Speckle Imaging Research Articles

Two-dimensional speckle tracking imaging analyses of the correlations between left atrial appendage function and stroke risk in nonvalvular atrial fibrillation patients.

Stroke incidence is the most severe complication associated with atrial fibrillation (AF), and the most common site of thrombus formation in AF patients is the left atrial appendage (LAA). This study was developed to use two-dimensional speckle tracking imaging (2D-STI) to explore associations between LAA strain/strain rate and stroke incidence and to evaluate the value of utilizing LAA strain and strain rate values to support the stratification of nonvalvular AF (NVAF) patients based on stroke risk. A total of 486 AF patients who had undergone transesophageal echocardiography to exclude potential intracardiac thrombosis between March 2021 and November 2022 were consecutively enrolled. Patients meeting the inclusion criteria were separated into two groups according to their history of stroke/transient ischemic attack (TIA). LAA strain and strain rate values in these patients were measured via 2D-STI. Multivariable logistic regression analysis was employed to determine independent risk factors for the construction of a combined predictive model. Of the 333 analyzed patients (134 females, aged 65 (56,72) years), 39 (11.71%, 39/333) had a history of stroke at the time of evaluation. Multivariate logistic regression analysis demonstrated that nonparoxysmal AF, CHA2DS2VASc score, LAA thrombus/spontaneous echo contrast (SEC), LAA strain, and strain rate were all predictors of stroke incidence among NVAF patients. The combined predictive model demonstrated excellent discriminative ability, with an AUC of 0.91 (95%CI 0.87-0.95, P < 0.001), and a sensitivity and specificity of 79.49% and 89.46%, respectively. The Hosmer-Lemeshow test confirmed good calibration, yielding a value of 0.98. Comparative decision curve analysis showed that the model provided superior net benefits compared to the CHA2DS2VASc score. Furthermore, the model exhibited improved predictive performance and reclassification for stroke when compared to the CHA2DS2VASc score (AUC 0.91 vs. 0.88, Z = 2.32, P = 0.02), accompanied by a significant increase in the net reclassification index (+ 5.44%, P < 0.001) and integrated discrimination improvement (8.21%, P < 0.001). These data demonstrate that LAA strain and strain rate, as measured via 2D-STI, can offer value when assessing LAA function in AF patients, potentially providing further predictive value to extant clinical risk scoring strategies.

Unsupervised CNN-based DIC method for 2D displacement measurement

Digital image correlation (DIC) is a widely used technique for non-contact measurement of deformation. However, traditional DIC methods face challenges in balancing calculation efficiency and the quantity of seed points. Deep learning approaches, particularly supervised learning methods, have shown promise in improving DIC efficiency. However, these methods require high-quality training data, which can be time-consuming to generate ground truth annotations. To address these challenges, we propose an unsupervised convolutional neural network (CNN) based DIC method for 2D displacement measurement. Our approach leverages an encoder-decoder architecture with multi-level feature extraction, a dual-path correlation block, and an attention block to extract informative features from speckle images with varying characteristics. We utilize a speckle image warp model to transform the deformed speckle image to the predicted reference speckle image based on the predicted 2D displacement map. The unsupervised training is achieved by comparing the predicted and original reference speckle images. To optimize the network's parameters, we employ a composite loss function that takes into account both the Mean Squared Error (MSE) and Pearson correlation coefficient. By using unsupervised convolutional neural network (CNN) based DIC method, we eliminate the need for extensive training data annotation, which is a time-consuming process in supervised learning DIC methods. We have conducted several experiments to demonstrate the validity and robustness of our proposed method. The results show a significant reduction in Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) compared to a method proposed by Zhao et al. This indicates that our unsupervised CNN-based DIC approach can achieve accuracy comparable to supervised CNN-based DIC methods. For implementation and evaluation, we provide PyTorch code and datasets, which will be released at the following URL :https://github.com/fead1/DICNet-corr-unsupervised-learning-.

Evolutionary Gravitational Neocognitron Neural Network-Based Blood Flow Velocity Prediction Using Multi-Exposure Laser Speckle Contrast Imaging

Wide-field and noncontact imaging technique called laser speckle contrast imaging (LSCI) is utilized to map blood flow. To greatly improve prediction accuracy, the block-matching along 3-dimensional transform domain collaborative filtering-dependent denoising technique is developed. To implement real-time denoising, the processing time makes complexity. Due to the existence of considerable noise and artifacts, this is challenging to achieve the acceptable level with less raw speckle images. Notwithstanding, it acts poorly while learning from the original LSCI speckle contrast images because of the uneven noise distribution. To overcome this issue, an evolutionary gravitational neocognitron neural network-based blood flow velocity prediction using multiple exposure laser speckle contrast imaging (EGNNN-BFVP-MeLSCI) is proposed. Initially, the input MeLSCI datasets are collected from real-time dataset. The input picture is enhanced and noise is removed using pre-processing technique called altered phase preserving dynamic range compression (APPDRC). Gray level co-occurrence matrix (GLCM) window adaptive approach-dependent feature extraction approach is used for the preprocessed pictures. Using GLCM window adaptive method, the picture characteristics, such as intensity information, images derivative, geodesic information, contrasts, energy, correlations, homogeneity, and entropy, are retrieved. Then, the extracted features are transferred into the EGNNN classifier for accurately predicting the blood flow velocity. The performance of proposed method is executed at python and evaluated under certain performance metrics, such as accuracy, precision, sensitivity, specificity, [Formula: see text]-measure, ROC, computation time, mean squared error, root mean squared error, predicted velocity. The proposed EGNNN-BFVP-MeLSCI method attains higher accuracy of 96.31%, 97.06%, and 93.52%, lower computational time of 97.22%, 91.39%, 96.41% compared with existing approaches, like DnCNN-BFVP-MeLSCI, CFD-BFVP-MeLSCI, DLS-BFVP-MeLSCI, CNN-BFVP-MeLSCI, DBN-BFVP-MeLSCI, CGAN-BFVP-MeLSCI and MVN-BFVP-MeLSCI, respectively.

DETECTION OF HAZARDOUS MATERIALS IN LASER CUTTING USING DEEP LEARNING AND SPECKLE SENSING

Abstract. The technology of laser cutting is widely used in various industries for processing materials. However, it generates a substantial amount of harmful dust, smoke, and aerosols, which pose a threat to the environment and endanger the health of workers. One potential method that has emerged to monitor the cutting process and identify materials in real-time is speckle sensing. This paper presents a novel material classification technique that employs a new deep-learning model architecture designed for speckle pattern images to classify materials according to the speckle patterns of the material's surface. The proposed approach involves training a convolutional neural network (CNN) on a large dataset of laser speckle patterns to recognize various material types for safe and efficient cutting. Material classification using speckle sensing enhances the process, reducing the time required to train the speckle images and the inference time for predicting the material from the speckle images. Experimental results demonstrate that the suggested method achieves high precision in categorizing materials, particularly hazardous ones. The model was evaluated on a test dataset of 3,000 new images, achieving an F1-score of 0.9781. The utilization of speckle sensing enables the proposed method to offer a fast, reliable, and accurate approach to material-aware laser cutting while mitigating the potential risks associated with the process.

Particle dispersion governs nano to bulk dynamics for tailored nanocomposite design

Nanoparticle addition can expand bioplastic use, as the resultant nanocomposite features e.g., improved mechanical properties. HypothesisIt is generally hypothesised that the nanoparticle-polymer interaction strength is pivotal to reduce polymer dynamics within the interphasial region and beyond. ExperimentsTranslating nanoscale phenomena to bulk properties is challenging, as traditional techniques that probe interphasial dynamics are limited to well-dispersed systems. Laser speckle imaging (LSI) enabled us to probe interphasial nanoscale dynamics of samples containing aggregated nanoparticles. We relate these LSI-derived relaxation times to bulk rheological properties at a micro scale. FindingsNanocomposites with well-dispersed PDMS-coated titanium dioxide nanoparticles of ∼100 nm showed higher viscosities than nanocomposites containing aggregated PVP- and PAA-coated nanoparticles of 200–2000 nm. Within the interphasial region, nanoparticle addition increased relaxation times by a factor 101–102, reaching ultraslow relaxations of ∼103 s. While the viscosity increased upon nanoparticle loading, interphasial relaxation times plateaued at 5 wt% for nanocomposites containing well-dispersed nanoparticles and 10 wt% for nanocomposites containing aggregated nanoparticles. Likely, interphasial regions between nanoparticles interact, which is more prominent in systems with well-dispersed nanoparticles and at higher loadings. Our results highlight that, contrary to general belief, nanoparticle dispersion seems of greater importance for mechanical reinforcement than the interaction between polymer and particle.

In vivo mapping of hemodynamic responses mediated by tubuloglomerular feedback in hypertensive kidneys

The kidney has a sophisticated vascular structure that performs the unique function of filtering blood and managing blood pressure. Tubuloglomerular feedback is an intra-nephron negative feedback mechanism stabilizing single-nephron blood flow, glomerular filtration rate, and tubular flow rate, which is exhibited as self-sustained oscillations in single-nephron blood flow. We report the application of multi-scale laser speckle imaging to monitor global blood flow changes across the kidney surface (low zoom) and local changes in individual microvessels (high zoom) in normotensive and spontaneously hypertensive rats in vivo. We reveal significant differences in the parameters of TGF-mediated hemodynamics and patterns of synchronization. Furthermore, systemic infusion of a glucagon-like-peptide-1 receptor agonist, a potential renoprotective agent, induces vasodilation in both groups but only alters the magnitude of the TGF in Sprague Dawleys, although the underlying mechanisms remain unclear.

Improved spatial speckle contrast model for tissue blood flow imaging: effects of spatial correlation among neighboring camera pixels.

Speckle contrast analysis is the basis of laser speckle imaging (LSI), a simple, inexpensive, noninvasive technique used in various fields of medicine and engineering. A common application of LSI is the measurement of tissue blood flow. Accurate measurement of speckle contrast is essential to correctly measure blood flow. Variables, such as speckle grain size and camera pixel size, affect the speckle pattern and thus the speckle contrast. We studied the effects of spatial correlation among adjacent camera pixels on the resulting speckle contrast values. We derived a model that accounts for the potential correlation of intensity values in the common experimental situation where the speckle grain size is larger than the camera pixel size. In vitro phantom experiments were performed to test the model. Our spatial correlation model predicts that speckle contrast first increases, then decreases as the speckle grain size increases relative to the pixel size. This decreasing trend opposes what is observed with a standard speckle contrast model that does not consider spatial correlation. Experimental data are in good agreement with the predictions of our spatial correlation model. We present a spatial correlation model that provides a more accurate measurement of speckle contrast, which should lead to improved accuracy in tissue blood flow measurements. The associated correlation factors only need to be calculated once, and open-source software is provided to assist with the calculation.

TOI-5344 b: A Saturn-like Planet Orbiting a Super-solar Metallicity M0 Dwarf

We confirm the planetary nature of TOI-5344 b as a transiting giant exoplanet around an M0-dwarf star. TOI-5344 b was discovered with the Transiting Exoplanet Survey Satellite photometry and confirmed with ground-based photometry (the Red Buttes Observatory 0.6 m telescope), radial velocity (the Habitable-zone Planet Finder), and speckle imaging (the NN-Explore Exoplanet Stellar Speckle Imager). TOI-5344 b is a Saturn-like giant planet (ρ = 0.80 g cm−3) with a planetary radius of 9.7 ± 0.5 R ⊕ (0.87 ± 0.04 R Jup) and a planetary mass of (0.42 ). It has an orbital period of days and an orbital eccentricity of . We measure a high metallicity for TOI-5344 of [Fe/H] = 0.48 ± 0.12, where the high metallicity is consistent with expectations from formation through core accretion. We compare the metallicity of the M-dwarf hosts of giant exoplanets to that of M-dwarf hosts of nongiants (≲8 R ⊕). While the two populations appear to show different metallicity distributions, quantitative tests are prohibited by various sample caveats.

Separated Twins or Just Siblings? A Multiplanet System around an M Dwarf Including a Cool Sub-Neptune

We report the discovery of two TESS sub-Neptunes orbiting the early M dwarf TOI-904 (TIC 261257684). Both exoplanets, TOI-904 b and c, were initially observed in TESS Sector 12 with twin sizes of and R ⊕, respectively. Through observations in five additional sectors in the TESS primary mission and the first and second extended missions, the orbital periods of the planets were measured to be 10.887 ± 0.001 and 83.999 ± 0.001 days, respectively. Reconnaissance radial velocity measurements (taken with EULER/CORALIE and SMARTS/CHIRON) and high-resolution speckle imaging with adaptive optics (obtained from SOAR/HRCAM and Gemini South/ZORRO) show no evidence of an eclipsing binary or a nearby companion, which, together with the low false-positive probabilities calculated with the statistical validation software TRICERATOPS, establishes the planetary nature of these candidates. The outer planet, TOI-904 c, is the longest-period M dwarf exoplanet found by TESS, with an estimated equilibrium temperature of 217 K. As the three other validated planets with comparable host stars and orbital periods were observed by Kepler around much dimmer stars (J mag > 12), TOI-904 c, orbiting a brighter star (J mag = 9.6), is the coldest M dwarf planet easily accessible for atmospheric follow-up. Future mass measurements and transmission spectroscopy of the similar-sized planets in this system could determine whether they are also similar in density and composition, suggesting a common formation pathway, or whether they have distinct origins.

Multimodal real-time imaging with laser speckle contrast and fluorescent contrast

IntroductionLaser speckle contrast imaging (LSCI) can achieve real-time 2D perfusion maps non-invasively. However, LSCI is still difficult to use in general clinical applications because of movement sensitivity and limitations in blood flow analysis. To overcome this, fluorescence imaging (FI) is combined with LSCI using a light source with a wavelength of 785 nm in near-infrared (NIR) region and validates to visualize real-time blood perfusion. Materials and methodsThe system was performed using Intralipid and indocyanine green (ICG) in a flow phantom that has three tubes and controlled the flow rate in 0–150 μl/min range. First, real-time LSCI was monitored and measured the change in speckle contrast by reperfusion. Then, we visualized blood perfusion of a rabbit ear under the non-invasive condition by intravenous injection using a total of five different ICG concentration solutions from 128 μM to 3.22 mM. ResultsThe combined system achieved the performance of processing laser speckle images at about 37–38 fps, and we simultaneously confirmed the fluorescence of ICG and changes in speckle contrast due to intralipid as a light scatterer. In addition, we obtained real-time contrast variation and fluorescent images occurring in rabbit's blood perfusion. ConclusionsThe aim of this study is to provide a real-time diagnostic imaging system that can be used in general clinical applications. LSCI and FI are combined complementary for observing tissue perfusion using a single NIR light source. The combined system could achieve real-time visualization of blood perfusion non-invasively.

Overlapping speckle correlation algorithm for high-resolution imaging and tracking of objects in unknown scattering media

Optical imaging in scattering media is important to many fields but remains challenging. Recent methods have focused on imaging through thin scattering layers or thicker scattering media with prior knowledge of the sample, but this still limits practical applications. Here, we report an imaging method named ‘speckle kinetography’ that enables high-resolution imaging in unknown scattering media with thicknesses up to about 6 transport mean free paths. Speckle kinetography non-invasively records a series of incoherent speckle images accompanied by object motion and the inherently retained object information is extracted through an overlapping speckle correlation algorithm to construct the object’s autocorrelation for imaging. Under single-colour light-emitting diode, white light, and fluorescence illumination, we experimentally demonstrate 1 μm resolution imaging and tracking of objects moving in scattering samples, while reducing the requirements for prior knowledge. We anticipate this method will enable imaging in currently inaccessible scenarios.

Intraprocedural application of a peripheral blood flow monitoring system during endovascular treatment for femoropopliteal disease

Sensors that implement laser speckle image streaming provide real-time, noninvasive assessment of peripheral blood flow during endovascular revascularization. This single-center feasibility study evaluated a laser speckle-based peripheral blood flow monitoring system in 24 patients with peripheral arterial disease. System-quantified blood flow values showed improvement at the conclusion of the procedure in 20 of 24 patients (83.3%). Of the four patients without improved flow values, waveform morphology improved in three. Waveforms graded as moderate to severe peripheral arterial disease decreased from 71% before the procedure to 25% after the procedure, with improvement in 19 of 24 patients. In this limited population, laser speckle imaging could offer a highly sensitive method of detecting intraprocedural pedal blood flow changes.

Photoacoustic speckle pattern interferometry for detecting cracks of different sizes.

A system and method for non-destructive detection of cracks of different width and depths based on digital speckle interferometry coupled with pulsed laser excitation is introduced and tested. Based on photoacoustic effect, acoustic waves are induced onto the rear of the samples by pumping a pulsed laser beam on it. The generated mechanical wave propagates from the rear surface of the sample to the front while front surface is monitored by speckle interferometry. In order to acquire information about surface deformation, the front surface is illuminated by continuous wave laser and interference are imaged onto the camera as speckle images. After processing the produced fringe patterns, it indicates the presence and location of the cracks in qualitative way. In this study, the system and method mentioned above are validated by detecting medium density fiberboard with simulated cracks. The fringe patterns from areas with or without defects are compared and discussed. Besides, the system and method to distinguish and predict cracks sizes is proposed and validated.

Two-dimensional speckle tracking imaging cardiac motion-based quantitative evaluation of global longitudinal strain among patients with coronary Heart Disease and functions of left ventricular ischemic myocardial segment.

To investigate two-dimensional speckle tracking imaging (2D-STI)-based quantitative evaluation of the influences of different levels of coronary artery stenosis on left ventricular functions and its clinical diagnostic values, 120 patients with coronary heart disease (CHD) were divided into control group (30 cases), mild stenosis group (30 cases), moderate stenosis group (30 cases), and severe stenosis group (30 cases) according to coronary angiography (CAG) results. They underwent routine ultrasound examination and 2D-STI examination. Receiver operating characteristic (ROC) curves were drawn to evaluate the sensitivity and specificity of different levels of coronary artery stenosis. Global longitudinal strain (GLS) of left ventricular myocardium among patients in moderate and severe stenosis groups remarkably declined (P < 0.05). Global radial strain (GRS) and global circular strain (GCS) among patients in severe stenosis group dramatically reduced (P < 0.05). ROC curves revealed that available GLS=-17.2 was the cut-off value for screening moderate coronary stenosis. The sensitivity, specificity, and area under the curve (AUC) amounted to 57.3%, 58.4%, and 0.573, respectively. GLS, GRS, and GCS could be used to screen severe coronary stenosis. When GLS=-16.5 was the cut-off value for screening severe coronary stenosis, sensitivity, specificity, and AUC amounted to 84.3%, 82.5%, and 0.893, respectively. With the aggravation of stenosis, left ventricular systolic function of CHD patients was impaired more significantly. 2D-STI technique could be adopted for the quantitative evaluation of left ventricular strain of patients with coronary stenosis and provided a new method for early clinical diagnosis of CHD.

Research on Recognition of Coal and Gangue Based on Laser Speckle Images.

Coal gangue image recognition is a critical technology for achieving automatic separation in coal processing, characterized by its rapid, environmentally friendly, and energy-saving nature. However, the response characteristics of coal and gangue vary greatly under different illuminance conditions, which poses challenges to the stability of feature extraction and recognition, especially when strict illuminance requirements are necessary. This leads to fluctuating coal gangue recognition accuracy in industrial environments. To address these issues and improve the accuracy and stability of image recognition under variable illuminance conditions, we propose a novel coal gangue recognition method based on laser speckle images. Firstly, we studied the inter-class separability and intra-class compactness of the collected laser speckle images of coal and gangue by extracting gray and texture features from the laser speckle images, and analyzed the performance of laser speckle images in representing the differences between coal and gangue minerals. Subsequently, coal gangue recognition was achieved using an SVM classifier based on the extracted features from the laser speckle images. The fusion feature approach achieved a recognition accuracy of 94.4%, providing further evidence of the feasibility of this method. Lastly, we conducted a comparative experiment between natural images and laser speckle images for coal gangue recognition using the same features. The average accuracy of coal gangue laser speckle image recognition under various lighting conditions is 96.7%, with a standard deviation of the recognition accuracy of 1.7%. This significantly surpasses the recognition accuracy obtained from natural coal and gangue images. The results showed that the proposed laser speckle image features can facilitate more stable coal gangue recognition with illumination factors, providing a new, reliable method for achieving accurate classification of coal and gangue in the industrial environment of mines.

Left atrial functional assessment a prime clue in solving the puzzle of stable angina symptoms in suspected coronary artery disease patients

Abstract Background Assessing clinically for significant coronary artery disease (CAD) in stable angina patients presents a formidable task. Routinely performed echocardiography is limited in diagnosing CAD with provision for the regional wall motion abnormality (RWMA) for left ventricle (LV) systolic dysfunction and altered mitral inflow velocities for LV diastolic dysfunction. However, the advent of two-dimensional (2D) speckle-tracking technique has established the era of strain imaging, opening new possibilities in echocardiography. It is now possible to have a detailed functional assessment of left atrium (LA). We utilised speckle tracking imaging to obtain strain parameters for LA function. Combining these strain parameters with the doppler myocardial velocities and mitral inflow velocities, may prove useful mode of imaging to diagnose significant CAD in stable angina patients. Purpose To study the parameters of left atrial functions utilising echocardiographic strain imaging and evaluate their correlation with the syntax score-II in patients with symptoms of stable angina. Methods 103 patients with symptoms of stable angina undergoing coronary angiography for suspected coronary artery disease(CAD), were considered for LA function assessment and compared with their syntax-II score. Results The LA reservoir function parameters, peak atrial longitudinal strain (PALS) and peak global systolic strain rate (LAsSR), decreased with increasing syntax-II score (p values 0.011 and 0.001 respectively) and the parameter of LA conduit function, peak global early diastolic strain rate (LAeSR) increased (p value &amp;lt;0.001). The LA filling pressures reflected by E/e`, also increased with more severe syntax-II score (p value &amp;lt;0.001). We, further, configured cut off values of &amp;lt; 23.56 for PALS, &amp;lt; 1.15 for LAsSR, &amp;gt; -1.09 for LAeSR, and E/e` ratio &amp;gt; 10.39 as predictors of significant CAD, with good sensitivity and specificity. Therefore, stable angina patients who had significant CAD on coronary angiogram represented by severe syntax score-II, had higher LA filling pressures and deranged LA function with transition from more of reservoir chamber to merely a conduit. Conclusion Our study shows a significant association between LA strain parameters (PALS, LAsSR, and LAeSR) and LA filling pressures (E/e`), with the presence of significant CAD in these patients. The stable angina patients with more severe CAD as quantified by their severe syntax score-II, have an impaired LA reservoir and LA functions more as a conduit, with elevated filling pressures. This study establishes a significant association between LA deformation strain variables and severity of CAD and hence LA strain imaging can be a useful tool to diagnose significant CAD in stable angina patients.

Reduced systolic flow efficacy in left ventricular dyssynchrony evident by blood speckle imaging

Abstract Introduction Intraventricular vortices facilitate efficient blood flow in a healthy heart. Changes in the blood flow pattern can cause energy loss and inefficient filling or ejection. Thus changes, or reduction in vorticity may therefore be of importance for cardiac function. Blood speckle imaging (BSI) is a novel blood flow visualization tool based on echocardiography, partially overcoming the angel dependency of conventional colour Doppler. BSI tracks speckles generated by the moving blood cells, similar to myocardial speckle tracking, but requires a very high frame rate limiting penetration. Dyssynchrony in left bundle branch block (LBBB) affects the systolic functions but there is limited insight into how LBBB alters the blood flow vorticity. Purpose We investigated the effect of dyssynchrony on blood flow hemodynamics using blood speckle imaging. Methods In eight anesthetized canine mongrels, left ventricular flow was visualized using BSI. A qualitative visual assessment of vortices during the cardiac cycle, together with a quantitative assessment based on kinetic energy loss and vorticity were made. Regional myocardial function parameters were measured by sonomicrometry. Peak septal flash strain in isovolumetric contraction (IVC) was measured by sonomicrometry (figure) as an indicator of dyssynchrony. Assessments were made at baseline, under right ventricular free wall pacing (RV pacing) mimicking LBBB, after induced LBBB by ablation and under cardiac resynchronization therapy (CRT). Results During IVC at baseline all animals had a central ventricular vortex. However during RV pacing and LBBB it was distorted in various patterns. RV pacing significantly reduced the number of vortices in systole and disrupted the central vortex in IVC (1.0±0.0 vs 0.4±0.5, p=0.01). Energy loss (EL) in systole increased (40.2±12.5 vs 55.3±23.3 mW/m, p&amp;lt;.05). Septal end systolic strain was significantly reduced (-8.8±5.1 vs -1.9±7.3 %, p&amp;lt;0.01) and septal flash strain was significantly increased (1.0±1.4 vs 7.7±3.6 and 6.6±3.8 [ER1] [ER2] %, p&amp;lt;0.01) in RV pacing and LBBB. CRT caused a realignment of the central vortex (0.8±0.5 vs0.3±0.5, p=0.03). The change in energy loss was not significant, but numerically reduced (55.4±38.8 vs 76.4±48.9 mW/m, p=0.06). See table and figure 1. Conclusions The main systolic vortex in IVC was disrupted during septal flash by RV pacing and LBBB, altering the flow pattern compared to baseline. The resultant unstructured flow pattern had increased energy loss in systole, indicating a less efficient flow pattern and less preservation of energy. It should be further explored if this is of importance to understand the reduced LV function and LV remodelling during dyssynchrony.Figure 1Table 1

Self-calibrated defocused speckle imaging for remote surface motion measurements

Defocused Speckle Imaging (DSI) is a non-contact optical method that can measure multiaxial object motions at microscopic sensitivity using a simple and mechanically robust optical setup. The object surface is illuminated by a laser beam, and the scattered interference speckle pattern is tracked with a defocused camera. DSI measurement sensitivity increases with distance, and the sensitivity can be tuned by simple camera defocus adjustment. These characteristics make DSI an attractive choice for tracking remote objects in field conditions. However, the use of DSI for practical measurements is limited because the speckle signals due to linear and rotational surface motions mix together, and because the instrument calibration requires accurate object range and surface orientation parameters.To address these issues, the work described here combines two recently presented concepts: 1) a defocused camera pair, and 2) a diffraction-based self-calibration principle. The proposed approach was demonstrated by a series of self-calibrated multiaxial motion measurements performed at an extended (30.7-m) distance. The studied motions included in-plane displacements and out-of-plane rotations (tilts), whereas out-of-plane displacements and in-plane rotations were excluded. The experiments showed DSI's capability for high tilt sensitivity down to 0.0006°, standalone remote angle measurements, and suitability for retroreflective surfaces. The diffraction-based self-calibration approach could monitor sampling distances at a 6.4 % accuracy and the relative surface angles of 2.5–7.4° at a 0.2° accuracy. The defocused camera pair tracked microscopic in-plane displacements (400 µm) and very fine out-of-plane tilts (0.003°) at a high accuracy, with a maximum uncertainty of 6.0 %.The proposed DSI approach is particularly suited for monitoring large objects and for operating in hazardous environments. The findings pave a way for interesting new applications, like high-range remote angle measurements, high-sensitivity straightness measurements, and 3D-positioning utilizing retroreflective markers that already exist in the built infrastructure.

Abstract 108: Mitochondria-Targeted S-Nitrosothiol MitoSNO Improves Neurological Recovery and Survival After Asphyxial Cardiac Arrest in Rats

Introduction: Mitochondria-targeted S-nitrosothiol MitoSNO offers protection against ischemia-reperfusion injury by attenuating the reverse electron transport of mitochondrial complex I during reperfusion. This study aimed to assess whether administration of MitoSNO after ROSC improves neurological and survival outcomes following cardiac arrest (CA). Methods: Adult male rats were subjected to 10 minute of asphyxial CA followed by mechanical ventilation and manual CPR. After successful CPR, animals were assigned to one of two experimental groups: receiving respiration buffer as a vehicle or MitoSNO (100 ng per dose). Based on our preliminary study, two doses of each drug were intravenously injected via femoral vein: immediately after ROSC and at 60 minutes post-ROSC. The survival time and neurological function score (NFS) were recorded for up to 72 h. Surgery, CPR, drug injections, echocardiography, and immunohistochemistry were performed in a blind manner. Results: MitoSNO significantly improved NFS and survival rate ( Fig A ). Echocardiography revealed that MitoSNO improved left ventricular ejection fraction 2 h post-ROSC compared to the vehicle. In another set of experiments, relative cerebral blood flow (rCBF) compared to baseline was invasively monitored at 2 h post-CA using a laser speckle imaging. The imaging showed CA caused a reduction in rCBF 2 h post-CA in the vehicle group, which was markedly improved by MitoSNO ( Fig B ). Western blotting assay showed, in brain 2 h post-CA, MitoSNO significantly mitigated protein levels of 3-NT, a marker for nitrogen free radical-modified proteins, and cleaved Caspase-3, an indicator of programmed cell death. Immunohistochemistry revealed that MitoSNO suppressed neuronal degeneration in vulnerable brain regions of surviving animals. Conclusions: Our study demonstrated that MitoSNO inhibited the production of oxidative stress in the brain and improved neurological and survival outcomes following CA in rats.

Light Scattering through a Drying Coating

Drying coatings undergo internal dynamic densification and rearrangement, which are challenging to discern with optical techniques due to their multiple scatterings of light. Experiments such as diffusing wave spectroscopy (DWS) and laser speckle imaging (LSI) leverage these multiple scatterings to reveal the in situ dynamics of the coating. In such experiments, the knowledge of the sample volume that can be accessed and therefore studied is fundamental, especially in cases of micrometer-scale coating thicknesses. In this paper, we present a robust and reliable method using transmission geometry to calculate the parameter l*, defined as the transport light mean-free path, which is strongly related to the volume of the sample that light explores in DWS and LSI experiments. We show how this dynamic parameter can be measured for liquid and solid film samples and, crucially, in the case of time-evolving samples, such as drying coatings of paint or ink, which has not been previously explored. We present a series of model ink samples and discuss the evolution of their densification during drying through quantification of dynamic l*.