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Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation

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Abstract

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green’s function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative \(\mu\)CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

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Acknowledgements

The authors wish to thank Christina Precht from the Vetsuisse Department for her help in conducting the in vivo sheep studies. The authors would also like to thank Nano Tera and the Swiss National Science Foundation for funding the research within the hear restore project (RTD 2013).

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Authors and Affiliations

  1. Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstr. 78, 3014, Bern, Switzerland

    Arne Feldmann & Philippe Zysset

  2. ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstr. 50, 3010, Bern, Switzerland

    Juan Anso, Brett Bell, Tom Williamson, Kate Gavaghan, Nicolas Gerber & Stefan Weber

  3. Department of Clinical Veterinary Medicine, Vetsuisse Faculty, University of Bern, Länggassstrasse 124, 3001, Bern, Switzerland

    Helene Rohrbach

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  1. Arne Feldmann
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  2. Juan Anso
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Correspondence to Arne Feldmann.

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Associate Editor Sean Kohles oversaw the review of this article.

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Feldmann, A., Anso, J., Bell, B. et al. Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation. Ann Biomed Eng 44, 1576–1586 (2016). https://doi.org/10.1007/s10439-015-1450-0

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  • DOI: https://doi.org/10.1007/s10439-015-1450-0

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