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There is a shortage of donor livers and patients consequently die on waiting lists worldwide. Livers are discarded if they are clinically judged to have a high risk of non-function following transplantation. With the aim of extending the pool of available donor livers, we assessed the condition of porcine livers by monitoring the microwave dielectric properties. A total of 21 livers were divided into three groups: control with no injury (CON), biliary injury by hepatic artery occlusion (AHEP), and overall hepatic injury by static cold storage (SCS). All were monitored for four hours in vivo, followed by ex vivo plurithermic machine perfusion (PMP). Permittivity data was modeled with a two-pole Cole-Cole equation, and dielectric properties from one-hour intervals were analyzed during in vivo and normothermic machine perfusion (NMP). A clear increasing trend in the conductivity was observed in vivo in the AHEP livers compared to the control livers. After four hours of NMP, separations in the conductivity were observed between the three groups. Our results indicate that dielectric relaxation spectroscopy (DRS) can be used to detect and differentiate liver injuries, opening for a standardized and reliable point of evaluation for livers prior to transplantation.

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Intestinal ischemia is a serious condition where the surgeon often has to make important but difficult decisions regarding resections and resection margins. Previous studies have shown that 3 h (hours) of warm full ischemia of the small bowel followed by reperfusion appears to be the upper limit for viability in the porcine mesenteric ischemia model. However, the critical transition between 3 to 4 h of ischemic injury can be nearly impossible to distinguish intraoperatively based on standard clinical methods. In this study, permittivity data from porcine intestine was used to analyze the characteristics of various degrees of ischemia/reperfusion injury. Our results show that dielectric relaxation spectroscopy can be used to assess intestinal viability. The dielectric constant and conductivity showed clear differences between healthy, ischemic and reperfused intestinal segments. This indicates that dielectric parameters can be used to characterize different intestinal conditions. In addition, machine learning models were employed to classify viable and non-viable segments based on frequency dependent dielectric properties of the intestinal tissue, providing a method for fast and accurate intraoperative surgical decision-making. An average classification accuracy of 98.7% was obtained using only permittivity data measured during ischemia, and 96.2% was obtained with data measured during reperfusion. The proposed approach allows the surgeon to get accurate evaluation from the trained machine learning model by performing one single measurement on an intestinal segment where the viability state is questionable.

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Electrical impedance spectroscopy is a well-established tool for monitoring changes in the electrical properties of tissue. Most tissue and organ types have been investigated in various studies. As for the small intestine, there are several published studies conducted on pig and rat models. This study investigates the changes in passive electrical properties of the complete wall of the human intestine non-invasively during ischemia. We aim to use the passive electrical properties to assess intestinal viability. The bioimpedance measurements were performed using a two-electrode set-up with a Solartron 1260 Impedance/gain-phase analyser. The small intestinal samples were resected from patients who underwent pancreaticoduodenectomy. Impedance measurements were conducted following resection by placing the electrodes on the surface of the intestine. A voltage was applied across the intestinal sample and the measured electrical impedance was obtained in the ZPlot software. Impedance data were further fitted into a Cole model to obtain the Cole parameters. The Py value was calculated from the extracted Cole parameters and used to assess the cell membrane integrity, thus evaluate the intestinal viability. Eight small intestinal segments from different patients were used in this study and impedance measurements were performed once an hour for a ten-hour period. One hour after resection, the impedance decreased, then increased the next two hours, before decreasing until the end of the experiment. For all the intestinal segments, the Py values first increased and reached a plateau which lasted for 1 - 2 hours, before it decreased irreversibly. The time interval where Py value reached the maximum is consistent with reported viable/non-viable limits from histological analysis.

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Acute intestinal ischemia is a life-threatening condition. The current gold standard, with evaluation based on visual and tactile sensation, has low specificity. In this study, we explore the feasibility of using machine learning models on images of the intestine, to assess small intestinal viability. A digital microscope was used to acquire images of the jejunum in 10 pigs. Ischemic segments were created by local clamping (approximately 30 cm in width) of small arteries and veins in the mesentery and reperfusion was initiated by releasing the clamps. A series of images were acquired once an hour on the surface of each of the segments. The convolutional neural network (CNN) has previously been used to classify medical images, while knowledge is lacking whether CNNs have potential to classify ischemia-reperfusion injury on the small intestine. We compared how different deep learning models perform for this task. Moreover, the Shapley additive explanations (SHAP) method within explainable artificial intelligence (AI) was used to identify features that the model utilizes as important in classification of different ischemic injury degrees. To be able to assess to what extent we can trust our deep learning model decisions is critical in a clinical setting. A probabilistic model Bayesian CNN was implemented to estimate the model uncertainty which provides a confidence measure of our model decisions.

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Importance: During monopolar electrosurgery in patients, current paths can be influenced by metal implants, which can cause unintentional tissue heating in proximity to implants. Guidelines concerning electrosurgery and active implants such as pacemakers or implantable cardioverter defibrillators have been published, but most describe interference between electrosurgery and the active implant rather than the risk of unintended tissue heating. Tissue heating in proximity to implants during electrosurgery may cause an increased risk of patient injury. Objective: To determine the temperature of tissue close to metal implants during electrosurgery in an in-vitro model. Design, Setting, and Participants: Thirty tissue samples (15 with a metal implant placed in center, 15 controls without implant) were placed in an in vitro measurement chamber. Electrosurgery was applied at 5-60 W with the active electrode at three defined distances from the implant while temperatures at four defined distances from the implant were measured using fiber-optic sensors. Main Outcomes and Measures: Tissue temperature increase at the four tissue sites was determined for all power levels and each of the electrode-to-implant distances. Based on a linear mixed effects model analysis, the primary outcomes were the difference in temperature increase between implant and control tissue, and the estimated temperature increase per watt per minute. Results: Tissues with an implant had higher temperature increases than controls at all power levels after 1 min of applied electrosurgery (mean difference of 0.16°C at 5 W, 0.50°C at 15 W, 1.11°C at 30 W, and 2.22°C at 60 W, all with p < 0.001). Temperature increase close to the implant was estimated to be 0.088°C/W/min (95% CI: 0.078-0.099°C/W/min; p < 0.001). Temperature could increase to above 43°C after 1 min of 60 W. Active electrode position had no significant effect on temperature increases for tissues with implant (p = 0.6). Conclusions and Relevance: The temperature of tissue close to a metal implant increases with passing electrosurgery current. There is a significant risk of high tissue temperature when long activation times or high power levels are used.

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Over the last four decades, there has been a pursuit for a non-invasive solution for glucose measurement, but there is not yet any viable product released. Of the many sensor modalities tried, the combination of electrical and optical measurement is among the most promising for continuous measurements. Although non-invasive prediction of exact glucose levels may seem futile, prediction of their trends may be useful for certain applications. Hypoglycemia is the most serious of the acute complications in type-1 diabetes highlighting the need for a reliable alarm, but little is known about the performance of this technology in predicting hypoglycemic glucose levels and associated trends. We aimed to assess such performance on the way to develop a multisensor system for detection of hypoglycemia, based on near-infrared (NIR), bioimpedance and skin temperature measurements taken during hypoglycemic and euglycemic glucose clamps in 20 subjects with type-1 diabetes. Performance of blood glucose prediction was assessed by global partial least squares and neural network regression models using repeated double cross-validation. Best trend prediction was obtained by including all measurements in a neural network model. Prediction of glucose level was inaccurate for threshold-based detection of hypoglycemia, but the trend predictions may provide useful information in a multisensor system. Comparing NIR and bioimpedance measurements, NIR seems to be the main predictor of blood glucose while bioimpedance may act as correction for individual confounding properties.

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Impedance cardiography (ICG) is a non-invasive method of hemodynamic measurement, mostly known for estimation of stroke volume and cardiac output based on characteristic features of the signal. Compared with electrocardiography, the knowledge on the morphology of the ICG signal is scarce, especially with respect to age-dependent changes in ICG waveforms. Based on recordings from ten younger (20-29 years) and ten older (60-79) healthy human subjects after three different levels of physical activity, the typical interbeat ICG waveforms were derived based on ensemble averages. Comparison of these waveforms between the age groups indicates the following differences: a later initial upward deflection for the younger group, an additional hump in the waveform from many older subjects not presented in the younger group, and a more pronounced second wave in the younger group. The explanation for these differences is not clear, but may be related to arterial stiffness. Further studies are suggested to determine whether these morphological differences have clinical value.

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In coronary artery bypass grafting there is a risk of graft occlusion which may result in myocardial infarction. A three-axis acceleration sensor may give additional information about heart function during surgery and the first postoperative days. This paper describes the assembly and packaging of a three-axis micro acceleration sensor for use in clinical trials. The sensor was connected to a cable for power supply and signal output and moulded in silicone. Testing of the encapsulation showed leakage currents well below the 10 muA limit for direct cardiac applications. A hydrogen peroxide gas plasma method was used for sterilization. In animal experiments the sensor was sutured to the heart and no fatigue failures ensued due to the cycling strain forces from the heart. The sensor has been qualified for clinical trials.

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The Wireless Sensors in Healthcare Project focused on the implementation of wireless technology in healthcare. Wireless biomedical sensors for monitoring of continuous invasive arterial blood pressure were developed and evaluated under controlled conditions during laparoscopic surgery. The project has resulted in the first publication of clinical use of a wireless biomedical sensor for invasive measurement of arterial blood pressure in a pilot study. A second demonstrator for wireless clinical decision support based on the first demonstrator was developed. Wireless technologies used were Bluetooth, wireless local area network and GPRS/mobile telephones. Further research is needed to evaluate the wireless clinical decision support system. Critical care nurses and nurse anesthetists are potential users of wireless technology. Their clinical expertise is important in development of-, and future use of wireless technology.

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Arterial blood carbon dioxide tension (PaCO2) during cardiopulmonary bypass (CBP) is important to the conduct of perfusion with alpha-stat or pH-stat strategy. Temperature changes during CBP complicate any attempts to monitor carbon dioxide tension in the exhaust outlet of an oxygenator (PexCO2) because CO2 becomes more soluble with decreasing temperatures. Normally, this would have been the obvious and easy choice of method to indirectly measure the patient's PaCO2. Several tests have been performed with ordinary capnographs modified to measure pCO2 at the oxygenator exhaust gas port. These tests have shown varying degrees of precision (Br I Anaesth 1999; 82(6): 843-46; 1 Extra-Corpor Technol 2003; 35(3): 218-23; Br JAnaesth 2000; 84: 536; J Extra-Corpor Technol 1994; 26: 64-67). Some of the best results have been achieved by Potger et al. (JExtra-Corpor Technol 2003; 35(3): 218-23), who found a strong correlation between the arterial temperature-corrected PexCO2 when using a standard capnograph monitoring the PaCO2 measured from a blood gas analyser (PbCO2). Our group has developed a new instrument, especially designed for oxygenator gas exhaust monitoring. The new instrument has automatic temperature correction, enabling it to show both original and corrected pCO2 values, simultaneously. Ordinary capnograph functions, such as zeroing, flow control and calibration routines, are included. The solution consists of a pCO2 sensor module, a temperature sensor, a water trap and a dedicated PC mounted on a heart-lung machine. Since the heart-lung machine was already equipped with a computer for data logging and a temperature sensor, only a box containing the pCO2 sensor module and the water trap had to be added. The PC uses a specially written program designed to collect data, make the necessary calculations and display the results on the computer screen. A temperature correction was developed based on a linear regression analysis for a data-set of 15 patients, assuming that the deviation between the measured PexCO2 from the oxygenator exhaust outlet and the PbCO2 from the blood gas analyser was linearly dependent on arterial temperature alone. Eighty-six blood gas samples were compared to the corrected PexCO2 values. The final product displayed good qualities of stability and was accurate when temperature fluctuated from 32 to 38 degrees C, even during rewarming, which has been reported to be a problem for other PexCO2 investigations (J Extra-Corpor Technol 2003; 35(3): 218-23).

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This paper presents the clinical testing of a new capnograph designed to measure the carbon dioxide tension at the oxygenator exhaust outlet in cardiopulmonary bypass (CPB). During CPB, there is a need for reliable, accurate and instant estimates of the arterial blood CO2 tension (PaCO2) in the patient. Currently, the standard practice for measuring PaCO2 involves the manual collection of intermittent blood samples, followed by a separate analysis performed by a blood gas analyser. Probes for inline blood gas measurement exist, but they are expensive and, thus, unsuitable for routine use. A well-known method is to measure PexCO2, ie, the partial pressure of CO2 in the exhaust gas output from the oxygenator and use this as an indirect estimate for PaCO2. Based on a commercially available CO2 sensor circuit board, a laminar flow capnograph was developed. A standard sample line with integrated water trap was connected to the oxygenator exhaust port. Fifty patients were divided into six different groups with respect to oxygenator type and temperature range. Both arterial and venous blood gas samples were drawn from the CPB circuit at various temperatures. Alfa-stat corrected pCO2 values were obtained by running a linear regression for each group based on the arterial temperature and then correcting the PexCO2 accordingly. The accuracy of the six groups was found to be (+/- SD): +/- 4.3, +/- 4.8, +/- 5.7, +/- 1.0, +/- 3.7 and +/- 2.1%. These results suggest that oxygenator exhaust capnography is a simple, inexpensive and reliable method of estimating the PaCO2 in both adult and pediatric patients at all relevant-temperatures.

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Patient monitoring devices supporting wireless transmission can facilitate transport and ambulation of patients in hospitals. To replace wired sensors with wireless sensors, the accuracy and resistance to interference of the wireless sensors have to be documented. We compared the performance of a wireless arterial blood pressure biomedical sensor prototype with standard wired sensors in a clinical setting. Four patients undergoing laparoscopic abdominal surgery were recruited for testing of the device. Lines to a wireless arterial blood pressure sensor and standard wired sensor were connected to the same arterial cannula inserted in the right radial artery. Data from both systems were logged for postprocedure statistical comparison. During the procedure, 13 other electric devices were used, either continuously or intermittently. A sample-by-sample comparison was performed for both wired and wireless data. Statistical tests showed mean difference of 0.71, standard deviation of 0.14, and confidence interval of -1.28 to 1.56), indicating no significant electromagnetic interference on invasive arterial blood pressure monitoring caused by biomedical devices used during surgery. The wireless pressure biomedical sensor with Bluetooth wireless transmission of signals did not interfere with biomedical devices used in the operating room or vice versa.

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