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[Methods, applications, and future perspectives of intraoperative tissue identification]
Sanja Hermanns1, Sascha Dammeier1, Alexander Neugebauer1
1Erbe Elektromedizin GmbH, Waldhörnlestr. 17, 72072, Tübingen, Deutschland.
Abstract:
Over the last century, there has been a steady development of new technologies for intraoperative tissue identification and differentiation. The applications are varied, with the core purpose being to identify target structures while preserving adjacent tissue and thereby follow a general paradigm of minimally invasive medicine. Particularly in oncology, a further asset of these technologies is the identification or classification of neoplastic tissue to support and improve therapy, for example, in breast cancer surgery.Many technologies under consideration make use of the different physical characteristics of treated tissues, such as induced fluorescence, optical coherence, and electrical impedance.Recent developments are focusing on moving from ex vivo to in situ and from asynchronous to real-time assistance of the clinicians, for example, by means of optical emission spectroscopy. Refinements of existing and the creation of new methods will include AI tools to make them more powerful while reducing the inter-operator variability in operative interventions. This talk addresses several aspects of the usage and suitability of these technologies for intraoperative, therapy-supporting application.
Insights
New technologies enhance intraoperative tissue identification, aiding minimally invasive surgery and cancer treatment. Advancements include real-time AI tools for improved accuracy and reduced variability in surgical interventions.
Area of Science:
- Biomedical Engineering
- Surgical Technology
- Medical Imaging
Context:
- Technological advancements over the past century have focused on intraoperative tissue identification and differentiation.
- Minimally invasive medicine relies on precise identification of target structures while preserving adjacent tissues.
- Oncology benefits significantly from technologies that identify or classify neoplastic tissue, improving cancer surgery outcomes, such as in breast cancer operations.
Purpose:
- To review and assess the utility and application of various technologies for intraoperative tissue identification.
- To highlight the evolution from ex vivo to in situ and asynchronous to real-time clinical assistance.
- To explore the integration of Artificial Intelligence (AI) in refining existing and developing new methods for enhanced surgical accuracy.
Summary:
- Technologies leverage distinct physical tissue characteristics like induced fluorescence, optical coherence, and electrical impedance.
- Recent developments emphasize real-time, in situ assistance, exemplified by optical emission spectroscopy.
- Future refinements involve AI integration to boost performance and minimize inter-operator variability in surgical procedures.
Impact:
- Improved surgical precision and patient outcomes through enhanced tissue differentiation.
- Facilitation of minimally invasive surgical techniques with greater confidence.
- Potential for AI-driven tools to standardize and elevate the quality of surgical interventions across different operators.
