Research

BOSTER sees itself as a scientific platform for application-centred projects on the technological transformation of the operating room and the clinical working environment. The work at BOSTER is characterised by the interdisciplinarity of a diverse partner landscape from research and industry.
The focus is on projects that are dedicated to the translation of key technologies from AI and robotics through the close integration of clinical users.
BOSTER benefits from the involvement of relevant partners from the fields of sustainability, ethics, data protection and cyber security in the projects.

Data-driven support systems to improve surgical practice

 

Rapidly developing artificial intelligence (AI) technologies offer enormous potential to support surgeons in their work through automated data analysis. In our application-oriented approaches, we address everyday challenges of clinical patient care such as the detection of critical scenarios within emergency care or the development of warning systems in the operating room. The individual care provided by medical expertise is not replaced, but rather profitably supplemented.

New form of visualisation through augmented reality (XR): Virtual and mixed reality

 

Developments in the field of augmented reality (also known as XR, metaverse or spatial computing) are opening up new potential in the visualisation of medical data, including for surgeons. Immersive 3D visualisation is being researched in various application scenarios. These include, for example, surgical treatment planning or the benefits in education and training for students and doctors.

Modern care standards through surgical robotics

Design ohne Titel (23)

The implementation of new robotic systems through to patient use requires new approaches and strategies for realisation within clinical treatment teams. Scientific support for the transfer of new technology into practice always focusses on patient-safe care. Among other things, research is focussing on the combination of robotics with other key technologies from AI and XR. The focus here is on increasing surgical precision while at the same time increasing patient comfort by reducing invasiveness.

Technology in the context of global surgical care

Studies have shown that around 5 billion people worldwide do not have sufficient access to surgical care. This particularly affects regions in the global South; in sub-Saharan Africa, South America and Asia*. BOSTER has set itself the task of analysing technologies from the privileged world in terms of their value for improving disadvantaged (low-resource) regions and implementing them in line with requirements. The scientific collaborations range from networking with globally active NGOs to existing healthcare facilities in the global South, such as the LAMU hospital – Centre for Reconstructive and Global Surgery in Jinja, Uganda.

Design ohne Titel (1)

*Alkire BC, Raykar NP, Shrime MG, Weiser TG, Bickler SW, Rose JA, … & Farmer PE (2015). Global access to surgical care: a modelling study. The Lancet Global Health, 3(6), e316-e323.

Publications

Dohmen J, Weber J, Arensmeyer J, Feodorovici P, Henn J, Schmidt J, Kalff JC, Matthaei H (2024). IDEAL–compliant implementation of the Dexter® surgical robot in cholecystectomy: a comprehensive framework and clinical outcomes. Innovative Surgical Sciences. https://doi.org/10.1515/iss-2024-0033

Huber T, Weber J, von Bechtolsheim F, Flemming S, Fuchs HF, Grade M, Hummel R, Krautz C, Stockheim J, Thomaschewski M, Wilhelm D, Kalff JC, Nickel F, Matthaei H (2024). Modifiziertes Delphi-Verfahren zur Konsensfindung für die Konzeption eines bundesweiten Curriculums für minimalinvasive und roboterassistierte Chirurgie in Deutschland (GeRMIQ). Zentralblatt für Chirurgie-Zeitschrift für Allgemeine, Viszeral-, Thorax-und Gefäßchirurgie. https://doi.org/10.1055/a-2386-9463  

Feodorovici P, Sommer N, Bergedieck P, Lingohr P, Kalff JC, Schmidt J, Arensmeyer JC (2024). Immersive collaborative virtual reality for case-based graduate student teaching in thoracic surgery: A piloting study. Surgery Open Science.  https://doi.org/10.1016/j.sopen.2024.10.008 

Arensmeyer J, Bedetti B, Schnorr P, Buermann J, Zalepugas D, Schmidt J, Feodorovici P (2024) A System for Mixed-Reality Holographic Overlays of Real-Time Rendered 3D-Reconstructed Imaging Using a Video Pass-through Head-Mounted Display—A Pathway to Future Navigation in Chest Wall Surgery. J Clin Med 13:2080. https://doi.org/10.3390/jcm13072080

Adrales G, Ardito F, Chowbey P, Morales-Conde S, Ferreres AR, Hensman C, Martin D, Matthaei H, Ramshaw B, Roberts JK, Schrem H, Sharma A, Tabiri S, Vibert E, Woods MS (2024) Laparoscopic cholecystectomy critical view of safety (LC-CVS): a multi-national validation study of an objective, procedure-specific assessment using video-based assessment (VBA). Surg Endosc 38:922–930. https://doi.org/10.1007/s00464-023-10479-y

Adrales G, Ardito F, Chowbey P, Morales-Conde S, Ferreres AR, Hensman C, Martin D, Matthaei H, Ramshaw B, Roberts JK, Schrem H, Sharma A, Tabiri S, Vibert E, Woods MS (2024) A multi-national, video-based qualitative study to refine training guidelines for assigning an “unsafe” score in laparoscopic cholecystectomy critical view of safety. Surg Endosc 38:983–991. https://doi.org/10.1007/s00464-023-10528-6

Bedetti B, Zalepugas D, Arensmeyer JC, Feodorovici P, Schmidt J (2023) Robotik in der Thoraxchirurgie. Pneumologie 77:374–385. https://doi.org/10.1055/a-1854-2770

Feodorovici P, Arensmeyer J, Schnorr P, Schmidt J (2023) Einsatz von erweiterten Realitäten (XR) in der Thoraxchirurgie. Zentralblatt Für Chir – Z Für Allg Visz Thorax- Gefäßchirurgie 148:367–375. https://doi.org/10.1055/a-2121-6478

Feodorovici P, Schnorr P, Bedetti B, Zalepugas D, Schmidt J, Arensmeyer JC (2023) Collaborative Virtual Reality Real-Time 3D Image Editing for Chest Wall Resections and Reconstruction Planning. Innov Technol Tech Cardiothorac Vasc Surg 18:525–530. https://doi.org/10.1177/15569845231217072

Henn J, Hatterscheidt S, Sahu A, Buness A, Dohmen J, Arensmeyer J, Feodorovici P, Sommer N, Schmidt J, Kalff JC, Matthaei H (2023) Machine Learning for Decision-Support in Acute Abdominal Pain – Proof of Concept and Central Considerations. Zentralblatt Für Chir – Z Für Allg Visz Thorax- Gefäßchirurgie 148:376–383. https://doi.org/10.1055/a-2125-1559

Dohmen J, Lessau M, Schmitz M, Kalff JC (2023) Recycling von chirurgischen Einweginstrumenten – lohnt sich das? Zentralblatt Für Chir – Z Für Allg Visz Thorax- Gefäßchirurgie 148:329–336. https://doi.org/10.1055/a-2122-7519

Henn J, Wyzlic PK, Esposito I, Semaan A, Branchi V, Klinger C, Buhr HJ, Wellner UF, Keck T, Lingohr P, Glowka TR, Manekeller S, Kalff JC, Matthaei H, the StuDoQ, Pancreas Study Group (2023) Surgical treatment for pancreatic cystic lesions—implications from the multi-center and prospective German StuDoQ|Pancreas registry. Langenbecks Arch Surg 408:28. https://doi.org/10.1007/s00423-022-02740-0

Henn J, Buness A, Schmid M, Kalff JC, Matthaei H (2021) Machine learning to guide clinical decision-making in abdominal surgery—a systematic literature review. Langenbecks Arch Surg 1–11. https://doi.org/10.1007/s00423-021-02348-w