The focus of the project is on the interoperability of medical devices and high-bit-rate wireless data transmission using 5G, among other technologies. The goal of ICCAS in the project.Open5GPaceMaker is to integrate Time Sensitive Networks (TSN) into an existing medical device in a hospital environment. To achieve this goal, the clinical requirements for signal transmission in medical devices, as well as current technical solutions from medical device manufacturers and communication technology vendors.
For Open5GPaceMaker, a demonstrator will be produced that allows real-time wireless transmission of its control commands within an operating room using TSN over 5G. Through an existing and long-standing collaboration with the University Hospital Leipzig, realistic tests of the developed demonstrators are performed. On the level of communications engineering, ICCAS works closely with project partners and contributes experience from the field of medical applications. In cooperation with the University Hospital Leipzig, the clinical requirements for TSN over 5G in a hospital environment will be determined and made available to the project partners. The results will be implemented and tested in the LivingLab
Due to rapid advances in medical and pharmacological research, physicians today have increasingly effective options for the treatment of cancer. However, as the appropriate drugs are increasingly tailored to the specific characteristics of the patient and disease, new challenges arise in taking into account the complex diagnostic data and available therapeutic information (e.g. clinical trials). Since 2020, the Innovation Center Computer Assisted Surgery (ICCAS) at Leipzig University Medical Center, together with the Clinic for Hematology, Cell Therapy and Hemostaseology at Leipzig University Hospital, has been developing the IT platform “KAIT” – a comprehensive system for the analysis of medical information, which is intended to support the process of therapy decision-making in the clinical picture of multiple myeloma in the long term. The aim is to provide the treating physicians with all the latest information on the available therapeutic options so that every decision can be made on the basis of the latest findings. This will make an important contribution to the treatment of myeloma patients in Germany, regardless of where they receive medical care. Within the VOLTA project, this new and innovative form of clinical assistance will be further developed and extensively tested and optimized with clinical experts. These measures will ensure that “KAIT” can make a reliable and safe contribution to everyday clinical practice in the long term.
The European medical response system is comprised of first responder units that are operating quickly and lightly. On occurring disasters (e.g., earthquakes, tsunamis, floods, etc.), these Emergency Medical Teams (EMT) are deployed on disaster relief missions to support the local medical system and avert humanitarian crises. As part of the “RescEU EMT” project, the European medical response system is being expanded to include modular, flexible units and special cells.
The “EMT Operating System” (EOS) is a field hospital information system, which is tailored to the requirements of EMT on disaster relief missions. Its idea was created and designed during the EUMFH-Project. The system supports the whole patient treatment process from triage to discharge and is highly configurable to adapt to the needs of the EMT. Despite EOS being primarily designed as an electronic patient record, it also includes essential functions for EMT mission and field hospital management. Besides patient management and treatment documentation, EOS enables quick department configuration, visualization of important hospital key performance indicators (patient admissions, triage category count, department workload, etc.) and reporting functionalities (e.g. to local government or WHO). Thus, EOS plays an essential role in monitoring and assessing the current situation and performance on a strategic and tactical level.
EOS provides highly customizable functionalities. They can be adjusted to the specific frameworks of different EMT entities or other requirements by specialized teams, e.g. Burn Assessment Teams. Generally speaking, EOS includes digital documentation and management of the usual processes within an EMT. However, detailed characteristics can differ.
EOS relies heavily on structured data entry and storage (in contrast to free texts). This ensures high information quality and supports fast and easy data input as well as automatic information aggregation in databases. The latter benefits the reporting obligation and allows for comparison between different missions or EMT installations.
Under commission by the avatera medical GmbH (https://www.avatera.eu/home), ICCAS is investigating the possibilities to optimize the positioning principles of a novel robotic system for laparoscopic interventions. In cooperation with the urology department of the University of Leipzig Medical Center, the requirements for the pre-positioning of the system at the OR-table were defined and transferred into robotic workspace simulations.
The aim of this work is to provide an intuitive procedure for the docking process of the robot at the OR-table and an optimized positioning for the robot arms at the patient for the best possible workspace during the intervention. ICCAS developed a guidance manual for the side docking of the system and currently investigates the feasibility for radical prostatectomies and combined hysterectomies and Lymphadenectomies.
In practice, medical decision-making to determine suitable therapeutic approaches for an individual patient is subject to both a medical and a regulatory framework. Indication-specific guidelines, which indicate the treatment options approved (and thus applicable) in the respective health care system, form the formal basis for this. Although physicians can also act outside of these guidelines (so-called off-label use), they usually need good reasons and the approval of the respective payer. Furthermore, clinical trials are of course an essential factor in the evaluation of the best possible therapeutic option, although this aspect cannot be attributed to routine care and is dependent on numerous external factors (range of trials, suitability of the patient, randomization, etc.).
The fundamental question in any therapy-associated decision-making process is which available option offers the highest chance of success with equally low risk for the individual clinical picture of a patient. However, due to the heterogeneity of the individual and the disease, this consideration is very complex and requires the parallel consideration of multiple factors. The limitation of the therapeutic scope of action facilitating this circumstance does not solve the problem of the cognitive simulation of all possible implications in order to determine an appropriate optimum. Furthermore, there is the legitimate question which circumstance can be regarded as optimal at all, since the definition of success or failure may differ between therapist and patient. For example, a therapy could lead to tremendous clinical success, but equally come with the high risk of an invasive side effect. These sometimes life-changing decisions therefore require a high level of safety, education, and communication on an equal footing between all parties involved.
A technical possibility to provide assistance in the process of medical decision making are clinical decision support systems, which match specific characteristics of a patient (e.g. clinical findings) with a previously created knowledge base to quantitatively evaluate all available options. The VISION-CRE project therefore focuses on the establishment of a “Cognitive Reasoning Engine (CRE)”, which complements the guideline-based specification of possible therapy options with a novel evidence-based evaluation level. The overall goal is to extend the existing decision support tools by evaluating already collected and recorded empirical data of the sequence: (1) patient:in, (2)therapy and (3) resulting reaction in order to draw valuable conclusions for the treatment of patients.
The GenoMed4All project is an EU-wide initiative for the establishment of a network-infrastructure to facilitate the exchange of clinical data in a federated learning framework. By integrating valuable clinical data up to multi-OMICS levels, the project aims to significantly improve quantitative analysis using machine learning (ML) and artificial intelligence (AI) methods. GenoMed4All focuses on a range of hematological diseases, which are becoming increasingly complex due to the particularly advanced utilization of precision diagnostics and personalized therapies.
In partnership with the Clinic and Polyclinic for Hematology, Cell Therapy and Hemostaseology at the University of Leipzig Medical Center, ICCAS is contributing to the mplementation of the federated data integration mechanisms as well as advanced data standardization based on HL7 FHIR.
External project site: https://genomed4all.eu
In the SaxoCell Systems project, ICCAS is developing mechanisms for secure tracking of necessary resources (analog and digital) in the context of ATMP development (e.g., findings, cells, pharmaceutical materials, etc.) on the basis of formal process models. For this purpose, the involved assets are first defined in the form of interoperable (HL7 FHIR) resources. Then, these digital images are instantiated within an IT platform based on a blockchain infrastructure and compared to an ideal process model with the principles of Good Manufacturing Practice (GMP). In the context of the SaxoCell overall project, the resulting supply chain management solution is intended to enable seamless traceability for ATMP manufacturing processes in order to enable superior and sustainable quality management in all areas of the intended platform.
External project page: https://saxocell.de
The vision of NFDI4DataScience (NFDI4DS) is to support all steps of the complex and interdisciplinary research data lifecycle, including collecting/creating, processing, analyzing, publishing, archiving, and reusing resources in Data Science and Artificial Intelligence.
The past years have seen a paradigm shift, with computational methods increasingly relying on data-driven and often deep learning-based approaches, leading to the establishment and ubiquity of Data Science as a discipline driven by advances in the field of Computer Science. Transparency, reproducibility and fairness have become crucial challenges for Data Science and Artificial Intelligence due to the complexity of contemporary Data Science methods, often relying on a combination of code, models and data used for training. NFDI4DS will promote fair and open research data infrastructures supporting all involved resources such as code, models, data, or publications through an integrated approach.
The overarching objective of NFDI4DS is the development, establishment, and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community in Germany. This will also deliver benefits for a wider community requiring data analytics solutions, within the NFDI and beyond. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artifacts available, interlinking them, and offering innovative tools and services. Based on the reuse of these digital objects, this enables new and innovative research.
NFDI4DS intends to represent the Data Science and Artificial Intelligence community in academia, which is an interdisciplinary field rooted in Computer Science. We aim to reuse existing solutions and to collaborate closely with the other NFDI consortia and beyond. In the initial phase, NFDI4DS will focus on four Data Science intense application areas: language technology, biomedical sciences, information sciences and social sciences. The expertise available in NFDI4DS ensures that metadata standards are interoperable across domains and that new ways of dealing with digital objects arise.
As one of the recently extended German centers for Artificial Intelligence (AI), ScaDS.AI aims to close the gap between efficient use of large amounts of data in both industry and research and advanced AI methods. For this purpose, the research topics at ScaDS.AI range from foundational AI methodology up to the application of AI in key areas like engineering, environmental systems, industry, and biomedical research, cooperating with many local companies and scientific institutions. Furthermore, increasing the public trust in AI is taken into consideration by integrating ethical and societal perspectives and making research available through the service center and Living Lab.
To push forward AI in the life sciences, ScaDS.AI cooperates with ICCAS by sharing research expertise and computing resources, focusing primarily on model-based, personalized cancer treatments.
The goal of ICCAS in the 5G-COMPASS project is to integrate current and future communication technology into medical (-technical) care. To achieve this goal, both medical device manufacturers and communication technology manufacturers must be supported in the development of their products. In the project, a test hardware will be developed that allows medical device manufacturers to easily test different communication channels (Wi-Fi, Li-Fi, 5G) and thus verify the performance of their products. On the other hand, realistic data is provided to the communication technology over different channels, thus enabling testing of the communication technology in a realistic environment. To this end, the company draws on its many years of expertise in modeling
surgical interventions and process automation. On the level of communications engineering, ICCAS is a user of the communications technology, works closely with the partners from communications engineering in the project and contributes requirements and experience from the field of medical applications. Selectively, it collaborates on the development of algorithms and configurations where specific adaptations for the field of medical applications are necessary. On the medical technology side, there is intensive collaboration with the partners KLS-Martin and SurgiTAIX. The results are implemented and tested in the LivingLab of ICCAS.