Automatized self-supervised learning for skin lesion screening.

Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body screening (TBS), i.e., identifying suspicious lesions or ugly ducklings (UDs) by visual inspection, can be challenging and often requires sound expertise in pigmented lesions. To assist users of varying expertise levels, an artificial intelligence (AI) decision support tool was developed. Our solution identifies and characterizes UDs from real-world wide-field patient images. It employs a state-of-the-art object detection algorithm to locate and isolate all skin lesions present in a patient's total body images. These lesions are then sorted based on their level of suspiciousness using a self-supervised AI approach, tailored to the specific context of the patient under examination. A clinical validation study was conducted to evaluate the tool's performance. The results demonstrated an average sensitivity of 95% for the top-10 AI-identified UDs on skin lesions selected by the majority of experts in pigmented skin lesions. The study also found that the tool increased dermatologists' confidence when formulating a diagnosis, and the average majority agreement with the top-10 AI-identified UDs reached 100% when assisted by our tool. With the development of this AI-based decision support tool, we aim to address the shortage of specialists, enable faster consultation times for patients, and demonstrate the impact and usability of AI-assisted screening. Future developments will include expanding the dataset to include histologically confirmed melanoma and validating the tool for additional body regions.

Radial matrix constraint influences tissue contraction and promotes maturation of bi-layered skin equivalents.

Human skin equivalents (HSEs) serve as important tools for mechanistic studies with human skin cells, drug discovery, pre-clinical applications in the field of tissue engineering and for skin transplantation on skin defects. Besides the cellular and extracellular matrix (ECM) components used for HSEs, physical constraints applied on the scaffold during HSEs maturation influence tissue organization, functionality, and homogeneity. In this study, we introduce a 3D-printed culture insert that exposes bi-layered HSEs to a static radial constraint through matrix adhesion. We examine the effect of various diameters of the ring-shaped culture insert on the HSE's characteristics and compare them to state-of-the-art unconstrained and planar constrained HSEs. We show that radial matrix constraint of HSEs regulates tissue contraction, promotes fibroblast and matrix organization that is similar to human skin in vivo and improves keratinocyte differentiation, epidermal stratification, and basement membrane formation depending on the culture insert diameter. Together, these data demonstrate that the degree of HSE's contraction is an important design consideration in skin tissue engineering. Therefore, this study can help to mimic various in vivo skin conditions and to increase the control of relevant tissue properties.

A Comparison of Proximal and Tracheal Airway Pressures During Pressure Controlled Ventilation.

BACKGROUND: Airway pressure is usually measured by sensors placed in the ventilator or on the ventilator side of the endotracheal tube (ETT), at the Y-piece. These remote measurements serve as a surrogate for the tracheal or alveolar pressure. Tracheal pressure can only be predicted correctly by using a model that incorporates the pressure at the remote location, the flow through the ETT, and the resistance of the ETT if the latter is a predictable function of Y-piece flow. However, this is not consistently appropriate, and accuracy of prediction is hampered. METHODS: This in vitro study systematically examined the ventilator pressure in dependence of compliance of the respiratory system (CRS), inspiratory time, and expiratory time during pressure-controlled ventilation by using a small intratracheal pressure sensor and a mechanical lung simulator. Pressures were measured simultaneously at the ventilator outlet, at the Y-piece, and in the trachea during pressure-controlled ventilation with a peak inspiratory pressure of 20 cm H2O and a PEEP of 5 cm H2O while changing CRS (10, 30, 60, 90, and 100 mL/cm H2O) and varying inspiratory time and expiratory time. RESULTS: Tracheal pressures were always lower (maximum 8 cm H2O during inspiration) or higher (maximum 4 cm H2O during expiration) than the pressures measured proximal to the ETT if zero-flow conditions were not achieved at the end of the breathing cycles. CONCLUSIONS: Dependent on CRS and the breathing cycle, tracheal pressures deviated from those measured proximal to the ETT under non-zero-flow conditions. Intratracheal pressure and pressure curve dynamics can differ greatly from the ventilator pressure, depending on the ventilator setting and the CRS. The small pressure sensor may be used as a measurement method of tracheal pressure via integration onto an ETT.

Continuous Monitoring of Blood Pressure and Vascular Hemodynamic Properties With Miniature Extravascular Hall-Based Magnetic Sensor.

Continuous measurement of vascular and hemodynamic parameters could improve monitoring of disease progression and enable timely clinical decision making and therapy surveillance in patients suffering from cardiovascular diseases. However, no reliable extravascular implantable sensor technology is currently available. Here, we report the design, characterization, and validation of an extravascular, magnetic flux sensing device capable of capturing the waveforms of the arterial wall diameter, arterial circumferential strain, and arterial pressure without restricting the arterial wall. The implantable sensing device, comprising a magnet and a magnetic flux sensing assembly, both encapsulated in biocompatible structures, has shown to be robust, with temperature and cyclic-loading stability. Continuous and accurate monitoring of arterial blood pressure and vascular properties was demonstrated with the proposed sensor in vitro with a silicone artery model and validated in vivo in a porcine model mimicking physiologic and pathologic hemodynamic conditions. The captured waveforms were further used to deduce the respiration frequency, the duration of the cardiac systolic phase, and the pulse wave velocity. The findings of this study not only suggest that the proposed sensing technology is a promising platform for accurate monitoring of arterial blood pressure and vascular properties, but also highlight the necessary changes in the technology and the implantation procedure to allow the translation of the sensing device in the clinical setting.

In-vitro investigation of endothelial monolayer retention on an inflow VAD cannula inside a beating heart phantom.

Ventricular assist devices (VADs) provide an alternative solution to heart transplantation for patients with end-stage heart failure. Insufficient hemocompatibility of VAD components can result in severe adverse events, such as thromboembolic stroke, and readmissions. To enhance VAD hemocompatibility, and avoid thrombus formation, surface modification techniques and endothelialization strategies are employed. In this work, a free form patterning topography is selected to facilitate the endothelialization of the outer surface of the inflow cannula (IC) of a commercial VAD. An endothelialization protocol for convoluted surfaces such as the IC is produced, and the retainment of the endothelial cell (EC) monolayer is evaluated. To allow this evaluation, a dedicated experimental setup is developed to simulate realistic flow phenomena inside an artificial, beating heart phantom with a VAD implanted on its apex. The procedural steps of mounting the system result to the impairment of the EC monolayer, which is further compromised by the developed flow and pressure conditions, as well as by the contact with the moving inner structures of the heart phantom. Importantly, the EC monolayer is better maintained in the lower part of the IC, which is more susceptible to thrombus formation and may therefore aid in minimizing the hemocompatibility related adverse events after the VAD implantation.

Measuring teamwork for training in healthcare using eye tracking and pose estimation.

Teamwork is critical for safe patient care. Healthcare teams typically train teamwork in simulated clinical situations, which require the ability to measure teamwork via behavior observation. However, the required observations are prone to human biases and include significant cognitive load even for trained instructors. In this observational study we explored how eye tracking and pose estimation as two minimal invasive video-based technologies may measure teamwork during simulation-based teamwork training in healthcare. Mobile eye tracking, measuring where participants look, and multi-person pose estimation, measuring 3D human body and joint position, were used to record 64 third-year medical students who completed a simulated handover case in teams of four. On one hand, we processed the recorded data into the eye contact metric, based on eye tracking and relevant for situational awareness and communication patterns. On the other hand, the distance to patient metric was processed, based on multi-person pose estimation and relevant for team positioning and coordination. After successful data recording, we successfully processed the raw videos to specific teamwork metrics. The average eye contact time was 6.46 s [min 0 s - max 28.01 s], while the average distance to the patient resulted in 1.01 m [min 0.32 m - max 1.6 m]. Both metrics varied significantly between teams and simulated roles of participants (p < 0.001). With the objective, continuous, and reliable metrics we created visualizations illustrating the teams' interactions. Future research is necessary to generalize our findings and how they may complement existing methods, support instructors, and contribute to the quality of teamwork training in healthcare.

The Introduction of an MR-Conditional Prototype for Cardiopulmonary Bypass Support: Technical Aspects and System Requirements.

INTRODUCTION: The use of cardiopulmonary bypass (CBP; also known as a heart-lung machine) in newborns with complex congenital heart defects may result in brain damage. Magnetic resonance imaging (MRI) assessments cannot be performed safely because the metal components used to construct CBP devices may elicit adverse effects on patients when they are placed in a magnetic field. Thus, this project aimed to develop a prototype MR-conditional circulatory support system that could be used to perform cerebral perfusion studies in animal models. METHODS: The circulatory support device includes a roller pump with two rollers. The ferromagnetic and most of the metal components of the roller pump were modified or replaced, and the drive was exchanged by an air-pressure motor. All materials used to develop the prototype device were tested in the magnetic field according to the American Society for Testing and Materials (ASTM) Standard F2503-13. The technical performance parameters, including runtime/durability as well as achievable speed and pulsation behavior, were evaluated and compared to standard requirements. The behavior of the prototype device was compared with a commercially available pump. RESULTS: The MRI-conditional pump system produced no image artifacts and could be safely operated in the presence of the magnetic field. The system exhibited minor performance-related differences when compared to a standard CPB pump; feature testing revealed that the prototype meets the requirements (i.e., operability, controllability, and flow range) needed to proceed with the planned animal studies. CONCLUSION: This MR-conditional prototype is suitable to perform an open-heart surgery in an animal model to assess brain perfusion in an MR environment.

The impact of right ventricular hemodynamics on the performance of a left ventricular assist device in a numerical simulation model.

OBJECTIVES: Left ventricular assist devices (LVADs) have been established as alternative to heart transplantation for patients with end-stage heart failure refractory to medical therapy. Right heart failure (RHF) after LVAD implantation is associated with inferior outcome. Its preoperative anticipation may influence the selection between a pure left ventricular and a biventricular device type and, thus, improve outcomes. Reliable algorithms to predict RHF are missing. METHODS: A numerical model was used for simulation of a cardiovascular circulation. The LVAD was placed as parallel circuit between left ventricle and aorta. In contrast to other studies, the dynamic hydraulic behavior of a pulsatile LVAD was replaced by that of a continuous LVAD. A variety of hemodynamic states was tested mimicking different right heart conditions. Adjustable parameters included heart rate (HR), pulmonary vascular resistance (PVR), tricuspid regurgitation (TR), right ventricular contractility (RVC) and pump speed. Outcome parameters comprised central venous pressure (CVP), mean pulmonary artery pressure (mPAP), cardiac output (CO) and occurrence of suction. RESULTS: Alteration of HR, PVR, TR, RVC and pump speed resulted in diverse effects on CO, CVP and mPAP, resulting in improvement, impairment or no change of the circulation, depending on the degree of alteration. CONCLUSIONS: The numerical simulation model allows prediction of circulatory changes and LVAD behaviour following variation of hemodynamic parameters. Such a prediction may be of particular advantage to anticipate RHF after LVAD implantation. It may help preoperatively to choose the appropriate strategy of only left ventricular or both left and right ventricular support.

Data-driven resuscitation training using pose estimation.

BACKGROUND: Cardiopulmonary resuscitation (CPR) training improves CPR skills while heavily relying on feedback. The quality of feedback can vary between experts, indicating a need for data-driven feedback to support experts. The goal of this study was to investigate pose estimation, a motion detection technology, to assess individual and team CPR quality with the arm angle and chest-to-chest distance metrics. METHODS: After mandatory basic life support training, 91 healthcare providers performed a simulated CPR scenario in teams. Their behaviour was simultaneously rated based on pose estimation and by experts. It was assessed if the arm was straight at the elbow, by calculating the mean arm angle, and how close the distance between the team members was during chest compressions, by calculating the chest-to-chest distance. Both pose estimation metrics were compared with the expert ratings. RESULTS: The data-driven and expert-based ratings for the arm angle differed by 77.3%, and based on pose estimation, 13.2% of participants kept the arm straight. The chest-to-chest distance ratings by expert and by pose estimation differed by 20.7% and based on pose estimation 63.2% of participants were closer than 1 m to the team member performing compressions. CONCLUSIONS: Pose estimation-based metrics assessed learners' arm angles in more detail and their chest-to-chest distance comparably to expert ratings. Pose estimation metrics can complement educators with additional objective detail and allow them to focus on other aspects of the simulated CPR training, increasing the training's success and the participants' CPR quality. TRIAL REGISTRATION: Not applicable.

How different augmented reality visualizations for drilling affect trajectory deviation, visual attention, and user experience.

PURPOSE: Previous work has demonstrated the high accuracy of augmented reality (AR) head-mounted displays for pedicle screw placement in spinal fusion surgery. An important question that remains unanswered is how pedicle screw trajectories should be visualized in AR to best assist the surgeon. METHODOLOGY: We compared five AR visualizations displaying the drill trajectory via Microsoft HoloLens 2 with different configurations of abstraction level (abstract or anatomical), position (overlay or small offset), and dimensionality (2D or 3D) against standard navigation on an external screen. We tested these visualizations in a study with 4 expert surgeons and 10 novices (residents in orthopedic surgery) on lumbar spine models covered by Plasticine. We assessed trajectory deviations ([Formula: see text]) from the preoperative plan, dwell times (%) on areas of interest, and the user experience. RESULTS: Two AR visualizations resulted in significantly lower trajectory deviations (mixed-effects ANOVA, p<0.0001 and p<0.05) compared to standard navigation, whereas no significant differences were found between participant groups. The best ratings for ease of use and cognitive load were obtained with an abstract visualization displayed peripherally around the entry point and with a 3D anatomical visualization displayed with some offset. For visualizations displayed with some offset, participants spent on average only 20% of their time examining the entry point area. CONCLUSION: Our results show that real-time feedback provided by navigation can level task performance between experts and novices, and that the design of a visualization has a significant impact on task performance, visual attention, and user experience. Both abstract and anatomical visualizations can be suitable for navigation when not directly occluding the execution area. Our results shed light on how AR visualizations guide visual attention and the benefits of anchoring information in the peripheral field around the entry point.

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network.

Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.

Testing of pandemic ventilators under early and agile development.

Aiming to address clinical requirements subsequent to SARS-CoV-2-related pulmonary disease, multiple research groups and industry groups carried out intensive studies to develop pandemic ventilators (PDVs). In vitro testing to critically evaluate the specific performance of the developed apparatuses is an essential requirement. This study presents a test protocol which promotes a test-oriented, iterative, and agile assessment and consecutive development of such PDVs. It allows for fast identification of specific characteristics of each PDV in the individual test features. The test protocol includes an evaluation of the accuracy of control systems and instruments at changing parameters, the oxygen dynamics, and the response to trigger signals. The test environment is a mechanical lung, which allows reproducing various lung mechanics and to simulate active breathing cycles. A total of three PDVs that are under development were iteratively tested, with a Hamilton T1 as a reference. Continuous testing of the PDVs under development enables quick identification of critical application aspects that deserve further improved. Based on the present test protocol, the ventilators demonstrate a promising performance justifying continued development.

Physiologic Data-Driven Iterative Learning Control for Left Ventricular Assist Devices.

Continuous flow ventricular assist devices (cfVADs) constitute a viable and increasingly used therapy for end-stage heart failure patients. However, they are still operating at a fixed-speed mode that precludes physiological cfVAD response and it is often related to adverse events of cfVAD therapy. To ameliorate this, various physiological controllers have been proposed, however, the majority of these controllers do not account for the lack of pulsatility in the cfVAD operation, which is supposed to be beneficial for the physiological function of the cardiovascular system. In this study, we present a physiological data-driven iterative learning controller (PDD-ILC) that accurately tracks predefined pump flow trajectories, aiming to achieve physiological, pulsatile, and treatment-driven response of cfVADs. The controller has been extensively tested in an in-silico environment under various physiological conditions, and compared with a physiologic pump flow proportional-integral-derivative controller (PF-PIDC) developed in this study as well as the constant speed (CS) control that is the current state of the art in clinical practice. Additionally, two treatment objectives were investigated to achieve pulsatility maximization and left ventricular stroke work (LVSW) minimization by implementing copulsation and counterpulsation pump modes, respectively. Under all experimental conditions, the PDD-ILC as well as the PF-PIDC demonstrated highly accurate tracking of the reference pump flow trajectories, outperforming existing model-based iterative learning control approaches. Additionally, the developed controllers achieved the predefined treatment objectives and resulted in improved hemodynamics and preload sensitivities compared to the CS support.

Micro-sized open-source and low-cost GPS loggers below 1 g minimise the impact on animals while collecting thousands of fixes.

GPS-enabled loggers have been proven as valuable tools for monitoring and understanding animal movement, behaviour and ecology. While the importance of recording accurate location estimates is well established, deployment on many, especially small species, has been limited by logger mass and cost. We developed an open-source and low-cost 0.65 g GPS logger with a simple smartphone-compatible user interface, that can record more than 10,000 GPS fixes on a single 30 mAh battery charge (resulting mass including battery: 1.3 g). This low-budget 'TickTag' (currently 32 USD) allows scientists to scale-up studies while becoming a 'wearable' for larger animals and simultaneously enabling high-definition studies on small animals. Tests on two different species (domestic dog, Canis lupus familiaris and greater mouse-eared bats, Myotis myotis) showed that our combination of optimised hardware design and software-based recording strategies increases the number of achievable GPS fixes per g device mass compared to existing micro-sized solutions. We propose that due to the open-source access, as well as low cost and mass, the TickTag fills a technological gap in wildlife ecology and will open up new possibilities for wildlife research and conservation.

Cytotoxic and Inflammatory Effects of Electronic and Traditional Cigarettes on Oral Gingival Cells Using a Novel Automated Smoking Instrument: An In Vitro Study.

Information about the potential oral health effects of vaping from electronic cigarettes (e-cigs) is still sparse and inconsistent. The purpose of this study was to compare the safety and cytotoxicity of e-cig liquid aerosols versus traditional cigarette (t-cig) smoke on human epithelial oral cells. T-cig smoke and e-cig aerosols were generated by a newly developed automated smoking instrument in order to simulate realistic user puffing behaviors. Air−liquid interface transwell cell cultures were exposed to standardized puff topography (puff duration: 2 s, puff volume: 35 mL, puff frequency: 1 puff every 60 s) of reference t-cigs or commercially available e-cigs at different air dilutions. Cell viability, morphology, and death rate were evaluated with MTT and TUNEL assays. The inflammatory cytokine gene expression of inflammatory genes was assessed by quantitative RT-PCR. E-cigs and t-cigs indicated similar adverse effects by enhancing cytotoxicity and cell death in a dose-dependent manner. E-cig aerosol and t-cig smoke treatment expressed upregulation of inflammatory cytokines up to 3.0-fold (p < 0.05). These results indicate that e-cig smoking may contribute to oral tissue−cell damage and tissue inflammation. Our approach allows the production of e-cig aerosol and t-cig smoke in order to identify harmful effects in oral tissues in vitro.

The HEV Ventilator: at the interface between particle physics and biomedical engineering.

A high-quality, low-cost ventilator, dubbed HEV, has been developed by the particle physics community working together with biomedical engineers and physicians around the world. The HEV design is suitable for use both in and out of hospital intensive care units, provides a variety of modes and is capable of supporting spontaneous breathing and supplying oxygen-enriched air. An external air supply can be combined with the unit for use in situations where compressed air is not readily available. HEV supports remote training and post market surveillance via a Web interface and data logging to complement standard touch screen operation, making it suitable for a wide range of geographical deployment. The HEV design places emphasis on the ventilation performance, especially the quality and accuracy of the pressure curves, reactivity of the trigger, measurement of delivered volume and control of oxygen mixing, delivering a global performance which will be applicable to ventilator needs beyond the COVID-19 pandemic. This article describes the conceptual design and presents the prototype units together with a performance evaluation.

Dual-Modality Volume Measurement Integrated on a Ventricular Assist Device.

OBJECTIVE: Ventricular assist devices (VADs) are implanted in patients suffering from end-stage heart failure to sustain the blood circulation. Real-time volume measurement could be a valuable tool to monitor patients and enable physiological control strategies to provide individualized therapy. However, volume measurement using one sensor modality requires re-calibration in the critical time post VAD implantation. METHODS: To overcome this limitation, we have integrated ultrasound and impedance volume measurement techniques into a cannula of an apical VAD. We tested both modalities across a volume range from 140-420 mL using two differently sized and shaped biventricular silicon heart phantoms, which were subjected to physiological pressures in an in-vitro test bench. We compared results from standard calibrated measurements with calculations found by a quadratic optimization for the single modality and their combination (dual-modality) and validated the results using twofold cross-validation. RESULTS: The dual-modality approach resulted in most favorable limits of agreement (LOA) of -0.83 ± 1.54% compared to -13.88 ± 5.90% for ultrasound and -43.45 ± 10.28% for electric impedance, separately. CONCLUSION: The results of the dual-modality approach were as accurate as the standard calibrated measurement and valid over a large range of volumes (140-420 mL). In this in-vitro study, we show how a dual-modality ventricular volume measurement of ultrasound and electric impedance increases the robustness and renders calibration obsolete. SIGNIFICANCE: Ventricular volumes could be measured accurately in the critical period post VAD implantation despite ventricular remodeling.

An algorithmic approach to determine expertise development using object-related gaze pattern sequences.

Eye tracking (ET) technology is increasingly utilized to quantify visual behavior in the study of the development of domain-specific expertise. However, the identification and measurement of distinct gaze patterns using traditional ET metrics has been challenging, and the insights gained shown to be inconclusive about the nature of expert gaze behavior. In this article, we introduce an algorithmic approach for the extraction of object-related gaze sequences and determine task-related expertise by investigating the development of gaze sequence patterns during a multi-trial study of a simplified airplane assembly task. We demonstrate the algorithm in a study where novice (n = 28) and expert (n = 2) eye movements were recorded in successive trials (n = 8), allowing us to verify whether similar patterns develop with increasing expertise. In the proposed approach, AOI sequences were transformed to string representation and processed using the k-mer method, a well-known method from the field of computational biology. Our results for expertise development suggest that basic tendencies are visible in traditional ET metrics, such as the fixation duration, but are much more evident for k-mers of k > 2. With increased on-task experience, the appearance of expert k-mer patterns in novice gaze sequences was shown to increase significantly (p < 0.001). The results illustrate that the multi-trial k-mer approach is suitable for revealing specific cognitive processes and can quantify learning progress using gaze patterns that include both spatial and temporal information, which could provide a valuable tool for novice training and expert assessment.

Pressure and Bernoulli-Based Flow Measurement via a Tapered Inflow VAD Cannula.

OBJECTIVE: Currently available ventricular assist devices provide continuous flow and do not adapt to the changing needs of patients. Physiological control algorithms have been proposed that adapt the pump speed based on the left ventricular pressure. However, so far, no clinically used pump can acquire this pressure. Therefore, for the validation of physiological control concepts in vivo, a system that can continuously and accurately provide the left ventricular pressure signal is needed. METHODS: We demonstrate the integration of two pressure sensors into a tapered inflow cannula compatible with the HeartMate 3 (HM3) ventricular assist device. Selective laser melting was used to incorporate functional elements with a small footprint and therefore retain the geometry, function and implantability of the original cannula. The system was tested on a hybrid mock circulation system. Static and simulated physiological flow and pressure profiles were used to evaluate the combined pressure and flow sensing capabilities of the modified cannula. RESULTS: The cannula prototypes enabled continuous pressure measurements at two points of their inner wall in the range of -100 and 200 mmHg. The developed, Bernoulli-based, two sensor model improved the accuracy of the measured simulated left ventricular pressure by eliminating the influence of flow inside the cannula. This method reduced the flow induced pressure uncertainty from up to 7.6 mmHg in single sensor measurements to 0.3 mmHg. Additionally, the two-sensor system and model enable the measurement of the blood flow through the pump with an accuracy of -0.14 ± 0.04 L/min, without dedicated flow sensors.

Transcatheter Mitral Valve Repair Simulator Equipped with Eye Tracking Based Performance Assessment Capabilities: A Pilot Study.

BACKGROUND: The increase in cardiovascular disease cases that require minimally invasive treatment is inducing a new need to train physicians to perform them safely and effectively. Nevertheless, adaptation to simulation-based training has been slow, especially for complex procedures. OBJECTIVES: We describe a newly developed mitral valve repair (MVR) simulator, equipped with new objective performance assessment methods, with an emphasis on its use for training the MitraClip™ procedure. METHODS: The MVR contains phantoms of all anatomical structures encountered during mitral valve repair with a transvenous, transseptal approach. In addition, several cameras, line lasers, and ultraviolet lights are used to mimic echocardiographic and fluoroscopic imaging and with a remote eye tracker the cognitive behaviour of the operator is recorded. A pilot study with a total of 9 interventional cardiologists, cardiac surgeons and technical experts was conducted. All participants performed the MitraClip procedure on the MVR simulator using standard interventional tools. Subsequently, each participant completed a structured questionnaire to assess the simulator. RESULTS: The simulator functioned well, and the implemented objective performance assessment methods worked reliably. Key performance metrics such as x-ray usage were comparable with results from studies assessing these metrics in real interventions. Fluoroscopy imaging is realistic for the transseptal puncture but reaches its limits during the final steps of the procedure. CONCLUSION: The functionality and objective performance assessment of the MVR simulator were demonstrated. Especially for complex procedures such as the MitraClip procedure, this simulator offers a suitable platform for risk-free training and education.