Vibroacoustic sensorics for medical device guidance

• Applicant: Professorin Dr. Gabriele A. Krombach
• Subject Area: Medical Physics, Biomedical Technology ; Nuclear Medicine, Radiotherapy, Radiobiology
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 504923173

We propose to use vibroacoustic signals that are generated during the interaction of medical interventional devices (e.g. needles, biopsy systems, catheters, graspers, interventional tools) with human tissue to add valuable information about clinical events, provide directional guidance and subsequently reduce related medical errors. Our prior work in that field has shown that the device tip (distal end) entering new tissue is to a large extent responsible for an audio signal received on the proximal end and that entering different tissues changes the audio characteristics. So far, we have managed to obtain data points in a laboratory setup using an initial sensor design attached to the proximal end and by that eliminating the need to develop dedicated clinical intervention tools, cables and reducing sterility issues. This technology likely will work without major alteration to existing and proven clinical tools. The research work of this proposal will attempt to introduce this laboratory technology to a specific needle-based clinical application (access to the femoral vessels - venous as well as arterial) that could lead to improve the quality of the procedure. A purpose build proximal MEMS audio sensor will transfer the data to an acquisition system that pre-processes the signal, extracts relevant features (advanced signal processing), and attempts to characterize (machine learning) important events during the intervention, like crossing main tissue layers or entering and leaving the vessel, and to give directional information towards the target destination and a confirmation on having reached the medical goal. We will closely interact with the clinical staff and record the actual procedure, interactions during the procedure, and other relevant events as a base for the system modeling. An important development step to understand and simulate signals and their behaviors is to build a dedicated synthetic phantom to model and match the findings of prior acquired results from entering animal tissue samples. This - together with the medical procedure information - is used to build a classification model that will allow us to simulate human interventions based on diagnostic imaging analysis (ultrasound). The setup will subsequently be tested, corrected, and optimized with real patient data obtained during a normal catheter procedure in a clinical interventional radiology setup. The next step is to validate the proposed guidance methodology in phantoms by indicating the increase in surgeonsperformance (targeting accuracy, speed of the procedure, confidence level. This research has enormous potential in other adjacent and connected research areas possibly allowing improved guidance accuracy, audio signal-based characterization of different soft tissues, as well as to provide additional guidance information and simulated haptic feedback/event information for a future (semi-)autonomous robotic surgery/catheter intervention.

• DFG Programme: Research Grants
• International Connection: Poland
• Cooperation Partner: Professor Dr. Michael Friebe