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.

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.

Constructing a Transient Ischemia Attack Model Utilizing Flexible Spatial Targeting Photothrombosis with Real-Time Blood Flow Imaging Feedback.

Transient ischemic attack (TIA) is an early warning sign of stroke and death, necessitating suitable animal models due to the associated clinical diagnostic challenges. In this study, we developed a TIA model using flexible spatially targeted photothrombosis combined with real-time blood flow imaging feedback. By modulating the excitation light using wavefront technology, we precisely created a square light spot (50 × 250 µm), targeted at the distal middle cerebral artery (dMCA). The use of laser speckle contrast imaging (LSCI) provided real-time feedback on the ischemia, while the excitation light was ceased upon reaching complete occlusion. Our results demonstrated that the photothrombus formed in the dMCA and spontaneously recanalized within 10 min (416.8 ± 96.4 s), with no sensorimotor deficits or infarction 24 h post-TIA. During the acute phase, ischemic spreading depression occurred in the ipsilateral dorsal cortex, leading to more severe ischemia and collateral circulation establishment synchronized with the onset of dMCA narrowing. Post-reperfusion, the thrombi were primarily in the sensorimotor and visual cortex, disappearing within 24 h. The blood flow changes in the dMCA were more indicative of cortical ischemic conditions than diameter changes. Our method successfully establishes a photochemical TIA model based on the dMCA, allowing for the dynamic observation and control of thrombus formation and recanalization and enabling real-time monitoring of the impacts on cerebral blood flow during the acute phase of TIA.

Multi-Scale-Denoising Residual Convolutional Network for Retinal Disease Classification Using OCT.

Macular pathologies can cause significant vision loss. Optical coherence tomography (OCT) images of the retina can assist ophthalmologists in diagnosing macular diseases. Traditional deep learning networks for retinal disease classification cannot extract discriminative features under strong noise conditions in OCT images. To address this issue, we propose a multi-scale-denoising residual convolutional network (MS-DRCN) for classifying retinal diseases. Specifically, the MS-DRCN includes a soft-denoising block (SDB), a multi-scale context block (MCB), and a feature fusion block (FFB). The SDB can determine the threshold for soft thresholding automatically, which removes speckle noise features efficiently. The MCB is designed to capture multi-scale context information and strengthen extracted features. The FFB is dedicated to integrating high-resolution and low-resolution features to precisely identify variable lesion areas. Our approach achieved classification accuracies of 96.4% and 96.5% on the OCT2017 and OCT-C4 public datasets, respectively, outperforming other classification methods. To evaluate the robustness of our method, we introduced Gaussian noise and speckle noise with varying PSNRs into the test set of the OCT2017 dataset. The results of our anti-noise experiments demonstrate that our approach exhibits superior robustness compared with other methods, yielding accuracy improvements ranging from 0.6% to 2.9% when compared with ResNet under various PSNR noise conditions.

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.

Predictive value of preoperative handgrip strength on postoperative outcomes in patients with gastrointestinal tumors: a systematic review and meta-analysis.

PURPOSE: This systematic review and meta-analysis aimed to explore the predictive value of preoperative handgrip strength on postoperative outcomes in patients with gastrointestinal tumors. METHODS: Databases including Cochrane Library, Pubmed, Embase, Web of Science, and CINAHL Complete were searched for articles published from the establishment of database until August 7, 2021. Two researchers independently screened the literature, extracted the data, and evaluated the quality. RESULTS: Eight studies were included, involving five prospective and three retrospective cohort studies with 2291 participants. The prevalence of preoperative low handgrip strength ranged from 11.8 to 62.7%. Preoperative low handgrip strength was associated with an increased risk of total complications (OR = 2.23, 95%CI = 1.43-3.50), pneumonia (OR = 5.16, 95%CI = 3.17-8.38), ileus (OR = 2.48, 95%CI = 1.09-5.65), and short-term mortality (OR = 7.28, 95%CI = 1.90-27.92). CONCLUSION: This systematic review and meta-analysis indicated that preoperative HGS had important value to predict certain adverse postoperative outcomes among patients with GI tumors. Low handgrip strength criteria, definition of total complications, and country are the potential sources of heterogeneity, and more research are required to test and update these results.

Cortical spreading depression induces propagating activation of the thalamus ventral posteromedial nucleus in awake mice.

BACKGROUND: As the relay centre for processing sensory information, the thalamus may involve in the abnormal sensory procedure caused by cortical spreading depression (CSD). However, few studies have focused on the transient response of thalamus during CSD. Our study aimed to investigate the neuronal activity of mouse thalamus ventral posteromedial nucleus (VPM) during CSD by in vivo micro-endoscopic fluorescence imaging of the genetic calcium probe GCaMP6s expressed in excitatory glutamatergic neurons. METHODS: Thirty-four transgenic VGluT2-GCaMP6s mice were used in the experiments. An endoscope was inserted into the VPM for image acquisition. CSD was induced by KCl topically applied unilaterally on the cranial dura. Data were acquired in awake (ipsilateral or contralateral VPM, saline instead of KCl, MK-801 treatment) and anaesthetized (isoflurane, pentobarbital) states. Statistical analysis was performed using analysis of variance (ANOVA) by SPSS. RESULTS: We found that after CSD induced in ipsilateral motor cortex, the neuronal activity increased and propagated from the posterior-lateral to the anterior-medial part of the VPM with an average speed of 3.47 mm/min. When CSD was induced in visual cortex, the response propagated in opposite direction, from the anterior-medial to the posterior-lateral part of the VPM. Aanaesthetics resulted in the suppression of VPM activation induced by CSD. No significant VPM activation was detected when CSD was induced in contralateral cortex or KCl was replaced by saline. When 5 mM MK-801 was applied to the dura, the electrode failed to record the DC shift of CSD, and there was no significant VPM activation after KCl application. CONCLUSION: CSD induced propagating activation of the ipsilateral VPM in awake mice. The response might correlate to the cortical location where CSD was induced and might be affected by anaesthetics. No significant VPM activation was detected in saline and mk801 experiment results indicated that this VPM activation is due to CSD rather than mouse motion or direct effect of the KCl applying to the intact dura. This finding suggests the potential involvement of thalamus in the migraine auras.

Quantitative laser speckle auto-inverse covariance imaging for robust estimation of blood flow.

We present a quantitative model to provide robust estimation of the decorrelation time using laser speckle auto-inverse covariance. It has the advantages of independence from the statistical sample size, speckle size, static scattering, and detector noise. We have shown cerebral blood flow imaging through an intact mouse skull using this model. Phantom experiments and two animal models, middle cerebral artery occlusion, and cortical spreading depression were used to evaluate its performance.

Risk factors and the utility of three different kinds of prediction models for postoperative fatigue after gastrointestinal tumor surgery.

BACKGROUND: Postoperative fatigue (POF) is a common complication after gastrointestinal tumor surgery, and it also brings negative effect on prognosis and life quality. However, there are no prediction models for POF, and studies of risk factors are not comprehensive. Therefore, the aim of this study is to investigate the risk factors and pick out the best prediction model for POF and to validate it. METHODS: A prospective study was conducted for patients undergoing elective gastrointestinal tumor surgery. Physiological, psychological, and socioeconomic factors were collected. Logistic regression, back-propagation artificial neural networks (BP-ANNs), and classification and regression tree (CART) were constructed and compared. RESULTS: A total of 598 patients consisting of 463 derivation sample and 135 validation sample were included. The incidence of POF in derivation sample, validation sample, and total were 58.3%, 57.0%, and 58.7%, respectively. Logistic regression results showed age, higher degree of education, lower personal monthly income, advanced cancer, hypoproteinemia, preoperative anxiety or depression, and limited social support were risk factors for POF. Receiver operating characteristic curve (ROC) and performance indices were used to test three models. BP-ANN was the best by the comparison of models, and its strong predictive performance was also validated. CONCLUSIONS: More attention should be paid on specific patients after gastrointestinal tumor surgery. BP-ANN is a powerful mathematical tool that could predict POF exactly. It may be used as a noninvasive screening tool to guide clinicians for early identification of high-risk patients and grading interventions.

Elastography with low-frame-rate laser speckle contrast imaging using the aliasing effect.

Elastography is an attractive technique for quantifying the mechanical properties of biological tissue. Here, we report an elastography method with low-frame-rate laser speckle contrast imaging (LSCI) using the aliasing effect. This method needs only one excitation source, a low-frame-rate camera, and no synchronization between excitation and acquisition. The accuracy of the elasticity measurement was validated on tissue-mimicking phantoms by comparing the value with the elasticity measured by a high-frame-rate LSCI and by the rheometer. Elastography was also performed on chicken breast in vitro.

Simultaneous viscosity and elasticity measurement using laser speckle contrast imaging.

Viscosity and elasticity are closely related to the physiological characteristics of biological tissues. This Letter reports a simultaneous quantitative measurement of these parameters realized with the laser speckle contrast imaging method. The propagation of a Rayleigh wave induced by an acoustic speaker is traced, and the frequency-dependent velocity dispersion is extracted with the frequency-wavenumber spectrum analysis method. The viscosity and elasticity moduli of oil-in-gelatin tissue-mimicking phantoms are calculated by fitting the dispersion curves to the Voigt model. The method is validated by comparing it with the results obtained by using a conventional mechanical rheometer.

Selective photoactivation of neural activity combined with laser speckle imaging of cerebral blood flow.

Neural activity leads to alterations in cerebral blood flow (CBF), i.e., neurovascular regulation, which is implicated in brain physiology and pathology. Here a method for simultaneous imaging of CBF and spatially selective photoactivation of neural activity is proposed. CBF was obtained by laser speckle contrast imaging, and a liquid-crystal spatial light modulator (LC-SLM) was used to generate photoactivation patterns targeting designated locations in the cortex. Animal experiments stimulating defined cortical regions of VGAT-ChR2 and wild-type mice were conducted, and experiments with low-intensity stimulation were performed to investigate the influence of background light produced by the LC-SLM.

Laser speckle contrast imaging of blood flow in the deep brain using microendoscopy.

Poor blood flow circulation can occur in the subcortical regions of the brain in many brain diseases. However, the limitations of light penetration imaging techniques hinder the detection of blood flow in deep brain tissues in vivo. Hence, in this Letter, we present a gradient index lens-based laser speckle contrast imaging system for time-lapse blood flow detection in subcortical regions of the brain. We monitored the hemodynamic changes in the thalamus of mouse models of acute hypoxia and transient middle cerebral artery occlusion as a proof of concept for practical applications.

Improving the sensitivity of velocity measurements in laser speckle contrast imaging using a noise correction method.

We demonstrate that noise is an important factor contributing to the decline of sensitivity and linear response range of velocity measurements for laser speckle contrast imaging. We propose to use a noise correction method to improve the sensitivity of velocity measurements. For a kind of camera in which the mean values of the dark noise have been subtracted and negative counts have been set to zero, we propose a method to estimate the true dark noise based on the maximum likelihood estimation, which expands the application scope of the noise correction method.

Improving the estimation of flow speed for laser speckle imaging with single exposure time.

Laser speckle contrast imaging is a full-field imaging technique for measuring blood flow by mapping the speckle contrast with high spatial and temporal resolution. However, the statically scattered light from stationary tissues seriously degrades the accuracy of flow speed estimation. In this Letter, we present a simple calibration approach to calculate the proportions of dynamically scattered light and correct the effect of static scattering with single exposure time. Both the phantom and animal experimental results suggest that this calibration approach has the ability to improve the estimation of the relative blood flow in the presence of static scattering.

Detecting relative speed changes of moving objects through scattering medium by using wavefront shaping and laser speckle contrast analysis.

Imaging through a scattering medium has been a main challenge in modern optical imaging field. Recently, imaging through scattering medium based on wavefront shaping has been reported. However, it has not been clearly investigated to apply the optical memory effect based iterative wavefront shaping technique in speed estimation of a moving object through scattering medium. Here, we proposed to combine the iterative wavefront shaping technique with laser speckle contrast analysis method to detect the relative speed changes of moving objects through scattering medium. Phantom experiments were performed to validate our method.

Novel systems for dynamically assessing insulin action in live cells reveals heterogeneity in the insulin response.

Regulated GLUT4 trafficking is a key action of insulin. Quantitative stepwise analysis of this process provides a powerful tool for pinpointing regulatory nodes that contribute to insulin regulation and insulin resistance. We describe a novel GLUT4 construct and workflow for the streamlined dissection of GLUT4 trafficking; from simple high throughput screens to high resolution analyses of individual vesicles. We reveal single cell heterogeneity in insulin action highlighting the utility of this approach - each cell displayed a unique and highly reproducible insulin response, implying that each cell is hard-wired to produce a specific output in response to a given stimulus. These data highlight that the response of a cell population to insulin is underpinned by extensive heterogeneity at the single cell level. This heterogeneity is pre-programmed within each cell and is not the result of intracellular stochastic events.

Coherent slow cortical potentials reveal a superior localization of resting-state functional connectivity using voltage-sensitive dye imaging.

The resting-state functional connectivity (RSFC) of spontaneous hemodynamic fluctuations is widely used to investigate large-scale functional brain networks based on neurovascular mechanisms. However, high-resolution RSFC networks based on neural activity have not been disclosed to explore the neural basis of these spontaneous hemodynamic signals. The present study examines the neural RSFC networks in mice at high spatial resolution using optical imaging with voltage-sensitive dyes (VSDs). Our results show that neural RSFC networks for the slow cortical potentials (0.1-4Hz) showed similar correlation patterns to the RSFC networks for the spontaneous hemodynamic signals, indicating a tight coupling between the slow cortical potential and the spontaneous hemodynamic signals during rest, but the bilateral symmetry of the RSFC networks for the slow cortical potentials was significantly lower than that for the spontaneous hemodynamic signals. Moreover, similar asymmetric neural activation patterns could also be found between the bilateral cortexes after stimulating the paws of mice. By increasing anesthetic levels to induce the reduction of consciousness, the RSFC networks for the slow cortical potentials persisted, but those for the spontaneous hemodynamic signals became discrete. These results suggest that the coherent slow cortical potentials underlie the spontaneous hemodynamic fluctuations and reveal a superior localization of RSFC networks. VSD imaging may potentially be used to examine the RSFC of neural activity, particularly under conditions of impaired neurovascular coupling.

Effectiveness of mind-body interventions in labour pain management during normal delivery: A systematic review and meta-analysis.

BACKGROUND: Labour pain is a common experience among women and poses risks to both the mother and neonate. Mind-body interventions have demonstrated effectiveness in diverse contexts, but their effectiveness in labour pain management remains controversial. OBJECTIVE: To identify the effects of each category of mind-body interventions on labour pain management, particularly pain intensity; the use of pharmacological pain relief medications; and the consequent outcomes, including the rate of caesarean section, duration of labour, and fear of childbirth. DESIGN: Systematic review and meta-analysis. METHODS: A systematic search for related articles was conducted in 10 databases. Randomised controlled trials focusing on the effectiveness of mind-body interventions in labour pain management were included. Two researchers independently conducted methodological quality assessments, data extraction and grading the evidence. Meta-analyses were conducted when studies measured the same outcomes. Standardised mean differences were calculated for continuous variables, whilst risk ratios were calculated for dichotomous variables. All analyses were performed using RevMan version 5.3. RESULTS: A total of 25 studies from 24 trials were included, and six categories of mind-body interventions, namely hypnosis, mindfulness, breathing skills, muscle relaxation techniques, guided imagery, and therapeutic touch, were identified. Specifically, hypnosis and mindfulness might be effective in relieving labour pain intensity, with large effect sizes (SMD: -1.45, 95 % confidence interval [CI] -2.34, -0.55, I2 = 91 %; SMD: -1.22, 95 % CI -2.07, -0.37, I2 = 93 %, respectively), but could not reduce the use of epidural analgesia. Mindfulness, in particular, yielded statistically significant reductions in the rate of caesarean section, with a small effect size (RR: 0.46, 95 % CI 0.21, 0.97, I2 = 49 %), and in fear of childbirth, with a medium effect size (SMD: -0.63, 95 % CI -1.09, -0.17, I2 = 65 %). Additionally, all categories of mind-body interventions were associated with a significantly decreased duration of labour compared with the control conditions. CONCLUSIONS: Mind-body interventions may have potential benefits in terms of decreasing labour pain intensity, the rate of caesarean section, the duration of labour, and fear of childbirth, with small-to-large effect sizes. Particularly, hypnosis and mindfulness exhibited significant positive effects in terms of relieving labour pain intensity, with large effect sizes. These interventions could serve as complementary or alternative methods for labour pain management in clinical practice. Nevertheless, further rigorous randomised controlled trials are warranted to confirm our results. REGISTRATION: CRD42024498600 (PROSPERO, January 15, 2024).

Repairing the in situ hybridization missing data in the hippocampus region by using a 3D residual U-Net model.

The hippocampus is a critical brain region. Transcriptome data provides valuable insights into the structure and function of the hippocampus at the gene level. However, transcriptome data is often incomplete. To address this issue, we use the convolutional neural network model to repair the missing voxels in the hippocampus region, based on Allen institute coronal slices in situ hybridization (ISH) dataset. Moreover, we analyze the gene expression correlation between coronal and sagittal dataset in the hippocampus region. The results demonstrated that the trend of gene expression correlation between the coronal and sagittal datasets remained consistent following the repair of missing data in the coronal ISH dataset. In the last, we use repaired ISH dataset to identify novel genes specific to hippocampal subregions. Our findings demonstrate the accuracy and effectiveness of using deep learning method to repair ISH missing data. After being repaired, ISH has the potential to improve our comprehension of the hippocampus's structure and function.