GRK 2543:  Intraoperative multi-sensor tissue identification in oncology

• Subject Area: Systems Engineering ; Medicine
• Term: since 2020
• Website: Homepage
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 409474577

In the oncological context, the differentiation of pathological tissue conditions in situ is of utmost relevance to enable improved diagnostics, complete tumor removal and better patient safety and prognosis. The current gold standard, the histopathological instantaneous section, entails a time delay due to the need to remove tissue, transport it and examine it in the laboratory. The goal of the research training group is to use multisensory measurements to improve the ability to assess the intraoperative situation in vivo and, in perspective, to replace the instantaneous section for as many indications as possible. To this end, new multimodal approaches to tissue differentiation are researched in order to complement current diagnostic procedures and provide more precise information during surgical interventions. So far, the focus has been on the conceptual design and functional verification of novel, multimodal sensor technologies for on applications in gynecology and urology. In order to enable a comprehensive differentiation of the tissue, the sensors measure optical tissue properties by infrared or Raman spectroscopy, as well as electrical and mechanical parameters. In the 1st cohort, it could be shown that all sensor concepts show sensitivity for tissue differentiation in an ex vivo context. The sensor principles must now be further developed for improved determination of spatial resolution as well as surface and deeper tissue characteristics, especially under the influence of neoadjuvant therapies. A further miniaturization and adaptation for intraoperative application is necessary to combine multiple sensors in a multimodal probe. The classification problem will be extended from a purely binary distinction between healthy tissue and tumor to a classification of malignancy grade, tumor type, and other tissue properties such as inflammation based on multimodal tissue differentiation measurements. The fusion of sensor principles is expected to result in the precise detection of tumor margins. In particular, this requires the coupling of the measurement points to the pathological findings, as well as the modeling and mapping of the organs for the localization of the recorded data. The close clinical collaboration with the physicians for sensor development, measurement procedures and interpretation of the results will be continued and expanded. The doctoral researchers will be guided by an interdisciplinary team of three supervisors. Together with a comprehensive qualification program, both within the discipline and interdisciplinary, they are optimally prepared for research and development in the field of medical technology. All eight doctoral students (1st cohort) in the natural sciences/engineering fields completed their doctorates.

• DFG Programme: Research Training Groups
• Applicant Institution: Universität Stuttgart
• Co-Applicant Institution: Eberhard Karls Universität Tübingen
• Spokesperson: Professor Dr.-Ing. Oliver Sawodny
• Participating Researchers: Privatdozent Dr. Bastian Amend; Professorin Dr. Sara Brucker; Professor Dr. Falko Fend; Professor Dr. Alois Herkommer; Professor Dr.-Ing. Hendrik Lensch; Professor Dr.-Ing. Stephan Reichelt; Professorin Dr. Katja Schenke-Layland; Professor Dr. Tilman Schäffer; Professorin Dr.-Ing. Cristina Tarín Sauer