An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies.

Introduction: Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and interpretation, triage decisions can be hard to make. While automation approaches can enhance these triage applications, tissue phantoms must be developed to train and mature these novel technologies. Here, we have developed a tissue phantom modeling the ultrasound views imaged during the enhanced focused assessment with sonography in trauma exam (eFAST). Methods: The tissue phantom utilized synthetic clear ballistic gel with carveouts in the abdomen and rib cage corresponding to the various eFAST scan points. Various approaches were taken to simulate proper physiology without injuries present or to mimic pneumothorax, hemothorax, or abdominal hemorrhage at multiple locations in the torso. Multiple ultrasound imaging systems were used to acquire ultrasound scans with or without injury present and were used to train deep learning image classification predictive models. Results: Performance of the artificial intelligent (AI) models trained in this study achieved over 97% accuracy for each eFAST scan site. We used a previously trained AI model for pneumothorax which achieved 74% accuracy in blind predictions for images collected with the novel eFAST tissue phantom. Grad-CAM heat map overlays for the predictions identified that the AI models were tracking the area of interest for each scan point in the tissue phantom. Discussion: Overall, the eFAST tissue phantom ultrasound scans resembled human images and were successful in training AI models. Tissue phantoms are critical first steps in troubleshooting and developing medical imaging automation technologies for this application that can accelerate the widespread use of ultrasound imaging for emergency triage.

Adaptive closed-loop resuscitation controllers for hemorrhagic shock resuscitation.

BACKGROUND: After hemorrhage control, fluid resuscitation is the most important intervention for hemorrhage. Even skilled providers can find resuscitation challenging to manage, especially when multiple patients require care. In the future, attention-demanding medical tasks like fluid resuscitation for hemorrhage patients may be reassigned to autonomous medical systems when availability of skilled human providers is limited, such as in austere military settings and mass casualty incidents. Central to this endeavor is the development and optimization of control architectures for physiological closed-loop control systems (PCLCs). PCLCs can take many forms, from simple table look-up methods to widely used proportional-integral-derivative or fuzzy-logic control theory. Here, we describe the design and optimization of multiple adaptive resuscitation controllers (ARCs) that we have purpose-built for the resuscitation of hemorrhaging patients. STUDY DESIGN AND METHODS: Three ARC designs were evaluated that measured pressure-volume responsiveness using different methodologies during resuscitation from which adapted infusion rates were calculated. These controllers were adaptive in that they estimated required infusion flow rates based on measured volume responsiveness. A previously developed hardware-in-loop test platform was used to evaluate the ARCs implementations across several hemorrhage scenarios. RESULTS: After optimization, we found that our purpose-built controllers outperformed traditional control system architecture as embodied in our previously developed dual-input fuzzy-logic controller. DISCUSSION: Future efforts will focus on engineering our purpose-built control systems to be robust to noise in the physiological signal coming to the controller from the patient as well as testing controller performance across a range of test scenarios and in vivo.

Hardware-in-Loop Comparison of Physiological Closed-Loop Controllers for the Autonomous Management of Hypotension.

Trauma and hemorrhage are leading causes of death and disability worldwide in both civilian and military contexts. The delivery of life-saving goal-directed fluid resuscitation can be difficult to provide in resource-constrained settings, such as in forward military positions or mass-casualty scenarios. Automated solutions for fluid resuscitation could bridge resource gaps in these austere settings. While multiple physiological closed-loop controllers for the management of hypotension have been proposed, to date there is no consensus on controller design. Here, we compare the performance of four controller types-decision table, single-input fuzzy logic, dual-input fuzzy logic, and proportional-integral-derivative using a previously developed hardware-in-loop test platform where a range of hemorrhage scenarios can be programmed. Controllers were compared using traditional controller performance metrics, but conclusions were difficult to draw due to inconsistencies across the metrics. Instead, we propose three aggregate metrics that reflect the target intensity, stability, and resource efficiency of a controller, with the goal of selecting controllers for further development. These aggregate metrics identify a dual-input, fuzzy-logic-based controller as the preferred combination of intensity, stability, and resource efficiency within this use case. Based on these results, the aggressively tuned dual-input fuzzy logic controller should be considered a priority for further development.

Training Ultrasound Image Classification Deep-Learning Algorithms for Pneumothorax Detection Using a Synthetic Tissue Phantom Apparatus.

Ultrasound (US) imaging is a critical tool in emergency and military medicine because of its portability and immediate nature. However, proper image interpretation requires skill, limiting its utility in remote applications for conditions such as pneumothorax (PTX) which requires rapid intervention. Artificial intelligence has the potential to automate ultrasound image analysis for various pathophysiological conditions. Training models require large data sets and a means of troubleshooting in real-time for ultrasound integration deployment, and they also require large animal models or clinical testing. Here, we detail the development of a dynamic synthetic tissue phantom model for PTX and its use in training image classification algorithms. The model comprises a synthetic gelatin phantom cast in a custom 3D-printed rib mold and a lung mimicking phantom. When compared to PTX images acquired in swine, images from the phantom were similar in both PTX negative and positive mimicking scenarios. We then used a deep learning image classification algorithm, which we previously developed for shrapnel detection, to accurately predict the presence of PTX in swine images by only training on phantom image sets, highlighting the utility for a tissue phantom for AI applications.

Development and Characterization of an Ex Vivo Testing Platform for Evaluating Automated Central Vascular Access Device Performance.

Access to the central vasculature is critical for hemodynamic monitoring and for delivery of life-saving therapeutics during emergency medicine and battlefield trauma situations but requires skill often unavailable in austere environments. Automated central vascular access devices (ACVADs) using ultrasound and robotics are being developed. Here, we present an ex vivo lower-body porcine model as a testing platform for evaluation of vascular devices and compare its features to commercially available platforms. While the commercially available trainers were simpler to set-up and use, the scope of their utility was limited as they were unable to provide realistic anatomic, physiologic, and sonographic properties that were provided by the ex vivo model. However, the ex vivo model was more cumbersome to set-up and use. Overall, both have a place in the development and evaluation pipeline for ACVADs before testing on live animals, thus accelerating product development and translation.

An Automated Hardware-in-Loop Testbed for Evaluating Hemorrhagic Shock Resuscitation Controllers.

Hemorrhage remains a leading cause of death, with early goal-directed fluid resuscitation being a pillar of mortality prevention. While closed-loop resuscitation can potentially benefit this effort, development of these systems is resource-intensive, making it a challenge to compare infusion controllers and respective hardware within a range of physiologically relevant hemorrhage scenarios. Here, we present a hardware-in-loop automated testbed for resuscitation controllers (HATRC) that provides a simple yet robust methodology to evaluate controllers. HATRC is a flow-loop benchtop system comprised of multiple PhysioVessels which mimic pressure-volume responsiveness for different resuscitation infusates. Subject variability and infusate switching were integrated for more complex testing. Further, HATRC can modulate fluidic resistance to mimic arterial resistance changes after vasopressor administration. Finally, all outflow rates are computer-controlled, with rules to dictate hemorrhage, clotting, and urine rates. Using HATRC, we evaluated a decision-table controller at two sampling rates with different hemorrhage scenarios. HATRC allows quantification of twelve performance metrics for each controller configuration and scenario, producing heterogeneous results and highlighting the need for controller evaluation with multiple hemorrhage scenarios. In conclusion, HATRC can be used to evaluate closed-loop controllers through user-defined hemorrhage scenarios while rating their performance. Extensive controller troubleshooting using HATRC can accelerate product development and subsequent translation.

Closed-Loop Controlled Fluid Administration Systems: A Comprehensive Scoping Review.

Physiological Closed-Loop Controlled systems continue to take a growing part in clinical practice, offering possibilities of providing more accurate, goal-directed care while reducing clinicians' cognitive and task load. These systems also provide a standardized approach for the clinical management of the patient, leading to a reduction in care variability across multiple dimensions. For fluid management and administration, the advantages of closed-loop technology are clear, especially in conditions that require precise care to improve outcomes, such as peri-operative care, trauma, and acute burn care. Controller design varies from simplistic to complex designs, based on detailed physiological models and adaptive properties that account for inter-patient and intra-patient variability; their maturity level ranges from theoretical models tested in silico to commercially available, FDA-approved products. This comprehensive scoping review was conducted in order to assess the current technological landscape of this field, describe the systems currently available or under development, and suggest further advancements that may unfold in the coming years. Ten distinct systems were identified and discussed.

Development of a Modular Tissue Phantom for Evaluating Vascular Access Devices.

Central vascular access (CVA) may be critical for trauma care and stabilizing the casualty. However, it requires skilled personnel, often unavailable during remote medical situations and combat casualty care scenarios. Automated CVA medical devices have the potential to make life-saving therapeutics available in these resource-limited scenarios, but they must be properly designed. Unfortunately, currently available tissue phantoms are inadequate for this use, resulting in delayed product development. Here, we present a tissue phantom that is modular in design, allowing for adjustable flow rate, circulating fluid pressure, vessel diameter, and vessel positions. The phantom consists of a gelatin cast using a 3D-printed mold with inserts representing vessels and bone locations. These removable inserts allow for tubing insertion which can mimic normal and hypovolemic flow, as well as pressure and vessel diameters. Trauma to the vessel wall is assessed using quantification of leak rates from the tubing after removal from the model. Lastly, the phantom can be adjusted to swine or human anatomy, including modeling the entire neurovascular bundle. Overall, this model can better recreate severe hypovolemic trauma cases and subject variability than commercial CVA trainers and may potentially accelerate automated CVA device development.

Evaluation of a Proportional-Integral-Derivative Controller for Hemorrhage Resuscitation Using a Hardware-in-Loop Test Platform.

Hemorrhage is a leading cause of preventable death in trauma, which can often be avoided with proper fluid resuscitation. Fluid administration can be cognitive-demanding for medical personnel as the rates and volumes must be personalized to the trauma due to variations in injury severity and overall fluid responsiveness. Thus, automated fluid administration systems are ideal to simplify hemorrhagic shock resuscitation if properly designed for a wide range of hemorrhage scenarios. Here, we highlight the development of a proportional-integral-derivative (PID) controller using a hardware-in-loop test platform. The controller relies only on an input data stream of arterial pressure and a target pressure; the PID controller then outputs infusion rates to stabilize the subject. To evaluate PID controller performance with more than 10 controller metrics, the hardware-in-loop platform allowed for 11 different trauma-relevant hemorrhage scenarios for the controller to resuscitate against. Overall, the two controller configurations performed uniquely for the scenarios, with one reaching the target quicker but often overshooting, while the other rarely overshot the target but failed to reach the target during severe hemorrhage. In conclusion, PID controllers have the potential to simplify hemorrhage resuscitation if properly designed and evaluated, which can be accomplished with the test platform shown here.

Development of the PhysioVessel: a customizable platform for simulating physiological fluid resuscitation.

Uncontrolled hemorrhage is a leading cause of death in trauma situations. Developing solutions to automate hemorrhagic shock resuscitation may improve the outcomes for trauma patients. However, testing and development of automated solutions to address critical care interventions, oftentimes require extensive large animal studies for even initial troubleshooting. The use of accurate laboratory or in-silico models may provide a way to reduce the need for large animal datasets. Here, a tabletop model, for use in the development of fluid resuscitation with physiologically relevant pressure-volume responsiveness for high throughput testing, is presented. The design approach shown can be applied to any pressure-volume dataset through a process of curve-fitting, 3D modeling, and fabrication of a fluid reservoir shaped to the precise curve fit. Two case studies are presented here based on different resuscitation fluids: whole blood and crystalloid resuscitation. Both scenarios were derived from data acquired during porcine hemorrhage studies, used a pressure-volume curve to design and fabricate a 3D model, and evaluated to show that the test platform mimics the physiological data. The vessels produced based on data collected from pigs infused with whole blood and crystalloid were able to reproduce normalized pressure-volume curves within one standard deviation of the porcine data with mean residual differences of 0.018 and 0.016, respectively. This design process is useful for developing closed-loop algorithms for resuscitation and can simplify initial testing of technologies for this life-saving medical intervention.

Development and Characterization of a Self-Tightening Tourniquet System.

Uncontrolled hemorrhage remains a leading cause of death in both emergency and military medicine. Tourniquets are essential to stopping hemorrhage in these scenarios, but they suffer from subjective, inconsistent application. Here, we demonstrate how tourniquet application can be automated using sensors and computer algorithms. The auto-tourniquet self-tightens until blood pressure oscillations are no longer registered by the pressure sensor connected to the pneumatic pressure cuff. The auto-tourniquet's performance in stopping the bleed was comparable to manual tourniquet application, but the time required to fully occlude the bleed was longer. Application of the tourniquet was significantly smoother, and less variable, for the automatic tourniquet compared to manual tourniquet application. This proof-of-concept study highlights how automated tourniquets can be integrated with sensors to provide a much more consistent application and use compared to manual application, even in controlled, low stress testing conditions. Future work will investigate different sensors and tourniquets to improve the application time and repeatability.

Supervisory Algorithm for Autonomous Hemodynamic Management Systems.

Future military conflicts will require new solutions to manage combat casualties. The use of automated medical systems can potentially address this need by streamlining and augmenting the delivery of medical care in both emergency and combat trauma environments. However, in many situations, these systems may need to operate in conjunction with other autonomous and semi-autonomous devices. Management of complex patients may require multiple automated systems operating simultaneously and potentially competing with each other. Supervisory controllers capable of harmonizing multiple closed-loop systems are thus essential before multiple automated medical systems can be deployed in managing complex medical situations. The objective for this study was to develop a Supervisory Algorithm for Casualty Management (SACM) that manages decisions and interplay between two automated systems designed for management of hemorrhage control and resuscitation: an automatic extremity tourniquet system and an adaptive resuscitation controller. SACM monitors the required physiological inputs for both systems and synchronizes each respective system as needed. We present a series of trauma experiments carried out in a physiologically relevant benchtop circulatory system in which SACM must recognize extremity or internal hemorrhage, activate the corresponding algorithm to apply a tourniquet, and then resuscitate back to the target pressure setpoint. SACM continues monitoring after the initial stabilization so that additional medical changes can be quickly identified and addressed, essential to extending automation algorithms past initial trauma resuscitation into extended monitoring. Overall, SACM is an important step in transitioning automated medical systems into emergency and combat trauma situations. Future work will address further interplay between these systems and integrate additional medical systems.

Innovative Solution for Airway Securement in Combat and Trauma Scenarios.

Airway management is one of the most challenging problems in prehospital combat casualty care. Airway assessment and intervention are second only to hemorrhage control in priority in the initial treatment of trauma patients, and airway compromise continues to account for approximately 1 in 10 preventable battlefield deaths. Combat medics often provide care in no- or low-light conditions, surrounded by the chaos of combat, and with the limited dexterity that accompanies bulky body armor, gloves, and heavy equipment. Far-forward medical care is also limited by available resources, which are often only what a combat medic can fit in the aid bag. Therefore, a procedure such as airway management that currently requires a high degree of skill becomes substantially more complex. Improved airway devices are listed among the top five in a comprehensive list of battlefield research and development priorities by the Defense Health Board, yet the challenge of airway management has received little investment compared to other causes of preventable battlefield death such as exsanguinating hemorrhage and traumatic brain injury.

Novel expandable architected breathing tube for improving airway securement in emergency care.

Life-saving interventions utilize endotracheal intubation to secure a patient's airway, but performance of the clinical standard of care endotracheal tube (ETT) is inadequate. For instance, in the current COVID-19 crisis, patients can expect prolonged intubation. This protracted intubation may produce health complications such as tracheal stenosis, pneumonia, and necrosis of tracheal tissue, as current ETTs are not designed for extended use. In this work, we propose an improved ETT design that seeks to overcome these limitations by utilizing unique geometries which enable a novel expanding cylinder. The mechanism provides a better distribution of the contact forces between the ETT and the trachea, which should enhance patient tolerability. Results show that at full expansion, our new ETT exerts pressures in a silicone tracheal phantom well within the recommended standard of care. Also, preliminary manikin tests demonstrated that the new ETT can deliver similar performance in terms of air pressure and air volume when compared with the current gold standard ETT. The potential benefits of this new architected ETT are threefold, by limiting exposure of healthcare providers to patient pathogens through streamlining the intubation process, reducing downstream complications, and eliminating the need of multiple size ETT as one architected ETT fits all.

Spectral Reflectance Can Differentiate Tracheal and Esophageal Tissue in the Presence of Bodily Fluids and Soot.

Endotracheal intubation is a common life-saving procedure implemented in emergency care to ensure patient oxygenation, but it is difficult and often performed in suboptimal conditions leading to high rates of patient complications. Undetected misplacement in the esophagus is a preventable complication that can lead to fatalities in 5-10% of patients who undergo emergency intubation. End-tidal carbon dioxide monitoring and other proper placement detection methods are useful, yet the problem of misplacement persists. Our previous work demonstrated the utility of spectral reflectance sensors for differentiating esophageal and tracheal tissues, which can be used to confirm proper endotracheal tube placement. In this study, we examine the effectiveness of spectral characterization in the presence of saline, blood, "vomit", and soot in the trachea. Our results show that spectral properties of the trachea that differentiate it from the esophagus persist in the presence of these substances. This work further confirms the potential usefulness of this novel detection technology in field applications.

[(1,4,8,11-Tetraazacyclotetradeca-1,4,8,11-tetrayl)tetraacetamide-kappa6N1,N4,N8,N11,O1,O8]copper(II) sulfate 4.5-hydrate.

The crystal structure of the title copper(II) complex, [Cu(C(18)H(36)N(8)O(4))]SO(4).4.5H(2)O, formed with the tetraamide cyclam derivative 2-(4,8,11-triscarbamoylmethyl-1,4,8,11-tetraazacyclotetradec-1-yl)acetamide (TETAM), is described. The macrocycle lies on an inversion centre occupied by the hexacoordinated Cu atom. The four macrocyclic tertiary amines form the equatorial plane of an axially Jahn-Teller elongated octahedron. Two O atoms belonging to two diagonally opposite amide groups occupy the apical positions, giving rise to a trans-III stereochemistry, while both the remaining pendant side arms extend outwards from the macrocyclic cavity and are engaged in hydrogen bonds with sulfate anions and co-crystallized water molecules.