Current Accuracy of Augmented Reality Neuronavigation Systems: Systematic Review and Meta-Analysis

BACKGROUND Augmented reality neuronavigation (ARN) systems can overlay three-dimensional anatomy and pathology without the need for a two-dimensional external monitor. Accuracy is crucial for their clinical applicability. We performed a systematic review regarding the reported accuracy of ARN systems and compared them with the accuracy of conventional infrared neuronavigation (CIN). OBJECTIVE Explore the current navigation accuracy of ARN systems and compare them with CIN. METHODS Pubmed and Embase were searched for ARN and CIN systems. For ARN: type of system, method of patient-to-image registration, accuracy method and accuracy of the system was noted. For CIN: navigation accuracy, expressed as target registration error (TRE), was noted. A meta-analysis was performed comparing the TRE of ARN and CIN systems. RESULTS 35 studies were included, 12 for ARN and 23 for CIN. ARN systems were divided into head-mounted display and heads-up display. In ARN, four methods were encountered for patient-to-image registration, of which point-pair matching was the one most frequently used. Five methods for assessing accuracy were described. 94 TRE measurements of ARN systems were compared with 9058 TRE measurements of CIN systems. Mean TRE was 2.5 mm (CI 95% 0.7 - 4.4) for ARN systems and 2.6 mm (CI 95% 2.1 - 3.1) for CIN systems. CONCLUSIONS In ARN, there seems to be lack of agreement regarding the best method to assess accuracy. Nevertheless, ARN systems seem able to achieve an accuracy comparable with CIN systems. Future studies should be prospective and compare TREs which should be measured in a standardized fashion

Towards Automated Ear Surgery: Improved Calibration and Registration Procedures

A micro-electro-mechanical system (MEMS) based hydrophone inserted into the cochlea may be utilized to study acoustic pressure distribution. The objective of this project, performed through collaboration between WPI and UniversitätsSpital Zürich, was to develop an improved procedure for experiments at the UniversitätsSpital Zürich that would increase the insertion accuracy. This is necessary due to the small scale, complex anatomy, and delicate nature of the inner ear. This was done by calibrating tools and completing registration and insertion processes. The goal was to achieve an overall accuracy of 250 microns, which was met with a final accuracy below 200 microns, suggestive that the devised procedure can provide an accurate roadmap for future experiments

Robotic System Development for Precision MRI-Guided Needle-Based Interventions

This dissertation describes the development of a methodology for implementing robotic systems for interventional procedures under intraoperative Magnetic Resonance Imaging (MRI) guidance. MRI is an ideal imaging modality for surgical guidance of diagnostic and therapeutic procedures, thanks to its ability to perform high resolution, real-time, and high soft tissue contrast imaging without ionizing radiation. However, the strong magnetic field and sensitivity to radio frequency signals, as well as tightly confined scanner bore render great challenges to developing robotic systems within MRI environment. Discussed are potential solutions to address engineering topics related to development of MRI-compatible electro-mechanical systems and modeling of steerable needle interventions. A robotic framework is developed based on a modular design approach, supporting varying MRI-guided interventional procedures, with stereotactic neurosurgery and prostate cancer therapy as two driving exemplary applications. A piezoelectrically actuated electro-mechanical system is designed to provide precise needle placement in the bore of the scanner under interactive MRI-guidance, while overcoming the challenges inherent to MRI-guided procedures. This work presents the development of the robotic system in the aspects of requirements definition, clinical work flow development, mechanism optimization, control system design and experimental evaluation. A steerable needle is beneficial for interventional procedures with its capability to produce curved path, avoiding anatomical obstacles or compensating for needle placement errors. Two kinds of steerable needles are discussed, i.e. asymmetric-tip needle and concentric-tube cannula. A novel Gaussian-based ContinUous Rotation and Variable-curvature (CURV) model is proposed to steer asymmetric-tip needle, which enables variable curvature of the needle trajectory with independent control of needle rotation and insertion. While concentric-tube cannula is suitable for clinical applications where a curved trajectory is needed without relying on tissue interaction force. This dissertation addresses fundamental challenges in developing and deploying MRI-compatible robotic systems, and enables the technologies for MRI-guided needle-based interventions. This study applied and evaluated these techniques to a system for prostate biopsy that is currently in clinical trials, developed a neurosurgery robot prototype for interstitial thermal therapy of brain cancer under MRI guidance, and demonstrated needle steering using both asymmetric tip and pre-bent concentric-tube cannula approaches on a testbed

Influence of the localization strategy on the accuracy of a neurosurgical robot system

Precise navigation of surgical instruments is one of the most important features of autonomous surgical robots. In this paper, we introduce a concept of robot localization strategy and analyse its influence on the overall application error of a robot system for frameless stereotactic neurosurgery named RONNA. Localization strategies utilize specific angles at which the robot can approach a target point, orientations, and types of movement during the procedure of physical space fiducial marker localization and positioning to the target points. The localization strategies developed in this study are a neutral orientation strategy (NOS), an orientation correction strategy (OCS) and a joint displacement minimization strategy (JDMS). To evaluate the robot positioning performance with the localization strategies applied, we performed laboratory phantom measurements using a different number of fiducial markers in the registration procedure. When three, four, and five fiducial markers were used, the application error for the NOS was 1.571±0.256 mm, 1.397±0.283 mm, and 1.327±0.274 mm, and for the OCS, it was 0.429±0.133 mm, 0.284±0.068mm, and 0.260±0.076 mm, respectively. The application error for the JDMS was 0.493±0.176 mm with four and 0.369±0.160 mm with five fiducial markers used

Comparing Measured and Theoretical Target Registration Error of an Optical Tracking System

The goal of this thesis is to experimentally measure the accuracy of an optical tracking system used in commercial surgical navigation systems. We measure accuracy by constructing a mechanism that allows a tracked target to move with spherical motion (i.e., there exists a single point on the mechanism—the center of the sphere—that does not change position when the tracked target is moved). We imagine that the center of the sphere is the tip of a surgical tool rigidly attached to the tracked target. The location of the tool tip cannot be measured directly by the tracking system (because it is impossible to attach a tracking marker to the tool tip) and must be calculated using the measured location and orientation of the tracking target. Any measurement error in the tracking system will cause the calculated position of the tool tip to change as the target is moved; the spread of the calculated tool tip positions is a measurement of tracking error called the target registration error (TRE). The observed TRE will be compared to an analytic model of TRE to assess the predictions of the analytic model

Neurosurgical Ultrasound Pose Estimation Using Image-Based Registration and Sensor Fusion - A Feasibility Study

Modern neurosurgical procedures often rely on computer-assisted real-time guidance using multiple medical imaging modalities. State-of-the-art commercial products enable the fusion of pre-operative with intra-operative images (e.g., magnetic resonance [MR] with ultrasound [US] images), as well as the on-screen visualization of procedures in progress. In so doing, US images can be employed as a template to which pre-operative images can be registered, to correct for anatomical changes, to provide live-image feedback, and consequently to improve confidence when making resection margin decisions near eloquent regions during tumour surgery. In spite of the potential for tracked ultrasound to improve many neurosurgical procedures, it is not widely used. State-of-the-art systems are handicapped by optical tracking’s need for consistent line-of-sight, keeping tracked rigid bodies clean and rigidly fixed, and requiring a calibration workflow. The goal of this work is to improve the value offered by co-registered ultrasound images without the workflow drawbacks of conventional systems. The novel work in this thesis includes: the exploration and development of a GPU-enabled 2D-3D multi-modal registration algorithm based on the existing LC2 metric; and the use of this registration algorithm in the context of a sensor and image-fusion algorithm. The work presented here is a motivating step in a vision towards a heterogeneous tracking framework for image-guided interventions where the knowledge from intraoperative imaging, pre-operative imaging, and (potentially disjoint) wireless sensors in the surgical field are seamlessly integrated for the benefit of the surgeon. The technology described in this thesis, inspired by advances in robot localization demonstrate how inaccurate pose data from disjoint sources can produce a localization system greater than the sum of its parts