Stochastic approach to error estimation for image-guided robotic systems

Accuracy of Robotic-Assisted Spinal Surgery-Comparison to TJR Robotics, da Vinci Robotics, and Optoelectronic Laboratory Robotics

BACKGROUND

The optoelectronic camera source and data interpolation serve as the foundation for navigational integrity in the robotic-assisted surgical platform. The objective of the current systematic review serves to provide a basis for the numerical disparity that exists when comparing the intrinsic accuracy of optoelectronic cameras: accuracy observed in the laboratory setting versus accuracy in the clinical operative environment. It is postulated that there exists a greater number of connections in the optoelectronic kinematic chain when analyzing the clinical operative environment to the laboratory setting. This increase in data interpolation, coupled with intraoperative workflow challenges, reduces the degree of accuracy based on surgical application and to that observed in controlled musculoskeletal kinematic laboratory investigations.

METHODS

Review of the PubMed and Cochrane Library research databases was performed. The exhaustive literature compilation obtained was then vetted to reduce redundancies and categorized into topics of intrinsic optoelectronic accuracy, registration accuracy, musculoskeletal kinematic platforms, and clinical operative platforms.

RESULTS

A total of 147 references make up the basis for the current analysis. Regardless of application, the common denominators affecting overall optoelectronic accuracy are intrinsic accuracy, registration accuracy, and application accuracy. Intrinsic accuracy of optoelectronic tracking equaled or was less than 0.1 mm of translation and 0.1° of rotation per fiducial. Controlled laboratory platforms reported 0.1 to 0.5 mm of translation and 0.1°-1.0° of rotation per array. There is a huge falloff in clinical applications: accuracy in robotic-assisted spinal surgery reported 1.5 to 6.0 mm of translation and 1.5° to 5.0° of rotation when comparing planned to final implant position. Total Joint Robotics and da Vinci urologic robotics computed accuracy, as predicted, lies between these two extremes-1.02 mm for da Vinci and 2 mm for MAKO.

CONCLUSIONS

Navigational integrity and maintenance of fidelity of optoelectronic data is the cornerstone of robotic-assisted spinal surgery. Transitioning from controlled laboratory to clinical operative environments requires an increased number of steps in the optoelectronic kinematic chain and error potential. Diligence in planning, fiducial positioning, system registration, and intraoperative workflow have the potential to improve accuracy and decrease disparity between planned and final implant position. The key determining factors limiting navigation resolution accuracy are highlighted by this Cochrane research analysis.

General first-order target registration error model considering a coordinate reference frame in an image-guided surgical system

Point-based rigid registration (PBRR) techniques are widely used in many aspects of image-guided surgery (IGS). Accurately estimating target registration error (TRE) statistics is of essential value for medical applications such as optically surgical tool-tip tracking and image registration. For example, knowing the TRE distribution statistics of surgical tool tip can help the surgeon make right decisions during surgery. In the meantime, the pose of a surgical tool is usually reported relative to a second rigid body whose local frame is called coordinate reference frame (CRF). In an n-ocular tracking system, fiducial localization error (FLE) should be considered inhomogeneous, that means FLE is different between fiducials, and anisotropic that indicates FLE is different in all directions. In this paper, we extend the TRE estimation algorithm relative to a CRF from homogeneous and anisotropic to heterogeneous FLE cases. Arbitrary weightings can be assumed in solving the registration problems in the proposed TRE estimation algorithm. Monte Carlo simulation results demonstrate the proposed algorithm's effectiveness for both homogeneous and inhomogeneous FLE distributions. The results are further compared with those using the other two algorithms. When FLE distribution is anisotropic and homogeneous, the proposed TRE estimation algorithm's performance is comparable with that of the first one. When FLE distribution is heterogeneous, proposed TRE estimation algorithm outperforms the other two classical algorithms in all test cases when ideal weighting scheme is adopted in solving two registrations. Possible clinical applications include the online estimation of surgical tool-tip tracking error with respect to a CRF in IGS. Graphical Abstract This paper provides the target registration error model considering a coordinate reference frame in surgical navigation.

Safety margins in robotic bone milling: from registration uncertainty to statistically safe surgeries

BACKGROUND

When robots mill bone near critical structures, safety margins are used to reduce the risk of accidental damage due to inaccurate registration. These margins are typically set heuristically with uniform thickness, which does not reflect the anisotropy and spatial variance of registration error.

METHODS

A method is described to generate spatially varying safety margins around vital anatomy using statistical models of registration uncertainty. Numerical simulations are used to determine the margin geometry that matches a safety threshold specified by the surgeon.

RESULTS

The algorithm was applied to CT scans of five temporal bones in the context of mastoidectomy, a common bone milling procedure in ear surgery that must approach vital nerves. Safety margins were generated that satisfied the specified safety levels in every case.

CONCLUSIONS

Patient safety in image-guided surgery can be increased by incorporating statistical models of registration uncertainty in the generation of safety margins around vital anatomy.

Towards unified electromagnetic tracking system assessment-static errors

Recent advances in Image-Guided Surgery allows physicians to incorporate up-to-date, high quality patient data in the surgical decision making, and sometimes to directly perform operations based on pre- or intra-operatively acquired patient images. Electromagnetic tracking is the fastest growing area within, where the position and orientation of tiny sensors can be determined with sub-millimeter accuracy in the field created by a generator. One of the major barriers to the wider spread of electromagnetic tracking solutions is their susceptibility to ferromagnetic materials and external electromagnetic sources. The research community has long been engaged with the topic to find engineering solutions to increase measurement reliability and accuracy. This article gives an overview of related experiments, and presents our recommendation towards a robust method to collect representative data about electromagnetic trackers.