Simulated versus physical bench tests: The economic evaluation of the InSilc platform for designing, developing, and assessing vascular scaffolds.

BACKGROUND: In silico medicine allows for pre-clinical and clinical simulated assessment of medical technologies and the building of patient-specific models to support medical decisions and forecast personal health status. While there is increasing trust in the potential central role of in silico medicine, there is a need to recognize its degree of reliability and evaluate its economic impact. An in silico platform has been developed within a Horizon 2020-funded project (In-Silc) for simulations functional to designing, developing, and assessing drug-eluting bioresorbable vascular scaffolds.The main purpose of this study was to compare the costs of 2 alternative strategies: the adoption of In-Silc platform versus the performance of only physical bench tests. METHODS: A case study was provided by a medical device company. The values of the model parameters were principally set by the project partners, with use of interviews and semi-structured questionnaires, and, when not available, through literature searches or derived by statistical techniques. An economic model was built to represent the 2 scenarios. RESULTS: The InSilc strategy is superior to the adoption of physical bench tests only. Ceteris paribus, the costs are 424,355€ for the former versus 857,811€ for the latter. CONCLUSIONS: In silico medicine tools can decrease the cost of the research and development of medical devices such as bioresorbable vascular scaffolds. Further studies are needed to explore the impact of such solutions on the innovation capacity of companies and the consequent potential advantages for target patients and the healthcare system.

A systematic review of low-cost simulators in ENT surgery.

BACKGROUND: Simulation training has become a key part of the surgical curriculum over recent years. Current trainees face significantly reduced operating time as a result of the coronavirus disease 2019 pandemic, alongside increased costs to surgical training, thus creating a need for low-cost simulation models. METHODS: A systematic review of the literature was performed using multiple databases. Each model included was assessed for the ease and expense of its construction, as well as its validity and educational value. RESULTS: A total of 18 low-cost simulation models were identified, relating to otology, head and neck surgery, laryngeal surgery, rhinology, and tonsil surgery. In only four of these models (22.2 per cent) was an attempt made to demonstrate the educational impact of the model. Validation was rarely formally assessed. CONCLUSION: More efforts are required to standardise validation methods and demonstrate the educational value of the available low-cost simulation models in otorhinolaryngology.

The Neurosphere Simulator: An educational online tool for modeling neural stem cell behavior and tissue growth.

Until very recently, distance education, including digital science labs, served a rather small portion of postsecondary students in the United States and many other countries. This situation has, however, dramatically changed in 2020 in the wake of the COVID-19 pandemic, which forced colleges to rapidly transit from face-to-face instructions to online classes. Here, we report the development of an interactive simulator that is freely available on the web (http://neurosphere.cos.northeastern.edu/) for teaching lab classes in developmental biology. This simulator is based on cellular automata models of neural-stem-cell-driven tissue growth in the neurosphere assay. By modifying model parameters, users can explore the role in tissue growth of several developmental mechanisms, such as regulation of mitosis or apoptotic cell death by contact inhibition. Besides providing an instantaneous animation of the simulated development of neurospheres, the Neurosphere Simulator tool offers also the possibility to download data for detailed analysis. The simulator function is complemented by a tutorial that introduces students to computational modeling of developmental processes.

Use of a Low-Cost Portable 3D Virtual Reality Gesture-Mediated Simulator for Training and Learning Basic Psychomotor Skills in Minimally Invasive Surgery: Development and Content Validity Study.

BACKGROUND: Simulation in virtual environments has become a new paradigm for surgeon training in minimally invasive surgery (MIS). However, this technology is expensive and difficult to access. OBJECTIVE: This study aims first to describe the development of a new gesture-based simulator for learning skills in MIS and, second, to establish its fidelity to the criterion and sources of content-related validity evidence. METHODS: For the development of the gesture-mediated simulator for MIS using virtual reality (SIMISGEST-VR), a design-based research (DBR) paradigm was adopted. For the second objective, 30 participants completed a questionnaire, with responses scored on a 5-point Likert scale. A literature review on the validity of the MIS training-VR (MIST-VR) was conducted. The study of fidelity to the criterion was rated using a 10-item questionnaire, while the sources of content-related validity evidence were assessed using 10 questions about the simulator training capacity and 6 questions about MIS tasks, and an iterative process of instrument pilot testing was performed. RESULTS: A good enough prototype of a gesture-based simulator was developed with metrics and feedback for learning psychomotor skills in MIS. As per the survey conducted to assess the fidelity to the criterion, all 30 participants felt that most aspects of the simulator were adequately realistic and that it could be used as a tool for teaching basic psychomotor skills in laparoscopic surgery (Likert score: 4.07-4.73). The sources of content-related validity evidence showed that this study's simulator is a reliable training tool and that the exercises enable learning of the basic psychomotor skills required in MIS (Likert score: 4.28-4.67). CONCLUSIONS: The development of gesture-based 3D virtual environments for training and learning basic psychomotor skills in MIS opens up a new approach to low-cost, portable simulation that allows ubiquitous learning and preoperative warm-up. Fidelity to the criterion was duly evaluated, which allowed a good enough prototype to be achieved. Content-related validity evidence for SIMISGEST-VR was also obtained.

A 3D trabecular bone homogenization technique.

PURPOSE: Bone is a hierarchical material that can be characterized from the microscale to macroscale. Multiscale models make it possible to study bone remodeling, inducing bone adaptation by using information of bone multiple scales. This work proposes a computationally efficient homogenization methodology useful for multiscale analysis. This technique is capable to define the homogenized microscale mechanical properties of the trabecular bone highly heterogeneous medium. METHODS: In this work, a morphology- based fabric tensor and a set of anisotropic phenomenological laws for bone tissue was used, in order to define the bone micro-scale mechanical properties. To validate the developed methodology, several examples were performed in order to analyze its numerical behavior. Thus, trabecular bone and fabricated benchmarks patches (representing special cases of trabecular bone morphologies) were analyzed under compression. RESULTS: The results show that the developed technique is robust and capable to provide a consistent material homogenization, indicating that the homogeneous models were capable to accurately reproduce the micro-scale patch mechanical behavior. CONCLUSIONS: The developed method has shown to be robust, computationally less demanding and enabling the authors to obtain close results when comparing the heterogeneous models with equivalent homogenized models. Therefore, it is capable to accurately predict the micro-scale patch mechanical behavior in a fraction of the time required by classic homogenization techniques.

Inexpensive, High-Fidelity Model to Simulate Ultrasound-Guided Pericardiocentesis for Cardiology Resident Training.

Adult cardiology residency training programs require residents to become proficient at many procedural skills, including pericardiocentesis. However, in many programs, opportunities to perform this procedure are limited. Expensive mannequins have been developed to assist with teaching this skill, however, the associated cost make them impractical for many programs. We hypothesized that a low-cost, high-fidelity pericardiocentesis model could be constructed using items easily accessible to any consumer. We describe a pericardiocentesis model made from pork skin, pork ribs, gelatin, a plastic bag, and an avocado. Total cost was less than CAD$40.00 and preparation time was approximately 60 minutes. The model was evaluated with a survey by 14 senior cardiology and critical care residents as well as 3 experienced senior cardiologists. Imaging results from the ultrasound revealed that the target fluid was easily visualized and all trainees were successful in aspirating fluid. The model was durable and withstood more than a dozen punctures, demonstrating its ability to train multiple residents. Respondents to the survey reported the model as highly realistic. All cardiology residents agreed or strongly agreed that the model should be incorporated into their formal curriculum. This study shows that a low-cost, high-fidelity model can be constructed and easily implemented into the formal curriculum of adult cardiology residency programs. It allows residents the opportunity to practice pericardiocentesis in a low-risk setting on a high-yield device.

A Selective Biogeography-Based Optimizer Considering Resource Allocation for Large-Scale Global Optimization.

Biogeography-based optimization (BBO), a recent proposed metaheuristic algorithm, has been successfully applied to many optimization problems due to its simplicity and efficiency. However, BBO is sensitive to the curse of dimensionality; its performance degrades rapidly as the dimensionality of the search space increases. In this paper, a selective migration operator is proposed to scale up the performance of BBO and we name it selective BBO (SBBO). The differential migration operator is selected heuristically to explore the global area as far as possible whist the normal distributed migration operator is chosen to exploit the local area. By the means of heuristic selection, an appropriate migration operator can be used to search the global optimum efficiently. Moreover, the strategy of cooperative coevolution (CC) is adopted to solve large-scale global optimization problems (LSOPs). To deal with subgroup imbalance contribution to the whole solution in the context of CC, a more efficient computing resource allocation is proposed. Extensive experiments are conducted on the CEC 2010 benchmark suite for large-scale global optimization, and the results show the effectiveness and efficiency of SBBO compared with BBO variants and other representative algorithms for LSOPs. Also, the results confirm that the proposed computing resource allocation is vital to the large-scale optimization within the limited computation budget.

A Modified Dragonfly Optimization Algorithm for Single- and Multiobjective Problems Using Brownian Motion.

The dragonfly algorithm (DA) is one of the optimization techniques developed in recent years. The random flying behavior of dragonflies in nature is modeled in the DA using the Levy flight mechanism (LFM). However, LFM has disadvantages such as the overflowing of the search area and interruption of random flights due to its big searching steps. In this study, an algorithm, known as the Brownian motion, is used to improve the randomization stage of the DA. The modified DA was applied to 15 single-objective and 6 multiobjective problems and then compared with the original algorithm. The modified DA provided up to 90% improvement compared to the original algorithm's minimum point access. The modified algorithm was also applied to welded beam design, a well-known benchmark problem, and thus was able to calculate the optimum cost 20% lower.

Broadening the Perspective of Cost-Effectiveness Modeling in Chronic Obstructive Pulmonary Disease: A New Patient-Level Simulation Model Suitable to Evaluate Stratified Medicine.

OBJECTIVES: To develop a health economic model that included a great diversity of patient characteristics and outcomes for chronic obstructive pulmonary disease (COPD), which can be used to inform decisions about stratified medicine in COPD. METHODS: The choice of patient characteristics and outcomes to include in the model was based on 3 literature reviews on multidimensional prognostic COPD indices, COPD phenotypes, and treatment effects in subgroups. A conceptual model was constructed including 14 patient characteristics, 7 intermediate outcomes (lung function, physical activity, exercise capacity, symptoms, disease-specific quality of life, exacerbations, and pneumonias), and 3 final outcomes (mortality, quality-adjusted life-years [QALYs], and costs). Regression equations describing the statistical associations between the patient characteristics and intermediate and final outcomes were estimated using the longitudinal data of 5 large COPD trials (19,378 patients). A patient-level simulation model was developed in which individual patients from the baseline population of the 5 trials are sampled and their outcomes over lifetime are predicted based on the regression equations. RESULTS: The base-case analysis (single-arm simulation representing treatment with tiotropium) showed that patients had a mean lung function decline of 43 mL/year, 0.62 exacerbations/year, a worsening of their physical activity and quality of life with 1.48 and 1.10 points/year, a life expectancy of 11.2 years, 7.25 QALYs, and total lifetime costs of £24,891. Results for a selection of treatment scenarios and subgroups were shown to demonstrate the potential of the model. CONCLUSIONS: We developed a unique patient-level simulation model that can be used to evaluate COPD treatment options for a variety of subgroups.

A hidden markov model for identifying differentially methylated sites in bisulfite sequencing data.

DNA methylation studies have enabled researchers to understand methylation patterns and their regulatory roles in biological processes and disease. However, only a limited number of statistical approaches have been developed to provide formal quantitative analysis. Specifically, a few available methods do identify differentially methylated CpG (DMC) sites or regions (DMR), but they suffer from limitations that arise mostly due to challenges inherent in bisulfite sequencing data. These challenges include: (1) that read-depths vary considerably among genomic positions and are often low; (2) both methylation and autocorrelation patterns change as regions change; and (3) CpG sites are distributed unevenly. Furthermore, there are several methodological limitations: almost none of these tools is capable of comparing multiple groups and/or working with missing values, and only a few allow continuous or multiple covariates. The last of these is of great interest among researchers, as the goal is often to find which regions of the genome are associated with several exposures and traits. To tackle these issues, we have developed an efficient DMC identification method based on Hidden Markov Models (HMMs) called "DMCHMM" which is a three-step approach (model selection, prediction, testing) aiming to address the aforementioned drawbacks. Our proposed method is different from other HMM methods since it profiles methylation of each sample separately, hence exploiting inter-CpG autocorrelation within samples, and it is more flexible than previous approaches by allowing multiple hidden states. Using simulations, we show that DMCHMM has the best performance among several competing methods. An analysis of cell-separated blood methylation profiles is also provided.

Global optimization using Gaussian processes to estimate biological parameters from image data.

Parameter estimation is a major challenge in computational modeling of biological processes. This is especially the case in image-based modeling where the inherently quantitative output of the model is measured against image data, which is typically noisy and non-quantitative. In addition, these models can have a high computational cost, limiting the number of feasible simulations, and therefore rendering most traditional parameter estimation methods unsuitable. In this paper, we present a pipeline that uses Gaussian process learning to estimate biological parameters from noisy, non-quantitative image data when the model has a high computational cost. This approach is first successfully tested on a parametric function with the goal of retrieving the original parameters. We then apply it to estimating parameters in a biological setting by fitting artificial in-situ hybridization (ISH) data of the developing murine limb bud. We expect that this method will be of use in a variety of modeling scenarios where quantitative data is missing and the use of standard parameter estimation approaches in biological modeling is prohibited by the computational cost of the model.

Process of medical simulator development: An approach based on personal experience.

With increasing demand for simulators from the healthcare community and increasingly sophisticated technology being used in the manufacture of medical simulators, the manufacture of healthcare simulators has become a multifaceted undertaking. Based on our experience in the field and our diverse backgrounds, we explore the processes and issues related to the development of these simulators and suggest ways for the developing teams to collaborate and coordinate with each other to achieve a successful outcome.

Ethics of Virtual Reality in Medical Education and Licensure.

The aim of this section is to expand and accelerate advances in curriculum developments and in methods of teaching bioethics.

Computer-Aided Surgical Simulation in Head and Neck Reconstruction: A Cost Comparison among Traditional, In-House, and Commercial Options.

BACKGROUND: Computer-aided surgical simulation (CASS) has redefined surgery, improved precision and reduced the reliance on intraoperative trial-and-error manipulations. CASS is provided by third-party services; however, it may be cost-effective for some hospitals to develop in-house programs. This study provides the first cost analysis comparison among traditional (no CASS), commercial CASS, and in-house CASS for head and neck reconstruction. METHODS: The costs of three-dimensional (3D) pre-operative planning for mandibular and maxillary reconstructions were obtained from an in-house CASS program at our large tertiary care hospital in Northern Virginia, as well as a commercial provider (Synthes, Paoli, PA). A cost comparison was performed among these modalities and extrapolated in-house CASS costs were derived. The calculations were based on estimated CASS use with cost structures similar to our institution and sunk costs were amortized over 10 years. RESULTS: Average operating room time was estimated at 10 hours, with an average of 2 hours saved with CASS. The hourly cost to the hospital for the operating room (including anesthesia and other ancillary costs) was estimated at $4,614/hour. Per case, traditional cases were $46,140, commercial CASS cases were $40,951, and in-house CASS cases were $38,212. Annual in-house CASS costs were $39,590. CONCLUSIONS: CASS reduced operating room time, likely due to improved efficiency and accuracy. Our data demonstrate that hospitals with similar cost structure as ours, performing greater than 27 cases of 3D head and neck reconstructions per year can see a financial benefit from developing an in-house CASS program.

Lessons Learned From the Development and Parameterization of a Computer Simulation Model to Evaluate Task Modification for Health Care Providers.

Computer simulation is a highly advantageous method for understanding and improving health care operations with a wide variety of possible applications. Most computer simulation studies in emergency medicine have sought to improve allocation of resources to meet demand or to assess the impact of hospital and other system policies on emergency department (ED) throughput. These models have enabled essential discoveries that can be used to improve the general structure and functioning of EDs. Theoretically, computer simulation could also be used to examine the impact of adding or modifying specific provider tasks. Doing so involves a number of unique considerations, particularly in the complex environment of acute care settings. In this paper, we describe conceptual advances and lessons learned during the design, parameterization, and validation of a computer simulation model constructed to evaluate changes in ED provider activity. We illustrate these concepts using examples from a study focused on the operational effects of HIV screening implementation in the ED. Presentation of our experience should emphasize the potential for application of computer simulation to study changes in health care provider activity and facilitate the progress of future investigators in this field.

Effectiveness and cost-effectiveness of embedded simulation in occupational therapy clinical practice education: study protocol for a randomised controlled trial.

BACKGROUND: Clinical placements are a critical component of the training for health professionals such as occupational therapists. However, with growing student enrolments in professional education courses and workload pressures on practitioners, it is increasingly difficult to find sufficient, suitable placements that satisfy program accreditation requirements. The professional accrediting body for occupational therapy in Australia allows up to 200 of the mandatory 1000 clinical placement hours to be completed via simulation activities, but evidence of effectiveness and efficiency for student learning outcomes is lacking. Increasingly placement providers charge a fee to host students, leading educators to consider whether providing an internal program might be a feasible alternative for a portion of placement hours. Economic analysis of the incremental costs and benefits of providing a traditional versus simulated placement is required to inform decision-making. METHODS/DESIGN: This study is a pragmatic, non-inferiority, single-blind, multicentre, two-group randomised controlled trial (RCT) with an embedded economic analysis. The RCT will compare a block of 40 hours of simulated placement (intervention) with a 40-hour block of traditional placement (comparator), with a focus on student learning outcomes and delivery costs. Six universities will instigate the educational intervention within their respective occupational therapy courses, randomly assigning their cohort of students (1:1 allocation) to the simulated or traditional clinical placements. The primary outcome is achievement of professional behaviours (e.g. communication, clinical reasoning) as assessed by a post-placement written examination. Secondary outcomes include proportions passing the placement assessed using the Student Practice Evaluation Form-Revised, changes in student confidence pre-/post-placement, student and educator evaluation of the placement experience and cost-effectiveness of simulated versus traditional clinical placements. Comprehensive cost data will be collected for both the simulated and traditional placement programs at each site for economic evaluation. DISCUSSION: Use of simulation in health-related fields like occupational therapy is common, but these activities usually relate to brief opportunities for isolated skill development. The simulated clinical placement evaluated in this trial is less common because it encapsulates a 5-day block of integrated activities, designed and delivered in a manner intended to emulate best-practice placement experiences. The planned study is rare due to inclusion of an economic analysis that aims to provide valuable information about the relationship between costs and outcomes across participating sites. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12616001339448 . Registered 26 September 2016.

Advanced Low-Cost Ultrasound-Guided Vascular Access Simulation: The Chicken Breast Model.

There is a growing body of literature that supports the use of ultrasound for vascular access. Advanced simulation has become a widely applied technique for training medical staff in vascular access. Nevertheless, advanced simulators are expensive and of limited usage. We describe both a step-wise systematic approach and an experimental cadaveric model of vascular access using a simple piece of chicken that can be easily used for trainees.

Cost-effective and low-technology options for simulation and training in neonatology.

The purpose of this review is to explore low-cost options for simulation and training in neonatology. Numerous cost-effective options exist for simulation and training in neonatology. Lower cost options are available for teaching clinical skills and procedural training in neonatal intubation, chest tube insertion, and pericardiocentesis, among others. Cost-effective, low-cost options for simulation-based education can be developed and shared in order to optimize the neonatal simulation training experience.