. Significance: Intraoperative parameters of renal cortical microperfusion (RCM) have been associated with postoperative ischemia/reperfusion injury. Laser speckle contrast imaging (LSCI) could provide valuable information in this regard with the advantage over the current standard of care of being a non-contact and full-field imaging technique. Aim: Our study aims to validate the use of LSCI for the visualization of RCM on ex vivo perfused human-sized porcine kidneys in various models of hemodynamic changes. Approach: A comparison was made between three renal perfusion measures: LSCI, the total arterial renal blood flow (RBF), and sidestream dark-field (SDF) imaging in different settings of ischemia/reperfusion. Results: LSCI showed a good correlation with RBF for the reperfusion experiment ( ; ) and short- and long-lasting local ischemia ( ; and ; , respectively). The correlation decreased for low flow situations due to RBF redistribution. The correlation between LSCI and SDF ( ; ) showed superiority over RBF ( ; ). Conclusions: LSCI is capable of imaging RCM with high spatial and temporal resolutions. It can instantaneously detect local perfusion deficits, which is not possible with the current standard of care. Further development of LSCI in transplant surgery could help with clinical decision making.
Background Ischemia at the site of an intestinal anastomosis is one of the most important risk factors for anastomotic leakage (AL). Consequently, adequate intestinal microperfusion is essential for optimal tissue oxygenation and anastomotic healing. As visual inspection of tissue viability does not guarantee an adequate objective evaluation of intestinal microperfusion, surgeons are in dire need of supportive tools to decrease anastomotic leakage after colorectal surgery. Methods In this feasibility study, laparoscopic laser speckle contrast imaging (LSCI) was used to evaluate intestinal microperfusion in an experimental ischemic bowel loop model. Both large and small ischemic loops were created from the small intestine of a pig; each loop was divided into 5 regions of interest (ROI) with varying levels of ischemia. Speckle contrast and local capillary lactate (LCL) was measured in all ROIs. Results Both real-time visualization of intestinal microperfusion and induced perfusion deficits was achieved in all bowel loops. As a result, the emergence of regions of intestinal ischemia could be predicted directly after iatrogenic perfusion limitation, whereas without LSCI signs of decreased intestinal viability could only be seen after 30 minutes. Additionally, a significant relation was found between LCL and LSCI. Conclusion In conclusion, LSCI can achieve real-time intraoperative visualization of intestinal microperfusion deficits, allowing for accurate prediction of long-term postoperative ischemic complications. With this revealing capacity, LSCI could potentially facilitate surgical decision-making when constructing intestinal anastomoses in order to mitigate ischemia-related complications such as AL.
Reversible amorphous–crystalline phase transitions are studied using complementary ultrafast differential scanning calorimetry and transmission electron microscopy techniques, which together allow a wealth of thermal and structural properties to be determined. The SeTe(As) system is investigated because these chalcogenide based materials have favorable properties as a phase-change memory material and in optical systems. Using calorimetry, we find that the addition of 10 at. % As to SeTe alloys strongly increases their glass forming ability, increasing both glass transition and crystallization temperatures while reducing critical quench rate. Ex situ investigation of SexTe90–xAs10 using electron microscopy and elemental mapping reveals a two-phase lamellar segregation mechanism, where a trigonal SeTe-phase and an amorphous As-rich phase are formed. These findings demonstrate the power of combining thermal and structural analysis techniques.
IntroductionOur aim is to develop a novel approach to hyperkinetic movement disorder classification, that combines clinical information, electromyography, accelerometry and video in a computer-aided classification tool. We see this as the next step towards rapid and accurate phenotype classification, the cornerstone of both the diagnostic and treatment process.Methods and analysisThe Next Move in Movement Disorders (NEMO) study is a cross-sectional study at Expertise Centre Movement Disorders Groningen, University Medical Centre Groningen. It comprises patients with single and mixed phenotype movement disorders. Single phenotype groups will first include dystonia, myoclonus and tremor, and then chorea, tics, ataxia and spasticity. Mixed phenotypes are myoclonus-dystonia, dystonic tremor, myoclonus ataxia and jerky/tremulous functional movement disorders. Groups will contain 20 patients, or 40 healthy participants. The gold standard for inclusion consists of interobserver agreement on the phenotype among three independent clinical experts. Electromyography, accelerometry and three-dimensional video data will be recorded during performance of a set of movement tasks, chosen by a team of specialists to elicit movement disorders. These data will serve as input for the machine learning algorithm. Labels for supervised learning are provided by the expert-based classification, allowing the algorithm to learn to predict what the output label should be when given new input data. Methods using manually engineered features based on existing clinical knowledge will be used, as well as deep learning methods which can detect relevant and possibly new features. Finally, we will employ visual analytics to visualise how the classification algorithm arrives at its decision.Ethics and disseminationEthical approval has been obtained from the relevant local ethics committee. The NEMO study is designed to pioneer the application of machine learning of movement disorders. We expect to publish articles in multiple related fields of research and patients will be informed of important results via patient associations and press releases.
Laser speckle contrast imaging (LSCI) is so sensitive to motion that it can measure the movement of red blood cells. However, this extreme sensitivity to motion is also its pitfall as the clinical translation of LSCI is slowed down due to the inability to deal with motion artefacts. In this paper we study the effectiveness of a real-time, multi-spectral motion artefact correction and compensation by subduing an in vitro flow phantom and ex vivo porcine kidney to computer-controlled motion artefacts. On the in vitro flow phantom, the optical flow showed a good correlation with the total movement. This model results in a better signal-to-noise ratios for multiple imaging distances and the overestimation of perfusion was reduced. In the ex vivo kidney model, the perfusion overestimation was also reduced and we were still able to distinguish between ischemia and non-ischemia in the stabilized data whereas this was not possible in the non-stabilized data. This leads to a notably better perfusion estimation that could open the door to a multitude of new clinical applications for LSCI.
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