps reperfused at a two-fold greater rate compared to sham and PAG treated flaps by LSCI (mean 12.9 flux/day vs. 6.9 flux/day, P=0.02). IHC mean microvascularity in sham flaps was 18 vessels/mm 2 compared to 47 vessels/mm 2 in H 2 S treated flaps (P=0.0092). Panniculus carnosis muscle thickness (408 μm vs. 234 μm) and myofibril count (56 vs. 38/100k μm 2 ) were preserved in H 2 S treated flaps (P=0.02, 0.04). H 2 S treatment upregulated VEGF while PAG was associated with decreased expression. Conclusion: H 2 S treated flaps have improved wound revascularization, tissue healing and angiogenic signaling. Blockade of H 2 S results in poor revascularization and decreased angiogenic protein expression. H 2 S pathways may play a critical role in the pathogenesis of impaired wound healing and could represent a potential therapeutic target for ischemic wounds.

Abstract 288: Impaired Ischemic Myocutaneous Wound Revascularization And Transdermal H 2 S Emissions In Diabetic Rats

Introduction: Hydrogen sulfide (H 2 S) has been recognized as an important signaling molecule in cellular O 2 sensing, wound healing and angiogenesis. Studies have shown abnormal H 2 S levels in diabetic patients with cardiovascular disease. Diminished H 2 S signaling may play a causative role in diabetic foot wounds. The Transdermal Arterial Gasotransmitter Sensor (TAGS) device measures real-time H 2 S emissions through the skin. In this work, we utilize the novel TAGS device to characterize transdermal H 2 S emissions during diabetic and non-diabetic wound healing for the first time. Methods: Dorsal peninsular-shaped myocutaneous ischemic flap wounds were created under anesthesia. Sprague Dawley (SD) and Zucker Diabetic Fatty (ZDF) rats (n=10 each) were compared. Transdermal H 2 S emissions, laser speckle contrast images (LSCI) and planimetric photos were serially taken from the wound flap area over 14 days. After animal sacrifice, healed flap tissue was collected for histologic (H&E) analysis of panniculus carnosus (skin muscle) viability as a proxy for degree of ischemic insult. Results: ZDF rats were significantly hyperglycemic (mean 516 mg/dL vs. 201 mg/dL for SD, P=0.002). Similar mean baseline (preoperative) H 2 S emissions were observed in SD (16 ppb) and ZDF (12 ppb) rats (P=0.25). During revascularization and healing, ZDF wounds emitted significantly less H 2 S (10 ppb at day 14) as compared to SD (28 ppb at day 14, P<0.01). ZDF wounds demonstrated impaired flap engraftment and revascularization by LSCI (mean 65.6 Perfusion Units (PU) for ZDF vs. 188.0 PU for SD at day 14, p<0.01) and planimetric analysis (mean 16.6% necrosis for ZDF vs. 5.3% necrosis for SD at day 14, p=0.01). Panniculus carnosus mean myofibril count, myofibril diameter, and layer thickness were significantly decreased (p<0.01) in the ZDF cohort, suggesting greater tissue ischemic insult and muscle loss. Conclusion: Diabetic rats have impaired wound H 2 S production and poor revascularization. These physiologic alterations are accompanied by greater wound necrosis and histologic ischemic insult. This suggests H 2 S abnormalities in diabetes may play a role in the pathogenesis of impaired wound healing and could represent a potential future therapeutic target for these difficult wounds.

Real-Time Cerebral Vessel Segmentation in Laser Speckle Contrast Image Based on Unsupervised Domain Adaptation.

Laser speckle contrast imaging (LSCI) is a full-field, high spatiotemporal resolution and low-cost optical technique for measuring blood flow, which has been successfully used for neurovascular imaging. However, due to the low signal–noise ratio and the relatively small sizes, segmenting the cerebral vessels in LSCI has always been a technical challenge. Recently, deep learning has shown its advantages in vascular segmentation. Nonetheless, ground truth by manual labeling is usually required for training the network, which makes it difficult to implement in practice. In this manuscript, we proposed a deep learning-based method for real-time cerebral vessel segmentation of LSCI without ground truth labels, which could be further integrated into intraoperative blood vessel imaging system. Synthetic LSCI images were obtained with a synthesis network from LSCI images and public labeled dataset of Digital Retinal Images for Vessel Extraction, which were then used to train the segmentation network. Using matching strategies to reduce the size discrepancy between retinal images and laser speckle contrast images, we could further significantly improve image synthesis and segmentation performance. In the testing LSCI images of rodent cerebral vessels, the proposed method resulted in a dice similarity coefficient of over 75%.

Semi-Automatic Tracking of Laser Speckle Contrast Images of Microcirculation in Diabetic Foot Ulcers

Foot ulcers are a severe complication of diabetes mellitus. Assessment of the vascular status of diabetic foot ulcers with Laser Speckle Contrast Imaging (LSCI) is a promising approach for diagnosis and prognosis. However, manual assessment during analysis of LSCI limits clinical applicability. Our aim was to develop and validate a fast and robust tracking algorithm for semi-automatic analysis of LSCI data. The feet of 33 participants with diabetic foot ulcers were recorded with LSCI, including at baseline, during the Post-Occlusive Reactive Hyperemia (PORH) test, and during the Buerger’s test. Different regions of interest (ROIs) were used to measure microcirculation in different areas of the foot. A tracking algorithm was developed in MATLAB to reposition the ROIs in the LSCI scans. Manual- and algorithm-tracking of all recordings were compared by calculating the Intraclass Correlation Coefficient (ICC). The algorithm was faster in comparison with the manual approach (90 s vs. 15 min). Agreement between manual- and algorithm-tracking was good to excellent during baseline (ICC = 0.896–0.984; p < 0.001), the PORH test (ICC = 0.790–0.960; p < 0.001), and the Buerger’s test (ICC = 0.851–0.978; p < 0.001), resulting in a tracking algorithm that delivers assessment of LSCI in diabetic foot ulcers with results comparable to a labor-intensive manual approach, but with a 10-fold workload reduction.

Improving imaging depth by dynamic laser speckle imaging and topical optical clearing for in vivo blood flow monitoring.

Laser speckle contrast imaging (LSI) is a promising non-invasive full-field blood flow monitoring technique. However, it is still far from clinic practice due to insufficient contrast-to-noise ratio (CNR) and limited detection depth. In this study, an in vivo laser speckle imaging visualization system was constructed to observe the blood circulation on a dorsal skin. A dynamic laser speckle imaging (dLSI) scheme, other than traditional laser speckle contrast analysis method, was applied to separate the dynamic light scattering from the static one to increase the image CNR. Based on the theoretical optimization for dLSI, at least two pixels are required for speckle pattern sampling and a spatial window size of 7 × 7 was optimal to balance the spatial resolution and statistical accuracy. The in vivo experiment observation shows that the CNR is improved 8.4 times by dLSI. The blood vessels were more pronounced, and more capillaries can be observed than in traditional laser speckle contrast images. Topical optical clearing technique by thiazone was combined with dLSI to increase the sampling depth from 700 to 1000 μm.

Multi-spectral laser speckle contrast images using a wavelength-swept laser.

.A multi-spectral laser speckle contrast imaging (MS-LSCI) system is proposed using only a single wavelength-swept laser, which provides both highly coherent and multi-spectral outputs to simultaneously generate laser speckle contrast images and multi-spectral images, respectively. Using a laser light swept from 770 to 821 nm at a repetition rate of 5 Hz and a CCD camera of 335 fps, 67 multi-spectral frame images are acquired in 0.76 nm wavebands over 51 nm spectral range. The spectral sub-windowing method of single wavelength-swept laser source is used to solve the lack of spectral information from a few individual light sources, which is a limitation of conventional MS-LSCI systems. In addition to the speckle flow index from the LSCI frames, the multi-spectrally encoded images can generate additional images of spectral absorbance. To further examine the performance of the MS-LSCI system, an in vivo cuff-induced ischemia experiment was conducted to show the real-time imaging of hemodynamic and blood oxygen saturation changes simultaneously over the entire field of view.

Aging effect on microcirculation: A multiscale entropy approach on laser speckle contrast images.

It has long been known that age plays a crucial role in the deterioration of microvessels. The assessment of such deteriorations can be achieved by monitoring microvascular blood flow. Laser speckle contrast imaging (LSCI) is a powerful optical imaging tool that provides two-dimensional information on microvascular blood flow. The technique has recently been commercialized, and hence, few works discuss the postacquisition processing of laser speckle contrast images recorded in vivo. By applying entropy-based complexity measures to LSCI time series, we present herein the first attempt to study the effect of aging on microcirculation by measuring the complexity of microvascular signals over multiple time scales. Forearm skin microvascular blood flow was studied with LSCI in 18 healthy subjects. The subjects were subdivided into two age groups: younger (20-30 years old, n = 9) and older (50-68 years old, n = 9). To estimate age-dependent changes in microvascular blood flow, we applied three entropy-based complexity algorithms to LSCI time series. The application of entropy-based complexity algorithms to LSCI time series can differentiate younger from older groups: the data fluctuations in the younger group have a significantly higher complexity than those obtained from the older group. The effect of aging on microcirculation can be estimated by using entropy-based complexity algorithms to LSCI time series.

Observation of vasculature alternation by intense pulsed light combined with physicochemical methods

Intense pulsed light (IPL) with low energy insufficient to completely destroy a vasculature was applied to rabbit ears to investigate vasculature alteration. Glycerol was combined with IPL to enhance the transfer efficacy of IPL energy. Both trans-illumination and laser speckle contrast images were obtained and analyzed after treatment. The application of IPL and glycerol combination induced vasodilation and improvement in blood flow. Moreover, such phenomenon was maintained over time. IPL may be applied to treat blood circulatory diseases by inducing vasodilation and to improve blood flow.

Analysis of laser speckle contrast images variability using a novel empirical mode decomposition: comparison of results with laser Doppler flowmetry signals variability.

Laser Doppler flowmetry (LDF) and laser speckle contrast imaging (LSCI) have emerged as noninvasive optical modalities to monitor microvascular blood flow. Many studies proposed to extract physiological information from LDF by analyzing signals variability. By opposition, such analyses for LSCI data have not been conducted yet. We propose to analyze LSCI variability using a novel data-driven method: the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). CEEMDAN is suitable for nonlinear and nonstationary data and leads to intrinsic mode functions (IMFs). It is based on the ensemble empirical mode decomposition (EEMD) which relies on empirical mode decomposition (EMD). In our work the average frequencies of LSCI IMFs given by CEEMDAN are compared with the ones given by EMD and EEMD. Moreover, LDF signals acquired simultaneously to LSCI data are also processed with CEEMDAN, EMD and EEMD. We show that the average frequencies of IMFs given by CEEMDAN depend on the signal-to-noise ratio (SNR) used in the computation but, for a given SNR, the average frequencies found for LSCI are close to the ones obtained for LDF. By opposition, EEMD leads to IMFs with frequencies that do not vary much when the SNR level is higher than a threshold. The new CEEMDAN algorithm has the advantage of achieving a complete decomposition with no error in the reconstruction but our study suggests that further work is needed to gain knowledge in the adjustment of the added noise level. CEEMDAN, EMD and EEMD are data-driven methods that can provide a better knowledge of LSCI.

The effects of a minimally invasive laser needle system on complete Freund’s adjuvant-induced arthritis

The present study aimed to investigate the effects of a minimally invasive laser needle system (MILNS) on the acute progression of arthritis. Previous studies showed controversial clinical results regarding the effects of low-level laser therapy on arthritis, with the outcomes depending upon stimulation parameters such as laser wavelength and dosage. Based on the positive effects of MILNS on osteoporotic mice, we hypothesized that MILNS could potentially suppress the progression of arthritis owing to its biostimulation effects. Eight C57BL/6 mice with complete Freund's adjuvant (CFA)-induced arthritis were used as acute progression arthritis models and divided into the laser and control groups (n = 4 each). In the laser group, after minimally invasive laser stimulation, laser speckle contrast images (LSCIs) were obtained every 6 h for a total of 108 h. The LSCIs in the control group were obtained without laser stimulation. The effects of MILNS on the acute progression of arthritis were indirectly evaluated by calculating the paw area and the average laser speckle index (LSI) at the arthritis-induced area. Moreover, the macrophage population was estimated in the arthritis-induced area. Compared to the control group, the laser group showed (1) lower relative variations of the paw area, (2) lower average LSI in the arthritis-induced area, and (3) lower macrophage population in the arthritis-induced area. These results indicate that MILNS may suppress the acute progression of CFA-induced arthritis in mice and may thus be used as a potential treatment modality of arthritis in clinics.

Linguistic Analysis of Laser Speckle Contrast Images Recorded at Rest and During Biological Zero: Comparison With Laser Doppler Flowmetry Data

Laser speckle contrast imaging (LSCI) is a newly commercialized imaging modality to monitor microvascular blood flow. Contrary to the well-known laser Doppler flowmetry (LDF), LSCI has the advantage of giving a full-field image of surface blood flow using simple instrumentation. However, laser speckle contrast images are not fully understood yet and their link with LDF signals still has to be studied. To quantify the similarity between LSCI and LDF symbolic sequences, we propose to use, for the first time, the index adapted from linguistic analysis and information theory proposed by Yang For this purpose, LSCI and LDF data were recorded simultaneously on the forearm of healthy subjects, at rest and during a vascular occlusion (biological zero). We show that there are different dynamical patterns for LSCI and LDF data, and the distances between these patterns differ through the space scales explored. Moreover, our results suggest that these different dynamical patterns could be linked to blood flow. The quantitative metric used herein therefore provides new information on LSCI and brings knowledge on links between LSCI and LDF.

Laser speckle contrast imaging: Multifractal analysis of data recorded in healthy subjects

The monitoring of microvascular blood flow can now be performed with laser speckle contrast imaging (LSCI), a new noninvasive laser-based technique. LSCI images have good spatial and temporal resolutions. Nevertheless, from now, few processing of these data have been performed to have a better knowledge on their properties. We herein propose a multifractal analysis of LSCI data recorded in the forearm of healthy subjects, based on the method from Halsey et al., one of the popular methods using the box-counting technique. In laser speckle contrast image time sequences, we studied time evolution of pixel values, as well as time evolution of pixel values averaged in regions of interest (ROI) of different sizes. The results are compared with the ones obtained with single-point laser Doppler flowmetry (LDF) signals recorded simultaneously to LSCI images. Our work shows that, for the range of scales studied and with the method from Halsey et al., time evolution of pixel values present narrow multifractal spectra, reminding the ones of monofractal data. However, we observe that when LSCI pixel values are averaged in ROI large enough and followed with time, the multifractal spectra become larger and closer to the ones of LDF signals. Single pixels from laser speckle contrast images may not possess the same multifractal properties as LDF signals. These findings could now be compared with the ones obtained with other ranges of scales and with data recorded from pathological subjects.

Albumin Therapy Enhances Collateral Perfusion after Laser-Induced Middle Cerebral Artery Branch Occlusion: A Laser Speckle Contrast Flow Study

Laser speckle contrast (LSC) was used to compare the extent of cortical ischemia in two inbred mouse strains that differed in their degree of collateral circulation, after laser occlusion of the distal middle cerebral artery, and after treatment with 25% albumin (ALB) or saline (control). Sequential LSC images acquired over ∼90 minutes were coaligned, converted to relative flow, and normalized to baseline. After 3-day survival, infarction was quantified by triphenyl tetrazolium chloride or magnetic resonance imaging. In the sparsely collateralized BALB/c strain, mean flow fell to 13% to 14% and 33% to 34% of baseline in central (core) and peripheral (penumbral) regions of interest, and ALB treatment at 30 minutes enhanced perfusion in both regions by ∼2-fold relative to saline, restoring flow to the benign-oligemic range centrally, and to the hyperemic range peripherally. The ALB-induced increment in parenchymal perfusion was disproportionate to the subtle flow increase in the occluded artery itself, suggesting that ALB improved collateral circulation. Cortical infarction in BALB/c mice was reduced 45% by ALB treatment. In contrast to BALB/c mice, the better-collateralized CD-1 strain developed milder ischemia, had smaller infarcts, and showed no differential benefit of ALB. We conclude that where native collateralization is insufficient (BALB/c strain), ALB treatment exerts a significant therapeutic effect after ischemia by augmenting collateral perfusion.

Assessing spatial resolution versus sensitivity from laser speckle contrast imaging: application to frequency analysis

For blood perfusion monitoring, laser speckle contrast (LSC) imaging is a recent non-contact technique that has the characteristic of delivering noise-like speckled images. To exploit LSC images for quantitative physiological measurements, we developed an approach that implements controlled spatial averaging to reduce the detrimental impact of the noise and improve measurement sensitivity. By this approach, spatial resolution and measurement sensitivity can be traded-off in a flexible way depending on the quantitative prospect of the study. As an application, detectability of the cardiac activity from LSC images of forearm using power spectrum analysis is studied through the construction of spatial activity maps offering a window on the blood flow perfusion and its regional distribution. Comparisons with results obtained with signals of laser Doppler flowmetry probes are performed.

Portable laser speckle perfusion imaging system based on digital signal processor

The ability to monitor blood flow in vivo is of major importance in clinical diagnosis and in basic researches of life science. As a noninvasive full-field technique without the need of scanning, laser speckle contrast imaging (LSCI) is widely used to study blood flow with high spatial and temporal resolution. Current LSCI systems are based on personal computers for image processing with large size, which potentially limit the widespread clinical utility. The need for portable laser speckle contrast imaging system that does not compromise processing efficiency is crucial in clinical diagnosis. However, the processing of laser speckle contrast images is time-consuming due to the heavy calculation for enormous high-resolution image data. To address this problem, a portable laser speckle perfusion imaging system based on digital signal processor (DSP) and the algorithm which is suitable for DSP is described. With highly integrated DSP and the algorithm, we have markedly reduced the size and weight of the system as well as its energy consumption while preserving the high processing speed. In vivo experiments demonstrate that our portable laser speckle perfusion imaging system can obtain blood flow images at 25 frames per second with the resolution of 640 × 480 pixels. The portable and lightweight features make it capable of being adapted to a wide variety of application areas such as research laboratory, operating room, ambulance, and even disaster site.

Efficient Processing of Laser Speckle Contrast Images

Though laser speckle contrast imaging enables the measurement of scattering particle dynamics with high temporal resolution, the subsequent processing has previously been much slower. In prior studies, generating a laser speckle contrast image required about 1 s to process a raw image potentially collected in 10 ms or less. In this paper, novel algorithms are described which are demonstrated to convert 291 raw images per second to laser speckle contrast images and as many as 410 laser speckle contrast images per second to relative correlation time images. As long as image processing occurs during image acquisition, these algorithms render processing time irrelevant in most circumstances and enable real-time imaging of blood flow dynamics.