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Force adaptive robotically assisted endomicroscopy for intraoperative tumour identification

  • Petros GiataganasEmail author
  • Michael Hughes
  • Guang-Zhong Yang
Original Article

Abstract

Purpose

For effective tumour margin definition for cancer surgery, there is an increasing demand for the development of real-time intraoperative tissue biopsy techniques. Recent advances in miniaturized biophotonics probes have permitted the development of endomicroscopy techniques that are clinically attractive. With these approaches, cellular-level imaging can be achieved through millimetre-scale flexible probes and be performed in real-time, in vivo and in situ. Due to the limited field of view and flexibility of these probes, however, large area tissue coverage for acquiring histology-like images over complex three-dimensional surfaces is challenging. This is particularly the case because current surgical robots, such as the Da \(\hbox {Vinci}^\circledR \), lack haptic feedback, making it difficult to maintain optimum tissue contact when these probes are deployed in vivo.

Methods

This paper proposes a simple force-controlled pick-up probe that can be integrated with the Da Vinci instruments for intraoperative endomicroscopy imaging. The device uses a new low-friction air bearing with adaptive axial force control to maintain constant contact between the tissue and the imaging probe, facilitating microscopy scans over complex surfaces. Detailed ex vivo user experiments have been conducted to demonstrate the effectiveness of the technique.

Results

The adaptive probe mount could achieve consistent low-magnitude probe–sample contact forces compared with a rigid mount. In the user study, the adaptive probe combined with a high frame rate endomicroscopy system allowed larger mosaics to be generated over curved surfaces.

Conclusions

The device can improve the performance of large area mosaicking over complex 3D surfaces with improved handling and intraoperative control.

Keywords

Endomicroscopy Endoscopy Adaptive control Robotic-assisted MIS Mosaicking Image Guidance 

Notes

Acknowledgments

This research is conducted with support from the EPSRC Grant EP/I027769/1: SMART Endomicroscopy. The authors would like to acknowledge Dr. Philip Pratt and Dr. Christos Bergeles for providing the necessary vision set-up to perform the experiments presented in this paper and Dr. George Mylonas for his assistance in this research.

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© CARS 2015

Authors and Affiliations

  1. 1.Hamlyn Centre for Robotic Surgery, Institute of Global Health InnovationImperial College LondonLondonUK

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