Assessment and comparison of target registration accuracy in surgical instrument tracking technologies

A fast co-registration scheme between camera and MRI for MRI-guided surgery

The co-registration between an optical tracker and Magnetic Resonance Imaging (MRI) space is an indispensable step for MRI-guided surgery. In this study, with a focus on RGB cameras as the tracker, we introduce an innovative co-registration scheme for tracker-to-MRI integration. Firstly, we design a cube-shaped registration model that is equipped with an ArUco marker on its exterior for RGB camera detection and houses four water blobs inside for MRI calibration. Secondly, we employ a line scan pulse sequence for the localization and reconstruction of the water blobs. Lastly, we establish the transformation relationship between the camera and MRI coordinate systems. Our registration scheme was implemented on a 0.35T MRI system, accompanied by a magnetically shielded RGB camera. In comparison to conventional image domain-based phantom blob reconstruction techniques, the line scanning method showcased lower registration errors and achieved scanning speeds over ten times faster. In needle localization accuracy experiments, the needle tip position, as determined by the ArUco marker on the handle, deviated by a mere 1.008 mm from its actual MRI scan position. Our results highlight the considerable potential for cost-effective RGB cameras in MRI-guided surgeries. Moreover, our registration scheme is not confined to RGB cameras and can be generalized to other optical trackers by simply substituting the corresponding marker. The proposed scheme promises to streamline and automate the co-registration process, thereby reducing surgery preparation time and bolstering the clinical applicability of MRI-guided surgeries.

Performance assessment of surgical tracking systems based on statistical process control and longitudinal QA

A system for performance assessment and quality assurance (QA) of surgical trackers is reported based on principles of geometric accuracy and statistical process control (SPC) for routine longitudinal testing. A simple QA test phantom was designed, where the number and distribution of registration fiducials was determined drawing from analytical models for target registration error (TRE). A tracker testbed was configured with open-source software for measurement of a TRE-based accuracy metric ε and Jitter (J ). Six trackers were tested: 2 electromagnetic (EM - Aurora); and 4 infrared (IR - 1 Spectra, 1 Vega, and 2 Vicra) - all NDI (Waterloo, ON). Phase I SPC analysis of Shewhart mean (x ¯ ) and standard deviation (s ) determined system control limits. Phase II involved weekly QA of each system for up to 32 weeks and identified Pass, Note, Alert, and Failure action rules. The process permitted QA in <1 min. Phase I control limits were established for all trackers: EM trackers exhibited higher upper control limits than IR trackers in ε (EM: x ¯ ε   ∼ 2.8-3.3 mm, IR: x ¯ ε   ∼ 1.6-2.0 mm) and Jitter (EM: x ¯ jitter   ∼ 0.30-0.33 mm, IR: x ¯ jitter   ∼ 0.08-0.10 mm), and older trackers showed evidence of degradation - e.g. higher Jitter for the older Vicra (p-value < .05). Phase II longitudinal tests yielded 676 outcomes in which a total of 4 Failures were noted - 3 resolved by intervention (metal interference for EM trackers) - and 1 owing to restrictive control limits for a new system (Vega). Weekly tests also yielded 40 Notes and 16 Alerts - each spontaneously resolved in subsequent monitoring.

Evaluation and Comparison of Target Registration Error in Active and Passive Optical Tracking Systems

Optical tracking systems combined with imaging modalities such as computed tomography and magnetic reso-nance imaging are important parts of image guided surgery systems. By determining the location and orientation of sur-gical tools relative to a patient's reference system, tracking systems assist surgeons during the planning and execution of image guided procedures. Therefore, knowledge of the tracking system-induced error is of great importance. To this end, this study compared one passive and two active optical tracking systems in terms of their Target Registration Error. Two experiments were performed to measure the systems' accuracy, testing the impact of factors such as the size of the measuring volume, length of surgical instruments and environmental conditions with orthopedic procedures in mind. According to the performed experiments, the active systems achieved significantly higher accuracy than the tested passive system, reporting an overall accuracy of 0.063 mm (SD = 0.025) and 0.259 mm (SD = 0.152), respectively.

Mixed reality as a novel tool for diagnostic and surgical navigation in orthopaedics

Purpose

This study presents a novel surgical navigation tool developed in mixed reality environment for orthopaedic surgery. Joint and skeletal deformities affect all age groups and greatly reduce the range of motion of the joints. These deformities are notoriously difficult to diagnose and to correct through surgery.

Method

We have developed a surgical tool which integrates surgical instrument tracking and augmented reality through a head mounted display. This allows the surgeon to visualise bones with the illusion of possessing “X-ray” vision. The studies presented below aim to assess the accuracy of the surgical navigation tool in tracking a location at the tip of the surgical instrument in holographic space.

Results

Results show that the average accuracy provided by the navigation tool is around 8 mm, and qualitative assessment by the orthopaedic surgeons provided positive feedback in terms of the capabilities for diagnostic use.

Conclusions

More improvements are necessary for the navigation tool to be accurate enough for surgical applications, however, this new tool has the potential to improve diagnostic accuracy and allow for safer and more precise surgeries, as well as provide for better learning conditions for orthopaedic surgeons in training.

The effect of intraoperative imaging on surgical navigation for laparoscopic liver resection surgery

Conventional surgical navigation systems rely on preoperative imaging to provide guidance. In laparoscopic liver surgery, insufflation of the abdomen (pneumoperitoneum) can cause deformations on the liver, introducing inaccuracies in the correspondence between the preoperative images and the intraoperative reality. This study evaluates the improvements provided by intraoperative imaging for laparoscopic liver surgical navigation, when displayed as augmented reality (AR). Significant differences were found in terms of accuracy of the AR, in favor of intraoperative imaging. In addition, results showed an effect of user-induced error: image-to-patient registration based on annotations performed by clinicians caused 33% more inaccuracy as compared to image-to-patient registration algorithms that do not depend on user annotations. Hence, to achieve accurate surgical navigation for laparoscopic liver surgery, intraoperative imaging is recommendable to compensate for deformation. Moreover, user annotation errors may lead to inaccuracies in registration processes.