Reflective Nested Simulations Supporting Optimizations within Sequential Railway Traffic Simulators

This article describes and discusses railway-traffic simulators that use reflective nested simulations. Such simulations support optimizations (decision-making) with a focus on the selection of the most suitable solution where selected types of traffic problems are present. This approach allows suspension of the ongoing main simulation at a given moment and, by using supportive nested simulations (working with an appropriate lookahead), assessment of the different acceptable solution variants for the problem encountered—that is, a what-if analysis is carried out. The variant that provides the best predicted operational results (based on a specific criterion) is then selected for continuing the suspended main simulation. The proposed procedures are associated, in particular, with the use of sequential simulators specifically developed for railway traffic simulations. Special attention is paid to parallel computations of replications both of the main simulation and of supportive nested simulations. The concept proposed, applicable to railway traffic modelling, has the following advantages. First, the solution variants for the existing traffic situation are analyzed with respect to the feasibility of direct monitoring and evaluation of the natural traffic indicators or the appropriate (multi-criterial) function. The indicator values compare the results obtained from the variants being tested. Second, the supporting nested simulations, which potentially use additional hierarchic nesting, can also include future occurrences of random effects (such as train delay), thereby enabling us to realistically assess future traffic in stochastic conditions. The guidelines presented (for exploiting nested simulations within application projects with time constraints) are illustrated on a simulation case study focusing on traffic assessment related to the track infrastructure of a passenger railway station. Nested simulations support decisions linked with dynamic assignments of platform tracks to delayed trains. The use of reflective nested simulations is appropriate particularly in situations in which a reasonable number of admissible variants are to be analyzed within decision-making problem solution. This method is applicable especially to the support of medium-term (tactical) and long-term (strategic) planning. Because of rather high computational and time demands, nested simulations are not recommended for solving short-term (operative) planning/control problems.

Interactive virtual 3D image reconstruction to assist renal surgery in patients with fusion anomalies of the kidney

Objective: Renal fusion anomalies are rare and usually present as horseshoe kidneys or crossed fusion ectopia. The complex renal anatomy seen in patients with these anomalies can present a challenge. Pre-operative planning is therefore paramount in the surgical management of these cases. Herein we report the use of interactive virtual three-dimensional (3D) reconstruction to aid renal surgery in patients with fusion anomalies of the kidney. Materials and Methods: A total of seven cases were performed between May 2016 and October 2020. 3D reconstruction was rendered by Innersight Labs using pre-operative computed tomography (CT) scans. Results: Five patients had malignant disease and two patients had benign pathology. Robotic and open operations were performed in four and three patients, respectively. Conclusion: The use of 3D reconstruction in the cases reported in this series allowed for the identification of variations in renal vasculature, and this informed the choice of operative approach. Oxford Centre for Evidence-Based Medicine Evidence Level: 4

Role of Radiologic Imaging in Otosclerosis

Purpose of Review To review the role of imaging in otosclerosis with an emphasis on pre- and post-operative imaging evaluation. Recent Findings Pre-operative CT imaging can help define the extent of bone involvement in otosclerosis and may help avoid surgical complications due to variant anatomy or unsuspected alternative causes of conductive hearing loss. In patients with recurrent hearing loss after surgery, CT imaging can clarify prosthesis position and re-assess anatomy. Summary CT imaging complements otologic exam and audiometry findings in patients with suspected otosclerosis, for pre-operative planning, and post-operative assessment for patients with recurrent symptoms.

Artificial Intelligence-a Paradigm shift in Health Care Management

Artificial Intelligence (AI) is gradually changing the practice of surgery with the advanced technological development of imaging, navigation, and robotic intervention. In this article, the recent successful and influential applications of AI in surgery are reviewed from pre-operative planning and intra-operative guidance to the integration of surgical robots. It ends with summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery. Robotic surgery is the use of computer technologies working in conjunction with robot systems to perform medical procedures. The technology is also known as computer-aided surgery and robot-assisted surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments in the field of Neuro Surgery.

O02 THE ROLE OF DEEP LEARNING IN PREDICTING COMPLEXITY AND COMPLICATIONS IN ABDOMINAL WALL RECONSTRUCTION

Aim The aim of our study was to evaluate the utility of image-based deep learning models (DLMs) to predict surgical complexity and postoperative outcomes in patients undergoing AWR. Material and Methods A prospective, tertiary center, hernia database was queried for open AWR patients with adequate pre-operative CT-scans. An 8-layer convolutional neural network (CNN) analyzed image characteristics in Python utilizing the open source Tensorflow© and OpenCV frameworks. Images were analyzed and batched into a training set (80%) and validation set (20%) used to analyze the model output, which was blinded to the CNN until testing. DLMs were run to assess surgical complexity based on need for component separation, surgical site infection (SSI), and pulmonary failure. The surgical complexity DLM was validated by comparison to 6 expert AWR surgeons. Results In total, 369 patient CT scans were utilized. The surgical complexity DLM performed well (ROC=0.744;p<0.0001), and when compared to surgeon prediction on the validation set, performed better with an accuracy of 81.3% compared to 65.0% (p < 0.0001). The SSI DLM was successful with an ROC of 0.898 (p < 0.0001). The DLM for predicting pulmonary failure was less effective with an ROC of 0.545 (p = 0.03). Conclusions DLMs were able to successfully predict surgical complexity and were more accurate than expert surgeons using objective, pre-operative imaging. DLMs were also successful in predicting SSI. This breakthrough may allow for enhanced pre-operative planning, including resource utilization and possible need for tertiary center referral. AI appears to be an exciting new management tool in complex AWR.

Initial Assessment of the Facial Trauma Patient

The initial evaluation of the craniofacial trauma patient must be systematic, thorough, and consistent to ensure that injuries are not missed. Life-threatening conditions are first identified using ATLS principles, and focused head and neck examination conducted by a specialist then follows. Imaging is used to guide operative planning, as many craniofacial injuries ultimately benefit from repair to prevent permanent cosmetic or functional deformity. Peri-operative care is often multi-disciplinary in nature, and specialist consultation should be performed in an efficient fashion. Finally, it should be noted that surgeons operating in the maxillofacial region are at high risk for transmission of COVID-19, and risk of COVID-19 sequelae must be balanced with risks associated with the delay of treatment of craniofacial injury.

Parking Policy as a Tool of Sustainable Mobility-Parking Standards in Poland vs. European Experiences

Contemporary cities generally lack the balance between the development of the spatial structure and the communication possibilities of the inhabitants. The high motorisation rate in Poland, as well as in other European countries, and the preferred choice of individual means of transportation have both contributed to a significant increase in congestion over the last 10 years. The aim of this research was to try to establish to what extent a consciously conducted parking policy can help control the mobility of inhabitants of selected Polish cities. The starting point for the analysis was the availability of parking spaces in residential areas, introduced as an imposed indicator in the operative planning documents. As part of the research, the authors of this paper analyzed the legal provisions of the operative Local Spatial Development Plans (MPZP) concerning the parking function for housing estates five of the biggest cities in Poland. The results were confronted with data on selected European cities. Nearly 550 planning documents from the years 2000–2019 and parking standards operating in individual countries were cataloged and analyzed. The research results show that for 20 years Polish cities have mainly been using the possibility of determining the minimum rate of parking spaces. Regulations attempting to limit the number of cars are incidental. However, this is a necessary direction of legislative changes.

Development of a Multi-Material 3D Printer for Functional Anatomic Models

Anatomic models are important in medical education and pre-operative planning as they help students or doctors prepare for real scenarios in a risk-free way. Several experimental anatomic models were made with additive manufacturing techniques to improve geometric, radiological, or mechanical realism. However, reproducing the mechanical behavior of soft tissues remains a challenge. To solve this problem, multi-material structuring of soft and hard materials was proposed in this study, and a three-dimensional (3D) printer was built to make such structuring possible. The printer relies on extrusion to deposit certain thermoplastic and silicone rubber materials. Various objects were successfully printed for testing the feasibility of geometric features such as thin walls, infill structuring, overhangs, and multi-material interfaces. Finally, a small medical image-based ribcage model was printed as a proof of concept for anatomic model printing. The features enabled by this printer offer a promising outlook on mimicking the mechanical properties of various soft tissues.