Vision-based deformation recovery for intraoperative force estimation of tool–tissue interaction for neurosurgery

Stamatia Giannarou,Konrad Leibrandt,Menglong Ye,Hani J. Marcus,Guang-Zhong Yang,Gauthier Gras

doi:10.1007/s11548-016-1361-z

Stamatia Giannarou, Konrad Leibrandt + Show 4 more

Open Access

https://doi.org/10.1007/s11548-016-1361-z

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Abstract

PurposeIn microsurgery, accurate recovery of the deformation of the surgical environment is important for mitigating the risk of inadvertent tissue damage and avoiding instrument maneuvers that may cause injury. The analysis of intraoperative microscopic data can allow the estimation of tissue deformation and provide to the surgeon useful feedback on the instrument forces exerted on the tissue. In practice, vision-based recovery of tissue deformation during tool–tissue interaction can be challenging due to tissue elasticity and unpredictable motion.MethodsThe aim of this work is to propose an approach for deformation recovery based on quasi-dense 3D stereo reconstruction. The proposed framework incorporates a new stereo correspondence method for estimating the underlying 3D structure. Probabilistic tracking and surface mapping are used to estimate 3D point correspondences across time and recover localized tissue deformations in the surgical site.ResultsWe demonstrate the application of this method to estimating forces exerted on tissue surfaces. A clinically relevant experimental setup was used to validate the proposed framework on phantom data. The quantitative and qualitative performance evaluation results show that the proposed 3D stereo reconstruction and deformation recovery methods achieve submillimeter accuracy. The force–displacement model also provides accurate estimates of the exerted forces.ConclusionsA novel approach for tissue deformation recovery has been proposed based on reliable quasi-dense stereo correspondences. The proposed framework does not rely on additional equipment, allowing seamless integration with the existing surgical workflow. The performance evaluation analysis shows the potential clinical value of the technique.

Highlights

Microsurgical techniques are arguably the most technically demanding skills that trainee surgeons must learn
Failure to respect the force thresholds of fragile neurovascular tissue can result in iatrogenic injury, which in turn carries a risk of disability or even death
Technological advances in surgical devices (NeuroArm, Steady-Hand Robot) and handheld instruments have allowed the integration of force sensing capabilities into surgical tools, resulting in the possibility of force feedback during an operation

Summary

Introduction

Microsurgical techniques are arguably the most technically demanding skills that trainee surgeons must learn. For example, sharp arachnoid dissection typically utilizes forces below 0.3N, levels that are often barely perceptible to surgeons. Failure to respect the force thresholds of fragile neurovascular tissue can result in iatrogenic injury, which in turn carries a risk of disability or even death. The clinical corollary is that tools that allow surgeons to better appreciate the forces they exert are likely to reduce the risk of operative complications, and improve patient outcomes. Research on the forces exerted during microsurgery has generally focused on the development of improved force feedback capabilities. Technological advances in surgical devices (NeuroArm, Steady-Hand Robot) and handheld instruments have allowed the integration of force sensing capabilities into surgical tools, resulting in the possibility of force feedback during an operation. Surgeons are able to rely on visual cues

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