Navigated real-time molecular analysis in the operating theatre: demonstration of concept

Mark Asselin; Martin Kaufmann; Julia Wiercigroch; Tamas Ungi; Andras Lasso; John Rudan; Gabor Fichtinger

doi:10.1117/12.2512586

8 March 2019 Navigated real-time molecular analysis in the operating theatre: demonstration of concept

Mark Asselin, Martin Kaufmann, Julia Wiercigroch, Tamas Ungi, Andras Lasso, John Rudan, Gabor Fichtinger

Proceedings Volume 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling; 109512C (2019) https://doi.org/10.1117/12.2512586
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

PURPOSE: In the operating theatre surgeons are accustomed to using spatially navigated tools in conjunction with standard clinical imaging during a procedure. This gives them a good idea where they are in the patients’ anatomy but doesn’t provide information about the type of tissue they are dissecting. In this paper we demonstrate an integrated system consisting of a spatially navigated surgical electrocautery combined with real-time molecular analysis of the dissected tissue using mass spectrometry. METHODS: Using the 3D Slicer software package, we have integrated a commercially available neurosurgical navigation system with an intra-operative mass spectrometer (colloquially referred to as the intelligent knife, or iKnife) that analyzes the charged ions in the smoke created during cauterization. We demonstrate this system using a simulated patient comprised of an MRI scan from a brain cancer patient deformably registered to a plastic skull model. On the skull model we placed porcine and bovine tissues to simulate cancerous and healthy tissue, respectively. We built a PCA/LDA model to distinguish between these tissue types. The tissue classifications were displayed in a spatially localized manner in the pre-operative imaging, in both 2D and 3D views. RESULTS: We have demonstrated the feasibility of performing spatially navigated intra-operative analysis of tissues by mass spectrometry. We show that machine learning can classify our sample tissues, with an average computed confidence of 99.37 % for porcine tissue and 99.36% for bovine tissue. CONCLUSION: In this paper we demonstrate a proof of concept system for navigated intra-operative molecular analysis. This system may enable intra-operative awareness of spatially localized tissue classification during dissection, information that is especially useful in tumor surgeries where margins may not be visible to the unassisted eye.

Citation Download Citation

Mark Asselin, Martin Kaufmann, Julia Wiercigroch, Tamas Ungi, Andras Lasso, John Rudan, and Gabor Fichtinger "Navigated real-time molecular analysis in the operating theatre: demonstration of concept", Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109512C (8 March 2019); https://doi.org/10.1117/12.2512586

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