Identifying diversity of patient anatomy through automated image analysis of clinical ultrasounds.

PURPOSE: Central venous catheterization (CVC) carries inherent risks which can be mitigated through the use of appropriate ultrasound-guidance during needle insertion. This study aims to comprehensively understand patient anatomy as it is visualized during CVC by employing a semi-automated image analysis method to track the internal jugular vein and carotid artery throughout recorded ultrasound videos. METHODS: The ultrasound visualization of 50 CVC procedures were recorded at Penn State Health Milton S. Hershey Medical Center. The developed algorithm was used to detect the vessel edges, calculating metrics such as area, position, and eccentricity. RESULTS: Results show typical anatomical variations of the vein and artery, with the artery being more circular and posterior to the vein in most cases. Notably, two cases revealed atypical artery positions, emphasizing the algorithm's precision in detecting anomalies. Additionally, dynamic vessel properties were analyzed, with the vein compressing on average to 13.4% of its original size and the artery expanding by 13.2%. CONCLUSION: This study provides valuable insights which can be used to increase the accuracy of training simulations, thus enhancing medical education and procedural expertise. Furthermore, the novel approach of employing automated data analysis techniques to clinical recordings showcases the potential for continual assessment of patient anatomy, which could be useful in future advancements.

Clinical Outcomes of Standardized Central Venous Catheterization Simulation Training: A Comparative Analysis.

OBJECTIVE: A standardized ultrasound-guided Internal Jugular Central Venous Catheterization (US-IJCVC) using online- and simulation-based training was first designed and then large-scale deployed at a teaching hospital institution to improve CVC surgical education. To understand the impact that the standardized training might have on patient complications, this study focuses on identifying the impact of the integration of an iteratively designed US-IJCVC training on clinical complications at a teaching hospital. DESIGN AND PARTICIPANTS: A comparative study was conducted using TriNetX, a global health research network. Using Current Procedural Terminology (CPT) codes and the International Statistical Classification of Diseases and Related Health Problems (ICD-10) codes, we identified the total number of patients with a CVC and mechanical, infectious, and thrombosis complications with and without billable ultrasound between July 1 to June 30 in 2016, 2017, and 2022. SETTING: A teaching hospital institution in Pennsylvania. RESULTS: Results showed a correlation between years and complications indicating, (1) mechanical complications billable ultrasound, (2) infectious complications billable ultrasound, and (3) thrombosis complications billable ultrasound were significantly lower with the large-scale deployment. Results also showed that (4) mechanical, infectious, and thrombosis complications with and without billable ultrasound are within the range that prior work has reported. CONCLUSION: These results indicate that there has been a decrease in mechanical, infectious, and thrombosis complications, which correlates with the US-IJCVC training large-scale deployment.

Shifting Perspectives: A proposed framework for analyzing head-mounted eye-tracking data with dynamic areas of interest and dynamic scenes.

Eye-tracking is a valuable research method for understanding human cognition and is readily employed in human factors research, including human factors in healthcare. While wearable mobile eye trackers have become more readily available, there are no existing analysis methods for accurately and efficiently mapping dynamic gaze data on dynamic areas of interest (AOIs), which limits their utility in human factors research. The purpose of this paper was to outline a proposed framework for automating the analysis of dynamic areas of interest by integrating computer vision and machine learning (CVML). The framework is then tested using a use-case of a Central Venous Catheterization trainer with six dynamic AOIs. While the results of the validity trial indicate there is room for improvement in the CVML method proposed, the framework provides direction and guidance for human factors researchers using dynamic AOIs.

PROGRESSIVE MEDICAL SIMULATION: AN ANALYSIS OF THE INTEGRATION OF PROGRESSIVE AND PERSONALIZED LEARNING IN CENTRAL LINE SIMULATORS.

Progressive learning gradually increases task difficulty as students advance in their education. One area that can benefit from it is medical education since it can optimize medical trainees' skill acquisition. While progressive learning can allow for skill transfer to patient encounters, personalized learning increases the efficiency and effectiveness of learning. However, it is not well understood the number of practice trials needed to reach proficiency. To evaluate whether progressive and personalized learning can enhance medical trainees' learning gains, the learning interface of the Dynamic Haptic Robotic Trainer (DHRT) for Central Venous Catheterization was assessed. Results showed that residents' performance on the DHRT did not differ based on task difficulty and residents' performance was as effective with less number of trials. The findings imply a need to integrate progressive and personalized learning on the DHRT simulator to ensure that residents are fully prepared for any patient scenario in a real-life encounter.

Evaluating the Impact of Assessment Metrics for Simulated Central Venous Catheterization Training.

INTRODUCTION: Performance assessment and feedback are critical factors in successful medical simulation-based training. The Dynamic Haptic Robotic Trainer (DHRT) allows residents to practice ultrasound-guided needle insertions during simulated central venous catheterization (CVC) procedures while providing detailed feedback and assessment. A study was performed to examine the effectiveness of the DHRT in training the important skills of needle tip tracking and aspiration and how these skills impact procedural complications in simulated CVC. METHODS: The DHRT data were collected for 163 residents at 2 hospitals for 6 simulated needle insertions. Users were given automated feedback on 5 performance metrics, which measure aspiration rate, arterial punctures, punctures through and through the vein, loss of access to the vein, and successful access to the vein. Aspiration rates and tip tracking rates were analyzed to determine their significance in preventing CVC complications and improving performance. RESULTS: Tip tracking rates higher than 40% were 2.3 times more likely to result in successful venous access than rates less than 10%. Similarly, aspiration rates higher than 80% were 2.6 times more likely to result in successful venous access than rates less than 10%. Proper tip tracking and aspiration both reduced mechanical complications. Resident performance improved for all metrics except tip tracking. CONCLUSIONS: Proper tip tracking and aspiration both reduced complications and increased the likelihood of success. However, the skill of tip tracking was not effectively learned through practice without feedback. Therefore, ultrasound-guided needle-based procedures, including CVC, can be improved by providing specific feedback to users on their ultrasound usage to track needle insertions.

Slow and Steady: Examining the impact of hands-on instructions on learnability of a training simulator to enhance development of core skills in Central Venous Catheterization.

Instructional design is the theory surrounding how learners perceive information and is prevalent in simulation-based medical education. Simulation is used for a variety of medical procedures including central venous catheterization (CVC). The dynamic haptic robotic trainer (DHRT) is a CVC teaching simulator developed to specifically focus on training the needle insertion portion of CVC. While the DHRT has been validated to teach CVC as well as other training methods, an opportunity was seen to redesign the instructions of the DHRT to increase the learnability of the system. A hands-on instructional walkthrough was designed. A group trained with the hands-on instructions was compared to a previous group to assess initial insertion performance. Results indicate that changing the instructional method to be hands-on may have an impact on system learnability and help reinforce development of core components of CVC.

Going the (social) distance: Comparing the effectiveness of online versus in-person Internal Jugular Central Venous Catheterization procedural training.

BACKGROUND: This study compares surgical residents' knowledge acquisition of ultrasound-guided Internal Jugular Central Venous Catheterization (US-IJCVC) between in-person and online procedural training cohorts before receiving independent in-person Dynamic Haptic Robotic Simulation training. METHODS: Three surgical residency procedural training cohorts, two in-person (N = 26) and one online (N = 14), were compared based on their performance on a 24-item US-IJCVC evaluation checklist completed by an expert physician completed after training. Pre- and post-training US-IJCVC knowledge was also compared for the online cohort. RESULTS: No significant change in the pass rates on the US-IJCVC checklist was found between in-person and online cohorts (p = 0.208). There were differences in the Economy of Time and Motion between in-person and online cohorts (p < 0.005). The online cohort had significant increases in US-IJCVC knowledge pre-to post-training (p < 0.008). CONCLUSION: Online training with independent simulation practice was as effective as in-person training for US-IJCVC.

Intra-Operative Bioprinting of Hard, Soft, and Hard/Soft Composite Tissues for Craniomaxillofacial Reconstruction.

Reconstruction of complex craniomaxillofacial (CMF) defects is challenging due to the highly organized layering of multiple tissue types. Such compartmentalization necessitates the precise and effective use of cells and other biologics to recapitulate the native tissue anatomy. In this study, intra-operative bioprinting (IOB) of different CMF tissues, including bone, skin, and composite (hard/soft) tissues, is demonstrated directly on rats in a surgical setting. A novel extrudable osteogenic hard tissue ink is introduced, which induced substantial bone regeneration, with ≈80% bone coverage area of calvarial defects in 6 weeks. Using droplet-based bioprinting, the soft tissue ink accelerated the reconstruction of full-thickness skin defects and facilitated up to 60% wound closure in 6 days. Most importantly, the use of a hybrid IOB approach is unveiled to reconstitute hard/soft composite tissues in a stratified arrangement with controlled spatial bioink deposition conforming the shape of a new composite defect model, which resulted in ≈80% skin wound closure in 10 days and 50% bone coverage area at Week 6. The presented approach will be absolutely unique in the clinical realm of CMF defects and will have a significant impact on translating bioprinting technologies into the clinic in the future.

FUN AND GAMES: DESIGNING A GAMIFIED CENTRAL VENOUS CATHETERIZATION TRAINING SIMULATOR.

Gamification, or adding elements of games to training systems, has the potential to increase learner engagement and information retention. However, the use of gamification has yet to be explored in Central Venous Catheterization (CVC) trainers which teach a commonly performed medical procedure with high incidence rates. In order to combat these errors, a Dynamic Haptic Robotic Trainer (DHRT) was developed, which focuses on vessel identification and access. A DHRT+ system is currently under development that focuses on whole procedure training (e.g. sterilization and catheter insertion), including a gamified Graphical User Interface. The goal of this paper was to (1) develop a game-like, patient-centered interface to foster personalized learning and (2) understand the perceived utility of gamification for CVC skill development with expert doctors. This paper outlines some of the potential benefits and deficits of the use of gamification in medical trainers that can be used to drive simulation design.

From the simulation center to the bedside: Validating the efficacy of a dynamic haptic robotic trainer in internal jugular central venous catheter placement.

BACKGROUND: The objective of this study was to validate the transfer of ultrasound-guided Internal Jugular Central Venous Catheterization (US-IJCVC) placement skills from training on a Dynamic Haptic Robotic Trainer (DHRT), to placing US-IJCVCs in clinical environments. DHRT training greatly reduces preceptor time by providing automated feedback, standardizes learning experiences, and quantifies skill improvements. METHODS: Expert observers evaluated DHRT-trained (N = 21) and manikin-trained (N = 36) surgical residents on US-IJCVC placement in the operating suite using a US-IJCVC evaluation form. Performance and errors by DHRT-trained residents were compared to traditional manikin-trained residents. RESULTS: There were no significant training group differences between unsuccessful insertions (p = 0.404), assistance on procedure (p = 0.102), arterial puncture (p = 0.998), and average number of insertion attempts (p = 0.878). Regardless of training group, previous central line experience significantly predicted whether residents needed assistance on the procedure (p = 0.033). CONCLUSION: The results failed to show a statistical difference between DHRT- and manikin-trained residents. This study validates the transfer of skills from training on the DHRT system to performing US-IJCVC in clinical environments.

OBJECTIVE ASSESSMENT METRICS FOR CENTRAL LINE SIMULATORS: AN EXPLORATION OF CAUSAL FACTORS.

The Dynamic Haptic Robotic Trainer (DHRT) was developed to minimize the up to 39% of adverse effects experienced by patients during Central Venous Catheterization (CVC) by standardizing CVC training, and provide automated assessments of performance. Specifically, this system was developed to replace manikin trainers that only simulate one patient anatomy and require a trained preceptor to evaluate the trainees' performance. While the DHRT system provides automated feedback, the utility of this system with real-world scenarios and expertise has yet to be thoroughly investigated. Thus, the current study was developed to determine the validity of the current objective assessment metrics incorporated in the DHRT system through expert interviews. The main findings from this study are that experts do agree on perceptions of patient case difficulty, and that characterizations of patient case difficulty is based on anatomical characteristics, multiple needle insertions, and prior catheterization.

Low-Cost Haptic Simulation Using Material Fracture.

Medical simulation training is widely used to effectively train for invasive medical procedures such as peripheral nerve blocks. Traditionally, accurate haptic training relies on expensive cadavers, manikins, or advanced haptic robots. Proposed herein is a novel concept for haptic training called the low-cost haptic force needle insertion simulator (LCNIS), which uses material fracture inside disposable cartridges to accurately replicate the force of inserting a needle into tissue. Cadaver and material fracture experiments were performed to develop and determine the accuracy of the LCNIS. The material testing showed that polycarbonate had the highest maximum needle puncture force of the materials tested, 9.85 N, and that fluorinated ethylene propylene had the lowest maximum puncture force, 0.84 N. The cadaver results showed that the error between the three peak forces in a cadaver and a cadaver mimicking cartridge was 1.00 N, 0.01 N, and 1.54 N. The standard deviation of these peaks was 0.60 N, 0.55 N, and 0.41 N. This novel method of haptic simulation can easily be adapted to recreate any type of force and, therefore, could be utilized to train for a wide variety of medical procedures.

Can Haptic Simulators Distinguish Expert Performance? A Case Study in Central Venous Catheterization in Surgical Education.

INTRODUCTION: High-tech simulators are gaining popularity in surgical training programs because of their potential for improving clinical outcomes. However, most simulators are static in nature and only represent a single anatomical patient configuration. The Dynamic Haptic Robotic Training (DHRT) system was developed to simulate these diverse patient anatomies during Central Venous Catheterization (CVC) training. This article explores the use of the DHRT system to evaluate objective metrics for CVC insertion by comparing the performance of experts and novices. METHODS: Eleven expert surgeons and 13 first-year surgical residents (novices) performed multiple needle insertion trials on the DHRT system. Differences between expert and novice performance on the following five metrics were assessed using a multivariate analysis of variance: path length, standard deviation of deviations (SDoD), average velocity, distance to the center of the vessel, and time to complete (TtC) the needle insertion. A regression analysis was performed to identify if expertise could be predicted using these metrics. Then, a curve fit was conducted to identify whether learning curves were present for experts or novices on any of these five metrics. RESULTS: Time to complete the insertion and SDoD of the needle tip from an ideal path were significantly different between experts and novices. Learning curves were not present for experts but indicated a significant decrease in path length and TtC for novices. CONCLUSIONS: The DHRT system was able to identify significant differences in TtC and SDoD between experts and novices during CVC needle insertion procedures. In addition, novices were shown to improve their skills through DHRT training.

Simulating Ultrasound Tissue Deformation Using Inverse Mapping.

Ultrasound guidance is used for a variety of surgical needle insertion procedures, but there is currently no standard for the teaching of ultrasound skills. Recently, computer ultrasound simulation has been introduced as an alternative teaching method to traditional manikin and cadaver training because of its ability to provide diverse scenario training, quantitative feedback, and objective assessment. Current computer ultrasound training simulation is limited in its ability to image tissue deformation caused by needle insertions, even though tissue deformation identification is a critical skill in performing an ultrasound-guided needle insertion. To fill this need for improved simulation, a novel method of simulating ultrasound tissue-needle deformation is proposed and evaluated. First, a cadaver study is conducted to obtain ultrasound video of a peripheral nerve block. Then, optical flow analysis is conducted on this video to characterize the tissue movement due to the needle insertion. Tissue movement is characterized into three zones of motion: tissue near the needle being pulled, and zones above and below the needle where the tissue rolls. The rolling zones were centered 1.34 mm above and below the needle and 4.53 mm behind the needle. Using this characterization, a vector field is generated mimicking these zones. This vector field is then applied to an ultrasound image using inverse mapping to simulate tissue movement. The resulting simulation can be processed at 3.1 frames per second. This methodology can be applied through future optimized graphical processing to allow for accurate real time needle tissue simulation.

Can Eye Tracking be Used to Predict Performance Improvements in Simulated Medical Training? A Case Study in Central Venous Catheterization.

Manikins have traditionally been used to train ultrasound-guided Central Venous Catheterization (CVC), but are static in nature and require an expert observer to provide feedback. As a result, virtual simulation and personalized learning has been increasingly adopted in medical education to efficiently provide quantitative feedback. The Dynamic Haptic Robotic Trainer (DHRT) trains surgical residents in CVC needle insertions by simulating various patient profiles and presenting personalized feedback on objective performance. However, no studies have examined the learning gains of the personalized learning feedback or the relation of feedback to what the user is focusing on during the training. Thus, this study was developed to determine the effectiveness of the current personalized learning interface through a long-term investigation with 7 surgical residents. The eye tracking analysis showed that residents spent significantly more time fixated on percent aspiration throughout the study; the more time participants spent looking at the Number of Insertions, Percent Aspiration and the Angle of Insertion on the DHRT GUI, the better they performed on subsequent trials on the DHRT system.

Evaluating Surgical Resident Needle Insertion Skill Gains in Central Venous Catheterization Training.

BACKGROUND: Training for ultrasound-guided central venous catheterization (CVC) is typically conducted on static manikin simulators with real-time feedback from a skilled observer. Dynamic haptic robotic trainers (DHRTs) are an alternative method that simulates various patient anatomies and provides consistent feedback for each insertion. This study evaluates CVC needle insertion efficiency and skill gains of both methods. MATERIALS AND METHODS: Fifty-two first-year surgical residents were trained by placing internal jugular (IJ) CVC needles in manikins (n = 26) or robots (n = 26). Manikin-trained participants received verbal feedback from an experienced observer, whereas robotically trained participants received quantitative feedback from the personalized DHRT learning interface. All participants were pretested on a Blue Phantom manikin; participants completed posttesting on a Blue Phantom manikin (n = 26) or a novel manikin (n = 26) with different vessel depth and position. During pretests and posttests residents were timed, motion-tracked, and scored on an IJ CVC checklist. RESULTS: (1) All skills on the IJ CVC checklist showed significant (P < 0.014) improvements from pretests to posttest; (2) Average angle of insertion, path length, and jerk improved significantly (P < 0.005); (3) Average procedural completion time, with standard error (SE) reported, decreased significantly from pretest (M = 3.516 min, SE = 0.277) to posttest (M = 1.997, SE = 0.409). CONCLUSIONS: No significant group differences were observed in overall skill gains, but residents' average procedural completion time decreased significantly from pretests to posttest. Overall results support DHRT as an effective method for training IJ CVC skills.

Looks can be deceiving: Gaze pattern differences between novices and experts during placement of central lines.

BACKGROUND: The objective of this study was to determine whether gaze patterns could differentiate expertise during simulated ultrasound-guided Internal Jugular Central Venous Catheterization (US-IJCVC) and if expert gazes were different between simulators of varying functional and structural fidelity. METHODS: A 2017 study compared eye gaze patterns of expert surgeons (n = 11), senior residents (n = 4), and novices (n = 7) during CVC needle insertions using the dynamic haptic robotic trainer (DHRT), a system which simulates US-IJCVC. Expert gaze patterns were also compared between a manikin and the DHRT. RESULTS: Expert gaze patterns were consistent between the manikin and DHRT environments (p = 0.401). On the DHRT system, CVC experience significantly impacted the percent of time participants spent gazing at the ultrasound screen (p < 0.0005) and the needle and ultrasound probe (p < 0.0005). CONCLUSION: Gaze patterns differentiate expertise during ultrasound-guided IJCVC placement and the fidelity of the simulator does not impact gaze patterns.

Investigating the Effect of Simulator Functional Fidelity and Personalized Feedback on Central Venous Catheterization Training.

OBJECTIVE: To compare the effect of simulator functional fidelity (manikin vs a Dynamic Haptic Robotic Trainer [DHRT]) and personalized feedback on surgical resident self-efficacy and self-ratings of performance during ultrasound-guided internal jugular central venous catheterization (IJ CVC) training. In addition, we seek to explore how self-ratings of performance compare to objective performance scores generated by the DHRT system. DESIGN: Participants were randomly assigned to either manikin or DHRT IJ CVC training over a 6-month period. Self-efficacy surveys were distributed before and following training. Training consisted of a pretest, 22 practice IJ CVC needle insertion attempts, 2 full-line practice attempts, and a posttest. Participants provided self-ratings of performance for each needle insertion and were presented with feedback from either an upper level resident (manikin) or a personalized learning system (DHRT). SETTING: A study was conducted from July 2016 to February 2017 through a surgical skills training program at Hershey Medical Center in Hershey, Pennsylvania. PARTICIPANTS: Twenty-six first-year surgical residents were recruited for the study. Individuals were informed that IJ CVC training procedures would be consistent regardless of participation in the study and that participation was optional. All recruited residents opted to participate in the study. RESULTS: Residents in both groups significantly improved their self-efficacy scores from pretest to posttest (p < 0.01). Residents in the manikin group consistently provided higher self-ratings of performance (p < 0.001). Residents in the DHRT group recorded more feedback on errors (228 instances) than the manikin group (144 instances). Self-ratings of performance on the DHRT system were able to significantly predict the objective score of the DHRT system (R2 = 0.223, p < 0.001). CONCLUSION: Simulation training with the DHRT system and the personalized learning feedback can improve resident self-efficacy with IJ CVC procedures and provide sufficient feedback to allow residents to accurately assess their own performance.

Integrating Cadaver Needle Forces Into a Haptic Robotic Simulator.

Accurate force simulation is essential to haptic simulators for surgical training. Factors such as tissue inhomogeneity pose unique challenges for simulating needle forces. To aid in the development of haptic needle insertion simulators, a handheld force sensing syringe was created to measure the motion and forces of needle insertions. Five needle insertions were performed into the neck of a cadaver using the force sensing syringe. Based on these measurements a piecewise exponential needle force characterization, was implemented into a haptic central venous catheterization (CVC) simulator. The haptic simulator was evaluated through a survey of expert surgeons, fellows, and residents. The maximum needle insertion forces measured ranged from 2.02 N to 1.20 N. With this information, four characterizations were created representing average, muscular, obese, and thin patients. The median survey results showed that users statistically agreed that "the robotic system made me sensitive to how patient anatomy impacts the force required to advance needles in the human body." The force sensing syringe captured force and position information. The information gained from this syringe was able to be implemented into a haptic simulator for CVC insertions, showing its utility. Survey results showed that experts, fellows, and residents had an overall positive outlook on the haptic simulator's ability to teach haptic skills.

Training Surgical Residents With a Haptic Robotic Central Venous Catheterization Simulator.

OJECTIVE: Ultrasound guided central venous catheterization (CVC) is a common surgical procedure with complication rates ranging from 5 to 21 percent. Training is typically performed using manikins that do not simulate anatomical variations such as obesity and abnormal vessel positioning. The goal of this study was to develop and validate the effectiveness of a new virtual reality and force haptic based simulation platform for CVC of the right internal jugular vein. DESIGN: A CVC simulation platform was developed using a haptic robotic arm, 3D position tracker, and computer visualization. The haptic robotic arm simulated needle insertion force that was based on cadaver experiments. The 3D position tracker was used as a mock ultrasound device with realistic visualization on a computer screen. Upon completion of a practice simulation, performance feedback is given to the user through a graphical user interface including scoring factors based on good CVC practice. The effectiveness of the system was evaluated by training 13 first year surgical residents using the virtual reality haptic based training system over a 3 month period. RESULTS: The participants' performance increased from 52% to 96% on the baseline training scenario, approaching the average score of an expert surgeon: 98%. This also resulted in improvement in positive CVC practices including a 61% decrease between final needle tip position and vein center, a decrease in mean insertion attempts from 1.92 to 1.23, and a 12% increase in time spent aspirating the syringe throughout the procedure. CONCLUSIONS: A virtual reality haptic robotic simulator for CVC was successfully developed. Surgical residents training on the simulation improved to near expert levels after three robotic training sessions. This suggests that this system could act as an effective training device for CVC.